{"title":"Methodology of geoinformation modeling of areas affected by amber mining","authors":"A. Martyn, O. Kachanovskyi, S. Bulakevych","doi":"10.31548/zemleustriy2022.01.12","DOIUrl":null,"url":null,"abstract":"The article considers modern possibilities of geoinformation technologies for geospatial modeling of areas affected by amber mining in Ukraine on the example of Rivne Region. The purpose of the study is to present a methodology for decoding satellite image materials for geoinformation modeling of the areas affected by amber mining. The use of actual materials of remote sensing of modern satellite systems in combination with geospatial models during land monitoring is analyzed. It was found that the calculation of the NDVI makes it possible to identify the contours of affected areas more clearly. An approach for assessing soil cover moisture content based on the use of norm-difference water indices is presented. It is noted that the assessment of soil moisture is one of the elements of thematic processing of satellite images which makes it possible to identify the areas where amber mining by hydraulic method was carried out. It is offered to consider the method of geoinformation modeling of areas affected by amber mining as a method of practical implementation of determining affected lands using remote sensing images, due to the regularities and features of spectral analysis of a photo image. The use of the methodology is presented on a specific example, namely on state-owned lands of Dubrovytsia Forestry of Rivne Region. The methodology will provide a technical basis for the decisions on the identification of affected land plots and their further monitoring. In addition, the methodology offered in the article will help to determine the directions of land reclamation and groups of affected lands.","PeriodicalId":56214,"journal":{"name":"Zemleustrij Kadastr i Monitoring Zemel''","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Zemleustrij Kadastr i Monitoring Zemel''","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31548/zemleustriy2022.01.12","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The article considers modern possibilities of geoinformation technologies for geospatial modeling of areas affected by amber mining in Ukraine on the example of Rivne Region. The purpose of the study is to present a methodology for decoding satellite image materials for geoinformation modeling of the areas affected by amber mining. The use of actual materials of remote sensing of modern satellite systems in combination with geospatial models during land monitoring is analyzed. It was found that the calculation of the NDVI makes it possible to identify the contours of affected areas more clearly. An approach for assessing soil cover moisture content based on the use of norm-difference water indices is presented. It is noted that the assessment of soil moisture is one of the elements of thematic processing of satellite images which makes it possible to identify the areas where amber mining by hydraulic method was carried out. It is offered to consider the method of geoinformation modeling of areas affected by amber mining as a method of practical implementation of determining affected lands using remote sensing images, due to the regularities and features of spectral analysis of a photo image. The use of the methodology is presented on a specific example, namely on state-owned lands of Dubrovytsia Forestry of Rivne Region. The methodology will provide a technical basis for the decisions on the identification of affected land plots and their further monitoring. In addition, the methodology offered in the article will help to determine the directions of land reclamation and groups of affected lands.