Automated extraction of various vegetative and water body indices from multisensor satellite data: a MATLAB approach View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2018-08

AUTHORS

Girish Gopinath, S. Nimmi

ABSTRACT

The increasing availability of remote sensing imageries with different spatial, spectral, temporal and radiometric characteristics expands the horizon of our choices in imageries and vegetation mapping. Among the various techniques in vegetation mapping the use of vegetative indices confiscates the simplest and easiest one to understand and calculate. This work proposes automatic extraction of different vegetation and water indices from ResourceSat-1(IRS-P6) images. The concept paves to calculate indices for any ResourceSat image prearranged to the program which is written in MATLAB 2013a. The effortlessly accessible images from its onboard sensors as Medium Resolution Linear Imaging Self-Scanner (LISS-III) and Advanced Wide Field Sensor (AWiFS) were considered to calculate six major indices like Normalized Difference Vegetation Index, Infrared Percentage Vegetation Index, Ratio Vegetation Index, Green Normalized Difference Vegetation Index, Green Red Vegetation Index, and Normalized Difference Water Index automatically. The program was written for any ResourceSat (LISS-III and AWiFS) data so that further analysis as well as calculation of more indices can be done by any individual within MATLAB. The user-friendly and time preserving feature makes MATLAB more powerful that any common user can deal with the analysis without the presence of any GIS experts that other softwares do. More... »

PAGES

397-404

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s41324-018-0183-1

DOI

http://dx.doi.org/10.1007/s41324-018-0183-1

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1101720442


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