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The earthquake-induced barrier lakes that are caused by landslides are at risk of bursting after excessive rainfall, and they are a serious threat to the surrounding residents. This paper proposes a change detection approach of the barrier lake using the method of post-classification comparison combined with background subtraction. The case studied in the paper is the detection of the Tangjiashan barrier lake, which is one of the largest lakes induced by the Wenchuan Earthquake on 12 May 2008. Both the pre- (31 March 2007) and post-earthquake (16 May 2008) images of the Advanced Land Observing Satellite (ALOS) Advanced Visible and Near Infrared Radiometer type 2 (AVINER-2) were collected in the paper. The results show that the river widened through the Zhangping area, increasing from 90 m pre-earthquake to 545 m post-earthquake, and the surface area of the barrier lake increased from 0.945 km2 to 1.471 km2. [ABSTRACT FROM AUTHOR]

This paper illustrates the capabilities of the Advanced Land Observing Satellite (ALOS) Phased Array Type L-band Synthetic Aperture Radar (PALSAR) instrument in the identification of macro- and meso-scale land deformation caused by the Wenchuan Earthquake of 12 May 2008. The specific location analysed is an area near the south west termination of the rupture zone where fault slip and surface deformations were relatively low and topography is relatively high. A full geometric processing of the interferometric synthetic aperature radar (InSAR) data is performed, including the removal of the stereoscopic effect, and the terrain effect fully compensated by identification and removal of layover and shadow areas. This allows for the full characterization of the main earthquake deformation. [ABSTRACT FROM AUTHOR]

The Satellite Differential Interferometric Synthetic Aperture Radar (DInSAR) has already demonstrated its potential to map co-, post- and inter-seismic deformation. This paper presents an.alysis of the surface-displacement field of the 12 May 2008 magnitude 8.0 Wenchuan Earthquake using the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) DInSAR. Six PALSAR interferograms of paths 471 to 476 are generated. A new approach, which uses the information of overlapping interferograms, has been developed to compensate for orbit error. The main advantage of this approach is that the calculation is performed without the need for phase unwrapping. Once the orbit error has been compensated for, the interferograms are then merged to form a single interferogram. The final mosaic of interferograms demonstrates a much more consistent co-seismic surface-displacement field than the original interferograms. [ABSTRACT FROM AUTHOR]

The Wenchuan Earthquake of magnitude 8.0 struck Sichuan Province in south-west China on 12 May 2008. This paper presents an overview of the use of multi-source satellite images in investigating the influence of this earthquake around the epicentral area. The results show the capability of remote sensing technique for damage detection in quake-hit areas. Optical satellite images (FORMOSAT-2 and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)) provide useful information, although rain and cloud limit the availability of satellite data. However, the Synthetic Aperture Radar (SAR) sensor provides information in all weather conditions. Combined optical satellite and SAR data have been used to assess the damage of earthquakes, including landslides, barrier lakes and collapsed buildings. From the interferogram of two phased array type L-band SAR (PALSAR)/Advanced Land Observing Satellite (ALOS) images, more than 100 cm of ground displacement was found in Beichuan County, one of the worst-affected earthquake areas. These examples show the use of satellite images in post-disaster damage assessment and planning during the rescue operation soon after a major event such as the 12 May 2008 earthquake. [ABSTRACT FROM AUTHOR]

A dual-frequency global positioning system (GPS) receiving set-up at Guwahati (26° 10' N, 91° 45' E), has been in operation for the last year and a half, providing total electron content (TEC) data as input for understanding pre-earthquake contributions to low-latitude atmospheric dynamics. The major China earthquake of 12 May 2008, with magnitude 8.0 and an epicentre at 31° 24' N, 103° 58' E is a rare event to facilitate extracting earthquake features on the TEC data, and hence low-latitude system perturbations. This paper begins with a brief discussion on the methods adopted in identifying TEC performance before an impending earthquake from ionospheric data, and presents results of analysis of the event of 12 May. TEC magnitudes recorded with latitude / longitude and elevation of satellites for every pass are linked with pre-earthquake TEC features and are used as inputs to identify epicentre position. The role of seismic-time refractive index variations is examined to explain the observed TEC characteristics. [ABSTRACT FROM AUTHOR]

MERIS (Medium Resolution Imaging Spectrometer) is a fine spectral and medium spatial resolution satellite sensor and is part of the core instrument payload of Envisat, the European Space Agency's (ESA) environmental research satellite, launched in March 2002. Designed primarily for ocean (‘MER’) and coastal zone remote sensing, this imaging spectrometer (‘IS’) now has a much broader environmental remit covering also land and atmospheric applications. This paper reviews (i) MERIS's development history, focusing on its changing mission objectives; (ii) MERIS's technical specification, including its radiometric, spectral and geometric characteristics, programmability and onboard calibration; (iii) decisions that led to modifications of MERIS's spectral, geometric and radiometric performance for land applications; (iv) MERIS's data products; and (v) some of the ways in which MERIS data might be used to provide information on terrestrial vegetation. [ABSTRACT FROM AUTHOR]

The land cover cartography from the optical remote sensing data can be carried out by using the multi-texture classification. In the multi-texture classification, the textural parameters, computed from local or global statistics of the image, are used as the quantitative descriptors to be classified. However, computation of textural parameters from grey-tone values is not relevant for the feature extracted data used in this study. So, textural analysis has to be performed on a binary image. In this paper, we present a method leading to the mapping of the spatial organization, so-called 'macro-texture', of a unique thematic set. The particularity of the proposed method resides in the use of the concept of granulometric analysis of a binary image for defining the macro-texture parameters. The local granulometry density is computed on a window that is centred at each pixel of the binary image. This computation generates grey-tone images that will be classified by using the K-means method. The final map obtained from the classification of the pixels described by macro-textural parameters can be considered as a map of the density of the set under study. The method has been tested and evaluated on Satellite pour l'Observation de la Terre (SPOT) and Landsat Thematic Mapper (TM) data. The data cover the two arid regions characterized by different stages of ligneous covers. [ABSTRACT FROM AUTHOR]

Abundant vegetation species and associated complex forest stand structures in moist tropical regions often create difficulties in accurately classifying land-use and land-cover (LULC) features. This paper examines the value of spectral mixture analysis (SMA) using Landsat Thematic Mapper (TM) data for improving LULC classification accuracy in a moist tropical area in Rondônia, Brazil. Different routines, such as constrained and unconstrained least-squares solutions, different numbers of endmembers, and minimum noise fraction transformation, were examined while implementing the SMA approach. A maximum likelihood classifier was also used to classify fraction images into seven LULC classes: mature forest, intermediate secondary succession, initial secondary succession, pasture, agricultural land, water, and bare land. The results of this study indicate that reducing correlation between image bands and using four endmembers improve classification accuracy. The overall classification accuracy was 86.6% for the seven LULC classes using the best SMA processing routine, which represents very good results for such a complex environment. The overall classification accuracy using a maximum likelihood approach was 81.4%. Another finding is that use of constrained or unconstrained solutions for unmixing the atmospherically corrected or raw Landsat TM images does not have significant influence on LULC classification performances when image endmembers are used in a SMA approach. [ABSTRACT FROM AUTHOR]