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1 June 2009 Spatial models for selecting the most suitable areas of rice cultivation in the Inland Valley Wetlands of Ghana using remote sensing and geographic information systems
Muralikrishna Gumma, Prasad S. Thenkabail, Hideto Fujii, Regassa Namara
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Journal of Applied Remote Sensing, Vol. 3, Issue 1, 033537 (June 2009). https://doi.org/10.1117/1.3182847
Abstract
The overarching goal of this research was to develop spatial models and demonstrate their use in selecting the most suitable areas for the inland valley (IV) wetland rice cultivation. The process involved comprehensive sets of methods and protocols involving: (1) Identification and development of necessary spatial data layers; (2) Providing weightages to these spatial data layers based on expert knowledge, (3) Development of spatial models, and (4) Running spatial models for determining most suitable areas for rice cultivation. The study was conducted in Ghana. The model results, based on weightages to 16-22 spatial data layers, showed only 3-4 % of the total IV wetland areas were "highly suitable" but 39-47 % of the total IV wetland areas were "suitable" for rice cultivation. The outputs were verified using field-plot data which showed accuracy between 84.4 to 87.5% with errors of omissions and commissions less than 23%. Given that only a small fraction (<15% overall) of the total IV wetland areas (about 20-28% of total geographic area in Ghana) are currently utilized for agriculture and constitute very rich land-units in terms of soil depth, soil fertility, and water availability, these agroecosystems offer an excellent opportunity for a green and a blue revolution in Africa.
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Muralikrishna Gumma, Prasad S. Thenkabail, Hideto Fujii, and Regassa Namara "Spatial models for selecting the most suitable areas of rice cultivation in the Inland Valley Wetlands of Ghana using remote sensing and geographic information systems," Journal of Applied Remote Sensing 3(1), 033537 (1 June 2009). https://doi.org/10.1117/1.3182847
Published: 1 June 2009
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KEYWORDS
Data modeling
Earth observing sensors
Remote sensing
High resolution satellite images
Roads
Reflectivity
Geographic information systems
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