Abstract: A computer-implemented method is provided for facilitating agricultural operations in an agricultural field. In one example embodiment, the method includes identifying, based on spatial sampling of soil spectrum data for an agricultural field, ground sampling locations within the field to obtain physical soil samples representative of soil makeup for the field. The method also includes generating a soil model particular to the field by correlating soil properties for soil included in the soil samples obtained from the identified ground sampling locations to particular soil spectral bands included in the soil spectrum data for the field at the corresponding ground sampling locations. The method then further includes compiling, using the soil model, a soil map of the entire field visually illustrating particular seeds and/or populations of seeds to plant at different locations across the field and/or particular nutrient applications to apply at different locations across the field.

Abstract: A method is provided for determining soil properties for an area of land, from soil spectrum data. In an embodiment, the method includes receiving soil spectrum data records from hyperspectral sensors that represent a mean soil spectrum of a specific geo-location of the area of land and removing interference signals from the spectrum data records to create soil spectral bands. The method also includes predicting a plurality of soil property datasets based on a partial least-square regression and the soil spectral bands and selecting specific soil property datasets from the plurality of soil property datasets to represent soil properties of the specific geo-location, wherein the specific soil property datasets include property data and spectral band data for spectral bands used to determine the property data. The specific soil property datasets may then be used to generate a crop prescription of recommended hybrid seeds or population densities for the specific geo-location.

Abstract: A method is provided for determining soil properties for an area of land, from soil spectrum data. In an embodiment, the method includes receiving soil spectrum data records from hyperspectral sensors that represent a mean soil spectrum of a specific geo-location of the area of land and removing interference signals from the spectrum data records to create soil spectral bands. The method also includes predicting a plurality of soil property datasets based on a partial least-square regression and the soil spectral bands and selecting specific soil property datasets from the plurality of soil property datasets to represent soil properties of the specific geo-location, wherein the specific soil property datasets include property data and spectral band data for spectral bands used to determine the property data. The specific soil property datasets may then be used to generate a crop prescription of recommended hybrid seeds or population densities for the specific geo-location.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for building and using soil models that determine soil properties from soil spectrum data is provided. In an embodiment, building soil model may be accomplished using soil spectrum data received via hyperspectral sensors from a land unit. A processor updates the soil spectrum data by removing interference signals from the soil spectrum data. Multiple ground sampling locations within the land unit are then determined based on the updated soil spectrum data. Soil property data are obtained from ground sampling at the ground sampling locations. Soil models that correlate the updated soil spectrum data with the soil property data are created based on the updated soil spectrum data and the soil property data. The soil models are sent to a storage for future use.

Abstract: A method for estimating soil properties within a field using hyperspectral remotely sensed data is provided. In an embodiment, estimating soil properties may be accomplished using a server computer system that receives, via a network, soil spectrum data records that are used to predict soil properties for a specific geo-location. Within the server computer system a soil preprocessing module receives one or more soil spectrum data records that represent a mean soil spectrum of a specific geo-location of a specified area of land. The soil preprocessing module then removes interference signals from the soil spectrum data, creating a set of one or more spectral bands. By removing interference signals, the spectral bands are not erroneously skewed from effects such as baseline drift, particle deviation, and surface heterogeneity. A soil regression module inputs the one or more soil spectral bands and predicts soil property datasets.

Abstract: A method for estimating soil properties within a field using hyperspectral remotely sensed data is provided. In an embodiment, estimating soil properties may be accomplished using a server computer system that receives, via a network, soil spectrum data records that are used to predict soil properties for a specific geo-location. Within the server computer system a soil preprocessing module receives one or more soil spectrum data records that represent a mean soil spectrum of a specific geo-location of a specified area of land. The soil preprocessing module then removes interference signals from the soil spectrum data, creating a set of one or more spectral bands. By removing interference signals, the spectral bands are not erroneously skewed from effects such as baseline drift, particle deviation, and surface heterogeneity. A soil regression module inputs the one or more soil spectral bands and predicts soil property datasets.