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The use of RapidEye observations to map cropping systems in highly fragmented agro-ecological landscapes in Africa

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Investigation of Maize Lethal Necrosis (MLN) severity and cropping systems mapping in agro-ecological maize systems in Bomet, Kenya utilizing RapidEye and Landsat-8 Imagery, , , , , , and . Geology, Ecology, and Landscapes, (January 2020)Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya., , , , , , , and . Sensors, 17 (11): 2537 (2017)Estimating maize lethal necrosis (MLN) severity in Kenya using multispectral high-resolution data, , , , , , , , and . Applied Geomatics, (January 2021)Maize pest and diseas mapping using RapidEye-based vegetation indices and machine learning methods, , , , and . (October 2016)Maize Cropping Systems Mapping Using RapidEye Observations in Agro-Ecological Landscapes in Kenya, , , , , , , and . Sensor, (2017)Predicting stem borer density in maize using RapidEye data and generalized linear models., , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2017)Importance of Remotely-Sensed Vegetation Variables for Predicting the Spatial Distribution of African Citrus Triozid (Trioza erytreae) in Kenya., , , , , and . ISPRS Int. J. Geo Inf., 7 (11): 429 (2018)The use of RapidEye observations to map cropping systems in highly fragmented agro-ecological landscapes in Africa, , , , , , and . (June 2016)