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Abstract：In recent years, Polarization SAR (PolSAR) has been widely used in the filed of crop biomass estimation. However, high dimensional features extracted from PolSAR data will lead to information redundancy which will result in low accuracy and poor transfer ability of the estimation model. Aiming at this problem, we proposed a estimation method of crop biomass based on automatic feature selection method using Genetic Algorithm (GA). Firstly, the backscattering coefficient, the polarization parameters and texture features were extracted from PolSAR data. Then, these features were automatically pre-selected by GA to obtain the optimal feature subset. Finally, based on this subset, a Support Vector Regression machine (SVR) model was applied to estimate crop biomass. The proposed method was validated using the GaoFen-3 (GF-3) QPSΙ (C-band, quad-polarization) SAR data. Based on wheat and rape biomass samples acquired from a synchronous field measurement campaign, the proposed method achieve relative high validation accuracy (over 80%) in both crop types. For further analyzing the improvement of proposed method, validation accuracies of biomass estimation models based on several different feature selection methods were compared. Compared with feature selection based on linear correlation, GA method has increased by 5.77% in wheat biomass estimation and 11.84% in rape biomass estimation. Compared with the method of Recursive Feature Elimination (RFE) selection, the proposed method has improved crops biomass estimation accuracy by 3.90% and 5.21%, respectively.Keywords：polarization SAR;estimation of crop biomass;genetic algorithm;feature selection;GaoFen-330|29|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Agricultural monitoring is essential for an adequate management of food production and distribution. Crop land and crop type classification, using remote sensing time series, form an important tool to capture the agricultural production information. The recently launched Sentinel-2 satellites provide unprecedented monitoring capacities in terms of spatial resolution, swath width and revisit frequency. The Sentinel-2 for Agriculture (Sen2Agri) system has been developed to fully exploit those capacities, by providing four relevant earth observation products for agricultural monitoring. Under the Dragon4 Program, the crop mapping with various satellite images and a specific focus on yellow river irrigated agricultural area in the Ningxia Hui Autonomous region in China was carried out with the Sentinel-2 for Agriculture system (Sent2Agri). 9 types of crop were classified and the crop type map in 2017 was produced based on 35 scenes Sentinel 2A/B images. The overall accuracy computed from the error confusion matrix is 88%, which include the cropped and uncropped types. After the removal of the uncropped area, the overall accuracy for cropped decrease to 73%. In order to further improve the crop classification accuracy, training dataset should be further improved and tuned.Keywords：Crop Mapping;Dragon Program;Sentinel 2;Sent2Agri system32|32|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：The aim of this paper is to offer a statistically sound method to make a precise account of the speed of land degradation and regeneration processes. Most common analyses of land degradation focus instead on the extent of degraded areas, rather than on the intensity of degradation processes. The study was implemented for the Potential Extent of Desertification in China (PEDC), composed by arid, semi-arid and dry sub-humid regions and refers to the period 2002 to 2012. The metrics were standard partial regression coefficients from stepwise regressions, fitted using Net Primary Productivity as the dependent variable, and year number and aridity as predictors. The results indicate that: 1) the extension of degrading lands (292,896 km2 or 9.12% of PEDC) overcomes the area that is recovering (194,560 km2 or 6.06% of PEDC); and 2) the intensity of degrading trends is lower than that of increasing trends in three land cover types (grassland, desert and crops) and in two aridity levels (semi-arid and dry sub-humid). Such outcome might pinpoint restoration policies by the Chinese government, and document a possible case of hysteresis.Keywords：land degradation;potential extent of desertification in China;environmental monitoring;vegetation temporal trends;standard partial regression coefficients31|34|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：This paper is devoted to the development and testing of the optimal procedures for retrieving biophysical crop variables by exploiting the spectral information of current multispectral optical satellite Sentinel-2 and Venµs and in view of the advent of the new Sino-EU hyperspectral satellite (e.g., PRISMA, EnMAP, and GF-5). Two different methodologies devoted to the estimation of biophysical crop variables Leaf area index (LAI) and Leaf chlorophyll content (Cab) were evaluated: (a) non-kernel-based and kernel-based Machine Learning Regression Algorithms (MLRA); (b) Sentinel-2 and Venμs data comparison for the analysis of the durum wheat-growing season. Results show that for Sentinel-2 data, GPR (Gaussian Process Regression) was the best performing algorithm for both LAI (R2 = 0.89 and RMSE = 0.59) and Cab (R2 = 0.70 and RMSE = 8.31). Whereas, for PRISMA simulated data the Kernel Ridge Regression (KRR) was the best performing algorithm among all the other MLRA (R2 = 0.91 and RMSE = 0.51) for LAI and (R2 = 0.83 and RMSE = 6.09) for Cab, respectively. Results of Sentinel-2 and Venμs data for durum wheat-growing season were consistent with ground truth data and confirm also that SWIR bands, which are used as tie-points in the PROSAIL inversion, are extremely useful for an accurate retrieving of crop biophysical parameters.Keywords：biophysical crop parameters;PRISMA;GF-5;Sentinel 2;Venμs22|30|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Approximately half of the world's population is at the risk of at least one vector-borne parasitic disease. The survival of intermediate hosts of vector-borne parasitic diseases is governed by various environmental factors, and remote sensing can be used to characterize and monitor environmental factors related to intermediate host breeding and reproduction, and become a powerful means to monitor the vector-borne parasitic diseases. Schistosomiasis is a parasitic disease that menaces human health. Oncomelania hupensis (snail) is the unique intermediate host of schistosoma, so monitoring and controlling the number of snail is key to reduce the risk of schistosomiasis transmission. In this paper, Landsat 8 OLI and Sentinel 2 MSI data had been used to obtain the environmental factors (vegetation, soil, temperature, terrain et al.), which are related to the multiplying and transmission of intermediate host. Then this study used T-S (Takagi-Sugeno) Fuzzy RS model to establish a new suitable index membership function due to the different RS data, and a long time series monitoring of snail distribution in Dongting Lake from 2014 to 2018 was achieved. A comparative analysis was performed to validate the predicted results against the field survey data. The results demonstrated the accuracy of the developed model in predicting the distribution of snails.Keywords：Schistosomiasis;snail;Sentinel 2;T-S Fuzzy34|35|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：A The AMEOS (Assimilating Multi-source Earth Observation Satellite data for crop pests and diseases monitoring and forecasting) project aims to bring together cutting edge research to provide pest and disease monitoring and forecast information, integrating multi-source information (Earth Observation, meteorological, entomological and plant pathological, etc.) to support decision making in the sustainable management of insect pests and diseases in agriculture. The main objective of the project, that is, improving crop diseases and pests monitoring and forecasting, will be achieved by utilizing EO data, developing new algorithms, and combining new and existing data from multi-source EO sensors to produce high spatial and temporal land surface information. The project foresees the assessment of the possibility of using available satellite images datasets to assess the evolution of diseases on permanent (olive groves, vineyards), or row crops (wheat) in Italy and China. The paper describes the results of the research activity which focused on: (i) improving the classification of the agricultural areas devoted to winter wheat and olive trees, starting from what has been made available from the Corine Land Cover initiative; (ii) developing an approach suitable to be automated for estimating trees by using Sentinel 2 images; (iii) developing a new index, REDSI (consisting of Red, Re1, and Re3 bands), for detecting and monitoring yellow rust infection of winter wheat at the canopy and regional scale. The research activity covers the: 1) Province of Lecce, that is the Italian area strongly affected, since 2015, by the Xylella fastidiosa disease which causes a rapid decline in olive plantations. 2) Province of Anyang, Neihuang county, which was affected by the yellow rust disease in the spring 2017.Keywords：Disease;reflectance;index;morphology;classification51|106|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Surface energy budget components (such as net radiation flux, sensible heat flux, latent heat flux and soil heat flux) at multiple temporal scales have significant meaning for understanding the energy and water cycle over the Tibetan Plateau (TP). In the framework of ESA-MOST Dragon Programme 4, the Surface Energy Balance System (SEBS) was tested and used to derive surface heat fluxes at different temporal scales over the TP by a combination use of geostationary satellite (FY-2C) data, polar orbiting satellite (SPOT/VGT, Terra/MODIS) data and ITPCAS forcing data. The validation results show there is a good agreement between derived heat fluxes and in situ measurements from Third Pole Environment Observation and Research Platform (TPEORP), which means the feasibility to derive surface heat fluxes over heterogeneous landscapes by a combination use of geostationary and polar orbiting satellite data in SEBS. The RMSEs for net radiation flux, sensible heat flux, latent heat flux and soil heat flux are 76.63 Wm-2, 60.29 Wm-2, 64.65 Wm-2 and 37.5 Wm-2, respectively. The diurnal, seasonal and inter-annual variation characteristics were also clearly identified through analyses of derived turbulent fluxes.Keywords：sensible heat flux;latent heat flux;parameterization;SEBS;the Tibetan Plateau40|35|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：The atmospheric carbon dioxide (CO2) concentration has increased to more than 405 parts per million (ppm) in 2017 due to human activities such as deforestation, land-use change and burning of fossil fuels. Although there is broad scientific consensus on the damaging consequences of the change in climate associated with increasing concentrations of greenhouse gases, fossil CO2 emissions have continued to increase in recent years mainly from rapidly developing economies and China is now the largest emitter of CO2 generating about 30% of all emissions globally. To allow more reliable forecast of the future state of the carbon cycle and to support the efforts for mitigation greenhouse gas emissions, a better understanding of the global and regional carbon budget is needed. Space-based measurements of CO2 can provide the necessary observations with dense coverage and sampling to provide improved constrains on of carbon fluxes and emissions. The Chinese Global Carbon Dioxide Monitoring Scientific Experimental Satellite (TanSat) was established by the National High Technology Research and Development Program of China with the main objective of monitoring atmospheric CO2 and CO2 fluxes at the regional and global scale. TanSat has been successfully launched in December 2016 and as part of the Dragon programme of ESA and the Ministry of Science and Technology (MOST), a team of researchers from Europe (UK and Finland) and China has evaluated early TanSat data and contrast it against data from the GOSAT mission and models. In this manuscript, we report on retrieval intercomparisons of TanSat data using two different retrieval algorithms, on validation efforts for the Eastern Asia region using GOSAT CO2 data and first assessments of TanSat and GOSAT CO2 data against model calculations using the GEOS-Chem model.Keywords：carbon cycle;spectroscopy;satellite remote sensing23|30|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this paper, we present long term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO Vertical Column Densities (VCDs) are used to validate OMI satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. The age weighted backward propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward propagated HCHO data does not show a strong spatial correlation with the OMI HCHO observations. The result shows the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants.Keywords：MAX-DOAS;OMI;NO2;formaldehyde;pollution transport40|22|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Shipborne observations obtained with the Coherent Doppler lidar (CDL) and radiosonde during 2014 campaign were used to study the structure of marine boundary layer in Yellow Sea. Vertical wind profiles corrected for ship motion was used to derive higher-order statistics, showing that motion correction is required and significant for turbulence analysis. During a day with weak mesoscale activity, a complexed three-layer structure system was observed. The lowest layer showed a typical stable boundary layer structure feature. An aerosol layer with abrupt variation in wind speed and relative humidity always appeared at the middle layer, the formation of which may be due to Kelvin-Helmholz instability. The top layer encountered a dramatic change in wind direction, which may result from the warm advection from the Eurasian continent on the basis of backward trajectory analysis. Furthermore, the MABL height in stable regime was derived from potential temperature, CDL Signal-to-Noise Ratio (SNR) and CDL vertical velocity variance, respectively. The Stable Boundary Layer (SBL) height in SBL can be derived from the inversion layer of potential temperature profile, and the mixing height in SBL can be retrieved from the vertical velocity variance gradient method. Neither the SBL height nor the mixing height is in agreement with the height retrieved from CDL SNR gradient method because of different definition and criterion. One of the limitations of SNR gradient method for MABL retrieval is that it is easier to be affected by the lofted decoupled aerosol layer, where the retrieved result is less suitable. Finally, the higher-order vertical velocity statistics within the marine stable boundary layer were investigated and compared with the previous studies, and different turbulence mechanisms have an important effect on the statistics deviation.Keywords：coherent Doppler Lidar;stable marine boundary layer;radiosonde;turbulence characteristics31|33|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In studies of upwelling, usually data from infrared and optical sensors are used which provide information on the Sea Surface Temperature (SST) and the Chlorophyll-a (Chl-a) concentration. In this paper, we show that also Synthetic Aperture Radars (SAR) images can give valuable contribution to such studies. Upwelling regions become detectable by SAR because they are associated with a reduction of the radar backscatter due to (1) the change of the stability of the air-sea interface (2) the presence of biogenic slicks. Furthermore, the boundary of upwelling regions consists of a line of increased radar backscatter due to the presence of convergent surface flow.Keywords：upwelling;synthetic aperture radar;cyclonic eddies;Agulhas Return Current;biogenic surface films;Chlorophyll concentration;air-sea interface;sea surface temperature47|26|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this study, a large time series of TerraSAR–X Stripmap co–polarized (HH–VV) Synthetic Aperture Radar (SAR) imagery collected over the Taylor Energy oil platform site in the Gulf of Mexico is exploited to investigate this 13 year–long unconventional oil spill. The σCPD approach is used to estimate the polluted area along time. In addition, a sensitivity analysis is undertaken to point out the dependence of σCPD to imaging (noise floor, incidence angle) and environment (sea state) parameters.Experimental results demonstrate that σCPD can be effectively used to monitor the Taylor Energy oil spill, estimating the polluted area. For the TSX SAR data avail- ability most dense period (year 2013), a daily spill of about 2.2 km2 is observed in average, even though high variability (about 2.0 km2) is experienced due to the un- conventional characteristics of the spill.Keywords：polarimetry;CPD;Taylor Energy;oil spill48|57|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this study, the azimuth cut-off method, typically used for SAR moderate wind speed estimation purposes, is analyzed under high wind regimes. Firstly, the importance of the pixel spacing, the size of the boxes selected for Synthetic Aperture Radar (SAR) image partitioning and the image texture in terms of homogeneities are discussed by considering their influence on the azimuth cut-off (λc) estimation. Secondly, a quality control analysis of the reliability of λc is carried out by evaluating the distance between the autocorrelation functions (ACF) and their correspondent fittings. This analysis points out the importance of filtering out the unreliable and unfeasible λc values in order to improve the wind speed estimation. The quality control procedure is based on a χ2 test, applied on a large Sentinel-1A dataset. The soundness of the test is verified by an increment in terms of correlation between λc estimations and wind speed values.This approach is, then, applied under high wind regimes, i.e.; tropical cyclones.Keywords：wind speed;azimuth cut-off;significant wave height55|52|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this study, we provide a summary of research advances in the field of maritime target detection using DP (dual-polarimetric) SAR (Synthetic Aperture Radar) imagery, accomplished during the European and China collaboration in the framework of the Dragon-4 program ID 32235. The main innovative contribution is twofold: a) we addressed ship detection proposing an improved GP-PNF (Geometrical Perturbation–Polarimetric Notch Filter), termed as IGP-PNF, that is characterized by a new feature vector that includes three new scattering features; b) we addressed oil platform detection by contrasting single-polarization SAR methods with polarimetric ones in order to quantify the extra- benefit carried on polarimetric information. The proposed theoretical framework is tested against actual multi-polarization SAR data. In particular, ship detection methods are verified against a Sentinel-1 SAR scene where a large number of ship is present; while, oil platform detection is discussed using TerraSAR-X SAR data. Experimental analysis show that: (1) the IGP-PNF method performs best in terms of clutter-to-target ratio; (2) coherent polarimetric information significantly outperforms single-polarization SAR measurements in highlighting targets in challenging cases.Keywords：marine target detection;dual-polarimetric SAR;GP-PNF;PCA;Sentinel-1;TS-X61|31|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this paper, studies on offshore wind farm wakes observed by spaceborne SAR (Synthetic Aperture Radar) are reviewed mainly based on our previous research. Particularly, we focus on investigating wind wakes and tidal current wakes observed by spaceborne SAR of TerraSAR-X, Gaofen-3 and Radarsat-2 in high spatial resolution, in two offshores wind farms, i.e. the Alpha Ventus in the North Sea and the one near Donghai bridge in the East China Sea. Representing examples of wind wakes and tidal current wakes observed by SAR in the two farms are presented and compared. A preliminary statistical analysis on morphology of wind feature downstream Alpha Ventus is presented as well. Besides these studies on wind wakes generated by a single offshore wind farm, we show an example of wakes downstream multiple wind farms in the North Sea to demonstrate "cluster" effect of multiple offshore wind farms on sea wind.Keywords：offshore wind farm wakes;synthetic aperture radar39|39|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：The Circum-Bohai-Sea Region is an important economic zone of China. The sea ice, which occurs at each winter, is the major marine hazard of the Bohai Sea. As a result, it is very important to evaluate the damage effects quantitatively in this region, which is seldom studied and analyzed systematically using long-time-series data. In this paper, the sea-ice disaster in the Bohai Sea is evaluated quantitatively based on the Sentinel-1 and GOCI. For different hazard-bearing bodies of the marine transportation and the offshore constructions, different sea-ice-hazard indexes are defined, which can be applied to analyze the sea-ice disaster quantitatively in the Bohai Sea, including the annual and inter-annual variations in the period from 2011 to 2017. The analysis results can provide the reference of the sea-ice monitoring in the Bohai Sea.Keywords：the Bohai Sea;sea-ice disaster;the quantitative evaluation;Sentinel-1;GOCI.48|27|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In this study, the north-western Pacific Ocean of Kuroshio region is selected as the experimental area to analyze the mesoscale eddies observation abilities of Sentinel-3A SRAL, including the independent detection abilities of Sentinel-3A SRAL and the improvement of mesoscale eddies detection abilities by data fusion with other satellite altimetry data. The Sentinel-3A SRAL data are mapped by the spatial-temporal objective analysis method to the sea level anomaly grid data. The mapping errors are analyzed by the comparisons between the grid data of different combinations and along the ground track of Jason-2/3. The independent detection abilities of Sentinel-3A SRAL are analyzed by the comparison between the grid data and the AVISO MSLA data. On the other hand, through the multi-satellite data fusion of different combinations of Sentinel-3A altimeter and other satellite altimeters such as Jason-2/3, the mesoscale eddies detection was performed based on the merged sea level anomaly data and the addition of Sentinel-3A SRAL data for the improvements of mesoscale eddies detection abilities by multi-satellite altimeters are concluded. It is concluded that Sentinel-3A SRAL has good abilities of mesoscale eddies detection as the combination of Jason-2 and Jason-3, and it is better than that of single altimeter of Jason-2 or Jason-3.Keywords：Sentinel-3;Altimeter;mesoscale eddy22|43|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Satellite geodesy is capable for observing glacier height changes and most recent studies focus on the decadal scale due to limitations of data acquisition and precision. Glaciers at Mt. (Qomolangma), locating at the Central Himalaya, have been studies from the 1970s to 2015. Here we obtained TerraSAR-X/TanDEM-X images observed in two epochs, a group around 2013 and another in 2017. Together with SRTM observed in 2000, we derived glacier geodetic glacier mass balance between 2000 and ~2013 and ~2013 and 2017. We proposed two InSAR procedures for deriving the second period, which yield with basically identical results of geodetic glacier mass balance. DEMs differencing between DEMs derived by TerraSAR-X/TanDEM-X show better precision than between TerraSAR-X/TanDEM-X formed DEM and SRTM, and are capable of providing geodetic glacier mass balance at sub-decadal scale. Glaciers at the Mt. Everest and its surroundings present obvious speeding up in mass lost rates before and after ~2013 for both the Chinese and the Nepalese sides. The previous obtained spatial heterogeneous pattern for glacier downwasting between 2000 and ~2013 generally kept the same after ~2013. Glaciers with lacustrine terminus present most rapid lost rates.Keywords：Everest;Qomolangma;Geodetic glacier mass balance;TerraSAR-X/TanDEM-X;Bistatic D-InSAR24|22|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Observation and modelling of the coupled energy and water balance is the key to understand hydrospheric and cryospheric processes at high elevation. The paper summarizes the progress to address this aspect in relation with different earth system elements, from glaciers to wetlands. The energy budget of two glaciers, i.e. Xiao Dongkemadi and Parlung No. 4, was studied by means of extended field measurements and a distributed model of the coupled energy and mass balance was developed and evaluated. The need for an accurate characterization of surface albedo was further documented for the entire Qinghai Tibet Plateau by numerical experiments with Weather Research and Forecast (WRF) on the sensitivity of the atmospheric boundary layer to the parameterization of land surface processes. A new approach to the calibration of a coupled distributed watershed model of the energy and water balance was demonstrated by a case – study on the Heihe River Basin in North West China. The assimilation of land surface temperature did lead to retrieval of critical soil and vegetation properties as the soil permeability and the canopy resistance to the exchange of vapour and carbon dioxide. The retrievals of actual Evapo – Transpiration (ET) were generated by the ETMonitor system and evaluated against eddy covariance measurements at sites spread throughout Asia. As regards glacier response to climate variability, the combined findings based on satellite data and model experiments showed that the spatial variability of surface albedo and temperature is significant and controls both glacier mass balance and flow. Experiments with both atmospheric and hydrosphere – cryosphere models documented the need and advantages of using accurate retrievals os land surface albedo to capture land – atmosphere interactions at high elevation.Keywords：ice;snow;albedo;energy water balance34|39|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：As part of Dragon 4 project, the water extents of Wuchang and Shengjin lakes have been extracted from Sentinel-2 time series, using all exploitable images since the beginning of the acquisitions in 2015. The aim of the study is to assess the capability of the Sentinel-2 constellation and Landsat 8 over the Anhui region, especially the high temporal resolution. A total of 32 dates have been used and 10 Landsat 8 images (Libra) have been added to try to reduce the temporal gaps in the Sentinel-2 acquisitions caused by cloudy conditions. Extractions were done using a SERTIT-ICube automatized routine based on a supervised Maximum Likelihood Classification. These extractions allow to recreate the dynamic of the two lakes and show the drought and wet periods. During the 3 years interval, the surface peaks on July 2016 for both lakes. The lowest level appears at two different dates for each lake; on January 2018 for Wuchang, on February 2017 for Shengjin. Wuchang Lake surface area appears to be more variable than Shengjin Lake, with many local maximum and minimum between the end of 2017 and April 2018. In the case of Wuchang Lake, floating vegetation is a problem for automatic water surface area extraction. The lake is covered by vegetation during long periods of time and the water below can't be detected by automatic radiometric means. Nevertheless, Sentinel-2 stays a pertinent and powerful tool for hydrological monitoring of lakes confirming the expectation from the remote sensing wetland community before launch. The presence of NIR and SWIR bands induces a strong discrimination between water and other classes, and the systematic acquisitions create dense time series, making analysis more consistent. It makes possible to sensor events occurring over short periods of time. Thanks to this a link can be done between endangered bird species, such as the Siberian Crane and the Lesser White-Fronted Goose and periodically flooded areas. These midterm results illustrated the pertinence and powerful of multi-source optical satellite data for environmental analysis.33|28|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Wetlands are among the most productive and essential ecosystems on earth, but they are also highly sensitive and vulnerable to climate change and human disturbance. One of the current scientific challenges is to integrate high-resolution remote sensing data of wetlands with wildlife movements, a task we achieve here for dynamic waterbird movements. We demonstrate that the White-naped cranes Antigone vipio wintering at Poyang Lake wetlands, southeast of China, mainly used the habitats created by the dramatic hydrological variations, i.e. seasonal water level fluctuation. Our data suggest that White-naped Cranes tend to follow the water level recession process, keeping close to the boundary of water patches at most of the time. We also highlight the benefits of interdisciplinary approaches to gain a better understanding of wetland ecosystem complexity.Keywords：Poyang Lake;Sentinel-1A;interdisciplinary approach;wetland monitoring;water surface;White-naped Cranes27|26|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：In 2017, China's central government approved the national strategy to build Xiong'an New Area (XNA, 100 km southwest to Beijing), which was announced as a "millennium strategy" and a "demo area" for a sustainable, modern, and innovative urban model. Xiong'an will draw in as much as $380 billion investment and is expected to help accelerate the development of the wider Beijing-Tianjin-Hebei (Jingjinji) Area. In this paper, present subsidence in the XNA area is investigated using InSAR observations for the first time. The 24 SAR images acquired by European Space Agency's Sentinel-1 satellites during the period from June 2017 to July 2018 suggest that in the north of Xiong County, the subsidence rate reach up to 90 mm/year, which is highly correlated with the exploitation of geothermal drilling. As the construction in the XNA area will significantly accelerate and its high-quality development, the InSAR findings could provide valuable information for future sustainable urban planning and underground infrastructure construction.Keywords：Xiong'an New Area;Subsidence;InSAR;geothermal heating;Sentinel-144|40|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation (ID: 32278), sub-project Multi-baseline SAR Processing for 3D/4D reconstruction (ID: 32278_2). The work here reported focuses on two important aspects of SAR remote sensing of tropical forests, namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions. Recent studies have shown that by using SAR tomography the backscattered power at 30 m layer above the ground is linearly correlated to the forest AGB (Above Ground Biomass). However, the two parameters that determine this linear relationship might vary for different tropical forest sites. For purpose of solving this problem, we investigate the possibility of using LiDAR derived AGB to help training the two parameters. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept. This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging, for which we simulate BIOMASS repeat pass tomography using ground-based TropiSCAT data with revisit time of 3 days and rainy days included. The resulting backscattered power variation at 30 m are within 1.5 dB. For this forest site, this error is translated into an AGB error of about 50-80 ton/ha, which is 20% or less of forest AGB.Keywords：Tropical forest;biomass;SAR tomography;LiDAR;temporal decorrelation22|34|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：The Swarm satellite mission was lunched on November 22, 2013, it is the first European Space Agency's constellation of three satellites, dedicated to monitoring geomagnetic field changes. The measurements delivered by the three satellite are very valuable for a range of applications, including earthquake prediction study. However, for more than 5 years, relatively little advancement has been achieved on establishing a systematic approach for detecting anomalies from the satellite measurements for predicting earthquakes. This paper presents the challenges of developing a pragmatic framework for automatic anomaly detection and highlights innovative features of functional components developed. Through a case study we demonstrate a functionality pipeline of the system in detecting anomalies, and present our solutions to coping with data sparsity and parameter tuning as well as insights into the differences between discovering seismic anomalies from periodic and non-periodic data observed by the Swarm satellites.Keywords：Anomaly detection;Swarm satellites;earthquake prediction study28|32|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：China has been affected by some of the world's most serious geological disasters and experiences high economic damage every year. Geohazards occur not only in remote areas but also in highly populated cities. In the framework of the DRAGON-4 32365 Project, this paper presents the main results and the major conclusions derived from an extensive exploitation of Sentinel-1, ALOS-2 (Advanced Land Observing Satellite 2), GF-3 (GaoFen Satellite 3), and latest launched SAR (Synthetic Aperture Radar), together with methods that allow the evaluation of their importance for various geohazards. Therefore, in the scope of this project, the great benefits of recent remote sensing data (wide spatial and temporal coverage) that allow a detailed reconstruction of past displacement events and to monitor currently occurring phenomena are exploited to study different areas and geohazards problems, including: surface deformation of mountain slopes; identification and monitoring of ground movements and subsidence; landslides; ground fissure; and building inclination studies. Suspicious movements detected in the different study areas were cross validated with different SAR sensors and truth data.Keywords：Dragon-4 project;Sentinel-1;GF-3;landslide;geohazards;InSAR63|83|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：The tremendous development of Synthetic Aperture Radar (SAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses greater challenges for correcting atmospheric effects due to the wider coverage of SAR imagery than ever. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate atmospheric delays, but they are limited by (1) the availability (and distribution) of GPS stations; (2) the low spatial resolution of NWM; and (3) the difficulties in quantifying their performance. To overcome these limitations, we have developed the Generic Atmospheric Correction Online Service for InSAR (GACOS) which utilizes the high-resolution European Centre for Medium-Range Weather Forecasts (ECMWF) products using an Iterative Tropospheric Decomposition (ITD) model. This enables the reduction of the coupling effects of the troposphere turbulence and stratification and hence achieves equivalent performances over flat and mountainous terrains. GACOS comprises a range of notable features: (1) global coverage, (2) all-weather, all-time usability, (3) available with a maximum of two-day latency, and (4) indicators available to assess the model's performance and feasibility. In this paper, we demonstrate some successful applications of the GACOS online service to a variety of geophysical studies.Keywords：InSAR;atmospheric correction;GACOS;Earthquake;Volcano;landslide;city subsidence61|32|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：It is a debated topic if there is any observable precursor anomalies prior to earthquake (EQ hereafter) and if the stronger EQ can be successfully predicted. During the last decades quite a lot of observable electromagnetic (EM) precursors were published by using a techniques equipped in either satellites or on ground-based stations. But there are only a few cases that the short-term precursor anomalies of EM field before earthquakes were observed by using alternate EM fields on ground. This paper will present a new EM observation network built in recent years and show a new finding of EM field with the variation of a one-year cycle observed using the network. As an example, the short-term precursor anomalies of apparent resistivity before the Yangbi EQ (Ms=5.1) occurred on March 17, 2017 in Yunnan province will be studied. The observed anomalous phenomena indicate that the anomaly before the EQ can be captured only if a reasonably effective method is used, and it is believed that continuously observed data on the fixed observation network for long time is a effective means for studying anomalies that appeared before earthquakes. This network can also play an important role in studying the EM environment from space.Keywords：Electromagnetic observation network;natural EM phenomena;precursor anomaly;apparent resistivity;space EM environment34|27|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
Abstract：Coastal regions are becoming increasingly vulnerable to flooding because of accelerating Sea-Level Rise (SLR), local ground subsidence, and changes in topography and morphology. Moreover, coastal areas are usually highly urbanized and increased human activities have an effect on the stability and preservation of the environment. For instance, the growing demand of new lands to accommodate the population and the industrial facilities in China has required the design and the deployment of land-reclamation projects from the ocean, with a marked impact on fragile coastal eco-systems. Specifically, the Yangtze River and Pearl River Estuary, two major estuaries of the world, have long been subject to intensive human activities over the past decades. Long-term ground subsidence evolution, topographic changes, and morphological variation of the coastal regions have drawn great attention. This paper provides an overview of well-established Earth Observation (EO) Remote Sensing (RS) technologies that are employed to continuously monitor the changes of urbanized regions. The combined use of EO-based DInSAR analyses along with the knowledge of the geomorphology of the coastal regions allows a more precise picture of the SLR risk in the investigated coastal regions. In this paper, we will concentrate on remote sensing technologies that allow the gathering of heterogeneous information, such as those based on the use of Synthetic Aperture Radar (SAR), satellite altimeters and tide gauge data. We will underline how human activities trigger changes in the living environment of coastal zones and the associated risks for the population. Observed coastline changes, coastal regions terrain subsidence, and offshore bathymetry have a pronounced effect on the increasing risk of flooding. Accordingly, we also present insights into some inundation model projections employed for evaluating the potential flooding risk in coastal regions.Keywords：flooding risk;sea-levelrise (SLR);ground subsidence;InSAR;anthropogenic geomorphologic changes36|36|0<HTML><L-PDF> <Enhanced-PDF> <Meta-XML>Updated：2025-04-02
