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A versatile crop yield estimator - Google Patents A method for estimating crop yield of an analyzed area, which is a region of interest, according to which imagery data is acquired from one or more remotely sensed sources, using a remote
REMOTE-SENSING YIELD ESTIMATION METHOD APPLICABLE TO CROP WHOLE GROWTH . . . The patent CN108509836A discloses a crop yield estimation method of dual-polarized synthetic aperture radar and crop model data assimilation, which fully combines the advantages of SAR remote-sensing data and WOFOST model to increase the yield simulation accuracy of the crop model
WO 2023 131949 A VERSATILE CROP YIELD ESTIMATOR - WIPO WO2023131949 - A VERSATILE CROP YIELD ESTIMATOR A method for estimating crop yield of an analyzed area, which is a region of interest, according to which imagery data is acquired from one or more remotely sensed sources, using a remote sensing platform or one or more satellites
Systems and Methods for Satellite Image Processing to Estimate Crop Yield This patent describes a system and method for estimating the yield of crop in a specific area using satellite image processing The system receives images captured by a satellite and analyzes them to determine information about the crop in the area
( 12 ) United States Patent ( 45 ) Date of Patent : Jun 16 , 2020 ( 54 ) SYSTEM AND METHOD FOR PREDICTING CROP YIELD ( 58 ) Field of Classification Search CPC GO6Q 50 02 See application file for complete search history ( 71 ) Applicant : OmniEarth , Inc , Rochester , NY ( US ) ( 56 ) References Cited
ESTIMATING CROP YIELD DATA - Patent application The method of claim 1, wherein the determining the harvesting scaling factor comprises: determining preliminary crop yield data based on the harvesting data; comparing the preliminary crop yield data with the historical crop yield data; and generating the harvesting scaling factor based on the comparing of the preliminary crop yield data wit
A scalable crop yield estimation framework based on remote sensing of . . . In this paper, we develop a generalizable framework that is mechanism-guided and practically parsimonious for crop yield estimation We then apply this framework to estimate crop yield for two crops (corn and wheat) in two contrasting regions, the US Corn Belt US-CB, and India’s Indo–Gangetic plain Wheat Belt IGP-WB, respectively
COA Based Adaptive Neuro-Fuzzy Inference System: Machine Learning . . . Abstract Accurate early estimation of crop yield is vital for effective agricultural planning, trade policy formulation, and enhancement of farmers’ income This study presents an optimized Adaptive Neuro-Fuzzy Inference System (ANFIS) integrated with the Chimp Optimization Algorithm (COA) to achieve reliable and precise crop yield prediction