Monitoring cotton crop condition through synergy of optical and radar remote sensing. Issue 2 (7th January 2022)

• Record Type: Journal Article
• Authors: Haldar, Dipanwita; Tripathy, Rojalin; Dave, Viral; Dave, Rucha; Bhattacharya, B. K.; Misra, Arundhati
• Is Part Of: Geocarto international. Volume 37:Issue 2(2022)
• Page Start: 377
• Page End: 395
• Publication Date: 2022-01-07
• Subjects: SAR remote sensing -- VI -- RVI -- RISAT-1 -- cotton biophysical parameters -- fresh and dry biomass -- Vegetation water content; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2020.1726506
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Synergistic use of Optical and Microwave remotely sensed data for cotton condition based on biophysical traits, indices from ground measurements and satellite derived reflectance were assessed. Regression models derived for estimating LAI, biomass and VWC using ground based indices were applied to satellite products. LAI, biomass and VWC of cotton with optical VIs as input ( R 2 = 0.42, 0.51 and 0.52) respectively were estimated. Correlation between RVI and plant height, crop age and VWC were found between 0.4 and 0.6. Fresh biomass from RVI ranged 100 –4000 gm −2, dry biomass from NDVI ranged 50–950 gm −2 and VWC 65–85%. Correlation between VIs and RVI was found to be non- significant. A multiple linear regression model using NDVI vs. LSWI and RVI were developed to assess LAI, biomass and VWC. The model predicted LAI with R 2 of 0.5 but failed to estimate biomass and VWC.