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公开(公告)号：US20210406745A1
公开(公告)日：2021-12-30
申请号：US17369835
申请日：2021-07-07
Applicant: The Climate Corporation
Abstract: A method for predicting field specific crop yield recommendations for a field may be accomplished using a server computer system that is configured and programmed to receive over a digital communication network, electronic digital data representing agricultural data records, including remotely sensed spectral property of plant records and soil moisture records. Using digitally programmed data record aggregation instructions, the computer system is programmed to receive digital data representing including remotely sensed spectral property of plant records and soil moisture records. Using the digitally programmed data record aggregation instructions, the computer system is programmed to aggregate the one or more digital agricultural records to create and store, in computer memory, one or more geo-specific time series over a specified time. Using the digitally programmed data record aggregation instructions, the computer system is programmed to select one or more representative features from the one or more geo-specific time series and create, for each specific geographic area, a covariate matrix in computer memory comprising the representative features selected from the one or more geo-specific time series. Using mixture linear regression instructions, the computer system is programmed to assign a probability value to a component group in a set of parameter component groups, where each component group within the set of parameter component groups includes one or more regression coefficients calculated from a probability distribution and an error term calculated from a probability distribution. Using distribution generation instructions, the computer system is programmed to generate the probability distributions used to determine the one or more regression coefficients and the error term, the probability distribution used to generate the error term is defined with a mean parameter set at zero and a variance parameter set to a field specific bias coefficient.
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公开(公告)号：US10827669B2
公开(公告)日：2020-11-10
申请号：US16505486
申请日：2019-07-08
Applicant: The Climate Corporation
Inventor： Lijuan Xu , Sanjay Lamsal
Abstract: A computer system and computer-implemented techniques for determining and presenting improved seeding rate recommendations for sowing hybrid seeds in a field is provided. In an embodiment, determining and presenting seeding rate recommendations for a field may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including hybrid seed type, and sowing row width. Using digitally programmed seeding query logic, within the server computer system, receiving digital data representing planting parameters including hybrid seed type information and sowing row width. The seeding query logic then retrieves a set of one or more seeding models from an electronic digital seeding data repository based upon the planting parameters. Each of the seeding model retrieved contain a regression model for the hybrid seed type modeling a relationship between plant yield and seeding rate on a specific field. Using mixture model logic, within the server computer system, generating an empirical mixture model in digital computer memory that represents a composite distribution of the set of one or more seeding models. The mixture model logic then generates an optimal seeding rate distribution dataset in digital computer memory based upon the empirical mixture model, where the optimal seeding rate distribution dataset represents the optimal seeding rate across all measure fields. Using optimal seeding rate recommendation logic, within the server computer system, calculating and presenting on a digital display device an optimal seeding rate recommendation that is based upon the optimal seeding rate distribution dataset.
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公开(公告)号：US10719638B2
公开(公告)日：2020-07-21
申请号：US15234943
申请日：2016-08-11
Applicant: THE CLIMATE CORPORATION
Inventor： Lijuan Xu , Anahita Hassanzadeh
Abstract: In an embodiment, a method comprises: receiving digital yield data representing yields of crops that have been harvested from an agricultural field; applying an empirical cumulative density function to the digital yield data to generate transformed digital yield data; smoothing the transformed digital yield data to result in generating and storing smooth transformed digital yield data; determining a first count value for a plurality of management classes; generating a plurality of first management zones for the agricultural field by clustering the smooth transformed digital yield data and using the first count value; generating a set of first merged management zones by merging one or more small management zones of the plurality of first management zones with their respective similar neighboring large zones; and storing the set of first merged management zones and the first count value in a set of management zone metrics.
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公开(公告)号：US20200151831A1
公开(公告)日：2020-05-14
申请号：US16734813
申请日：2020-01-06
Applicant: The Climate Corporation
IPC: G06Q50/02
Abstract: A method for determining national crop yields during a growing season is accomplished using a server computer system that receives observed agricultural data records for a specific geo-location at a specific time. The server calculates weather index values from the agricultural data records that represent crop stress on plants. Geo-specific weather indices are generated from the weather index values, which then are aggregated to generate aggregated weather index data series. Representative features are selected from each aggregated weather index data series to create a covariate matrix for each geographic area. Crop yield for the geographic area is calculated using a linear regression model based on the covariate matrix for the specific geographic area. The server determines a national crop yield for the specific year as a sum of the crop yields for the specific geographic areas nationally adjusted using national yield adjustment instructions.
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公开(公告)号：US10342174B2
公开(公告)日：2019-07-09
申请号：US14885886
申请日：2015-10-16
Applicant: The Climate Corporation
Inventor： Lijuan Xu , Sanjay Lamsal
Abstract: A computer system and computer-implemented techniques for determining and presenting improved seeding rate recommendations for sowing hybrid seeds in a field is provided. In an embodiment, determining and presenting seeding rate recommendations for a field may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including hybrid seed type, and sowing row width. Using digitally programmed seeding query logic, within the server computer system, receiving digital data representing planting parameters including hybrid seed type information and sowing row width. The seeding query logic then retrieves a set of one or more seeding models from an electronic digital seeding data repository based upon the planting parameters. Each of the seeding model retrieved contain a regression model for the hybrid seed type modeling a relationship between plant yield and seeding rate on a specific field. Using mixture model logic, within the server computer system, generating an empirical mixture model in digital computer memory that represents a composite distribution of the set of one or more seeding models. The mixture model logic then generates an optimal seeding rate distribution dataset in digital computer memory based upon the empirical mixture model, where the optimal seeding rate distribution dataset represents the optimal seeding rate across all measure fields. Using optimal seeding rate recommendation logic, within the server computer system, calculating and presenting on a digital display device an optimal seeding rate recommendation that is based upon the optimal seeding rate distribution dataset.
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Patent Agency Ranking
公开(公告)号：US11062223B2
公开(公告)日：2021-07-13
申请号：US14956657
申请日：2015-12-02
Applicant: The Climate Corporation
Abstract: A method for predicting field specific crop yield recommendations is disclosed. A computer system receives data records, including remotely sensed spectral property of plant records and soil moisture records. The system aggregates the records to create geo-specific time series over a specified time. The system selects representative features from the geo-specific time series and creates, for each specific geographic area, a covariate matrix in computer memory comprising the representative features. The system assigns a probability value to a component group in a set of parameter component groups, where each component group includes one or more regression coefficients and an error term calculated from probability distributions. The system is programmed to generate generates the probability distributions used to determine the regression coefficients and the error term, the probability distribution used to generate the error term is defined with a mean parameter set at zero and a variance parameter set to a field specific bias coefficient.
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公开(公告)号：US20210144908A1
公开(公告)日：2021-05-20
申请号：US17083288
申请日：2020-10-28
Applicant: The Climate Corporation
Inventor： Lijuan Xu , Sanjay Lamsal
Abstract: A computer system and computer-implemented techniques for determining and presenting improved seeding rate recommendations for sowing hybrid seeds in a field is provided. In an embodiment, determining and presenting seeding rate recommendations for a field may be accomplished using a server computer system that receives over a digital communication network, electronic digital data representing hybrid seed properties, including hybrid seed type, and sowing row width. Using digitally programmed seeding query logic, within the server computer system, receiving digital data representing planting parameters including hybrid seed type information and sowing row width. The seeding query logic then retrieves a set of one or more seeding models from an electronic digital seeding data repository based upon the planting parameters. Each of the seeding model retrieved contain a regression model for the hybrid seed type modeling a relationship between plant yield and seeding rate on a specific field. Using mixture model logic, within the server computer system, generating an empirical mixture model in digital computer memory that represents a composite distribution of the set of one or more seeding models. The mixture model logic then generates an optimal seeding rate distribution dataset in digital computer memory based upon the empirical mixture model, where the optimal seeding rate distribution dataset represents the optimal seeding rate across all measure fields. Using optimal seeding rate recommendation logic, within the server computer system, calculating and presenting on a digital display device an optimal seeding rate recommendation that is based upon the optimal seeding rate distribution dataset.
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公开(公告)号：US10769733B2
公开(公告)日：2020-09-08
申请号：US16734813
申请日：2020-01-06
Applicant: The Climate Corporation
Abstract: A method for determining national crop yields during a growing season is accomplished using a server computer system that receives observed agricultural data records for a specific geo-location at a specific time. The server calculates weather index values from the agricultural data records that represent crop stress on plants. Geo-specific weather indices are generated from the weather index values, which then are aggregated to generate aggregated weather index data series. Representative features are selected from each aggregated weather index data series to create a covariate matrix for each geographic area. Crop yield for the geographic area is calculated using a linear regression model based on the covariate matrix for the specific geographic area. The server determines a national crop yield for the specific year as a sum of the crop yields for the specific geographic areas nationally adjusted using national yield adjustment instructions.
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公开(公告)号：US20200183048A1
公开(公告)日：2020-06-11
申请号：US16791918
申请日：2020-02-14
Applicant: The Climate Corporation
Abstract: A method for determining national crop yields during the growing season is provided. In an embodiment, a server computer system receives agricultural data records for a particular year that represent covariate data values related to plants at a specific geo-location at a specific time. The system aggregates the records to create geo-specific time series for a geo-location over a specified time. The system creates aggregated time series from a subset of the geo-specific time series. The system selects a representative feature from the aggregated time series and creates a covariate matrix for each specific geographic area in computer memory. The system determines a specific state crop yield for a specific year using linear regression to calculate the specific state crop yield from the covariate matrix. The system determines a national crop yield for the specific year using the sum of the state crop yields for the specific year nationally adjusted.
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公开(公告)号：US10564316B2
公开(公告)日：2020-02-18
申请号：US14675992
申请日：2015-04-01
Applicant: The Climate Corporation
IPC: G01V99/00 , G01N21/359 , G01N33/00 , G06Q10/04 , G01W1/10 , G01N33/24 , G01N21/17 , G01N21/31 , A01B79/00
Abstract: A method for determining national crop yields during the growing season using regional agricultural data is provided. In an embodiment, determining national crop yields during the growing season may be accomplished using a server computer system that receives, via a network, agricultural data records that are used to forecast a national crop yield for a particular year. Within the server computer system an agricultural time series module receives one or more agricultural data records that represent a type of covariate data value related to plants at a specific geo-location at a specific time. The agricultural time series module then aggregates the agricultural data records to create one or more geo-specific time series that represent a specific geo-location over a specified time. The agricultural time series module creates one or more aggregated time series that represent geographic areas from a subset of the one or more geo-specific time series. A crop yield estimating module selects a representative feature from the one or more aggregated time series and creates a covariate matrix for each specific geographic area in computer memory of the server computer system. The crop yield estimating module determines a specific state crop yield for a specific year by using a linear regression module to calculate the specific state crop yield from the covariate matrix that represents the specific state for that specific year. The crop estimation module determines a national crop yield for the specific year by using the distribution generation module to calculate the national crop yield for a specific year from the sum of the specific state crop yields for the specific year nationally adjusted using a national yield adjustment module.
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