Abstract
In this study we tested whether we can use a temporal series of 16 day Moderate Resolution Imaging Spectroradiometer (MODIS) derived normalized difference vegetation index (MODIS NDVI) data for the 2010–11 season to distinguish fields of soyabean from those of maize and tobacco with different planting dates in large scale commercial farms of Zimbabwe. We also test statistically for an optimal phenological stage (whether green up onset, green peak, or senescence) at which we can distinguish these crops. Furthermore, we test whether we can use rainfall to explain any anomalies in crop NDVI profiles data for the same season. Our results indicate that when planting date is considered as a variable, it is possible to distinguish soyabean, maize and tobacco using MODIS NDVI profiles during the early green up stage, as well as, during the late green up stage. In addition, our results confirm the effect of rainfall on the NDVI signal of crops, with a decrease in rainfall having a dipping effect on the NDVI and vice versa.
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Acknowledgments
We acknowledge the support of the African Institute for Agrarian Studies (AIAS) and Ruzivo Trust who facilitated fieldwork logistics. We also want to acknowledge Joseph Chiriseri, a colleague who helped out in data collection for the entire fieldwork exercise. Thanks are also due to Ezekia Svotwa of the Tobacco Research Board, for providing valuable comments and suggestions.
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Maguranyanga, C., Murwira, A. & Sibanda, M. Distinguishing Maize, Soyabean and Tobacco Fields Using Temporal MODIS 16 Day NDVI Images in the Large Scale Commercial Farming Areas of Zimbabwe. J Indian Soc Remote Sens 43, 79–87 (2015). https://doi.org/10.1007/s12524-014-0395-3
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DOI: https://doi.org/10.1007/s12524-014-0395-3