Статья

Visualization and analysing the state of hydrotechnical construction via geospatial methods (on the example of Kharshi pumping stations cascade)

Zokhid MamatkulovDepartment of Geodesy and Geoinformatics, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Kory Niyoziy str., 100000 Tashkent, UzbekistanJaloliddin RashidovTashkent Institute of Irrigation and Agricultural Mechanization Engineers, Kory Niyoziy str. 39, 100000 Tashkent, UzbekistanG EshchanovaEnglish Language Department, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Kory Niyoziy str. 39, 100000 Tashkent, UzbekistanM BerdievTashkent Institute of Irrigation and Agricultural Mechanization Engineers, Kory Niyoziy str. 39, 100000 Tashkent, UzbekistanSarvar AbdurakhmonovDepartment of Geodesy and Geoinformatics, Tashkent Institute of Irrigation and Agricultural Mechanization Engineers, Kory Niyoziy str., 100000 Tashkent, Uzbekistan

IOP Conference Series Earth and Environmental Scienceconference2020en

ABI

Аннотация

Abstract In the given article the state of Kharshi pumping station, which is considered as one of the huge pumping stations cascade in Central Asia is described through analysing and visualising the geographic information systems (GIS) and remote sensing (RS) methods. As data there were used Shuttle Radar Topographic Mission - SRTM and high-resolution optical images of the area, provided by ESRI. For data processing and visualization, there was used the software of ArcGIS 10.5 by ESRI company and the results were obtained. At the same time the geographical location of pumping stations and water elevating points and the state of water flowing canals were analysed remotely along with the results from the cross-sectional area of cascade were obtained. In assessing, the accuracy of results it was compared with the data based on field search work and the obtained results from the distance showed 86% accuracy.

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Темы

Engineering and Agricultural Innovations Advanced Computational Techniques in Science and Engineering Metaheuristic Optimization Algorithms Research

Идентификаторы

DOI: 10.1088/1755-1315/614/1/012086

Цитирования и источники

Цитирований: 16 Использованных источников: 6

Показатели — AkademScholar