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• W969273703 abstract "discussed. The use of regression techniques in this type of analysis, where errors occur in the data, is considered. Green leaf area index, green biomass and green cover were successfully estimated but the ratio vegetation indices were not good indicators of brown vegetation. Airborne and satellite borne optical sensors recording in the visible to short wave infrared spectrum (04-2 5 ,um) receive solar radiation reflected from the Earth's sur face. It is our task to use these data to map surface features. Images derived from these data are being used increasingly in a wide range of disciplines although the use of remotely sensed data in a digital format to produce maps is less extensive outside the remote sensing community. Digital data can however, be used to estimate quantities of variables on the ground, eg vegetation biomass and crop yield. Maps which need to be updated regularly and which require more than point sample data can be produced from the information derived from remotely sensed data. The aim of this paper is to discuss research in which a methodology to use remotely sensed data for estimating biomass and green leaf area index (GLAI) of pasture has been developed. Reference is made to three pieces of research: In the first, an empirical modelling methodology is examined using remotely sensed data with a high spatial and spectral resolution over a small area (Curran and Williamson 1985). In the second study, a refined methodology is applied to a contrast ing area using data at a lower spectral and spatial resolution (Williamson 1990). In the final piece of research, the applicability of the methodology in a semi-arid area is discussed. Methodologies developed for grassland areas may be extended to yield estimates of crops which have a long green grass growth stage such as wheat. Remotely sensed data can provide information on grassland features such as: biomass for calculating carrying capacity, cover levels for assessing soil erosion potential and curing rates for bushfire monitoring." @default.
• W969273703 created "2016-06-24" @default.
• W969273703 creator A5027939521 @default.
• W969273703 date "1990-01-01" @default.
• W969273703 modified "2023-09-27" @default.
• W969273703 title "Developing a methodology for estimating grassland variables with remotely sensed data." @default.
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