公开(公告)号：US10338272B2

公开(公告)日：2019-07-02

申请号：US14866160

申请日：2015-09-25

Applicant: The Climate Corporation

Inventor： Haitao Xiang ,  Xianyuan Yang ,  Nick Koshnick ,  Nick Cisek

IPC: G01W1/10 ,  A01B79/00 ,  G01N21/17 ,  G01N21/31 ,  G01N33/00 ,  G01N33/24 ,  G01V99/00 ,  G06Q10/04 ,  G01N21/359

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. The soil property datasets include specific soil properties relevant to determining fertility of the soil or soil property levels that may influence soil management at a specific geo-location. The soil regression module then takes the multiple soil property datasets and selects multiple specific soil property datasets that best represent the existing soil properties. Included in the soil property datasets are the multiple soil properties predicted and the spectral band data used to determine the specific soil properties. The soil regression module sends this predicted data to a soil model database.

公开(公告)号：US20170090068A1

公开(公告)日：2017-03-30

申请号：US14866160

申请日：2015-09-25

Applicant: The Climate Corporation

Inventor： Haitao Xiang ,  Xianyuan Yang ,  Nick Koshnick ,  Nick Cisek

IPC: G01V99/00 ,  G01N33/24

CPC classification number: G01V99/005 ,  A01B79/005 ,  G01N21/359 ,  G01N33/0098 ,  G01N33/24 ,  G01N2021/1793 ,  G01N2021/3155 ,  G01N2201/0616 ,  G01N2201/129 ,  G01W1/10 ,  G06Q10/04

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. The soil property datasets include specific soil properties relevant to determining fertility of the soil or soil property levels that may influence soil management at a specific geo-location. The soil regression module then takes the multiple soil property datasets and selects multiple specific soil property datasets that best represent the existing soil properties. Included in the soil property datasets are the multiple soil properties predicted and the spectral band data used to determine the specific soil properties. The soil regression module sends this predicted data to a soil model database.