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| Filter results4 paper(s) found. |
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1. Mapping African soils at 30m resolution - iSDAsoil - Western Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... J. Crouch, K. Shephard, M. Miller, J. Collinson, P. Singh, P. Pypers, R. Van den bosch, C. Van beek, M. Chernet, S. Aston |
2. Mapping African soils at 30m resolution - iSDAsoil - Eastern Time Zones“iSDAsoil” combines remote sensing data and other geospatial information with carefully stratified point samples subjected to spectral analysis and traditional wet chemistry reference analysis. State of the art machine learning techniques were used to create digital maps of 17 agronomically important soil properties at 3 depths, including estimates of uncertainty. iSDAsoil is designed to encourage sharing and we hope that the owners of other soil and agronomic data, in industry... C. Van beek, M. Chernet, S. Aston, M. Miller, J. Collinson, K. Shephard, J. Crouch, T. Terhoeven-urselmans |
3. Performance of Remote Sensing Data and Machine Learning for Wheat Disease DetectionThe use of agrochemicals has many impacts on humans’ health and generates many environmental issues. However, a suitable management of agrochemicals inputs, such as insecticides, fungicides, and herbicides, is crucial to the success of wheat crops under climate change conditions. The use of remote sensing technologies in agriculture was raised within the technological evolution of materials and techniques during last decades. The development of new and cheap sensors has been the main reason... Y. Lebrini, A. Ayerdi-gotor |
4. Detecting the Impact of Hail Damage on Maize Crops in Smallholder Farms Using Unmanned Aerial Vehicles Derived Multispectral DataNatural disasters such as hailstorms are now frequent and negatively impact smallholder farmers' livelihoods. In these events, there is a need for robust and innovative techniques for monitoring the extent of their damage in smallholder croplands to optimise production. In this regard, this study sought to evaluate the utility of drone-derived multispectral data in estimating crop health elements (i.e., equivalent water thickness (EWT), chlorophyll content, and leaf area index (LAI) of maize... M. Sibanda |