{"id":3201,"date":"2026-02-12T15:50:36","date_gmt":"2026-02-12T12:50:36","guid":{"rendered":"https:\/\/resources.today\/en\/?p=3201"},"modified":"2026-02-12T15:50:36","modified_gmt":"2026-02-12T12:50:36","slug":"11nzor425","status":"publish","type":"post","link":"https:\/\/resources.today\/en\/11nzor425.html","title":{"rendered":"The use of unmanned aerial vehicles for mapping national economic objects"},"content":{"rendered":"

Shaytura Sergey Vladimirovich<\/strong>
\nMoscow State University of Technology and Management named after K.G. Razumovsky (First Cossack University), Moscow, Russia
\nE-mail: swshaytura@gmail.com
\nORCID: https:\/\/orcid.org\/0000-0002-5621-5460<\/a>
\nRSCI: https:\/\/elibrary.ru\/author_profile.asp?id=143842<\/a><\/p>\n

Shaitura Natalya Sergeevna<\/strong>
\nRussian State Agrarian University \u2014 Moscow Agricultural Academy named after K.A. Timiryazev, Moscow, Russia
\nE-mail: n.shaytura@rgau-msha.ru
\nORCID: https:\/\/orcid.org\/0000-0002-9422-910X<\/a>
\nRSCI: https:\/\/elibrary.ru\/author_profile.asp?id=171577<\/a><\/p>\n

Samorokov Vladislav Sergeevich<\/strong>
\nRussian University of Transport (MIIT), Moscow, Russia
\nE-mail: samorokov2018@inbox.ru
\nORCID: https:\/\/orcid.org\/0009-0004-2494-5217<\/a>
\nRSCI: https:\/\/elibrary.ru\/author_profile.asp?id=1223087<\/a><\/p>\n

Grigorovich Kirill Evgenevich<\/strong>
\nRussian University of Transport (MIIT), Moscow, Russia
\nE-mail: kirilltzibulin@gmail.com
\nORCID: https:\/\/orcid.org\/0009-0007-7698-1967<\/a><\/p>\n

Beliaev Andrei Vladislavovich<\/strong>
\nRussian University of Transport (MIIT), Moscow, Russia
\nE-mail: JollyAndrey@yandex.ru
\nORCID: https:\/\/orcid.org\/0009-0004-1567-9631<\/a><\/p>\n

Abstract.<\/strong> This article examines modern methods for mapping economic assets using unmanned aerial vehicles (UAVs). The relevance of the study stems from the growing need for timely and highly accurate geospatial data for various economic sectors (agriculture, forestry, infrastructure, etc.). The study is theoretical and methodological in nature, based on literature analysis and modeling of aerial survey processes. While no specific geographic area was chosen, typical mapping scenarios for several types of economic assets-agricultural fields, forest areas, and linear infrastructure facilities are considered to illustrate the methods. These examples were chosen because they represent different tasks: mapping relatively open areas (agricultural land), areas with complex terrain and vegetation (forests), and extended objects (roads, power lines, etc.). The purpose of the work is to analyze the capabilities of drone technology for creating maps and terrain models and to identify their advantages and limitations compared to traditional mapping methods. This article describes the technical means used (drone types, sensors, software) and aerial survey methodology, taking into account factors affecting data quality (image resolution, accuracy requirements, weather conditions, etc.). The results of theoretical modeling and comparative analysis are presented, demonstrating the effectiveness of using drones for mapping various objects. The main research questions are: what are the advantages and limitations of using drones for mapping compared to traditional methods; and what methodological techniques ensure high accuracy and efficiency in mapping economic objects using drones.<\/p>\n

Keywords:<\/strong> drone; unmanned aerial vehicle; mapping; national economic facilities; UAS; GIS cartography; geoinformatics; geoinformation service<\/p>\n","protected":false},"excerpt":{"rendered":"

Shaytura Sergey Vladimirovich Moscow State University of Technology and Management named after K.G. Razumovsky (First Cossack University), Moscow, Russia E-mail: swshaytura@gmail.com ORCID: https:\/\/orcid.org\/0000-0002-5621-5460 RSCI: https:\/\/elibrary.ru\/author_profile.asp?id=143842 Shaitura Natalya Sergeevna Russian State Agrarian University \u2014 Moscow Agricultural Academy named after K.A. Timiryazev, …<\/p>\n","protected":false},"author":4,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[48,5],"tags":[],"class_list":["post-3201","post","type-post","status-publish","format-standard","hentry","category-issue-4-2025","category-article"],"_links":{"self":[{"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/posts\/3201","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/users\/4"}],"replies":[{"embeddable":true,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/comments?post=3201"}],"version-history":[{"count":1,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/posts\/3201\/revisions"}],"predecessor-version":[{"id":3202,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/posts\/3201\/revisions\/3202"}],"wp:attachment":[{"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/media?parent=3201"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/categories?post=3201"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/resources.today\/en\/wp-json\/wp\/v2\/tags?post=3201"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}