The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Mar. 10, 2020

Filed:

Dec. 30, 2016
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Marcus O. Freitag, Pleasantville, NY (US);

Hendrik F. Hamann, Yorktown Heights, NY (US);

Levente Klein, Tuckahoe, NY (US);

Siyuan Lu, Yorktown Heights, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); A01G 22/00 (2018.01); G06N 20/00 (2019.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06K 9/00657 (2013.01); A01G 22/00 (2018.02); G06K 9/6256 (2013.01); G06N 20/00 (2019.01); G06T 7/0016 (2013.01); G06K 2209/17 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/10032 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30188 (2013.01);
Abstract

A computer-implemented method for crop type identification using satellite observation and weather data. The method includes extracting current and historical data from pixels of satellite images of a target region, generating temporal sequences of vegetation indices, based on the weather data, converting each timestamp of the temporal sequences into a modified temporal variable correlating with actual crop growth, training a classifier using a set of historical temporal sequences of vegetation indices with respect to the modified temporal variable as training features and corresponding historically known crop types as training labels, identifying a crop type for each pixel location within the satellite images using the trained classifier and the historical temporal sequences of vegetation indices with respect to the modified temporal variable for a current crop season, and estimating a crop acreage value by aggregating identified pixels associated with the crop type.


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