DECISION-MAKING SUPPORT SYSTEM REGARDING THE OPTIMIZAION PROCESS OF CROP CULTIVATION USING REMOTE SENSING DATA

Abstract

This paper explores the development of an information system to support decision-making in agriculture, specifically focusing on optimizing crop production. This system leverages the power of remote sensing (RS) data, which offers valuable insights into crop health and environmental conditions from a bird's-eye view. By analyzing this data, the proposed system empowers farmers with the information they need to make informed choices throughout the agricultural season, ultimately leading to increased yields and improved resource management.

Following the introduction, the paper delves into the core functionalities of the information system. It details the process of acquiring RS data from various platforms, such as Landsat, Sentinel-2, or PlanetScope satellites. Here, the discussion emphasizes the importance of selecting data with appropriate spatial and temporal resolution to capture the most relevant details for specific agricultural applications. Pre-processing techniques for handling the raw RS data are then discussed, outlining methods for removing noise and errors to ensure the accuracy of subsequent analyses. The paper then details the implementation of various algorithms for data analysis. These algorithms extract meaningful features from the pre-processed RS data, such as vegetation indices that provide insights into plant health and biomass, or other indicators that can detect potential crop stress due to nutrient deficiencies or water scarcity.