Abstract
On April 26, 2015, an earthquake of magnitude 7.8 on the Richter scale occurred, with epicentre at Barpak (28°12'20''N,84°44'19''E), Nepal. Landslides induced due to the earthquake and its aftershock added to the natural disaster claiming more than 9000 lives. Landslides represented as lines that extend from the head scarp to the toe of the deposit were mapped by the staff of the British Geological Survey and is available freely under Open Data Commons Open Database License(ODC-ODbL) license at the Humanitarian Data Exchange Program. This collection of 5578 landslides is used as preliminary ground truth in this study with the aim of producing polygonal delineation of the landslides from the polylines via object oriented segmentation. Texture measures from Sentinel-1a Ground Range Detected (GRD) Amplitude data and eigenvalue-decomposed Single Look Complex (SLC) polarimetry product are stacked for this purpose. This has also enabled the investigation of landslide properties in the H-Alpha plane, while developing a classification mechanism for identifying the occurrence of landslides.
Highlights
The Nepal Earthquake of April 26, 2015, is compared in terms of damage to the great earthquake of 1934, (Rana, 1935), and is regarded as part of a cycle of major earthquakes that occur due to the tectonic fault running through Nepal
Ground Range Detected (GRD) data products from the Sentinel1a satellite is used for generating Gray-Level Co-Occurrence Matrix (GLCM) and Gabor features for region growing segmentation
Numerous use of texture measures for segmentation can be found in the literature, it has not been explored with data from Sentinel-1a for delineating landslides
Summary
The Nepal Earthquake of April 26, 2015, is compared in terms of damage to the great earthquake of 1934, (Rana, 1935), and is regarded as part of a cycle of major earthquakes that occur due to the tectonic fault running through Nepal. With the launch of Sentinel-2 and Sentinel-3 satellite system, the complete sentinel mission will eventually enable unprecedented monitoring of the earth’s environment, (Kramer, 2012) In this investigation, Ground Range Detected (GRD) data products from the Sentinel1a satellite is used for generating Gray-Level Co-Occurrence Matrix (GLCM) and Gabor features for region growing segmentation. Phase information is lost in GRD conversion, but the phase information on Single Look Complex (SLC) images can be used by generating Entropy, Alpha and Anisotropic, (Cloude et al, 2002), data This is accomplished by decomposing speckle filtered and debursted images using eigenvalue decomposition, (Lee and Pottier, 2009). In total 3760 landslides were recorded inside this particular footprint, a smaller region inside this footprint as shown, is used as Area of study This coincided with the availability of Digital Elevation Model for the area. VV Probabilistic Quantizer 32 11x11 All 1 Contrast,Dissimilarity,Homogeneity, Mean,Variance,Correlation Energy,Entropy, Angular Second Momentum theta={0,45,90,135}
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