STM Journals Peer-reviewed research from Consortium e-Learning Network

Research & Reviews : Journal of Space Science & Technology

Vegetation Studies Using VIs, TIR, LULC and OCCs: Review

  1. Sheron Henry Christy

Abstract

Utilizing remote sensing images for vegetation cover mapping can prove a major role in finding an economical mean to analyze and observe vegetation cover changes over a large area. Easy algorithms in form of vegetation indices can be helpful for impactful evaluations of same. SAVI index can help for estimating accurately biomass aboveground in dry forest areas. Thermal infrared remote sensing data can be further utilized to retrieve biophysical & biochemical parameters of vegetation. Variations in LULC (land use land cover) can provide useful information regarding man-made activities over a decade affecting adversely ecological systems. Integrating further RS data in OCC (one class classifier) to categorize vegetation has many advantages in addition to challenges which are discussed in this paper.

Keywords

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