Radar Vegetation Index for assessing cotton crop condition using RISAT-1 data. Issue 4 (11th March 2020)

• Record Type: Journal Article
• Authors: Haldar, Dipanwita; Dave, Viral; Misra, Arundhati; Bhattacharya, Bimal
• Is Part Of: Geocarto international. Volume 35:Issue 4(2020)
• Page Start: 364
• Page End: 375
• Publication Date: 2020-03-11
• Subjects: Radar Vegetation Index -- cotton crop -- vegetation water content -- RISAT-1 -- crop parameters; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2018.1516249
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Periodic crop condition monitoring is of prime importance in cotton belt of western India for water stress management. In this article, vegetation water content (VWC) is assessed using Radar Vegetation Index (RVI) derived from the RISAT-1 data during July to September, vegetative to first picking phase, for utilizing its potential for large area cotton condition assessment. The RVI estimation from dual-polarized data has been demonstrated for regional applications. Prediction models of VWC for cotton crop using RVI and in situ ground measurements depicts significant relationship, with R 2 varying from 0.5 to 0.6 and RMSE of 0.3–0.7 kg m −2 . High correlation exists between RVI with crop age and crop biomass with R 2 varying from 0.55 to 0.7, this proves useful for sowing date prediction. The results showed good validation ( R 2 = 0.8) for operational applications. The estimated VWC was found with 30–35% error above 4 kg m −2 biomasses as compared to 20–25% in lower ranges.