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Efficient land use based on remote sensing data
Author(s) -
Y. M. Kenzhegaliyev
Publication year - 2021
Publication title -
problemy agrorynka
Language(s) - English
Resource type - Journals
eISSN - 2708-9991
pISSN - 1817-728X
DOI - 10.46666/2021-3.2708-9991.20
Subject(s) - computer science , remote sensing , land cover , raster graphics , field (mathematics) , geographic information system , land use , agricultural land , vegetation (pathology) , spatial analysis , agriculture , data mining , artificial intelligence , geography , mathematics , engineering , medicine , civil engineering , archaeology , pathology , pure mathematics
The goal -is to explore ways of using Earth remote sensing data for efficient land use. Methods - detailed information on current location of certain types of agricultural crops in the study areas has been summarized, which opens up opportunities for the effective use of cultivated areas. It was revealed that the basis of the principle of the method under consideration is the relationship between the state and structure of vegetation types with its reflective ability. It has been determined that information on the spectral reflective property of the vegetation cover in the future can help replace more laborious methods of laboratory analysis. For classification of farmland, satellite images of medium spatial resolution with a combination of channels in natural colors were selected. Results - a method for identifying agricultural plants by classification according to the maximum likelihood algorithm was considered. The commonly used complexes of geoinformation software products with modules for special image processing allow displaying indicators in the form of raster images. It is shown that the use of Earth remote sensing data is the most relevant solution in the field of crop recognition and makes it possible to simplify the implementation of such types of work as the analysis of the intensity of land use, the assessment of the degree of pollution with weeds and determination of crop productivity. Conclusions - the research results given in the article indicate that timely information on the current location of certain types of agricultural crops in the studied territories significantly simplifies the implementation of the tasks and increases the resource potential of agricultural lands. In turn, the timing of the survey and the state of environment affect the spectral reflectivity of vegetation.

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