LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL
Locating landslides and determining its extent is deemed an important task in estimating loss and damage and carry out mitigation works. As landslides are recurring phenomena in the research site, Siwalik Hills of western Nepal, freely available Sentinel-2 satellite images were considered to delinea...
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Copernicus Publications
2019-12-01
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Series: | ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
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doaj-adcf11d3e6dc49a99e067f390ccbbe952020-11-25T02:31:45ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502019-12-01IV-5-W291510.5194/isprs-annals-IV-5-W2-9-2019LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPALP. B. Budha0P. B. Budha1A. Bhardwaj2Centre for Space Science and Technology Education in Asia and the Pacific, Dehradun, IndiaGreenhood Nepal, Kathmandu, NepalPhotogrammetry and Remote Sensing Department, Indian Institute of Remote Sensing, Dehradun, IndiaLocating landslides and determining its extent is deemed an important task in estimating loss and damage and carry out mitigation works. As landslides are recurring phenomena in the research site, Siwalik Hills of western Nepal, freely available Sentinel-2 satellite images were considered to delineate landslides. The method employed in this process was Object-Based Image Analysis carried out in eCognition software using multiresolution segmentation algorithm. Parameters taken for segmentation were a scale of 20, the shape of 0.3, and compactness of 0.5. When a threshold value of < 0.35 in NDVI was used to distinguish landslides from image objects, some non-landslide objects were also selected. These false positives were removed successively using the threshold values on different bands, band ratios, slope information, hillshade and geometrical properties of image objects. There were altogether 264 landslides detected in the study area with size ranging from 300 m<sup>2</sup> to 1675 m<sup>2</sup> and landslide density of approximately 2 per km<sup>2</sup>. The accuracy, when compared to reference inventory, showed correctness and completeness measuring 80.28% and 66.27% respectively. These results showed semi-automatic landslide extraction was successful and Sentinel-2 can be used for similar tasks in other areas of Siwalik.https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-5-W2/9/2019/isprs-annals-IV-5-W2-9-2019.pdf |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
P. B. Budha P. B. Budha A. Bhardwaj |
spellingShingle |
P. B. Budha P. B. Budha A. Bhardwaj LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
author_facet |
P. B. Budha P. B. Budha A. Bhardwaj |
author_sort |
P. B. Budha |
title |
LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL |
title_short |
LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL |
title_full |
LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL |
title_fullStr |
LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL |
title_full_unstemmed |
LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL |
title_sort |
landslide extraction from sentinel-2 image in siwalik of surkhet district, nepal |
publisher |
Copernicus Publications |
series |
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
issn |
2194-9042 2194-9050 |
publishDate |
2019-12-01 |
description |
Locating landslides and determining its extent is deemed an important task in estimating loss and damage and carry out mitigation works. As landslides are recurring phenomena in the research site, Siwalik Hills of western Nepal, freely available Sentinel-2 satellite images were considered to delineate landslides. The method employed in this process was Object-Based Image Analysis carried out in eCognition software using multiresolution segmentation algorithm. Parameters taken for segmentation were a scale of 20, the shape of 0.3, and compactness of 0.5. When a threshold value of < 0.35 in NDVI was used to distinguish landslides from image objects, some non-landslide objects were also selected. These false positives were removed successively using the threshold values on different bands, band ratios, slope information, hillshade and geometrical properties of image objects. There were altogether 264 landslides detected in the study area with size ranging from 300 m<sup>2</sup> to 1675 m<sup>2</sup> and landslide density of approximately 2 per km<sup>2</sup>. The accuracy, when compared to reference inventory, showed correctness and completeness measuring 80.28% and 66.27% respectively. These results showed semi-automatic landslide extraction was successful and Sentinel-2 can be used for similar tasks in other areas of Siwalik. |
url |
https://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/IV-5-W2/9/2019/isprs-annals-IV-5-W2-9-2019.pdf |
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