The Great Plains Corridor rangeland project at Texas A&M University uses natural vegetation systems as phenological indicators of seasonal development and climatic effects on regional growth conditions. A method has been developed to quantitatively measure vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values from ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter correlated with aboveground green biomass and vegetation moisture content. The project aims to determine the feasibility of using ERTS-type data to map regional vegetation conditions throughout the growing season in the Great Plains. A network of ten test sites in six states was established, with ground observations recorded every eighteen days. ERTS-1 MSS data were acquired for four full seasons and processed to analyze spectral reflectance data. The data were corrected for seasonal sun angle differences to allow temporal comparisons. The study found that the Band Ratio Parameter (BRP), calculated as the difference between radiance values in bands 5 and 7 divided by their sum, is significant for vegetation condition analysis. A transformed vegetation index (TVI) was derived from BRP, normalized to eliminate seasonal sun angle differences and atmospheric attenuation. TVI values were highly correlated with vegetation condition, particularly at the Throckmorton site, where vegetation moisture content and green biomass accounted for most of the variation. The project confirmed the feasibility of using ERTS-1 data for regional vegetation monitoring and agricultural applications. The results support the basic hypotheses of the study, including the use of repetitive multispectral data to monitor the "green wave effect" and the importance of temporal effects in distinguishing landforms, soils, and vegetation types. The study also evaluated the potential of an operational satellite system for monitoring natural vegetation in the Great Plains Corridor.The Great Plains Corridor rangeland project at Texas A&M University uses natural vegetation systems as phenological indicators of seasonal development and climatic effects on regional growth conditions. A method has been developed to quantitatively measure vegetation conditions over broad regions using ERTS-1 MSS data. Radiance values from ERTS-1 spectral bands 5 and 7, corrected for sun angle, are used to compute a band ratio parameter correlated with aboveground green biomass and vegetation moisture content. The project aims to determine the feasibility of using ERTS-type data to map regional vegetation conditions throughout the growing season in the Great Plains. A network of ten test sites in six states was established, with ground observations recorded every eighteen days. ERTS-1 MSS data were acquired for four full seasons and processed to analyze spectral reflectance data. The data were corrected for seasonal sun angle differences to allow temporal comparisons. The study found that the Band Ratio Parameter (BRP), calculated as the difference between radiance values in bands 5 and 7 divided by their sum, is significant for vegetation condition analysis. A transformed vegetation index (TVI) was derived from BRP, normalized to eliminate seasonal sun angle differences and atmospheric attenuation. TVI values were highly correlated with vegetation condition, particularly at the Throckmorton site, where vegetation moisture content and green biomass accounted for most of the variation. The project confirmed the feasibility of using ERTS-1 data for regional vegetation monitoring and agricultural applications. The results support the basic hypotheses of the study, including the use of repetitive multispectral data to monitor the "green wave effect" and the importance of temporal effects in distinguishing landforms, soils, and vegetation types. The study also evaluated the potential of an operational satellite system for monitoring natural vegetation in the Great Plains Corridor.