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Vona, V

Aston, S

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Authors

Kulmany, I.M

Vona, V

Vona, M

Szekeres, L

Bede, L

Milics, G

Kovacs, B

Crouch, J

Shephard, K

Miller, M

Collinson, J

Singh, P

Pypers, P

van den Bosch, R

van Beek, C

Chernet, M

Aston, S

van Beek, C

Chernet, M

Aston, S

Miller, M

Collinson, J

Shephard, K

Crouch, J

Terhoeven-Urselmans, T

Topics

Adoption of Precision Agriculture

Plenary

Type

Poster

Oral

Year

2020

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Authors

Filter results3 paper(s) found.
1. Delineation of site-specific management zones based on soil apparent electrical conductivity (ECa) measurement combining traditional soil sampling method Site-specific management requires the identification of treatment areas based on homogeneous characteristics. The designation of subfield regions is challenging because of complex correlations appearing in spatial variability of soil properties and nutrient concentrations. The research was conducted on two neighbouring fields (48 ha and 15 ha) in Fejér county, Hungary. Soil ECa mapping was carried out on 22 October, 2019 and soil samples were taken on 15 November, 2019.... I.M. Kulmany, V. Vona, M. Vona, L. Szekeres, L. Bede, G. Milics, B. Kovacs
2. 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
3. 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

Filter results3 paper(s) found.

1. Delineation of site-specific management zones based on soil apparent electrical conductivity (ECa) measurement combining traditional soil sampling method

Site-specific management requires the identification of treatment areas based on homogeneous characteristics. The designation of subfield regions is challenging because of complex correlations appearing in spatial variability of soil properties and nutrient concentrations. The research was conducted on two neighbouring fields (48 ha and 15 ha) in Fejér county, Hungary. Soil ECa mapping was carried out on 22 October, 2019 and soil samples were taken on 15 November, 2019.... I.M. Kulmany, V. Vona, M. Vona, L. Szekeres, L. Bede, G. Milics, B. Kovacs

2. 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

3. 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