Remotely-sensed spectral indicators of sorghum development and their use in growth modeling

Abstract

Earth Resources Technology Satellite (LANDSAT) multispectral scanner (MSS) data for five overpass dates (3/5, 21/5, 8/6, 28/6 and 1/8) during the 1976 grain sorghum growing season (Bell County, Texas) and weather data were used to estimate the plant growth measurements leaf area index (LAI), biomass, plant height, plant cover, and grain yield. Vegetaton indices derived from LANDSAT data were correlated to crop development and growing conditions as measured with LAI and biomass samples. Largest LAI and perpendicular vegetation index (PVI) calculated from LANDSAT spectral data occurred at the half-bloom (HB) stage of development. The PVI was significantly correlated with sorghum PGM on the earliest sampling date (3/5/76) when vegetative ground cover was only 20%. Regression analysis indicated that the PVI explained 79% of the variaton in estimating LAI over the first four sampling dates. On the other hand, the regression of PVI, solar-thermal units, and a soil water index accounted for 90% of the variation in LAI measurements. This result indicated that plant-growth models that mimic plant response to soil and climatic environments will improve yield estimates over those arrived at from spectral data alone. Since LAI is used in growth models to partition energy between plants and soil in the evapotranspiration subroutine and to estimate light interception in the photosynthesis subroutine, LAI estimates from LANDSAT would provide this information for use either as (1) input data, or (2) feedback data to check on growth model predictions and retrack the model, if necessary.