Satellite high-spatial-resolution multispectral imagery for crop type identification using Sentinel Application Platform and R software

Abstract

Information systems and their management are the main tools in all aspects of human life. Computer science is an integral part of 21st-century farming. The interaction of computer technology and nature is important in the agricultural industry. One of the main tools in data collection, management, and analysis is a satellite. Satellite images are used in analyzing crop health, detecting crop losses, and managing fields from data collected over an observed period of time. This study used high-resolution satellite imagery to obtain field data and identify the type of crops by using R software computing. These studies may help farmers to monitor their losses, and administrative authorities to prevent possible falsification of crop losses. Therefore, a year-long crop growth analysis was conducted in the Amur Region, Russia, on the All-Russian Scientific Research Institute of Soybean agricultural field. Two types of crops were identified in the field using computer technology based on analyzed data. The results of the analyzes will be used in the subsequent determination of crops in the agricultural development program of the Amur Region.