Conference Agenda

The objective of this CLIMATE-TPE project is: To improve the understanding of the interactions between the Asian monsoon, the plateau surface (including its permafrost and lakes) and the Tibetan plateau atmosphere in terms of water and energy budgets in order to assess and understand the causes of changes in cryosphere and hydrosphere in relation to changes of plateau atmosphere in the Asian monsoon system and to predict the possible changes in water resources in the Third Pole Environment. A core innovation of the project is to verify or falsify recent hypotheses (e.g. links between plateau heating and monsoon circulation, snow cover and monsoon strength, soil moisture and timing of monsoon) and projections of the changes of glaciers and permafrost in relation to surface and tropospheric heatings on the Tibetan plateau as precursors of monsoon pattern changes and glaciers retreat, and their impacts on water resources in South East Asia.

We use earth observation, in-situ measurements and modelling to advance process understanding relevant to monsoon scale predictions, and improve and develop coupled regional scale hydroclimatic models to explain different physical links and scenarios that cannot be observed directly. Three work-packages (WP) are defined in the project to address three specific objectives. Objective 1) advancement of the understanding of microwave scattering and emission under complex terrains with permafrost and freeze – thawing conditions. The focus is to reduce current uncertainties in microwave satellite observations over complex terrain and improve retrieval accuracies of soil moisture and freeze-thaw states by deploying in-situ observations, laboratory experiment and numerical modelling. Objective 2) Advancement of physical understanding and quantification of changes of water and energy budgets in the TPE. The focus here is to integrate current understandings in the mechanism of changes in water and energy budget in TPE using satellite data products and numerical modelling. Objective 3) Advancement of quantifying changes in surface characteristics and monsoon interactions. All variables related to water and energy budgets in TPE will be subject to systematic analysis to endure their consistence in terms of climate data records. The variables will include albedo, vegetation coverage, soil thermal and hydraulic properties, LST, soil moisture, lake levels and land use changes among others.

In this contribution we focus on WP1: Observation and modelling of microwave scattering and emission under complex terrains and including permafrost and freeze and thawing.

We have deployed the ESA L-band (1.41 GHz) Radiometer (ELBARA-III, Schwank et al. 2010) since the beginning of 2016 at the central micrometeorological station (latitude: 33.919750, longitude: 102.153183, WGS’84) of the Maqu network of the Tibetan Plateau. ELBARA-III is provided by ESA for experimental observation for the calibration and validation of SMOS data and products.

1) We have conducted ELBARA measurements, covering one complete freeze-thawing cycles, for advancing understanding of the mass and energy exchanges involved in the freeze/thaw process.

2) The collected ELBARA observations are analysed with the recently developed effective temperature model by Lv et al. (2014) to better understand the microwave emission signals, including the validation of ESA’s SMOS and NASA’s SMAP radiometer brightness temperatures (T_B).

3) The collected ELBARA and other in-situ data are used to investigate the effectiveness in two recently developed methods to merge existing satellite data of different frequencies (e.g. for low resolution data SCAT/ASCAT, SSM/I, AMSRE-E/2, SMOS, and high resolution data ASAR/S-1) (Dente et al. 2014; Lv et al. 2014), so that a consistent soil moisture data product can be generated by using the same consistent framework, contributing to the ESA Climate Change Initiative.

Young scientists engaged in this project:

1. Dr. Rogier van der Velde, University of Twente, email: r.vandervelde@utwente.nl, remote sensing of soil moisture
2. Dr. Yijian Zeng, University of Twente, email: y.zeng@utwente.nl, data assimilation
3. Dr. Xin Wang, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou, China, remote sensing of soil moisture
4. Dr. Xuelong Chen (postdoc, UT) land-atmosphere interactions, boundary layer processes
5. Dr. Donghai Zheng (postdoc, UT) water cycle in the upper Yellow River basin, hydrological modelling
6. Shaoning Lv (PhD student, UT-NIEER) Microwave emission, Soil Moisture and its Impacts on Climate Forecasting
7. Qiang Wang (PhD student, UT) Soil moisture monitoring using Aquarius data
8. Binbin Wang (PhD student, UT-ITP) Energy balance of high plateau lakes
9. Xu Yuan (PhD student, UT) The role of sea surface salinity in the Indian Ocean and its effect on the South Asian monsoon
10. Hong Zhao (PhD student, UT) Retrieval of soil thermal and hydraulic parameters from satellite observations
11. Dongyu Jia (PhD student, NIEER) land-atmosphere interaction study in cold region
12. Prof. Weiqiang Ma, Institute of Tibetan Plateau, CAS, email: wqma@itpcas.ac.cn, remote sensing and atmospheric modelling of land-atmosphere processes
13. Dr. Cunbo Han (postdoc, ITP) land surface processes modelling
14. Lian Liu (PhD student, ITP) Retrieval of thermal and hydraulic parameters from satellite observations on the glaciers
15. Dr. Cristina Aguilar, University of Cordoba, e-mail: caguilar@uco.es
16. Dr. Rafael Pimentel(postdoc, UC)remotely sensed data fusion and assimilation for snow and hydrological modelling. University of Cordoba
17. Gabriel Delgado Leal(PhD student, UC) Water and energy fluxes regime in snow mountain regions
18. Marta Sáenz de Rodrigáñez (PhD student, UC) Remote sensing data fusion to generate long and high resolution time series of snow and hydrological variables
19. Dr. Jian Peng (postdoc, LMU) Thermal and microwave remote sensing of surface energy and water fluxes.
20. Dr. Christiaan van der Tol, University of Twente, email: c.vandertol@utwente.nl, remote sensing of fluorescence
21. Jan Hofste (PhD student, UT),University of Twente, email: j.g.hofste@utwente.nl, remote sensing of land surface by scatterometry and spectroscopy

The Third Pole Environment (TPE) centered on the Tibetan plateau and the Himalayas feeds Asia s largest rivers which provide water to 1.5 billion people across ten countries. Due to its high elevation, TPE plays a significant role in global atmospheric circulation and is highly sensitive to climate change. Intensive exchanges of water and energy fluxes take place between the Asian monsoon, the plateau land surface (lakes, glaciers, snow and permafrost) and the plateau atmosphere at various temporal and spatial scales, but a fundamental understanding of the details of the coupling is lacking especially at the climate scale.
Based on in-situ measurements, satellite remote sensing and numerical modeling, several main achievements have been acquired to promote the understanding of water and energy cycles over the Tibetan Plateau. (1) In-situ measurements: Systematic underestimations of soil heat flux by soil heat flux plate have been proved with estimation from in-situ soil moisture and temperature measurements in CAMP/Tibet. The comparison between in-situ soil heat flux and estimated values from temperature prediction-correction method shows that they have the same heat flux flow direction and phase. However, the in-situ values measured by heat flux plate are generally smaller than the estimation. It was also identified that variations in soil moisture had important effects on carbon exchange in this alpine steppe ecosystem. Both the photosynthesis and respiration were active under high soil moisture content, and suppressed during periods of water shortage. Precise measurements of evaporation and understanding of the physical controls on turbulent heat flux over lakes at different time scales have fundamental significance for catchment-scale water balance analysis and local-scale climate modeling. To test the performance of lake-air turbulent exchange models over high-altitude lakes and to understanding the driving forces for turbulent heat flux and obtain the actual evaporation over the small high-altitude lakes, an eddy covariance observational system was built above the water surface of the small Nam Co Lake. Also we analyzed the variability and trends of daily precipitation extremes over the northern and southern side of central Himalaya, case study on evaluation of future precipitation scenario using statistical downscaling model over humid, sub humid and arid region of Nepal. (2) Remote sensing: Combing satellite remote sensing data and surface meteorological forcing data, land surface heat fluxes at multi-spatiotemporal scales over the Tibetan Plateau have been achieved. The parameterization schemes for diffused and reflected downward shortwave radiation flux of the TESEBS model were improved by introducing the parameters sky-view factor (SVF) and terrain configuration factor (Ct). (3) Model simulation: WRF model was used to estimate surface parameters and related meteorological elements over the Tibetan Plateau. The ground-measured surface variables and land surface heat fluxes were compared to WRF model values. The comparisons show good consistency. Lake-air interactions at Nam Co lake were analyzed through evaluating two popular lake-air exchange models: a bulk aerodynamic transfer model (B Model) and a multi-layer model (M Model). It was found that both models underestimated turbulent fluxes. This was due to inaccurate values of the Charnock coefficient and the roughness Reynolds number which are both important parameters for calculating the roughness length for momentum over water. Also Regional Atmospheric Modeling System (RAMS) was applied to the study of the effect of the topographical altitude of the Tibetan Plateau (TP) on a severe drought event which took place in eastern China from November 2008 to January 2009. (4) Hydrological model: Flow generated from Upper Indus Basin (UIB) originates in Hindukush-Karakoram-Himalaya region, Pakistan. The initial water supply reinstates after winter, depending upon the accumulated snow aggregate and subsequent temperature. Seasonal temperature dictates the state and fate of snow and glacier melt during summer. Recently, developing evidence of warming at high-mountains is accelerated regarded as Elevation dependent warming (EDW). We have identified trends, analyzed variability, and assessed changes in annual and seasonal maximum, minimum, mean and diurnal temperature range. (5) Training of young scientists in the area of climate and environment. Four PhD students have been sent to European partner for joint training. Two of them have got PhD degree in University of Twente under the supervision of European PI (Prof. Z. (Bob) Su) and Chinese PI (Prof. Yaoming Ma). Several European students from our partner also come to China regularly for joint field visiting and academic exchange.

Surface soil moisture (SSM) plays a significant role in various domains of science such as agriculture, hydrology, meteorology and ecology. However, the spatial resolution of microwave SSM products is too coarse for regional and local applications. Most of the current optical/thermal infrared SSM retrieval models cannot estimate the quantitative volumetric soil water content directly without establishing empirical relationships between SSM measurements and satellite derived proxies of SSM. Therefore, this study mainly estimates SSM directly from Chinese geostationary meteorological satellite FY-2E data with a high spatial resolution of 5 km based on an improved elliptical SSM retrieval model developed from the synergistic use of the diurnal cycles of Land Surface Temperature (LST) and Net Surface Shortwave Radiation (NSSR). The original model is developed with bare soil. The coefficients of the original model are not distinguished from different Fractional Vegetation Cover (FVC). To optimize the model for SSM estimation at regional scale, the present study improved the original model by accounting for the influence of FVC, which is based on a dimidiate pixel model and MODIS NDVI product. Ultimately, a preliminary validation was conducted using the ground measurements in the south of Maqu City, in the source area of the Yellow River. A correlation coefficient (R) of 0.620, a root mean square error (RMSE) of 0.146 m³/m³ and a bias of 0.038 m³/m³ are found between in-situ measurement and FY-2E-derived SSM from original model. While it reveals a better relationship between FY-2E-derived SSM from improved model and ground measurement with a R of 0.845, a RMSE of 0.064 m³/m³ and a bias of 0.017 m³/m³. In order to provide more accurate SSM, high accuracy FVC, LST and NSSR are still needed. In addition to the point scale validation, cross comparison with other existing SSM products will be conducted in the future studies.

Urbanization leads to modifications of surface energy balance which governs the momentum, heat and mass transfer between urban canopy layer and the atmosphere, thus impacts dynamic processes in the urban ABL and ultimately influence the local, regional and even global climate. It is essential to obtain accurate urban ABL observations to enhance our understanding of land-atmosphere interaction process over the urban area and help to improve the prediction ability of numerical model. However, up to now, there are rarely observations in high-altitude cities. This poster introduced the urban flux observation conducted in a high-altitude city, Lhasa, using eddy-covariance technique and large aperture Scintillometer. As the first results, the diurnal patterns of the surface energy balance and energy partitioning in the winter of 2016 were discussed.

Lakes are an important part of the landscape on the Tibetan Plateau. The area that contains most of the plateau lakes has been expanding in recent years, but the impact of lakes on lake-atmosphere energy and water interactions is poorly understood and precise measurements of evaporation and understanding of the physical controls on turbulent heat flux over lakes at different time scales is rarely studied due to lack of observational data. To meet the above demands, an eddy covariance observational system was built above the water surface of the small Nam Co Lake (with an altitude of 4715 m and an area of approximately 1.4 km2, mean depth of 7 m) in April 2012 and the results are given by using data over ice free periods in 2012 and 2013 as follows: Firstly, the roughness length for momentum is 3.35×10-4 m over the small lake and the atmosphere is dominated by unstable and neutral conditions. The proper Charnock coefficient (α=0.031) and the roughness Reynolds number (R_r=0.56) for z_0m simulation are obtained for Bulk aerodynamic transfer model (B model) simulation. The simulated heat flux is validated independently with observations in 2013. The B model, with parameters optimized for the specific wave pattern in the small lake, could provide reliable and consistent results with EC measurements, and B model simulations are suitable for data interpolation due to inadequate footprint or malfunction of the EC instrument. Secondly, wind speed shows significance at half-hourly time scales, whereas water vapor and temperature gradients have higher correlations over daily and monthly time scales in lake-air turbulent heat exchange. Lastly, the total evaporation in this small lake (approximately 812 mm) is approximately 200 mm larger than that from adjacent Nam Co (approximately 627 mm) during their ice-free seasons. Moreover, the energy stored during April to June is mainly released during September to November, suggesting an energy balance closure value of 0.97 over the entire ice-free season. These results provide a foundation for application of remote sensing data over the high-altitude small lakes.

With contributions from: Markku Similä, Xi Zhang, Bernat Martinez, Jungang Yang, Jacqueline Boutin, Jin Wang, and their co-authors.

The project is divided into three major parts: (1) development of an algorithm for the retrieval of sea surface salinity based on combined active/passive microwave imagers; (2) data validation and oceanic application of new satellite altimeters and SWIM (“Surface Waves Investigation and Monitoring“, which is a scanning radar altimeter); and (3) devising techniques for sea ice parameter extraction and sea ice monitoring using data from most advanced satellite sensors.

The recent studies in part (1) deal with the development, evaluation and improvement of the sea surface salinity (SSS) retrieval algorithm under unfavorable conditions. A method for considering the effect of rain, implemented by the Chinese team, is based on L-band CAP (Combined Active-Passive) observations. The L-band GMFs (Geophysical Model Functions) are developed and the radiation characteristic of the rough sea surface is analyzed for rain-free and rainy conditions, respectively. Using this approach, the effect of rain-induced roughness can be corrected when calculating the SSS.

The objective of part (2) is the identification of eddies and their spatial-temporal variation characteristics on the Chinese seas using radar altimeters. The recent work of the European team is structured as a three-step approach: (a) improvement of retracker algorithms for the European altimeter missions, (b) development of geophysical corrections adapted to coastal zones, in particular focussing on the wet troposphere, (c) computations of geostrophic currents and derivation of mesoscale eddies. The Chinese partners recently have been working on inter-comparisons of data from Sentinel-3 SRAL, HY-2A RA, and Jason-2. The accuracy of, e. g., significant wave height retrievals as a function of the distance from the coast is analysed. The new algorithms shall be evaluated and validated in the next phases of the project (2018-2019) using in-situ and other reference data.

The work on sea ice monitoring (part 3) has been focussed on (a) the use of radar altimetry and SAR images for calculating ice thickness and sea ice concentration, and (b) a feasibility study concerning the performance of single-pass interferometric SAR for the retrieval of sea ice surface topography. The Chinese team, with contributions from the European partners, developed a new algorithm for retrieving the sea ice freeboard based on a new approximation of the echo waveform. This method resulted in more accurate freeboard estimates. A European group evaluated the achievable accuracy of ice surface height variations for different satellite InSAR configurations and analysed Tandem-X data acquired over sea ice as an example. Another Sino-European team concentrated on the determination of sea ice concentration and thickness from RS-2 ScanSAR images obtained over the Bohai Sea in winter 2012/2013.

In this introductory talk we will provide a brief overview of the different activities, which then will be described in more detail in subsequent presentations.

ESA’s Sentinel-3 mission was successfully launched in February 2016. It carries a new altimeter-SAR Radar Altimeter (SRAL) which works on two modes of Low-Resolution Mode (LRM) and SAR mode. SRAL improves the along-track resolution (approximately 300m) in SAR mode using a delay/Doppler technique. SRAL is expected to provide even better measurements of sea surface height, significant wave height and wind speed than the conventional altimetry, especially in the coastal zone. In addition, Chinese first satellite altimeter-HY-2A Radar Altimeter (RA) has been in orbit more than 4 years, and Sentinel-3 SRAL and HY-2A RA are Simultaneous in orbit currently. In this study, sea surface height data of Sentinel-3 SRAL are analyzed by the comparison of the distribution and time series variability of SLA data between the different altimeters (Sentinel-3 SRAL, HY-2A RA, Jason-2) data and tide gauge data in the China Sea. Significant wave height data of SRAL are evaluated by the comparison with buoys data in the China Sea. The performance of SRAL observation over the coastal regions is analyzed. The accuracy and reliability of SRAL data are analyzed in the different locations with the different distances to the coast. Finally, the preliminary performance of Sentinel-3 SRAL and the evaluation of HY-2A RA in the China Sea are summarized.

The sea surface salinity (SSS) is one of the key parameter for scientific community to understanding the ocean better. Equipped with an L-band radiometer, SMOS and Aquarius provide an unprecedented SSS data set of the global oceans. Enormous efforts are devoted to the development, evaluation and improvement of the SSS retrieval algorithm especially under some unfavorable conditions, i.e., the rain. Rain drops induce freshening and roughness effect to the sea surface. The fact that both mechanisms causing TB to increase makes it challenging to retrieval sea surface salinity when it rains. This presentation describes a method to retrieval the SSS under the rainy conditions based on the L-band CAP (Combined Active-Passive) observations. The L-band GMFs (Geophysical Model Functions) are developed and the radiation characteristic of the rough sea surface is analyzed for the rain free and rainy conditions respectively. The excess emissivity of H/V polarization is found to rise as the rain rate increases with a slope of 0.0003/mm·h^-1, which means a 1-psu error at the rain rate of 10mm/h. The dependence of the sea surface emissivity (sensitive to both roughness and freshening) on the backscatter (only sensitive to roughness) is obtained and the rain-induced roughness effect is corrected. The bias of retrieved SSS shows no clear dependence on the rain rate and the standard deviation of SSS error is about 0.5psu. The above results confirm the feasibility of this new retrieval algorithm for the SSS remote sensing in the rainy weather with the CAP observations.

Scientists from the Chinese National Satellite Ocean Application Service (NSOAS) and the Finnish Meteorological Institute (FMI) have jointly studied two fundamental sea ice parameters, sea ice concentration (SIC) and sea ice thickness (SIT) in the Bohai Sea. The case study was motivated by the risks the sea ice can cause for off-shore activities. Although the ice season is relatively short, usually from December to March, it can cause damage even in mild winters. On average level-ice thickness varies from 20 to 40 cm depending on the weather conditions.

We targeted the winter of 2012–2013 due to the availability of RADARSAT-2 (RS-2) ScanSAR imagery over the Bohai Sea. Our approach was to utilize several satellite sensors to create SIC and SIT charts.

The data set at our disposal consisted of 11 RS-2 SAR HH/HV images, daily AMSR2 imagery, four MODIS images and 31 in-situ measurements collected from the oil field platforms during the period from 2 January to 19 February 2013.

Basis for the calculations was the segmentation of SAR images using the Iterated Conditional Mode optimization and the extraction of different segment-wise features from them. The following texture features turned out to be the most useful in this connection: entropy, HH-polarization spatial autocorrelation, two quantities describing the shape of the variogram and HH-polarized corner points. These features were utilized in the SAR based SIC estimation. The scaled entropy alone yielded the best results in the SIT estimation.

The selection of the features in the SIC estimates was performed automatically by searching through all feature combinations and minimizing the residual error sum. Two different methods were tested: a linear model and a nonlinear Multi-Layer Perceptron neural network. Both approaches provided good results for very low or very high ice concentrations. For this data set, the linear model performed better. As a reference data we have used the in-situ measurements, the MODIS based SIC charts and the optical HJ-1B image.

The total ice volume in the study area was estimated using the thermodynamic sea ice model HIGHTSI with atmospheric boundary layer forcing (the reanalyzed ECMWF data). The ice drift was taken into account using the AMSR2 based ASI SIC chart with a resolution of 3.125 km. The ASI SIC chart was adjusted for the Bohai Sea conditions by the University of Bremen. The spatial distribution of the HIGHTSI SIT model field was then improved using statistics calculated from the AMSR2 data. The result was interpolated into a 1 km spatial grid and used as the background field h_B for the SAR based SIT estimation.

The background field and the SAR features were combined using a liner model that included a modulation term between h_B and each feature. Also here the minimization of the residual sum was the objective criterion in the feature selection. Somewhat surprisingly only a single feature, the scaled entropy, gave the best estimation results. As a reference data we used the MODIS based ice thickness chart as well as the field measurements.

The approach applied in this study has potential to be implemented operationally for the Bohai Sea ice service. However, more in-situ measurements as well as tuning the estimation model parameters are necessary, because the current study covers only one winter season. The obtained results should be regarded as guidelines for further research

Altimeter waveform retracking correction is essential to get accurate sea ice freeboard. Some empirical fitting methods have been proposed, and these methods simulate the waveform by fitting to echo and empirically positioning the retracking point. In this paper, we develop a new method to retrack lead elevation by simulating the lead echo waveform using a composite cubic Bezier curve which is stable. The lead waveform is first divided into several segments, for each segment, the cubic Bezier curve is used to simulate the waveform. For ice, an improved offset center of gravity (OCOG) method is used. A new sea ice freeboard retrieval algorithm by using Cryosat-2 SAR-mode data is then performed combining the Bezier curve waveform fitting and an improved OCOG method.

The sea ice freeboard is calculated in following steps. The first step is to discriminate sea surface and the ice. The discrimination is based on the fact that the shape variation in echo waveform depending on whether the echo is dominated by specular reflections from leads, or by diffuses reflections from ice. The pulse peakiness (PP) and the stack standard deviation (SSD) parameters are used to discriminate the ice/water type. Returns from leads are identified by PP > 18 and a SSD<4, while echoes from ice floes are identified by PP < 9 and SSD > 4. Secondly, for echoes from leads, we use a more sophisticated Bezier curve to fit the echo to get retracking point, and the retracking point is set where rise reached 70% of the waveform maximum. For echoes from ice floes, a modified OCOG is used, and the retracking point is positioned at the point where the rise reaches 95% of the computed OCOG amplitude. Thirdly, to obtain an accurate freeboard, we obtain local sea level height as shown followed. We use a linear interpolation on the difference between lead elevations and mean sea surface height (MSS) for each Cryosat-2 track, and then yield the sea surface anomaly (SSA, the deviation between the actual sea surface elevation and the MSS). At last, the sea ice freeboard can be retrieved by sea ice surface elevations minus MSS and SSA.

We directly compare the freeboard retrievals by proposed method and L2I products of CryoSat-2 to IceBridge data. A mean bias of 1.3cm was found with the uncertainty of 0.025m which is a latitude-dependent gradient. For two IceBridge campaign periods in March 2015 and April 2016, mean differences of 1.57 and 1.09cm are for the freeboard retrievals by proposed method, while mean differences of 1.75 and 1.84cm are found when using Cryosat-2 L2I products. This suggests the proposed method is capable of reconciling the sea ice freeboard from radar altimetry data sets with a high accuracy.

Ocean wave is a kind of fluctuation caused by the wind in the ocean. The ocean waves are very complex phenomena, the study of the ocean waves is of great significance on the marine engineering, marine development, transportation and shipping, marine fishing and aquaculture and other activities. In-situ observations, satellite remote sensing and numerical models are the important means of obtaining ocean waves information. Especially, satellite remote sensing is the important method of obtaining global ocean waves information synchronously. In this study, the significant wave height (SWH) of ocean waves obtained by T/P, Jason-1/2, ENVISAT, Cryosat-2 and HY-2A satellite altimeter and ENVISAT ASAR wave spectrum are used to generate the global ocean wave remote sensing data of 2000~2015 with the spatial and temporal resolution of 0.25° and one day. Firstly, all satellite data are validated and corrected by the comparison between them and the National Data Buoy Center (NDBC) buoys data. Then global ocean wave remote sensing data are obtained by the inverse distance weighting method. Finally, the resulting data are evaluated by the buoys data.

In this paper, sea-ice radial drift is studied based on the single-look complex (SLC) data of Sentinel-1A/B SAR. The method for sea-ice drift retrieval is developed using Doppler shift. The estimated Doppler frequency and predicted geometric Doppler shift are calculated for each unit of the Doppler grid, then the Doppler centroid anomaly can be obtained. According to the analysis of the uncertainties from the orbit, attitude, antenna pattern, topography, etc., the error in the Doppler centroid anomaly can be eliminated as far as possible to acquire the standard Doppler centroid anomaly. Furthermore, the standard Doppler centroid anomaly is converted to sea-ice radial drift velocity. Finally, the developed method will be validated through the comparison with not only a conventional cross-correlation method, but also measurements from a drifting ice buoy.

HY-2A is the first satellite mission for the dynamic environmental parameters measurements of China which has been launched successfully on August 16th, 2011. The multi-bands scanning microwave radiometer (RM) is one of the key sensors onboard the HY-2A satellite with the primary objective of measuring SST, surface wind speed, water vapor and cloud liquid content from space. On the basis of HY-2A RM observations, the sensitivity of some brightness temperature (TB) channels to the rain rate and the wind speed are analyzed. Two TB combinations which show minor sensitivity to rain are obtained. Meanwhile, the sensitivity of the TB combination to the wind speed is even better to the original TB channel. Based on these TB combinations, a wind speed retrieval algorithm is developed and validated. The wind speed retrieval accuracy is better than 2 m/s for rainy conditions, which is evidently superior to the HY-2A RM standard product.

Sea ice is not only an important part of the global climate system, but also affects the development of oil ,gas and mineral resources in the Arctic. In addition, the sea ice can affect the perforation of the "Arctic Waterway" and cause harm to production activities such as sea-related production and maritime traffic. That monitor the sea ice drift and obtain accurate sea ice drift direction and speed is of great significance to the study of climate analysis, safe navigation of ships and management of offshore oil platform.

At present, all the study of sea ice drift monitoring is based on the intensity information of SAR satellite image. However, due to the influence of speckle noise, the Algorithms of ice motion monitoring could not work well. With the development of synthetic aperture radar (SAR) technology, the texture have been shown to greatly improve the classification ability of sea ice with SAR image. Therefore, the texture of sea ice SAR image is expected to improve the sea ice drift detection capability.

Based on the above, The Sentinel-1 SAR data were utilized to detect and analyze the strengthen ability of sea ice drift monitoring by using the SAR image texture. Eight kinds of texture features such as contrast, correlation, dissimilarity, entropy, mean were extracted from Sentinel-1 SAR data. A total of 66 sea ice samples which were divided into new ice, young ice and first year ice three types were selected for the experiment. First, normalized cross-correlation method is used to evaluate whether the texture is suitable for sea ice drift monitoring by comparing the following four results: match position is correct or not, the ratio of the maximum value and the second value of match results, the ratio of the maximum value and the mean value of match results, and the ratio of the maximum value and the triple variance of match results. In addition to that the effect of different sea ice types and resolution on the correctness of matching is analyzed from the results.

Then, the SURF method is used to evaluate the sea ice by comparing the following three results: the matching accuracy rate of from SAR image and eight texture, the correct matching logarithm of feature point, and the accuracy of correct matching feature pairs. The use of the SURF method for sea ice drift monitoring can produce many misaligned feature pairs, we use the following ways to determine the feature pairs is correct or not: The approximate velocity and direction of the sea ice drift are determined by artificial visual judgment, and then the velocity and direction calculated by the SURF feature point are considered correct which is within the error range of the approximate velocity and direction. The experimental results show that the texture feature is more suitable for the sea ice drift monitoring than the SAR image itself.

Ship surveillance plays an important role in maritime traffic control, shipping safety, fishery supervision, maritime accident rescue, and oceanic rights protection. Synthetic Aperture Radar (SAR) has been widely used in ship surveillance as it has a full day, all-weather imaging capabilities. A great deal of research has been done on vessel detection using SAR; however, it is still difficult to detect the "weak" target under terrible sea conditions. The "weak" target with low target-sea contrast (TSC) is easy to be lost, and the existence of strong sea clutter can cause false alarm target. Therefore, this paper mainly focuses on the detection of "weak" vessels with polarimetric SAR.

1) High-resolution SAR sensors have a wide azimuth beam width, as well as a large range bandwidth. During SAR image formation, multiple squint angles and radar wavelengths are integrated to synthesize the full resolution SAR image. Based on this principle, the original single-look complex image SAR data was decomposed into different sub-aperture images in azimuth direction and sub-band images in range direction through time-frequency decomposition method. The scattering difference between the vessel and the ocean in the sub-aperture images or sub-band images is studied. We found that the vessel targets had coherence attributes between different sub-apertures, but the sea surface is significant differences and exists decoherence effect.

2) The complex coherence product of the sub-images polarimetric SAR is introduced and a plurality of sub images are formed into image pairs similar to the interferogram. Polarization coherent optimal parameter named PSCO (polarmetric SAR sub-aperture /spectral coherence optimal) is constructed by combining multiple sub images pairs and the concept of permanent scatterers’ detection in polarimetric interferometry. The performance of PSCO is tested using RADARSAT-2 quad-pol data. By comparing the enhancement ability of ship-sea contrast, the ability of clutter suppression and the calculation time, we choose 3 as the number of sub-images for PSCO. The CA-CFAR method is used to detect the ship for PSCO, and compared with CA-CFAR method based on HV polarization. The results show that the proposed method can suppress the sea clutter well and improve the detection performance. This method is suitable for terrible sea conditions, strong clutter and other complex sea background for vessel detection.

Internal waves occur almost everywhere on the shelves and slope. The generation and propagation of internal waves are closely related to the ocean bottom topography, tidal current, large-scale circulation and stratification. Therefore, internal waves have an obvious local property which shows different characteristics in different areas. Remote sensing data has been widely used in the temporal-spatial distributions, generation and evolution, parameter inversion of the internal waves and is the best instrumentality for detection of internal waves on a near-global scale. The MODIS imagery owns the advantages of large swath area and near-daily global coverage, but influenced by the weather greatly. SAR has the ability of all-weather and day-and-night observation, although data coverage is limited. This paper combines SAR and MODIS images effectively to observe internal waves on a near-global scale. The ASAR and MODIS imagery on global scale over the period of 2011 was processed. The distribution of internal waves is presented by extracting crests of internal waves. Regions of internal waves are frequently observed of Pacific, Indian Ocean and Atlantic of the internal waves are presented. The further analysis of the scale, propagation law and the temporal-spatial distributions characteristics of the internal waves in the typical occurrence area are also conducted.

In this paper, a support vector machines (SVM) regression model is proposed to extract integral ocean wave parameters such as significant wave height (SWH) and mean wave period (MWP) from the ASAR wave mode images. Calibrated ASAR wave images can be applied directly to retrieve SWH and MWP without prior information. The model was established based on the nonlinear relationship between the sigma0, the variance of the normalized SAR image, SAR image spectrum spectral decomposition parameters, SWH and MWP. The input parameters of the SVM regression model are feature parameters extracted from ASAR images and the SWH provided by European Centre for medium range weather forecasts (ECMWF) is the output. A global data set of 30771 pairs of ASAR wave mode images and collocated ERA-Interim data from ECMWF is used to train SVM model. Based on the matching dataset, the particle swarm optimization (PSO) algorithm is applied to optimize the input kernel parameters of the SVM regression model and establish the SVM model. The SWH extracted by this model was compared with the ERA-Interim data and the buoy data. The RMSE of SWH is 0.34m and 0.48m and the correlation is 0.94 and 0.81, respectively. The MWP was also validated by ERA-Interim data and buoy data, the RMSE is 0.68s and 1.08s, and the Scatter Index is 0.04 and 0.09, respectively. The results show that the SVM regression model is an effective method to extract SWH from SAR data. The advantage of this model is that SAR data may serve as an independent data sources to extract SWH, which can avoid the complicated solution process of wave spectrum.

Abstract：As a kind of marine natural disaster, Green Tide has been appearing every year along the Qingdao Coast, bringing great loss to this region, since the large-scale bloom in 2008. Therefore, it is of great value to obtain the real time dynamic information about green tide distribution. In this paper, methods of optical remote sensing and microwave remote sensing are employed in Green Tide Monitoring Research. A specific remote sensing data processing flow and a green tide information extraction algorithm are designed, according to the optical and microwave data of different characteristics. In the aspect of green tide spatial distribution information extraction, an automatic extraction algorithm of green tide distribution boundaries is designed based on the principle of morphology dilation/erosion. And key issues in information extraction, including the division of green tide regions, the obtaining of basic distributions, the limitation of distribution boundary, and the elimination of islands, have been solved. The automatic generation of green tide distribution boundaries from the results of remote sensing information extraction is realized. Finally, a green tide monitoring system is built based on IDL/GIS secondary development in the integrated environment of RS and GIS, achieving the integration of RS monitoring and information extraction.

A series of oil spill accidents has occurred frequently with the development of petroleum industry and marine oil transportation,which lead to serious oil pollution.For instance,the oil spill in Penglai,China 19-3 oil field and Dalian,Xingang,China has caused great ecological and economic losses,Therefore,it is meaningful for monitoring oil spill information in real time to prevent oil spill disasters.Based on the multi-source Synthetic Aperture Radar(SAR)image data,this paper has carried out research on the remote sensing monitoring of oil spill,and the operational monitoring system of marine oil spill based on Geographic Information System(GIS)is developed,which realize the integration of preprocessing multi-source remote sensing image data,extracting oil spill monitoring information,making oil spill thematic map and publishing oil spill monitoring reports.In order to realize the rapid processing of multi-source image data integration,the original data is analyzed based on Geospatial Data Abstraction Library(GDAL)open source raster spatial data conversion library and realized image reading,geometric correction and so on;the algorithm of multi-scale image segmentation and gray contrast characteristic extraction are encapsulated on the basis of the previous step,which achieve automatic processing of SAR image block,segmentation,oil spill identification,merging,parameter assignment,etc,the one-key processing of oil spill extraction is realized;for the application demand of oil spill monitoring,production of various kinds of standardized products, automatically add the elements of cartographic decoration elements,image parameters,oil spill area,the source of oil spill and other kinds of information,real-time generate thematic reports.

The Poyang Lake and Dongting Lake are Chinas two largest freshwater lakes. Located in the middle reaches of the Yangtze River catchment these large floodplain lakes are home to four Ramsar sites initiated by the UNESCO, to foster wetland conservation. The wetlands in and around the lakes provide numerous important ecosystem services for human well-being, e.g. freshwater resources, retention area for Yangtze River floods, buffer for drought events, natural habitats for millions of endemic and migratory birds, etc. However, anthropogenic influences and related degradation of the lakes wetlands have dramatically increased.

In the project presentation current advances and first results of EO data analyses will be exhibited. EO data, especially from the new European Sentinel-family available since 2014, provide high-resolution information about the Earth surface. Multi-sensor satellite data are used to generate time series for the assessment of water surface and wetland dynamics. Qualitative and quantitative analyses will provide insights into the changes on the Earth’s surface in and around the Yangtze flood plain lakes that have taken place due to anthropogenic influence during the last 10 to 15 years. The results show that: Both lakes have shown a shrinking trend in water surface extent. Wetlands are increasingly used for natural resources exploitation, e.g. sand mining on lake ground and the cultivation of economically important plants at lake shores.

Within the project duration the potential of newly available Sentinel-data in combination with historic satellite data (Landsat, Envisat, etc.) and Chinese satellite data will be demonstrated for the generation of longer and preferably consistent Earth observation time series.

The spatial and temporal variation characteristics of the inundation extent for a lake have a great influnce on landscape structure and function of wetland ecosystem. Poyang Lake is the largest freshwater lake in

China. Poyang Lake wetland is a very important wetland in the world for biodiversity conservation. It is very important to measure accurately the water surface dynamics of the Poyang Lake. In this paper, the scatterplot between lake level and MODIS-derived inundation area of the Poyang Lake was used as a starting point, and the uncertainty of inundation areas with lake water levels was discussed. The results showed that: (1) though a significant linear relationship was found for the water level and inundation area for the Poyang Lake, the water surface area shows uncertainty; (2) Water level in Poyang Lake is higher in the south and lower in the north when lake water level is low, and the spatial heterogeneity of water level was decreasing with lake level increasing; (3) Water level slope in Poyang Lake in the time period of water withdrawal was greater than that in flood period; (4) Affected by fishery practice by levees of dish-shaped sublakes, the water surface area of the sublakes in water withdrawal period is greater than that in flood period. Sand mining also changed the water extent around the sandpits when in low lake level. Therefore the inundation extent for Poyang Lake was affected by topography of lake basin, water discharge from the tributaries in Poyang Lake watershed, and the backwater effect of the Yangtze River, as well as with human activities such as sand mining and fishing practice with levees.

Atmospheric water vapour effects represent one of the major error sources of repeat-pass Interferometric Synthetic Aperture Radar (InSAR), and limit the accuracy of InSAR derived surface displacements. The spatio-temporal variations of atmospheric water vapour make it a challenge to measure small-amplitude surface displacements with InSAR. In previous studies, several InSAR atmospheric correction models have been successfully demonstrated: (1) Ground based correction models such as those using Global Navigation Satellite System (GNSS) observations. Such correction models are limited by the availability (and distribution) of ground observations. (2) Space based correction models including those involving NASA Moderate Resolution Imaging Spectroradiometer (MODIS) and/or ESA Medium Resolution Imaging Spectrometer (MERIS). They are sensitive to the presence of clouds and there might be a time difference between space based water vapour and radar observations. (3) Numerical Weather Model (NWM) based correction models including those using European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim and/or Weather Research and Forecasting (WRF). Similar to space based correction models, there might be a time difference between NWM and radar observations. Taking into account the inherited advatanges and limitations of GNSS, MODIS and ECMWF water vapour products, we present a global and near-real-time InSAR atmospheric correction model in this paper.

Tropospheric delays can be routinely retrieved from ground based GNSS arrays in all-weather conditions and also in real-time. We develop an Iterative Tropospheric Decomposition (ITD) interpolation model that decouples the total tropospheric delays into (i) a stratified component highly correlated with topography therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. The decoupled interpolation model can then be employed to generate improved dense tropospheric delay maps compared with previsous GNSS-based models. In order to deal with areas with limited (or no) GNSS stations, we introduce the operational high resolution ECMWF (HRES-ECMWF, ~16 km), available near real-time, as well as MODIS near IR water vapour data whenever available as constrains of the ITD model, which makes the correction model globally available in all-weather conditions at any time for the first time. The applications of the ITD model to Sentinel-1 interferograms show that approximately 68%-78% of noise reduction can be achieved.

Foundation: National Science Foundation of China (No.41374077)

The first Control Source Extremely Low Frequency (CSELF) network has been built recently under the support of National Development and Reform Commission of China, which distributed in the Beijing Capital Area (BCA) and Southern Section of South North Seismic Belt (SNSB) in China for earthquake monitoring study. The network can be a part of earthquake stereoscopic monitoring system when it is combined with the satellite observation.

The network can not only receive the natural electromagnetic signal but also the artificial electromagnetic signal from the powered transmitter. A experiment of the system has been performed during 2016. The powered artificial electromagnetic signals are transmitted from 5:00 to 7:00 and from 17:00 to 19:00(GMT+8) every day. The signals at 4 different frequencies (216, 63, 12.3, 3.46 Hz) are transmitted and recorded. The natural electromagnetic signal from 1000Hz to 1000s are recorded continuously. The five electromagnetic components (North-South electric field :Ex, East-West electric field: Ey, North-South magnetic field: Hx, East-West magnetic field: Hy, and vertical magnetic field：Hz) are measured at each station of the network. The spectra of each component, impedance tensor, apparent resistivity and Impedance phase etc. are calculated using the similar software to MT data processing software. The original time series and the preliminarily processed results are transferred to the data center in the Institute of Geology, China Earthquake Administration through the CEA intranet. The further data processing and analysis are carried out in the institute for earthquake monitor study.

The artificial source electromagnetic signal is analyzed in both time and frequency domain. The adaptive filtering method was used to the raw time series data to extract the target frequency’s signal. The preliminary result showed that the amplitudes of the electromagnetic field of the artificial signals are obviously bigger than those of the natural signal. The power spectral density of the artificial signals are about 1-2 decades bigger than the natural signals for the same frequencies. The polarization characteristics of the electric and the magnetic field are studied for both source signals and the relationship between them are studied.,

In addition to the study in the feature of the artificial source electromagnetic field, we are making a tentative research on the relationship between the electromagnetic variation and the earthquake events. Some anomalies before and after Jinggu M5.9 earthquake (Dec.6, 2014) appeared in the observed data at Jinggu station for recorded natural signals. The spectrum variations appeared before and after Litang M5.1 earthquake (Sep. 23,2016) in the observed data at Jinggu station for recorded artificial signals.

Spaceborne InSAR has been a well-known established technique since the first Earth-observing SAR satellite ERS-1 was launched on 17 July 1991. Cross-track InSAR can produce a digital elevation model (DEM), and differential InSAR (DInSAR) is able to measure crustal movement and deformation caused by, for example, subsidence, landslide, earthquake, volcanic, and glacier flows. Today, Synthetic Aperture Radar (SAR) data are acquired globally from many modern satellites: Sentinel-1 operated by the European Space Agency, ALOS-2 operated by the National Space Development Agency of Japan, Radarsat-2 operated by the Canadian Space Agency, TerraSAR-X and TanDEM-X operated by the German Space Agency, and the COSMO-SkyMed constellation operated by the Italian Space Agency.

Gaofen 3 (GF-3), as a Chinese ocean surveillance satellite, was launched from the Taiyuan Satellite Launch Centre on 10 August 2016, and has been in operation since January, 2017. It carries a multi-polarized C-band SAR sensor and operates in 12 working modes, capable of imaging Earth’s surface from high-resolution (1 m) to extremely-wide-swath (650 km). The advanced technological criteria of GF-3 satellite ensure high-quality SAR images, providing an opportunity for Chinese SAR interferometry (InSAR) study.

This work aims to verify interferometric ability of the level 1 SLC data and discuss the optional InSAR processing strategy for GF-3 satellite. Sample SAR data in strip map mode were collected in Tianjin and Shanghai to the InSAR test operations, and post-processed precise orbits are used to improve the coregistration. First, the azimuth offsets between azimuth spectra sub-looking images are investigated to confirm the SLC focusing quality. Second, DEM assisted coregistration (Arikan, M., 2007) is compared with the traditional polynomial method. The DEM assisted coregistration relies on the precise orbit, and it shows better coherence for GF-3 InSAR processing even in smooth topographic areas. By comparing the GF-3 interferogram with S1A result in Shanghai, an area of about 1 x 1 km are confirmed to be subsidence. The test results verify that GF-3 SAR data are capable in InSAR application of measuring ground movements, while continuous data acquisition and near real time precise orbit are necessary for scientific and engineering application in the future.

Arikan, M., van Leijen, F., Guang, L. and Hanssen, R.F., 2007, November. Improved image alignment under the influence of elevation. In Proceedings of FRINGE.

3D SAR Tomography (TomoSAR) [1-4] and 4D SAR Differential Tomography (Diff-TomoSAR) [8-14] exploit multi-baseline SAR data stacks to create an important new innovation of SAR Interferometry, to sense complex scenes with multiple scatterers mapped into the same SAR cell. In addition to the 3-D shape reconstruction and deformation solution in complex urban/infrastructure areas [2,4], and recent cryospheric ice investigations [5], emerging tomographic remote sensing applications include forest scenarios [3,6,7], e.g. tree height and biomass estimation, sub-canopy topographic mapping, and even search, rescue and surveillance. However, these scenes are characterized by temporal decorrelation of scatterers, orbital, tropospheric and ionospheric phase distortion and an open issue regarding possible height blurring and accuracy losses for TomoSAR applications particularly in densely vegetated mountainous rural areas. Thus, it is important to extend characterisations of temporal decorrelation, orbital, tropospheric and ionospheric phase distortion.

We report here on 3D imaging (especially in vertical layers) over densely vegetated mountainous rural areas using 3-D SAR imaging (SAR tomography) derived from data stacks of X-band COSMO-SkyMed Spotlight and L band ALOS-1 PALSAR data stacks over Dujiangyan Dam, Sichuan, China. The new TanDEM-X 12m DEM is being used to assist co - registration of all the data stacks first. Then, atmospheric correction is being assessed using weather model data such as ERA-I, MERRA, MERRA-2, WRF; Linear phase-topography correction and MODIS spectrometer correction will be compared and ionospheric correction methods are discussed to remove tropospheric and ionospheric delay. Then the new TomoSAR method with the TanDEM-X 12m DEM is described to obtain the number of scatterers inside each pixel, the scattering amplitude and phase of each scatterer and finally extract tomograms (imaging), their 3D positions and motion parameters (deformation). A progress report will be shown on these different aspects.

This work is partially supported by the CSC and UCL MAPS Dean prize through a PhD studentship at UCL-MSSL.

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A 6.4-magnitude earthquake occurred near Pishan County on 3^rd July, 2015. The epicenter was recorded at 37.459°N, 78.154°E, according to the USGS. The moment tensor solution from the USGS indicates that the earthquake was the result of a reverse fault rupture on a south-dipping fault (United States Geological Survey, 2015). This region is affected by the south-north converging India-Eurasia collision. The continental collision of the India and Eurasia plates is associated with a relative convergence rate of 40-50 mm/yr (Liu J. et al., 2015, Liang and Gan, 2013). Northward underthrusting of India beneath Eurasia has led to the development of the west Kunlun orogens and generates numerous earthquakes which consequently make this area one of the most seismically hazardous regions on Earth (United States Geological Survey, 2015). Using Synthetic Aperture Radar interferometry (InSAR), we mapped the near-field surface displacement of this event to better characterize, the seismic source parameters. Analysis of the interferograms obtained during ascending and descending orbits of the Sentinel-1A satellite in IW mode and modeling using a two-step inversion strategy suggest that this event involved thrust motion on a south-dipping fault. The best-fit slip model in the inversion suggests that the majority of the coseismic slip was concentrated on a thrust fault with a strike of 112°, a dip of 25° and an average rake angle of 89°. The maximum slip was ~1.2 m at a depth of ~12.5 km. The accumulative seismic moment was up to 4.5x10¹⁸ N×m, which is equivalent to a magnitude of Mw 6.4. The InSAR results supplied near-field geodetic measurements and provided independent constraints on the source parameters of this rupture.

In April 25, 2015, a strong earthquake occurred about 80 kilometers northwest of Kathmandu, the capital of Nepal. The surface wave magnitude measured by China Earthquake Network Center is Ms8.1 (http://news.ceic.ac.cn/CC20150425141126.html), and the moment magnitude calculated by the Harvard University CMT based on the focal mechanism is Mw7.9 (http://www.globalcmt.org/CMTsearch.html). And the magnitude of the Nepal earthquake is similar to that of the Wenchuan earthquake on the eastern boundary of the Tibetan Plateau in May 12, 2008. After the main shock, two aftershocks greater than magnitude seven broke out. The earthquake affected many parts of Nepal, Tibet, India, Chinese Bangladesh, Bhutan, caused a total of more than 30000 casualties. The earthquake is a thrust type earthquake that occurred in the subduction zone of Himalaya since the 8 magnitude earthquake in 1934. Most areas of Nepal are located in the mountains region of southern Himalaya. Although located on a small fault basin, the capital Kathmandu is still on the hanging wall of the Himalaya fault zone. The special terrain and geomorphic conditions cause the loss of radar coherent signal energy, which is not conducive to InSAR deformation observation. In addition, because the earthquake occurred in the heavily forested areas, in order to reduce the effect of forest on electromagnetic waves, to achieve the monitoring of surface deformation caused by the earthquake, this paper uses ALOS2/PALSAR2 dual polarization data to study. The data is the synthetic aperture radar data acquired and processed by the PALSAR-2 sensor on the ALOS-2 satellite. The working band of the sensor is L band, and the polarization of the data used in this paper is HH/HV. In this paper, we use the synthetic aperture radar differential interferometry to obtain the partial coseismic deformation field of Nepal earthquake. The results show that when the revisit period is short, InSAR technology plays an important role in the region, provide the deformation information of high signal-to-noise ratio for the earthquake. The InSAR results revealed that the Kathmandu region was strongly uplifted during the earthquake, and the area is the maximum deformation area. Corresponding to it, large surface subsidence occurred on the north side of Kathmandu, and the deformation field is consistent with the characteristics of pure thrust type earthquakes. In addition, in order to make full use of the dual polarization characteristics of the data, on the basis of obtaining the seismic deformation, this paper studies the correlation of polarization images. It is found that the intensity of polarization image changes before and after the earthquake. And we make a simple evaluation of the building damage in Kathmandu area. The results show that the extreme value of seismic deformation occurs in the west of Kathmandu City, and the low value of the correlation of polarization image also appears in the area. Therefore, there exists spatial correlation between deformation and image correlation. The correlation distribution of different polarization images is not completely consistent, perhaps because of the different degree of damage to the building. It provides a new way to detect the seismic damage of buildings by using multi polarization images.

Outward growth and associated slip partitioning of the Tibetan Plateau is always a heated spot in the geosciences field worldwide. Dalbute fault zone is a rare transpressive fault along the northern margin of the Tibet, which plays an import role in absorbing the plateau’s northward expansion. And most importantly, the middle segmentation of the Dalbute fault zone is quite close to the Karamay City (less than 30 km in distance), a very important petroleum city in the Xinjiang Province, China. Therefore, the fault zone’s seismic activity has drawn the most consideration. GPS monitoring displays that, there occurs a sudden reduce (~5-8 mm/yr) in the northward velocities of the Tibet when cutting across the NE-SE-striking Dalbute fault zone. Previous researches attribute the rate drop to the fault’s over-thrusting. Except for the crustal thickening, we notice that the strike-slip directed displacement also takes part in the Tibet’s outward growth, like absorbing the northeastward extrusion of the Junggar Basin in the northern Tian Shan range. But this speculation lacks of quantification. Besides, whether the Heshituolegai basin, Tuoli basin, Baerluker Mountain are the termination tectonics of the Dalbute fault zone still remained unclear. We plan to apply radar images provided by the Dragon project to dig into these scientific questions. We use the Small Baseline PS-InSAR technique to quantify the slip rate field, faulting segmentation, seismic activity and the possible termination structures for the Dalbute fault zone. The slip partitioning mechanism between the strike-slip and thrusting submotions will also be constrained through the help of different flying azimuth (ascending and descending) of radar satellite and the verification from the campaign and permanent GPS measurements. This study is also a meaningful exploration for slip portioning mechanism among terminus of a transpressive fault arround the Tibet. This research will also provide some useful results for the future works on protecting against and mitigating earthquake disasters in the urban areas.

Synthetic aperture radar (SAR) can penetrate clouds and haze and obtain information on ground conditions at various times of day and under different weather conditions. Since the 1950s, SAR has been widely used in the fields of surface subsidence monitoring, topographic mapping, resource exploration, environmental remote sensing and military applications, etc. In recent years, with the rapid development of SAR technology, building change detection in SAR images has become a research hotspot, especially after an earthquake. SAR technology can overcome the effects of bad weather and obtain images rapidly after earthquakes.

Information on seismic damage to buildings in SAR images from different time phases, especially in post-earthquake SAR images, is easily disturbed by other factors that affect the accuracy of information discrimination. To identify and evaluate the distribution of seismic damage accurately and make full use of the abundant texture features in the SAR image, a method for texture feature change detection in SAR images based on the watershed segmentation algorithm is proposed in this paper. We calculate the omnidirectional texture values of 8 types of texture features based on gray level co-occurrence matrices (GLCMs) .Based on the optimization of texture feature parameters, the principal components of feature parameters are segmented using the watershed segmentation algorithm, and the feature object image is obtained. Conventional methods of change detection based on texture features usually take the pixel as the calculating unit. This method introduces the concept of object orientation and carries out the calculation of the difference map at the object level. Finally, the classification threshold values for different levels of seismic damage are selected, and the identification of building damage is achieved. Using ALOS data from before and after the 2010 Yushu earthquake as an example to verify the effectiveness of the method, the overall accuracy of the building extraction is 88.9%. Compared with pixel-based methods, methods based on gray features, and methods based on single texture features, it is shown that the proposed method is effective.

The method made a breakthrough in the following ways. (1)Taking the texture feature object as the unit used in the change detection algorithm, the concept of object orientation is introduced to change detection, which represents a break from the conventional change detection methods that use the pixel as the unit.(2) The watershed segmentation algorithm is applied to texture features based on statistics, which makes the segmentation more meaningful.

Earthquake is among the most catastrophic natural disasters which seriously threat people’s lives and property. Since most of deaths and injuries in earthquakes are primarily caused by building collapse, rapid and accurate detection of collapsed buildings in urban areas is vitally important to emergency rescue and damage assessment. However, it’s often difficult to achieve suitable pre-event SAR data due to the unexpectedness and suddenness of earthquakes.

The polarimetric SAR (PolSAR) is capable of measuring the amplitude and phase of backscattered signals in four combinations of polarization. Moreover, it is sensitive to the characteristics of target like shape, size, material, structure and orientation. These make it become a potential data source to researches on building collapse extraction by using only post-earthquake SAR image. Based on this, many researches have been conducted (Li et al., 2012; Zhao et al., 2013). One issue existing is the misidentification of collapsed buildings and intact buildings which are not parallel to the SAR flight path since the scattering mechanism of the oriented intact buildings change to volume scattering dominant and reflection asymmetric. To eliminate this deficiency, the optimum polarimetric contrast enhancement (OPCE) method (Yang et al., 2000) is introduced to identify the collapsed buildings (Zhang et al., 2015). Using this method, the contrast of the intact buildings and collapsed buildings is enhanced through rotating the transmitting and receiving polarimetric antenna states. However, polarimetric information is not considered when applying this method. Yang et al. (2004) extended the OPCE method and combined it with the entropy and two polarimetric similarities, i.e. generalized optimum polarimetric contrast enhancement (GOPCE).

In this paper, we propose a new building collapse identification method based on the GOPCE method and the corresponding process framework is also presented. Moreover, the homogeneity feature of the grey level co-occurrence matrix (GLCM) is introduced to modify the GOPCE method. The case study is Yushu county where a Ms 7.1 earthquake occurred on April 14th, 2010. One post-earthquake Radasat-2 PolSAR image acquired on April 21th is utilized to test the proposed methods. By comparing with the OPCE and GOPCE methods, the GOPCE combined with homogeneity method performs better and more collapsed buildings are correctly detected. The misclassification of collapsed buildings and oriented intact buildings is also reduced. Experiments show that our proposed method can meet both time efficiency and detection accuracy requirements of earthquake rescue.

Acknowledgement

This work is supported by the Dragon 4 Cooperation Program [32244] and the National Natural Science Foundation of China [41571337].

The 2008 Wenchuan earthquake resulted in thousands of geo-hazards including landslides, and debris flows. In this paper, we will attempt to use time series InSAR techniques to monitor the activities of two post-seismic geohazards, namely the Daguangbo landslide and the Wenjiagou debris flow.

Caused by the 2008 Wenchuan earthquake, the Daguangbao landslide is one of the largest landslides in the world. The whole mountaintop collapsed in the 2008 earthquake, leading to a height change up to 500 meters. TanDEM-X data is used to generate a high resolution post-seismic DEM in this paper. The high gradients of topographic errors and the decorrelation caused by vegetation in mountainous areas make the processing of Tandem-X data challenging. To solve this, we propose a re-flattening iterative method to generate a post-seismic DEM. 15 Sentinel SAR images were acquired during March 2015 to March 2016. The time series displacements of the Daguangbao landslide are obtained using our advanced InSAR TS+AEM method with the Sentinel-1 SAR images and high-resolution post-seismic TanDEM-X DEM. Four active zones are observed with a maximum displacement rate of 8 cm/year, suggesting that this landslide is still active even 8 years after the earthquake.

The Wenjiagou debris flow was the second largest landslide in the Wenchuan earthquake. The volume of the deposits is determined by comparing the post-seismic DEM derived from tandem-x data and the pre-seismic SRTM. In this site, a complex project has been set up to prevent potential debris flows by separating water and mud. Our InSAR results from Sentinel-1 observations (2015~2016) suggest that the source area of this debris flow is still active due to steep topography and rainfalls, whilst the project site and its downstream are stable. The impacts of this debris flow prevention project are to be discussed.

The Red River Fault (RRF) is a major strike-slip fault running about 1000 km from southeast Tibet to South China Sea. As a result of the collision of the India and Eurasian plates, the fault is complicated, the average displacement rate is 2 to 5 mm/year and decreases from north to south. Investigation of the fault deformation information is significant to study its dynamic pattern, however, the large topography variations make it difficult to collect ground observations using GNSS.

Interferometric Synthetic Aperture Radar (InSAR), as a valued geodetic tool, has been applied in mapping crustal deformation at the scale of hundreds of kilometres with a high spatial resolution (e.g. a few metres to tens of metres) over the past two decades. Sentinel-1A was launched in April 2014, Sentinel-1B in April 2016 and both have been collecting data routinely. In the RRF zone, Sentinel-1 data are being acquired every 12/24 days with both satellites. The small temporal baseline, together with small spatial baselines (i.e. orbital separations) greatly improve interferometric coherence at C-band. In addition, Sentinel-1 images cover a wide footprint, 250 km from near to far range in Interferometric Wide Swath (TOPS) mode. Since October 2014, there have been over 400 Sentinel-1 images collected from 4 descending and 3 ascending tracks covering the RRF zone. Also, over 1500 ALOS-1 images collected between 2007 and 2011 are available in this region, and ALOS-2 data are being systematically acquired since 2014. The long wavelength (L-band) of ALOS-1/2 ensures good coherence. All the above-mentioned factors make it now possible to use InSAR to monitor slow-slip crustal deformation in this region.

The SAR data are interferometrically processed using our automatic processing chain based on the InSAR Scientific Computing Environment (ISCE) software. The variable climate in RRF zone challenges InSAR observing and processing, we calibrate the interferograms for atmospheric water vapour using high-resolution ECMWF products. Finally, time series analysis is performed to determine the interseismic deformation rate of the RRF using the in-house InSAR time series inversion package (InSAR TS + AEM, Li et al. 2009). It includes an advanced network correction approach for residual orbital correction and an atmospheric phase screen estimation with a priori deformation model. The InSAR measurements will be discussed to implicate future seismic hazard in the RRF zone.

Li, Z., Fielding, E. J., Cross, P. 2009: Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake. IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, 9.

Conventional dInSAR techniques have been frequently used in the past for deformation mapping including the mapping of landslide activities. However, several difficulties arise when attempting to apply dInSAR in areas with steep slopes and rugged topography, high humidity and dense vegetation cover such as over the Three Gorges Region. In addition to these difficulties, it is shown that the maximum detectable displacement gradient of dInSAR can be exceeded in our case study area even when using the highest resolution TerraSAR-X data.

A sub-Pixel Offset Tracking approach (sPOT) is applied to monitor slow-moving landslides in densely vegetated and steep terrain. This approach is shown of being capable of measuring centimetre-level landslide rates by using natural scatterers in densely vegetated terrain in line with measurements derived from corner reflectors.

The potential and limitations of TSX-ST (TerraSAR-X Staring Spotlight) data on measuring surface deformation using dInSAR and offset tracking techniques are assessed through case studies on the southern banks of the Yangtze River, in particular whether the improvement of the resolution of Staring Spotlight mode helps to address some of the issues that were encountered previously.

In addition, we show how the TanDEM-X Coregistered Single look Slant range Complex (TDX CoSSC) data can be employed to produce a 6 m resolution DEM. The impact of using different sources of DEMs is then assessed on deformation measurements via offset tracking and dInSAR.

Finally, the relationship between landslide occurrence and possible hydrological driving factors is assessed to infer possible landslide mechanisms.

This work was partially supported by the China Scholarship Council (CSC) and UCL through a PhD studentship at UCL-MSSL.

For decades, crustal motion and surface deformation processes have been investigated with differential SAR Interferometry. This geodetic technique can lead to very good estimations of ground movement, when applied to co- and interseismic processes, land subsidence phenomena, landslides or volcanic motion with significant deformation magnitudes. However, its application still presents a challenge considering wide-scale, subtle ground movement that is hardly measurable with InSAR in the presence of often indistinguishable orbital, atmospheric or topographic noise.

Different SAR sensors such as ESA’s ERS-1/2, ESA’s Envisat ASAR, ESA’s Sentinel-1 and JAXA’s ALOS PALSAR are tested in this study to assess their capability to achieve the required accuracy in the interferometric phase for monitoring slow, low magnitude surface movements (in the low mm-level). This applies to, for example, observations of glacial isostatic uplift, interseismic strain accumulation or small subsidence processes.

The range of possible error sources, such as residual orbital artefacts or atmospheric water vapour, require to be addressed in order to allow the extraction of any subtle deformation signals. Their elimination from interferograms present the biggest challenge due to their ‘masking’ characteristic.

This study advances currently known time series inversion methods for deformation monitoring and mapping of natural hazards. Results from two InSAR time series approaches are compared. On the one hand, this comprises an improved time series inversion package developed at the University of Glasgow and Newcastle University (“InSAR TS+AEM”, Li et al. 2009), based on the more classical and well established Small Baseline approach. This includes an advanced network correction approach for residual orbital effects and an atmospheric phase screen estimation with an a priori deformation model. On the other hand, a new technique is tested for reducing image artefacts and to derive a time series from InSAR data: A combined approach of Principal Component Analysis and Independent Component Analysis aims to separate the desired ground deformation signal from unwanted noise in interferograms. The idea is to take advantage of the signals’ different spatial and temporal characteristics and to decompose the mixtures into statistically independent components in space and time to filter out geophysical deformation.

Li, Z., Fielding, E. J., Cross, P. 2009: Integration of InSAR Time-Series Analysis and Water-Vapor Correction for Mapping Postseismic Motion After the 2003 Bam (Iran) Earthquake. IEEE Transactions on Geoscience and Remote Sensing, Vol. 47, 9.

Damxung area is the place where strong earthquakes happen frequently, and the former studies have shown that there is a close relationship between strong earthquakes and active faults in this place, so it is necessary for us to study the distribution, geometric structure and motion characteristics of the faults if we want to know the initiation mechanism and seismogenic environment of the earthquakes. In this paper, by using a wide range of remote sensing data such as Landsat-7 ETM+, ALOS, GF-2, Sentinel-1 and DEM data, and utilizing a wide variety of image enhancement technology such as multiband color composite, PCA and ratio analysis based on these data, active fault information was extracted and the remote sensing interpretation marks about active faults were established, and finally, we displayed the the distribution and activity of the Yadong-Gulu fault and the Jiali fault in the study area. Our results have shown that: the Yadong-Gulu fault mainly consisted of normal faults and strike slip faults, and it could be divided into three parts. The north part of the Yadong-Gulu fault had direction toward NNE with part of it buried, and normal faults developed associating with strike slip faults. The middle part of the Yadong-Gulu fault had direction toward NE, and the fault was exposed, and the main faults of it were sinistral strike-slip normal faults. The south part of the Yadong-Gulu fault had a direction toward NNE, which then changed to NS on south, and the fault was partly buried with many secondary faults around it, and it mainly consisted of dextral strike-slip normal faults which had formed many graben basins. The Jiali fault was buried partly in the study area and could be divided into two branches, and it was dextral strike-slip normal fault. The wide existence of fault triangular facet, pull-apart basin and river break in the remote sensing images revealed that this area had a tectonic background characterizing by stretch and twist, which was mainly governed by upwelling movement on vertical direction and extension movement on horizontal direction of the middle Tibetan Plateau which was caused by the subduction of the India Plate. The remote sensing interpretation in this paper reflected the current characteristics of faults’ activities in the study area, and the characteristics of these activities had a close relationship with the earthquakes. What’s more, the results of this study also showed that enhancement processing upon remote sensing image could highlight some specific landforms and geological structure information, and the remote sensing image had unparalleled advantages compared with field geological investigation, and remote sensing technology had a bright prospect in geological investigation and geological disaster monitoring.

Abstract: The Qinghai Tibet Plateau is the world's youngest and most active plateau, due to the collision between the India plate and the Asian plate led to most of the region's fault zone is active, a lot of small earthquakes between Mw5.0 and Mw6.0 occurred every year, these small earthquakes can cause ground subsidence, influence in fault state. Based on the ENVISAT satellite data, the surface deformation caused by small Tibet earthquake were analyzed obtain the coseismic deformation field, comparative analysis the surrounding areas of land subsidence caused by the small earthquakes, and use the GPS data to verify, results showed that there was high consistency between the SAR data acquisition deformation and GPS measurement result.

Keywords: coseismic deformation, small earthquake, surface deformation

1. research status

The Qinghai Tibet Plateau is the world's youngest and most active plateau, with an average altitude of more than 5000 m, the main structural features currently are the results of the India plate and the Asian plate collision since the 50-60Ma. Because the impact time is new, tectonic collision and orogeny of the intact are save well, and many continental dynamic process after collision are continues, so the Tibetan Plateau is the most ideal place for the new structure research.

Qinghai Tibet Plateau is a strongly rising block surrounded by the surrounding active faults. The surrounding fracture surface tend to plateau interior, thus formed in the mountains around the edge of the plateau to plateau lowland obduction "coronary morphology structure". The type of peripheral plateau active tectonics dominated by fracture structure, its basic characteristics are the reverse fault internal fault dip plateau. The southern boundary of the Tibetan Plateau is the main boundary fault zone in Himalaya, the west adjacent to the Yika La Kunlun fault zone and the Pamir Plateau; the northern boundary along the northern margin of West Kunlun fault zone, the Altun fault and the northern margin of Qilian Mountains fault zone, curving to six mountain fault zone; the Eastern boundary along the Longmen Mountain Fault Zone, An’ninghe fault and Xiaojiang Fault with the extension of the twists and turns.

Select the Lhasa block as the study area, analysis the surface deformation of Mw5.0~6.0 earthquake in the study area, using the traditional two track difference method for data processing, the basic idea is to generate two pass interference using two images before and after of the surface change experimentation area, topographic information removed from the interferogram. Then can get the deformation information. The basic process is needed before the earthquake and after the earthquake SAR data and DEM data, the data before the earthquake as the main image formed interferogram with the post earthquake data, simulated interferogram using DEM, the simulated interferogram is subtracted from the interferogram by SAR data, then form the differential interferogram. The advantage of this method is that it does not need the phase unwrapping of the interferogram to avoid the difficulty of understanding, but also can obtain the precision of the deformation results.

2. research significance

The Qinghai Tibet Plateau is an earthquake prone area, especially some small earthquakes (Mw5.0~6.0). These earthquakes release the earth's crust stress, reduce the probability of strong earthquakes in the fault, and effectively alleviate the seismic risk in the region. At the same time, through the study of the mechanism of the occurrence of small earthquakes, we can obtain the geophysical parameters. It provides valuable information for the assessment of regional seismic hazard.

Study on deformation field of small earthquakes in Lhasa block since 90s of last century using InSAR technique. In March 24, 2010 the Tibet area (N32.51 degrees, E92.83 degrees) a Mw5.6 earthquake as an example, using the traditional differential method pass interference to obtain the coseismic deformation field of the earthquake, coseismic interferograms obtained using multiple sets of different seismic data, through data analysis to obtain the coseismic displacement of the interferometric phase, clear surface displacement caused by the earthquake. At the same time, the use of GPS data to verify the accuracy of the result, inverse the fault parameters based on coseismic deformation field and GPS data, to obtained the detailed parameters of fault, which can provide the basis for the subsequent study of fault and the mechanism of earthquake.

This work will report the studies undertaken in the past year, which is aimed to developing viable methods and techniques for detecting anomalies from space and terrestrial electromagnetic data that are observed by the SWARM satellite and the network of the Control Source Extremely Low Frequency (CSELF) in China and investigating the correlation between anomalies and earthquakes. We have developed an effective algorithm for detecting anomalies from time series data and evaluated them over benchmark datasets, as well as preliminarily on electromagnetic data observed by the Swarm satellites and by the CSELF. We will present a number of issues related to the Swarm satellite data, the methods required to process the data, and finally present a comparative case study of the Jingpu earthquake using the Swarm and CSELF data.

Within the framework of the DRAGON project, the Institute of Electronics, Chinese Academy of Sciences (IECAS) continuously had a tight collaboration with the European and the Chinese partners. Joint research is around the 3 scientific topics: hybrid-polarity (HP) architecture, vegetation classification, and multi-aspect polarimeric scattering mechanism.
As to the study on hybrid-polarity (HP) architecture, an improved version of the HP architecture is proposed in order to overcome the two implementation difficulties concerning calibration issue and transmit configuration. Polarimetric SAR (PolSAR) systems based on this improved HP architecture do not only have mitigated transmit distortions through a pre-distortion technique, but also have the ability to transmit arbitrary polarizations, thus supporting all dual- and quad-polarimetric modes which uses orthogonal linear polarization basis in reception. Here, the supported dual-polarimetric modes include the circular transmit linear receive (CTLR) mode and π/4 mode of compact polarimetry. A prototype system has been built for further experimental verifications and experiments.
In the aspect of polarimetric classification, a supervised PolSAR image classification based on nearest-regularized subspace (NRS) and the vegetation classification based on the decision tree classifier are respectively studied. NRS is a representation-based classification approach. The polarimetric SAR feature space is constructed by the components of different target decomposition algorithms for each pixel, including those scattering components of Freeman, Huynen, Krogager, Yamaguchi, Arii decomposition, as well as the eigenvalues, eigenvectors and their consequential parameters such as entropy, anisotropy and mean scattering angle. Furthermore, because that all these representation-based methods were originally designed to be pixel-wise classifiers which only consider the polarimetric features while ignoring the spatial-contextual information, Markov Random Field (MRF) is also introduced into our scheme. Preliminary experiments display that the proposed NRS-MRF method outperforms other compared approaches with few training percent, including SVM, NRS and SVM-MRF. For vegetation classification applications, in order to make full use of PolSAR features’ scattering mechanism description, a decision tree classifier comes into use due to its simple and hierarchical structure. Since a decision tree classifier is flexible in terms of the discriminant rules, a hierarchical classification process based on Fisher Linear Discriminant (FLD) is built. Furthermore, the feedback adjustments of the classification results, such as feature combinations, partition algorithms and split sequences, make it possible to improve the accuracy of some specific classes. The experiment regarding the AIRSAR-Flevoland data illustrates that this method can obtain a good classification accuracy, and that it can extract useful information from the entire classification process in order to form new expert knowledge, such as the PolSAR features, classifying algorithms, and relationships between the classes.
Referring to the multi-aspect polarimeric scattering mechanism, the anisotropic scattering property is analyzed and two parameters both derived from traditional polarimetric entropy is proposed. One is called multi-aperture polarimetric entropy(MAPE), describes both depolarisation and directivity. The other is called sub-aperture entropy(SAE), describes change of depolarisation with look angle. These two parameters are used to separate targets which have both strong directivity and specific scattering mechanism, have specific scattering mechanism but not directivity, have neither directivity nor specific scattering mechanism. The effectiveness of the new parameters is validated with real polarimetric Circular SAR data, acquired by the Institute of Electronics airborne CSAR system at P-band.

In this report, we will introduce the main research progress of forest above ground biomass (AGB) estimation study based on integration of multi-dimensional SAR data. It mainly contains the following three aspects. (1) We proposed a three-steps semi-empirical radiometric terrain correction approach for PolSAR data. The three steps of terrain effects correction are polarization orientation angle, effective scattering area, and angular variation effect corrections. Based on the LiDAR-derived forest AGB data, detailed analysis and evaluation were carried on for the three correction steps. (2) Base on the simplified InSAR decorrelation model (SINC model) and Algebraic Difference theory, we developed a terrain correction approach for coherence image of InSAR data. And the method was evaluated by space-borne and air-borne InSAR data. (3) Based on the X-band single-pass InSAR data and P-band PolSAR data acquired by multi-dimensional SAR system (CASMSAR) of China, we developed one combined estimation approach of forest AGB based on multi-dimensional SAR data by integrating the terrain correction methods proposed above.

Virtual Dispalacement Method for Tree Volume

Location: Congress Hall