Improving the methods of Agricultural mapping using remote sensing data
Abstract
Based on remote sensing data, it is possible to create a real-time database of agricultural sectors of the study area, in particular, types of crops, fisheries, arable land, and other sectors of agriculture. Remote sensing techniques can also be used to help determine crop yields, parasite spread, increased damage, and soil conditions using satellite imagery and aerial photography. In agricultural mapping, a classification algorithm is required that ensures the reliability and accuracy of the data extracted from the remote sensing data. Research and experiments have shown that increasing the accuracy of classification results requires not only the selection of a perfect algorithm but also a high level of knowledge and skills in the field in which the research is conducted. The mapping of agricultural sectors, in particular the classification of crops, also requires close acquaintance with the existing types of crops in the region, their dependence on natural and climatic conditions, and their development trends.