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  • 标题:Need for application of remote sensing technologies for development of agro-industrial complex
  • 本地全文:下载
  • 作者:Elena Denisova ; Victoria Silova
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:285
  • 页码:1-6
  • DOI:10.1051/e3sconf/202128501005
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Agricultural production has influence on all areas of social activity. In the modern context of agro-industrial complex development, ensuring the economic security of the country directly depends on availability and suitability of the land, the degree of developed land. Land is a source of food, profits, economic independence of each region, the state of which depends on continuous monitoring and application of advanced technologies. The purpose of the work is to determine quantitative and qualitative state of arable land in the Volgograd region, the level of spread of degradation processes based on digital and remote sensing technologies, as well as the creation of graphic documentation necessary for making economic forecasts and plans. Availability and use of arable land in 33 municipal districts of the Volgograd region are unequal. The largest number of arable land is 5,4 % in Pallasovsky district, the smallest one is 1,3 % in Sredneakhtubinsky district. The differentiation of the region into five natural-agricultural and three land-assessment areas is caused by the necessity to register soil fertility during agricultural use of arable land, both in irrigated arable land and non-irrigated. According to the statistical records the irrigated arable land is used only in the amount of 20 %. 88 % of the region’s territory is subject to degradation processes. The land with the cadastral number 34:21:040003:67and an area of 137,2 hectares is characterized by a high degree of territory blurring, degradation of soil cover, which led to the loss of humus and removal to the upper layers of the soil of salt marshes. Remote sensing techniques allow obtaining reliable information and making social and economic forecasts in large areas in a short period of time.
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