Document Type
Article
Publication Date
10-20-2016
Keywords
Normalized Difference Vegetation Index (NDVI); land cover; supervised classification; land slide risk; remotely sensed soil moisture; logistic regression
Digital Object Identifier (DOI)
https://doi.org/10.3390/geosciences6040045
Abstract
Unfavorable land cover leads to excessive damage from landslides and other natural hazards, whereas the presence of vegetation is expected to mitigate rainfall-induced landslide potential. Hence, unexpected and rapid changes in land cover due to deforestation would be detrimental in landslide-prone areas. Also, vegetation cover is subject to phenological variations and therefore, timely classification of land cover is an essential step in effective evaluation of landslide hazard potential. The work presented here investigates methods that can be used for land cover classification based on the Normalized Difference Vegetation Index (NDVI), derived from up-to-date satellite images, and the feasibility of application in landslide risk prediction. A major benefit of this method would be the eventual ability to employ NDVI as a stand-alone parameter for accurate assessment of the impact of land cover in landslide hazard evaluation. An added benefit would be the timely detection of undesirable practices such as deforestation using satellite imagery. A landslide-prone region in Oregon, USA is used as a model for the application of the classification method. Five selected classification techniques—k-nearest neighbor, Gaussian support vector machine (GSVM), artificial neural network, decision tree and quadratic discriminant analysis support the viability of the NDVI-based land cover classification. Finally, its application in landslide risk evaluation is demonstrated.
Rights Information
This work is licensed under a Creative Commons Attribution 4.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Geosciences, v. 6, issue 4, art. 45
Scholar Commons Citation
Dahigamuwa, Thilanki; Yu, Qiuyan; and Gunaratne, Manjriker, "Feasibility Study of Land Cover Classification Based on Normalized Difference Vegetation Index for Landslide Risk Assessment" (2016). Civil and Environmental Engineering Faculty Publications. 46.
https://digitalcommons.usf.edu/egx_facpub/46
