Науково-методичні засади дистанційного агроекологічного моніторингу та прогнозування

Abstract

Goal. To improve the system of remote agroecological monitoring and forecasting of the impact of climate warming on grain yields. Methods. NOAA STAR NESDIS (National Environmental Satellite Data Information Services) satellite data were used to determine the climatic parameters of the earth’s surface. The impact of warming on vegetation was determined by the NDVI satellite indicator from the website STAR NESDIS NOAA — Satellite Applications and Research of NOAA’s National Environmental Satellite Data Information Services — Center for the Use of Satellite Research and Information of the US National Oceanic and Atmospheric Administration. Erosion degradation of agricultural landscapes was performed using an unmanned aerial vehicle of flying wing type. The Pentax W60 camera was used as a sensor, with the following camera settings: 1/2.3” CCD matrix, shutter when shooting 1/51/320. ISO 501600 in Digital SR mode (5 MP), in serial mode. Surveying routes were constructed in the form of a spiral to avoid distortion of orthophotos in the analysis. The analysis was performed using the following software: AgisoftPhotoscan, ErdasImage. Results. Information is given on the implementation of the new research program of the National Academy of Agrarian Sciences “Satellite agroecological monitoring, agro-resource management and forecasting the impact of climate change on the productivity of agro-ecosystems (“Agrocosmos”) based on the report of Academician NAAS O.I. Furdychko for 2021. It is shown that the use of remote sensing/GIS technologies is an effective tool for operational monitoring of agricultural landscapes, moisture supply, drought, erosion degradation, and forecasting the impact of global warming on grain yields. The efficiency of using satellite indicators in forecasting grain productivity was established. Conclusions. According to published sources and experimental data, remote sensing methods in the agroecological monitoring system are an effective tool for obtaining up-to-date information on the state of agricultural resources, moisture supply, manifestations of desertification, soil erosion, and forecasting. According to satellite data, it is possible to perform an index analysis of crop productivity and make an early forecast of their yields. The expediency of using unmanned aerial vehicles (UMAV) in determining the erosion degradation of soils was proved. An appropriate method of using UMAV was proposed, which has been tested on the territory of the Bohodukhiv administrative district of the Kharkiv region.