Geoinformation monitoring of green stands using remote sensing methods
DOI:
https://doi.org/10.31548/forest2020.02.004Abstract
A green plantations monitoring is an important work, which includes regular monitoring of urban landscapes in order to identify negative timely changes and to prepare the informed decisions to prevent their degradation. In modern conditions, it is advisable to improve this process by using remote sensing methods, the materials of which are processed in geographic information systems, which allows to establish an automated monitoring system of green areas.
The purpose of the study is to substantiate the feasibility of geo-information monitoring of urban landscapes using remote sensing methods, including unmanned aerial vehicles. To achieve this goal, structural schemes of the monitoring system organization to get the information about green plantation conditions are proposed, together with the possibilities of using orthophotoplans, which are obtained by remote sensing methods for the needs of regular study of urban landscapes.
Repeated remote monitoring of the green plantations condition allows to detect the timely changes that have occurred with tree and shrub vegetation over a period in an automated mode. The use of remote sensing materials in this case can be used as a documentary basis to justify the implementation of measures for landscaping. Due to the expensive cost of high-resolution materials, we recommend to use in the process of urban landscape monitoring proposed approach with regular surveys of unmanned aerial vehicles for greenery facilities.
On the basis of the conducted researches the multifunctional structure of the green plantings monitoring system is offered and carrying out of digital transformation of monitoring process of urban landscapes condition is recommended. These studies indicate the feasibility of introducing regular automated monitoring of green areas with the involvement of remote sensing methods, including using unmanned aerial vehicles.
Keywords: GIS, remote sensing, unmanned aerial vehicle, detection of changes in urban landscapes, observation of vegetation condition.
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