Current and potential uses of optical remote sensing in rice-based irrigation systems: a review
T. G. Van Niel and T. R. McVicar
Australian Journal of Agricultural Research
55(2) 155 - 185
Published: 01 March 2004
Abstract
For high water usage cropping systems such as irrigated rice, the positive outcomes of producing a staple food source and sustaining the economy often come at the cost of high resource use and environmental degradation. Advances in geospatial technology will play an increasingly important role in raising productivity and resource use efficiency and reducing environmental degradation, both worldwide and within Australia. This paper reviews the current use of one of these technologies, remote sensing, with the rice-growing region in Australia as a case study. Specifically, we review applications of remote sensing in crop identification, area measurement, regional yield forecasting, and on-farm productivity monitoring and management. Within this context, consideration is given to classification algorithms and accuracy assessment, hyperspectral remote sensing, positional and areal accuracy, linear mixture modelling, methane (CH4) emissions, yield forecasting techniques, and precision agriculture. We also discuss the potential for using remote sensing to assess crop water use, which has received little attention in rice-based irrigation systems, even though it is becoming increasingly important in land and water management planning for irrigation areas. Accordingly, special attention is given to the role of remote sensing with respect to the surface energy balance, the relationship between surface temperature and remotely sensed vegetation indices, and water use efficiency. A general discussion of other geospatial issues, namely geographic information systems and spatial interpolation, is provided because earth-science analysis using remote sensing is often intrinsically integrated with other spatially based technologies and aspects of geographical science.Keywords: crop identification, area measurement, yield, productivity, water use mapping.
https://doi.org/10.1071/AR03149
© CSIRO 2004