Rinat Gulyaev, A. Sultonov, R. Yunusov, D.R. Rafikov, Kamila Gulyaeva, Oybek Kimsanbaev, Bakhtiyor Kakhkhorov
{"title":"RESULTS OF AUTOMATIC COTTON CROPS MAPPING USING REMOTE SENSING DATA AND A PLANT GROWTH SIMULATION MODEL","authors":"Rinat Gulyaev, A. Sultonov, R. Yunusov, D.R. Rafikov, Kamila Gulyaeva, Oybek Kimsanbaev, Bakhtiyor Kakhkhorov","doi":"10.17930/agl2023211","DOIUrl":null,"url":null,"abstract":"The paper presents the results of application of the method of automatic generation of representative and unbiased set for in-season cotton crop mapping, based on crop simulation model, previously parameterized using ground truth and satellite data. The method provided confident mapping of cotton fields without using actual ground-truth information or a-priori information about their in-season phenology. Overall mapping accuracy calculated using relevant ground truth data for cotton fields has reached 95.6 %. Consideration of time series of NDVI values as a model of phase characteristics allowed using relatively simple criteria to identify typical representatives of the selected crop on the basis of analysis of their seasonal phenology and made it possible to build a reference sample for modeling and further classification.","PeriodicalId":44979,"journal":{"name":"AgroLife Scientific Journal","volume":"102 21","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2023-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AgroLife Scientific Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17930/agl2023211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"AGRONOMY","Score":null,"Total":0}
引用次数: 0
Abstract
The paper presents the results of application of the method of automatic generation of representative and unbiased set for in-season cotton crop mapping, based on crop simulation model, previously parameterized using ground truth and satellite data. The method provided confident mapping of cotton fields without using actual ground-truth information or a-priori information about their in-season phenology. Overall mapping accuracy calculated using relevant ground truth data for cotton fields has reached 95.6 %. Consideration of time series of NDVI values as a model of phase characteristics allowed using relatively simple criteria to identify typical representatives of the selected crop on the basis of analysis of their seasonal phenology and made it possible to build a reference sample for modeling and further classification.
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