TY - JOUR AU - Rakhymberdina, Marzhan Yessenbekovna AU - Kulenova, Natalya Anatolyevna AU - Shaimardanov, Zhassulan Kudaibergenovich AU - Assylkhanova, Zhanna Alexandrovna AU - Toguzova, Marzhan Melsovna AU - Kassymov, Dauren Kuttybayevich PY - 2022/09/01 Y2 - 2024/03/28 TI - Using Remote Sensing Data to Support Intelligent Agricultural GIS to Monitor the Condition of Arable Land and Crops JF - Chemical Engineering Transactions VL - 94 SP - 883-888 SE - Research Articles DO - 10.3303/CET2294147 UR - https://www.cetjournal.it/index.php/cet/article/view/CET2294147 AB - The article reviews the modern state of the multi-level agricultural land monitoring system in Kazakhstan, as an element of the precision farming system, carried out both at the state level and in the context of land users. The main constraints to the widespread use of remote sensing (RS) and unmanned aerial vehicles (UAV) data were identified. The large extent of the country's territory, different climatic conditions, large differences in the altitude of the terrain impose an impact on the choice of methods of data processing and interpretation. Data from Sentinel, Landsat, Modis satellites are used as input data, on which software applications of the most common in agriculture are based. On the basis of conducted monitoring of agricultural lands in KH "Mayak" farm in Pavlodar region with the use of available online applications, programs, native web services, UAV evaluated the potential of multi-level use of remote sensing in modern conditions of Kazakhstan. The results of the UAV survey with a mobile RTK station allow ensuring the accuracy of the map at a scale of 1: 1000. ER -