RESULTS OF AUTOMATIC COTTON CROPS MAPPING USING REMOTE SENSING DATA AND A PLANT GROWTH SIMULATION MODEL

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Rinat GULYAEV
Azamat SULTONOV
Ravil YUNUSOV
Damir RAFIKOV
Kamila GULYAEVA
Oybek KIMSANBAEV
Bakhtiyor KAKHKHOROV

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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How to Cite
Rinat GULYAEV, Azamat SULTONOV, Ravil YUNUSOV, Damir RAFIKOV, Kamila GULYAEVA, Oybek KIMSANBAEV, & Bakhtiyor KAKHKHOROV. (2023). RESULTS OF AUTOMATIC COTTON CROPS MAPPING USING REMOTE SENSING DATA AND A PLANT GROWTH SIMULATION MODEL. AgroLife Scientific Journal, 12(2), 81–86. https://doi.org/10.17930/AGL2023211
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