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| Filter results5 paper(s) found. |
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1. Spatial Interpolation for Mapping Hydraulic Soil Properties in GIS EnvironmentSoil water information is an essential input for environmental, hydrological or land surface models. There is a need for reliable soil water information with current coverage in the area. A number of 60 soil profiles data were evaluated for the performance of estimates inverse distance weighting to map some of the soil quality properties. soil profiles were used for the application of geostatistics. Maps with the investigated coverage were produced with the soil information available about soil... M.A. Abdelrahman, A.M. Saleh, M.M. El sharkawy, E. Farg, S.M. Arafat |
2. Mapping African soils at 30m resolution - iSDAsoil: leveraging spatial agronomy in farm-level advisory for smallholdersField level soil data has been the foundation of agronomic advisory, but traditional methods involving on-farm sampling are too expensive for a large proportion of African smallholders. Building on the work of the African Soil Information Service (AfSIS), Innovative Solutions for Decision Agriculture (iSDA) and partners have created an agronomic soil database which covers the entire African continent at a spatial resolution of 30 m. “iSDAsoil” combines remote sensing data and other... J. Crouch |
3. 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 |
4. 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 |
5. High-Throughput Field Phenotyping of Ascochyta Blight Disease Severity in Chickpea Using Multispectral ImagingAscochyta blight (AB) caused by Ascochyta rabiei (Pass.) Labr. is an important and widespread disease of chickpea (Cicer arietinum L.) worldwide. The disease is particularly severe under cool and humid weather conditions, leading to crop losses at all stages of chickpea growth. Screening for resistant cultivars remains the most effective, economical and ecological method of disease management. However, traditional phenotyping methods that relying on trained experts are... F. Ibn el mokhtar, S. Krimibencheqroun , , A. Harkani , H. Houmairi , O. Idrissi , E. Abdellah , E. Abdellah |