Record Details

Mapping invasive plant <i>Prosopis juliflora</i> in arid land using high resolution remote sensing data and biophysical parameters

NOPR - NISCAIR Online Periodicals Repository

View Archive Info
 
 
Field Value
 
Title Mapping invasive plant Prosopis juliflora in arid land using high resolution remote sensing data and biophysical parameters
 
Creator Vidhya, R.
Vijayasekaran, D.
Ramakrishnan, S.S.
 
Subject Invasive plant
SVM classification
Vegetation Indices
Classification accuracy
 
Description 1135-1144
In this study, high resolution remote sensing data is used to extract Prosopis juliflora (P.juliflora), which is a major invader in the study area. Support Vector Machine (SVM) classification is applied to map this invader with Normalized Difference Vegetation Index (NDVI) as an additional parameter. Optimal kernel selection has been done for SVM classification, and a polynomial kernel has been selected for the analysis. SVM polynomial kernel generated the overall accuracy of 70% and Kappa of 0.63. Classification results were compared with the results of conventional maximum likelihood classification (MLC). It was observed that the classification accuracy is improved from 68% to 74% when NDVI was used in MLC. But, when the SVM approach was used with NDVI, the accuracy dramatically increased to 93%. This is because the NDVI is a ratio based index, which introduces information about biophysical properties, thereby helping in better separation of P.juliflora.
 
Date 2017-05-29T09:58:04Z
2017-05-29T09:58:04Z
2017-06
 
Type Article
 
Identifier 0975-1033 (Online); 0379-5136 (Print)
http://nopr.niscair.res.in/handle/123456789/42009
 
Language en_US
 
Rights CC Attribution-Noncommercial-No Derivative Works 2.5 India
 
Publisher NISCAIR-CSIR, India
 
Source IJMS Vol.46(06) [June 2017]