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Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/783
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| Title: | Use of multi-source data sets for land use/land cover classification in a hilly terrain for landslide study. |
| Authors: | Kanungo, D P
Sarkar, S |
| Keywords: | Land use
Land cover
Image classification
Multi-source
Landslide
2011 |
| Issue Date: | 5-Mar-2012 |
| Abstract: | The land use/land cover (LULC) information of an area is essential for monitoring and
management of natural resources. It is an important input for many geological,
hydrological, ecological and agricultural models. In this study, the IRS-1C LISS-III data
have been used as the primary data source along with NDVI (Normalized Difference
Vegetation Index) and DEM (Digital Elevation Model) images as additional data layers to
improve the LULC classification accuracy in a hilly terrain. Image classification is
performed using most widely used Maximum Likelihood Classifier (MLC). The IRS-1C
PAN image is used as the reference data for generating training and testing datasets. The
preparation of reference data is ably supported with field data as well as information from
topographic maps. The results show a reasonable improves in the accuracy of
classification on incorporation of NDVI and DEM as ancillary data. The LULC map thus
prepared is useful as one of the input data layers for landslide hazard study. High spatial
resolution IRS-1CPAN and PAN-sharpened LISS-III images were used to prepare a
landslide distribution map which was verified from field surveys. Landslide density is
found to be maximum in barren lands, followed by agriculture land, built-up land, tea
plantation area, and forest cover. The relation between LULC and landslide density thus
obtained was later used as an input for landslide susceptibility mapping. |
| Description: | Disaster & Development, Vol. 5 (1), pp.35-51. |
| URI: | http://hdl.handle.net/123456789/783 |
| Appears in Collections: | Published Articles
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