Quantification of grassland properties: how it can benefit from geoinformatic technologies?

Abstract

The emergence of advanced geoinformatic techniques raises the feasibility of successfully quantifying grassland properties. Accurate quantification of these parameters faces opportunities and challenges, both of which are reviewed critically in this paper. The principle of quantifying grassland properties is presented first, together with the requirements, followed by a review of the grassland properties (percentage grass cover, grassland biomass and grassland degradation) that have been quantified. Assessment of quantification accuracy has evolved from reliance on the R ² value of regression analysis to comparison against independent samples, with the highest accuracy being 89%. Achievement of higher accuracy is hindered by three obstacles, namely positional uncertainty of in situ samples, differential ground and image sampling intervals, and temporal irreversibility of historical satellite images. It is proposed that the global positioning system (GPS) be used to handle the first challenge, and hyperspatial resolution images to minimize disparity in the sampling intervals. The third challenge should be tackled through radiometric calibration of historic images based on invariant ground targets. With the emergence of hyperspectral imagery (e.g. AVIRIS and CASI), more grassland features (e.g. grassland productivity and carrying capacity) can be quantified in the future in a geographic information system (GIS). It is concluded that advances in the geoinformatic technology will enable more grassland properties to be quantified more accurately.