1. bookVolumen 3 (2020): Edición 1 (August 2020)
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eISSN
2545-2843
Primera edición
30 Sep 2018
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1 tiempo por año
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access type Acceso abierto

Geostatistical Methods as a Tool Supporting Revitalization of Industrially Degraded and Post-Mining Areas

Publicado en línea: 10 Aug 2020
Volumen & Edición: Volumen 3 (2020) - Edición 1 (August 2020)
Páginas: 30 - 40
Recibido: 01 Feb 2020
Aceptado: 01 Mar 2020
Conferencia Detalles
License
Formato
Conferencia
eISSN
2545-2843
Primera edición
30 Sep 2018
Calendario de la edición
1 tiempo por año
Idiomas
Inglés
Abstract

Post-industrial and post-mining areas have often been under strong anthropogenic pressure for a long time. As a result, such areas, after the ending of industrial activity require taking steps to revitalize them. It may cover many elements of the natural or urban environment, such as water, soil, vegetated areas, urban development etc. To carry out revitalization, it is necessary to determine the initial state of such areas, often using selected chemical, geophysical or ecological. After that it is also important to properly monitor the state of such areas to assess the progress of the revitalization process. For this purpose a variety of change detection technics were developed. Post-industrial areas are very often characterized by a large extent, are difficult to access, have complicated land cover. For this reason, it is particularly important to choose appropriate methods to assess the degree of pollution of such areas. Such methods should be as economical as possible and time-effective. A very desirable feature of such methods is that they should allow a quick assessment of the entire area. Geostatistics supplemented by modern remote sensing can be effective for this purpose. Nowadays, using remote sensing, it is possible to gather information simultaneously from the entire, even vast area, with high spatial, spectral and temporal resolution. Geostatistics in turn provides many tools that are able to enable rapid analysis and inference based on even very complicated often scarce spatial data sets obtained from ground measurement and satellite observations. The goal of the article was to present selected results obtained using geostatistical methods also related to remote sensing, which may be helpful for decision makers in revitalizing post-industrial and post-mining areas. The results described in this paper were based mostly on the previous studies, carried out by authors.

Keywords

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