Linking remotely sensed forage quality estimates from WorldView-2 multispectral data with cattle distribution in a savanna landscape |
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| Institution: | 1. Department of Earth Observation, Institute of Geography, Friedrich Schiller University Jena, Jena, Germany;2. Ecosystem Earth Observation, Council for Scientific and Industrial Research, Pretoria, South Africa;3. Department of Geography, Geoinformatics and Meteorology, University of Pretoria, Pretoria, South Africa;4. Department of Biogeochemical Processes, Max Planck Institute for Biogeochemistry, Jena, Germany;5. Scientific Services, South African National Parks, Skukuza, South Africa;6. Centre of African Ecology, School of Animal, Plant and Environmental Sciences, University of Witwatersrand, Johannesburg, South Africa;7. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA;1. Professor, Animal and Range Sciences Department, New Mexico State University, Las Cruces, NM 88003, USA;2. Graduate Research Assistants, Animal and Range Sciences Department, New Mexico State University, Las Cruces, NM 88003, USA;3. Professor and John E. Rouse Chair, Department of Animal Sciences, Colorado State University, Fort Collins, CO 80523, USA;4. Professor, Department of Animal Science, University of California, Davis, CA 95616, USA;5. Postdoctoral Scholars, Department of Animal Science, University of California, Davis, CA 95616, USA;6. Research Associate, Northern Agricultural Research Center, Montana State University, Havre, MT 59501, USA;1. Department of Wildland Resources and the Ecology Center, Utah State University, Logan, UT 84322-5230, USA;2. Department of Plants, Soils and Climate and the Ecology Center, Utah State University, Logan, UT 84322-4820, USA;3. Rocky Mountain Research Station, US Forest Service, Missoula, MT 59801, USA |
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| Abstract: | Remote sensing has recently been used to map forage quality for rangeland management. However, the validity of the remotely sensed forage quality can best be assessed when it connects well with the animal unit. In this study we used the new WorldView-2 multispectral imagery to estimate and map forage quality (nitrogen concentration) as a step to explain GPS based cattle distribution in a rangeland of Southeastern Zimbabwe. Nitrogen concentration was successfully estimated and mapped (Rcv2 = 0.66, relative error = 0.13%) using partial least squares regression (PLSR). The integration of GPS based cattle distribution patterns with forage quality in a GIS showed that cattle locations significantly clustered in areas of high forage quality. The results of this study suggest that new multispectral data with unique band settings such as WorldView-2 improves the estimation and mapping of forage quality in rangelands at landscape level. In addition, our results indicate that remotely sensed forage quality can be used to explain herbivore distribution, particularly cattle grazing patterns in rangelands. |
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| Keywords: | WorldView-2 Nitrogen GPS Cattle Rangeland Partial least squares regression |
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