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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Main Authors: P. B. Budha, A. Bhardwaj
Format: Article
Language:English
Published: Copernicus Publications 2019-12-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access: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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spelling 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 &lt;&thinsp;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&thinsp;m<sup>2</sup> to 1675&thinsp;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 &lt;&thinsp;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&thinsp;m<sup>2</sup> to 1675&thinsp;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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