Chou Xie

Analysis of ALOS PALSAR InSAR data for mapping water level changes in Yellow River Delta wetlands

Wetlands play a key role in regional and global environments and are critically linked to many major issues such as climate change, water quality, hydrological and carbon cycles, and wildlife habitat and biodiversity. It is very important to measure water level changes and consequently water storage capacity changes in wetlands to enable wetland protection and reconstruction. In this study, HH polarization L-band synthetic aperture radar (SAR) data were used in conjunction with synchronous field measurements and investigations to investigate the potential to detect water level changes under different types of wetlands. After evaluating factors that influence interferometric coherence, the framework for measuring water level changes using interferometric synthetic aperture radar (InSAR) phase information is presented in this article. Additionally, the SAR data obtained are used to investigate InSAR-derived water level changes in Yellow River Delta wetlands. The results show that InSAR technology has great potential for application in mapping water level changes in coastal wetlands, and InSAR-derived water level changes can supply unprecedented spatial details.

Forest and deforestation identification based on multitemporal polarimetric RADARSAT-2 images in Southwestern China

In the southwest of China, it is anticipated that synthetic aperture radar (SAR) will become an important tool for forest inventory because of its all-weather capabilities. The Zhazuo area in Guizhou Province of southwest China, with a typical Karst landform, was selected as the test site. Six RADARSAT-2 polarimetric images were acquired in order to analyze polarimetric backscattering behavior and temporal variation of forest and deforested area. Polarimetric decomposition was conducted, and Pauli and Freeman-Durden decomposition were demonstrated to be more suitable for identifying forest and deforestation respectively. Finally, a scheme for multitemporal polarimetric SAR data fusion was proposed, which could greatly improve image quality and make forest identification more efficient. Support vector machine classification showed that the overall accuracy for forest identification was 87.63%, and the accuracy could be enhanced to 91.49% after gamma filtering.

Subsurface microwave remote sensing and scattering modelling on hyper-saline soil: Example of Lop Nur

Subsurface microwave remote sensing is a direction of Synthetic Aperture Radar (SAR) research. With the penetration capability, SAR is capable of detecting the subsurface targets and materials, especially in arid environment. Lop Nur Lake is located at the east of Tarim Basin in Xinjiang province of China, which is described as “dry core” of the world, and it can provide conditions for SAR penetration. This paper presents preliminary analysis about Lop Nur, and gives out an abstract subsurface structure about it. Then, the major scattering processes are concluded and a two-layer scattering model is developed. Based on parameters of soil samples, some rules about Lop Nur evolution will be figured out. With Genetic Algorithm (GA), an inversion procedure is constructed. All the attempts are viewed as the basis of future comprehensive interpretation about Lop Nur phenomenon.

Detection subsurface hyper-saline soil in Lop Nur using full-polarimetric SAR data

This paper presents the research results about Lop Nur using full-polarimetric technology. Lop Nur Lake is one of the driest places in the world and finally lost its last drop of water in 1972. It is well known for its “Earth Ear” feature in optical remote sensing images. Likewise, “Ear” feature is shown in Synthetic Aperture Radar (SAR) images, and even larger because of penetration effect. With the penetration capability SAR is capable of detecting the subsurface targets and materials, especially in arid environment. As for SAR images, both C-band and L-band, there are two key features about Lop Nur area. One is the whole Lop Nur area is high-bright that means the backscattering is much stronger than other sites, such as Gobi, desert and so on. The other feature is the “Ear” pattern formation. polarimetric analysis about these two questions will be conducted based on past research results and field investigations.

Land Desertification in the Source Region of the Yellow River, Northeast Qinghai Xizang Plateau

Land degradation is a great threat to the world for the future, and it is not merely an environmental issue, but has been a social and economic problem as well. The source region of the Yellow River located in the northeast of the Qinghai-Xizang Plateau, and its eco-environment is very fragile for the especial geographic location in recent years. The eco-environment degrades very quickly influenced by natural factor together with human being factor in these years, in which desertification is main aspect of environment changing in this region. However, the previous study on the desertification mainly focused on the Gonghe Basin, and the systematic research was unavailable. This study showed, for the first time, the present status, classification and spatial distribution of land desertification in the whole region, based on the data obtained through field investigation and Landsat TM image (4,3 and 2 bands) of September 2000. According to our research, the desertified land in the study area mainly concentrated in the Gonghe Basin and Upland Plain Area, and the total area of desertification land is 13434.8 km2 , or 14.65% of the entire land in the aim region.

The Glacier Identification using SAR Interfermetric and Polarimetric Information in Qinghai-Tibetan Plateau

For climatological and hydrological investigations, the areas covered by glacier and their spatial variability are important parameters, particularly in Qinghai-Tibetan Plateau. A interferometric SAR technique not only can produce a high-resolution digital elevation models but also can identify the surface object with coherence coefficients. This property of SAR polarimetry is particularly useful in classification. In this paper we analyze to demonstrate the method and result for the glacier identification integrated intensity of backscattering from Envisat/ASAR images, coherence coefficients of repeat pass interferometry from ASAR and ALOS/PalSAR, and full polarimetric SAR from PalSAR.

Multi-Temporal Polarimetric SAR and Optical Data Fusion for Land Cover Mapping in Southwest China

Zhazuo area located in Guizhou Province of southwest China was selected as the test site of this study. Based on six polarimetric RADARSAT-2 images, this paper presents the analysis on polarimetric and temporal variation backscattering behavior of typical targets such as residential areas, farmlands, forests and water bodies within the test site. The multi-temporal polarimetric SAR data fusion, as well as SAR and optical data fusion was conducted to improve the land cover classification. The analysis shows that there are significant differences of polarimetric backscattering and temporal variation behavior among different land cover types. The fusion of the multi-temporal polarimetric SAR data highlights the significant reduction of speckle noises, better land cover discrimination and improved visual appearance of SAR image. The fusion of SAR images with QuickBird data efficiently improves the land cover classification. This study demonstrates that high-precision land cover thematic mapping with SAR data in combination with optical remote sensing image in cloudy and rainy areas is feasible.

Ortho-rectification of high-resolution SAR image in mountain area by DEM

Because of the side-looking imaging characteristics, the quality of Synthetic Aperture Radar (SAR) image is badly affected by variable terrain. Such terrain can introduce large displacements in the SAR image geometry that inhibits the collocation of SAR-derived quantities with geographically referenced information acquired from other sources. So it is necessary to eliminate such inherent geometric distortions by generating a radar ortho-imagery that corresponds to a well defined map projection. In this paper, aiming at the newest high-resolution SAR data-RADARSAT-2 and TerraSAR-X, an effective ortho-rectification method was studied in detail and the result showed this method could achieve high geo-location accuracy.

Water level change time series extraction of Yellow River Delta based on small baseline subset approach

The water level change has a great impact on the composition of plant species, the variety of the species and the succession of the colony of the Yellow River Delta wetland. However, due to the lack of enough hydrological sites, it is very difficult to obtain the water level change of the wetlands, especially those covered with vegetation. Synthetic aperture radar Interferometry (InSAR) has been proposed and used to solve the problem. However, with limited InSAR pairs, water level change time series cannot be obtained. In this paper, an InSAR time series analysis method called small baseline subset approach (SBAS) has been used to solve this problem. A total of 13 scenes of PALSAR L band SAR images are used for small baseline subset analysis. Only interferometric pairs with average coherence above 0.3 in the region of interest (wetlands with vegetation cover) are selected. Then small baseline subset approach was applied to interferograms after flattening, removal of the phase of terrain, filtering and phase unwrapping using minimum cost flow algorithm. Finally time series of relative water level change from June 28th, 2007 to December 31th, 2008 was obtained. Preliminary results on test sites showed an approximate linear-rate water level change. Our experiments showed the feasibility and potential of wetland water level change monitoring using SBAS.

Subsurface targets detection with Shannon entropy

Synthetic Aperture Radar (SAR) has the penetration of the drying dielectric layer, which can detect subsurface targets and buried characteristics. It took fully polarimetric SAR datasets of the subsurface in Lop Nur Palaeo-lacustrine basin for example to compute Shannon entropy parameter and analyze its image features, and then compare those with the other polarization parameters and polarization decomposition results from scattering mechanism and image features. The results show that the introduced Shannon entropy can describe the actual situation and express the image features more obvious in study area, so it has an important reference value for subsurface targets detection and buried characteristics extraction.