Discriminating and mapping the C3 and C4 composition of grasslands in the northern Great Plains,USA |
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| Affiliation: | 2. Livestock and Forestry Research Station, Division of Agriculture, University of Arkansas, Batesville 72501;3. Cooperative Extension Service, Bourbon County, University of Kentucky, Paris 40361;4. Department of Agronomy, The Pennsylvania State University, University Park 16802;1. School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, China;2. Department of Geography and Planning, University of Toronto, Toronto ON M5S3G3, Canada;3. School of Geographical Sciences, Fujian Normal University, Fuzhou 350117, China;4. Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China;5. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China |
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| Abstract: | There is uncertainty about the extent and distribution of grasslands following the C3 and C4 photosynthetic pathways. Since these grasses have an asynchronous seasonal profile it should be possible to estimate and map the C3–C4 composition of grasslands from multi-temporal remote sensing imagery. This potential was evaluated using 30 weekly composite MERIS MTCI images for South Dakota, USA. Derived relationships between the remotely sensed response and composition of grasslands were significant, with R2 ∼ 0.6. It also appears possible to map broad classes of grassland composition, with a three class (high, medium and low C3 cover) classification having an accuracy of 77.8%. |
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