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1. WO2022011236 - SYSTEMS AND METHODS FOR QUANTIFYING AGROECOSYSTEM VARIABLES THROUGH MULTI-TIER SCALING FROM GROUND DATA, TO MOBILE PLATFORMS, AND TO SATELLITE OBSERVATIONS

Publication Number WO/2022/011236
Publication Date 13.01.2022
International Application No. PCT/US2021/041051
International Filing Date 09.07.2021
IPC
G06K 9/00 2022.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
A01C 21/00 2006.1
AHUMAN NECESSITIES
01AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
CPLANTING; SOWING; FERTILISING
21Methods of fertilising
G01N 33/00 2006.1
GPHYSICS
01MEASURING; TESTING
NINVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
33Investigating or analysing materials by specific methods not covered by groups G01N1/-G01N31/131
G06K 9/62 2022.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
G06Q 50/02 2012.1
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
50Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
02Agriculture; Fishing; Mining
Applicants
  • THE BOARD OF TRUSTEES OF THE UNIVERSITY OF ILLINOIS [US]/[US]
Inventors
  • WANG, Sheng
  • GUAN, Kaiyu
  • PENG, Bin
  • JIANG, Chongya
  • WANG, Sibo
Agents
  • MOHRHAUSER, Luke T.
  • MCKEE, BRUCE W.; SEASE, EDMUND J.; HANSING, MARK D.; HARTUNG, KIRK M.; NEBEL, HEIDI S.; EDGAR, CASSANDRA JOAN; LINK, JILL N.; GILCHRIST, MICHAEL C.; JOHNSON, GLENN; KENNEDY, JONATHAN L.; GUNNERSON, GREGORY LARS; LUTH, SARAH M. D.; KEPPLER, BRIAN D.; ROMANO, CHARLES P.; SOWATZKE, TINA YIN; SPIEKER, JULIE L.; HALLMAN, JOSEPH M.
Priority Data
63/050,53410.07.2020US
63/180,81128.04.2021US
Publication Language English (en)
Filing Language English (EN)
Designated States
Title
(EN) SYSTEMS AND METHODS FOR QUANTIFYING AGROECOSYSTEM VARIABLES THROUGH MULTI-TIER SCALING FROM GROUND DATA, TO MOBILE PLATFORMS, AND TO SATELLITE OBSERVATIONS
(FR) SYSTÈMES ET PROCÉDÉS POUR QUANTIFIER DES VARIABLES D'AGROÉCOSYSTÈME PAR AJUSTEMENT À PLUSIEURS NIVEAUX ALLANT DE DONNÉES AU SOL, À DES PLATEFORMES MOBILES ET À DES OBSERVATIONS SATELLITAIRES
Abstract
(EN) The ability to scale data can provide numerous advantages, especially with regard to agricultural information. For example, agroecosystems include land and data associated with the land, such as physical traits and information. This can include, for example, information related to the soil, crops, other vegetation, and other information related to the land. In order to be able to quickly and accurately know such information and traits, ground truth data can be scaled using aerial and/or satellite imagery. Models and other machine learning can utilize ground truth data to scale limited field area data (e.g., 0.1-1 km) and accurately apply the same to large swaths of land (e.g., >100 km2) with accuracy for the field traits and/or characteristics.
(FR) La capacité à ajuster l'échelle des données peut offrir de nombreux avantages, en particulier en ce qui concerne les informations agricoles. Par exemple, des agroécosystèmes comprennent le terrain et des données associées au terrain, tels que des attributs physiques et des informations. Ils peuvent comprendre, par exemple, des informations relatives au sol, aux cultures, à d'autres végétaux et d'autres informations relatives au terrain. Afin de pouvoir connaître rapidement et avec précision ces informations et attributs, des données réelles au sol peuvent être ajustées à l'aide d'une imagerie aérienne et/ou satellitaire. Des modèles et un autre apprentissage machine peuvent utiliser des données réelles au sol pour ajuster des données de zone de champ limitée (par exemple, 0,1-1 km) et les appliquer précisément à de larges étendues de terrain (par exemple, > 100 km2) avec une précision pour les attributs et/ou les caractéristiques de terrain.
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