Hybrid algorithms for geospatial analysis of dam location points in protective tasks for protected areas

• Published in: Vestnik Dagestanskogo gosudarstvennogo tehničeskogo universiteta. Tehničeskie nauki (Online) Vol. 48; no. 2; pp. 40 - 49
• Main Authors: Rodriguez Vasquez, S., Mokrova, N. V.
• Format: Journal Article
• Language: English; Russian
• Published: Dagestan State Technical University 31.07.2021
• Subjects: distance analysis; geospatial analysis algorithm; gis; hydrological network; representative spatial objects
• ISSN: 2073-6185; 2542-095X; 2542-095X
• DOI: 10.21822/2073-6185-2021-48-2-40-49

Objective. In recent decades, criteria for identifying potential areas have evolved hand in hand with technological tools such as geographic information systems (GIS). However, the criteria for the preservation of protected areas are often not taken into account, thus causing damage to environmental biodiversity that can become irreparable. This paper presents the way of optimizing the process of locating key terrain points by developing a hybrid algorithm for geospatial analysis in QGIS. The goal is to speed up computational time, which is a critical variable for the entire key point detection process, and to suggest potential areas that do not pose a threat to biodiversity. Methods. The strategy used is based on two fundamental assumptions: identifying the tops of spatial objects (rivers) and analyzing the distances between spatial objects (rivers and adjacent territories). The tops extraction allows obtaining potential points, while the distance analysis allows selecting among them those points that are in the range acceptable for locating a dam, provided that the least possible damage to the biodiversity of the adjacent territory is caused. The algorithm was validated using the example of the hydrological network of Manicaragua, Cuba. Results. The results were compared in terms of the calculation time used, the number of valid tops extracted, and the percentage reduction in the total number of areas. This comparison was made using one, two and three vector layers (.shp) with spatial objects representing strategic protected areas. Conclusion. The results obtained show that the more representative the space data (.shp) used, the more effective the results obtained using the algorithm are in relation to environmental protection tasks. A reduction of up to 13% from originally detected key points has been achieved.