ENVISAT Advanced Synthetic Aperture Radar Data Research Articles

Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series

We present ground deformations in response to water level variations at the Toktogul Reservoir, located in Kyrgyzstan, Central Asia. Ground deformations were measured by Envisat Advanced Synthetic Aperture Radar (ASAR) and Sentinel-1 Differential Interferometric Synthetic Aperture Radar (DInSAR) imagery covering the time periods 2004–2009 and 2014–2016, respectively. The net reservoir water level, as measured by satellite radar altimetry, decreased approximately 60 m (∼13.5 km3) from 2004–2009, whereas, for 2014–2016, the net water level increased by approximately 51 m (∼11.2 km3). The individual Small BAseline Subset (SBAS) interferograms were heavily influenced by atmospheric effects that needed to be minimized prior to the time-series analysis. We tested several approaches including corrections based on global numerical weather model data, such as the European Centre for Medium-RangeWeather Forecasts (ECMWF) operational forecast data, the ERA-5 reanalysis, and the ERA-Interim reanalysis, as well as phase-based methods, such as calculating a simple linear dependency on the elevation or the more sophisticated power-law approach. Our findings suggest that, for the high-mountain Toktogul area, the power-law correction performs the best. Envisat descending time series for the period of water recession reveal mean line-of-sight (LOS) uplift rates of 7.8 mm/yr on the northern shore of the Toktogul Reservoir close to the Toktogul city area. For the same area, Sentinel-1 ascending and descending time series consistently show a subsidence behaviour due to the replenishing of the water reservoir, which includes intra-annual LOS variations on the order of 30mm. A decomposition of the LOS deformation rates of both Sentinel-1 orbits revealed mean vertical subsidence rates of 25 mm/yr for the common time period of March 2015–November 2016, which is in very good agreement with the results derived from elastic modelling based on the TEA12 Earth model.

Spaceborne SAR data for global urban mapping at 30 m resolution using a robust urban extractor

With more than half of the world population now living in cities and 1.4 billion more people expected to move into cities by 2030, urban areas pose significant challenges on local, regional and global environment. Timely and accurate information on spatial distributions and temporal changes of urban areas are therefore needed to support sustainable development and environmental change research. The objective of this research is to evaluate spaceborne SAR data for improved global urban mapping using a robust processing chain, the KTH-Pavia Urban Extractor. The proposed processing chain includes urban extraction based on spatial indices and Grey Level Co-occurrence Matrix (GLCM) textures, an existing method and several improvements i.e., SAR data preprocessing, enhancement, and post-processing. ENVISAT Advanced Synthetic Aperture Radar (ASAR) C-VV data at 30m resolution were selected over 10 global cities and a rural area from six continents to demonstrate the robustness of the improved method. The results show that the KTH-Pavia Urban Extractor is effective in extracting urban areas and small towns from ENVISAT ASAR data and built-up areas can be mapped at 30m resolution with very good accuracy using only one or two SAR images. These findings indicate that operational global urban mapping is possible with spaceborne SAR data, especially with the launch of Sentinel-1 that provides SAR data with global coverage, operational reliability and quick data delivery.

Object-Based Fusion of Multitemporal Multiangle ENVISAT ASAR and HJ-1B Multispectral Data for Urban Land-Cover Mapping

The objectives of this research are to develop robust methods for segmentation of multitemporal synthetic aperture radar (SAR) and optical data and to investigate the fusion of multitemporal ENVISAT advanced synthetic aperture radar (ASAR) and Chinese HJ-1B multispectral data for detailed urban land-cover mapping. Eight-date multiangle ENVISAT ASAR images and one-date HJ-1B charge-coupled device image acquired over Beijing in 2009 are selected for this research. The edge-aware region growing and merging (EARGM) algorithm is developed for segmentation of SAR and optical data. Edge detection using a Sobel filter is applied on SAR and optical data individually, and a majority voting approach is used to integrate all edge images. The edges are then used in a segmentation process to ensure that segments do not grow over edges. The segmentation is influenced by minimum and maximum segment sizes as well as the two homogeneity criteria, namely, a measure of color and a measure of texture. The classification is performed using support vector machines. The results show that our EARGM algorithm produces better segmentation than eCognition, particularly for built-up classes and linear features. The best classification result (80%) is achieved using the fusion of eight-date ENVISAT ASAR and HJ-1B data. This represents 5%, 11%, and 14% improvements over eCognition, HJ-1B, and ASAR classifications, respectively. The second best classification is achieved using fusion of four-date ENVISAT ASAR and HJ-1B data (78%). The result indicates that fewer multitemporal SAR images can achieve similar classification accuracy if multitemporal multiangle dual-look-direction SAR data are carefully selected.

Effects of changing rice cultural practices on C-band synthetic aperture radar backscatter using Envisat advanced synthetic aperture radar data in the Mekong River Delta

Changes in rice cultivation systems have been observed in the Mekong River Delta, Vietnam. Among the changes in cultural practices, the change from transplanting to direct sowing, the use of water-saving technology, and the use of high production method could have impacts on radar remote sensing methods previously developed for rice monitoring. Using Envisat (Environmental Satellite) ASAR (Advanced Synthetic Aperture Radar) data over the province of An Giang, this study showed that the radar backscattering behaviour is much different from that of the reported traditional rice. At the early stage of the season, direct sowing on fields with rough and wet soil surface provides very high backscatter values for HH (Horizontal transmit - Horizontal receive polarisation) and VV (Vertical transmit - Vertical receive polarisation) data, as a contrast compared to the very low backscatter of fields covered with water before emergence. The temporal increase of the backscatter is therefore not observed clearly over direct sowing fields. Hence, the use of the intensity temporal change as a rice classifier proposed previously may not apply. Due to the drainage that occurs during the season, HH, VV and HH/VV are not strongly related to biomass, in contrast with past results. However, HH/VV ratio could be used to derive the rice/non-rice classification algorithm for all conditions of rice fields in the test province. The mapping results using the HH/VV polarization ratio at a single date in the middle period of the rice season were assessed using statistical data at different districts in the province, where very high accuracy was found. The method can be applied to other regions, provided that the synthetic aperture radar data are acquired during the peak period of the rice season, and that few training fields provide adjusted threshold values used in the method.

Application of ENVISAT ASAR Data in Mapping Rice Crop Growth in Southern China

This research letter presents preliminary results of mapping rice crop growth using ENVISAT advanced synthetic aperture radar (ASAR) alternating polarization HH/HV data. Four ASAR HH/HV images were collected in the early rice-growth cycle in the test site in 2006, and the temporal response of ASAR data to the rice field was analyzed. The height and biomass of rice were measured during acquisition of ASAR data, and empirical relationships were established between the backscattering coefficient and these two parameters. Based on the temporal variation of the radar response, a method for mapping a rice growth area was developed using the combination of ASAR HH and HV polarization data between two acquisition dates. The results confirm that C-band SAR data have great potential in the development of an operational system for monitoring rice crop growth in Southern China.

ENVISAT ASARデータを用いた洋上の高解像度風速分布推定

The estimation of the high resolution wind speed distribution is required for the potential evaluation for the wind power generation over the sea. In this paper an algorithm is presented which enables high-resolution sea surface wind fields to be retrieved from the advanced synthetic aperture radar (ASAR) data acquired by European remote sensing satellite ENVISAT. The wind speeds are compared with the normalized radar cross section (NRCS) around the coast of Amami-Oshima Island. As a result, there is a high correlation (r=0.97) in NRCS derived from ASAR and the in-situ sea surface wind speed. The estimation RMSE of the ASAR wind speed is about 1.2 m/s. Thus, if the ENVISAT ASAR data is used, we can estimate the sea surface wind speed distribution with a resolution of about 125m.

Derivation of surface soil moisture from ENVISAT ASAR wide swath and image mode data in agricultural areas

Water and energy fluxes at the interface between the land surface and atmosphere are strongly dependent on surface soil moisture content, which is highly variable in space and time. It has been shown in numerous studies that microwave remote sensing can provide spatially distributed patterns of surface soil moisture. In order to use remote-sensing-derived soil moisture information for practical applications as, for example, flood forecasting and water balance modeling in mesoscale areas, frequent large-area coverage is a prerequisite. New sensor generations such as ENVISAT Advanced Synthetic Aperture Radar (ASAR) or RADARSAT allow for image acquisitions in different imaging modes and geometries. Imaging modes with the capability of large-area coverage, such as the Wide Swath Mode of ENVISAT ASAR, are of special interest for practical applications in this context. This paper presents a semiempirical soil moisture inversion scheme for ENVISAT ASAR data. Different land cover types as well as mixed-image pixels are taken into account in the soil moisture retrieval process. The inversion results are validated against in situ measurements, and a sensitivity analysis of the model is conducted.

Modeling temporal evolution of junco marshes radar signatures

In this work, multitemporal synthetic aperture radar (SAR) data in conjunction with an electromagnetic (EM) model and a vegetation growth model were used to monitor and explain burn-regrowth events of junco vegetation in a wetland environment. The data used were from Radarsat-1, ENVISAT Advanced Synthetic Aperture Radar (ASAR), and European Remote Sensing 2 (ERS-2) temporal series. The EM model is based on radiative transfer theory and describes junco vegetation as a set of vertical dielectric cylinders on a flat flooded surface. It was used, together with the vegetation growth model, to predict the temporal evolution of the radar response during a burn-regrowth event. This simulation was compared with the ERS-2 vertical (VV) data. It was observed a "bell-shaped" temporal trend that was confirmed by the simulated data with a mean error of 2.5 dB. Additionally, in view of current and future ENVISAT ASAR Alternating Polarization Mode Precision data, the horizontal (HH) SAR temporal response was also simulated giving as a result strong differences between simulated HH and VV temporal trends. These differences are in good agreement with the ones observed between Radarsat-1 HH and ERS-2 VV SAR data acquired at close dates and also with the same differences observed between HH and VV ENVISAT ASAR data. Electromagnetic modeling results provide a sound theoretical interpretation of these observations.

Dual-polarization measurements at C-band over the ocean: results from airborne radar observations and comparison with ENVISAT ASAR data

This paper presents an analysis of measurements of the normalized radar cross-section (NRCS) in vertical and horizontal polarizations over the ocean obtained from the C-band airborne radar STORM. The dataset was collected during the experiment called "Validation with a Polarimetric Airborne Radar of ENVISAT SAR over the Ocean (VALPARESO)", which took place during the calibration/validation phase of the ENVISAT Advanced Synthetic Aperture Radar (ASAR). From this dataset, the properties of the polarization ratio are discussed and in particular its dependencies with radar geometry (incidence and azimuth angle) as well as with meteorological conditions (wind and sea state). The polarization ratio is found to be dependent on incidence and azimuth angles. Its dependence with incidence angle is found to be significantly different from empirical models previously proposed in the literature. It also exhibits some correlation with surface conditions (wind and wave) with a more important correlation with significant wave steepness. Two new analytical formulations are proposed to model the polarization ratio, one as a function of incidence angle only, the second one with additional dependence with azimuth angle. It is shown that it is necessary to consider an azimuth-dependent polarization ratio for incidence angles larger than 30/spl deg/. Comparisons with the polarization ratio from ENVISAT ASAR images are used to assess this model.