ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Download
Citation
Volume IV-5/W2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5/W2, 9–15, 2019
https://doi.org/10.5194/isprs-annals-IV-5-W2-9-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-5/W2, 9–15, 2019
https://doi.org/10.5194/isprs-annals-IV-5-W2-9-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

  05 Dec 2019

05 Dec 2019

LANDSLIDE EXTRACTION FROM SENTINEL-2 IMAGE IN SIWALIK OF SURKHET DISTRICT, NEPAL

P. B. Budha1,2 and A. Bhardwaj3 P. B. Budha and A. Bhardwaj
  • 1Centre for Space Science and Technology Education in Asia and the Pacific, Dehradun, India
  • 2Greenhood Nepal, Kathmandu, Nepal
  • 3Photogrammetry and Remote Sensing Department, Indian Institute of Remote Sensing, Dehradun, India

Keywords: Landslide Inventory, Object-Based Image Analysis, Image Segmentation, Semiautomatic Feature Extraction

Abstract. 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 m2 to 1675 m2 and landslide density of approximately 2 per km2. 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.