MULTISPECTRAL REMOTE SENSING DATA PROCESSING FOR CROP DETECTION

Temurbek Kuchkorov; Abror Mamataliev

Авторы

Temurbek Kuchkorov TUIT named after Muhammad al-Khwarizmi
Abror Mamataliev Tashkent University of Information Technologies named after Muhammad al-Khwarizmi

Ключевые слова:

crop detection, image preprocessing, multispectral remote sensing, precision agriculture, vegetation indices, Wingtra drone

Аннотация

Multispectral remote sensing plays a crucial role in crop detection and health assessment by providing detailed spectral information for agricultural monitoring. This study focuses on the processing of multispectral imagery to analyze crop conditions, using data acquired from a drone WingtraOne II equipped with a multispectral sensor. Images were captured on multiple dates during the 2024 growing season to track vegetation changes over time. The data processing workflow includes radiometric and geometric corrections, mosaicking, and orthorectification to ensure accuracy and consistency. Vegetation indices such as NDVI, SAVI, and EVI were calculated to assess crop vigor and detect potential stress factors. The findings highlight the effectiveness of multispectral imaging in precision agriculture, providing valuable insights for optimizing crop management.

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