Possibilities of GIS-technologies in implementing large-scale mapping during field practices of students-geographers
Abstract
Experimental results of remote satellite data processing with different resolution from 3 to 60 m of bands are discussed in the article.
The purpose of the article is to present and justify various options for using satellite imagery data and technologies of geographic information systems (GIS technologies) to solve various problems, taking into account previous research experience.
The main material. The author suggests using Sentinel-2 and PlanetScope to compile large-scale maps of territories of different sizes. Based on the improvement of the methodology (previously used by the author), it is proposed to distinguish plant groups as indicative objects of indicative contours using remote sensing data. The second reference object is the contours of water bodies. We propose using colors (RGB), shapes and roughness to identify the contours of objects, but given the actual material of the field outputs to key areas. These characteristics can indirectly determine geomorphology. Based on spectral characteristic images, we consider the seasons, vegetation periods, and territory. During the filed practice students process a data set for different periods and analyze this information to study landscape changes. Based on studies from 2015 to 2019, a database for landscape monitoring of the protected area is being formed. The author with students and other researchers have determined that it is necessary to separately analyze northern and southern parts of the Slobozhansky National Nature Park. QGis and ArcGis tools allow you to prepare data and do overlay analysis to compile a hypothesis map, and then the resulting map.
Conclusions and further research. It is established that the number of classes and the classification method depend on the properties of the objects of study. The best results were shown by isolating the contours of plant communities by the method of automatic classification by identifying key areas.
It has been experimentally established that the decoding of satellite images PlanetScope gives the best results in small areas. For decoding of a larger area, Sentinel-2 gives the best results, the thematic image data of which is more generalized. Based on the information received from thematic maps, we have attributive data on the topography, geological structure, soil for each contour. All information will be used for the landscape monitoring base in the Slobozhansky National Nature Park.
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Copyright (c) 2019 Аліна Овчаренко
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