USING THE LANDSAT SATELLITE SYSTEM FOR WINTER WHEAT MONITORING IN THE WESTERN UKRAINE TERRITORY

Автор(и)

  • Serhii Bulakevych National University of Water and Environmental Engineering

Ключові слова:

Satellite monitoring, remote sensing LANDSAT, agromonitoring

Анотація

Today, there are many ways to monitor crops throughout the season. Among them – the use of satellites and drones, sheet diagnostics, analysis of soil samples. This article discusses the technology of using Landsat remote sensing data for solving problems of monitoring the state of winter wheat in WesternUkraine. The issues of yield forecasting were also considered. The studies were conducted on one of the fields of the agro-farm. Volovikov using Landsat remote sensing imagery for 2010-2011. (August, April, July). The technology of creating geo-information models of the main indices is described, namely: the distribution models of the NDVI index – and the distribution models of the GVIindex (Green Vegetation Index). These models were indicators of the vegetation of green plants. On their basis, a quantitative assessment of the ascent and growth of winter wheat was carried out. Also in this study, the integration of digital elevation models and Landsat remote sensing materials was carried out, using the tools of cartographic algebra, problem areas were identified in which adecrease in the yield of winter wheat was observed. The reasons for this state were established, and decisions were made to correct the structure of the crop rotation (for the future), and the coordinates of sites that need special agronomic support with further integration of this geospatial information into the system of precision farming were determined. Studies show that aftergeoinformational analysis of cartographic materials of agrochemical indicators, topography, remote sensing data for different periods of plant vegetation, it is possible to obtain an upto-date informational picture of the state of the study area and effectively implement land management and agrotechnical measures, namely: correct the structure of crop rotation, fertilize, detect areas affected by pests and diseases, process well-defined problems areas, and to make informed management decisions.

Біографія автора

Serhii Bulakevych, National University of Water and Environmental Engineering

Applicant

Посилання

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Improving the timeliness of winter wheat production forecast in the

United States of America, Ukraine and China using MODIS data and NCAR

Growing Degree Day information / Franch B., Vermote E. F., Becker-Reshef I. et al. (2015). Remote Sens Environ 161. R. 131–148.

Matton, N.; Canto, G. S.; Waldner, F.; Valero, S.; Morin, D.; Inglada, J.; Arias, M.; Bontemps, S.; Koetz, B.; Defourny, P. An Automated Method for Annual Cropland Mapping along the Season for Various Globally-Distributed Agrosystems Using High Spatial and Temporal Resolution Time Series. Remote Sens. 2015, 7, R. 13208–13232.

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