A method of remote sensing of landscape potential for the construction of small hydropower facilities based on geospatial data Abstract

Abstract

The paper explores the strategic use of geospatial data in the context of small hydropower development, focusing on the integration of remote sensing techniques and SPARQL queries. Geospatial data, including satellite images, digital terrain models (DRMs) and hydrological maps, are said to play a key role in determining the optimal location of small hydropower plants along river corridors. These data sets provide essential insights into topographic features, river morphology, land use patterns and hydrological dynamics, facilitating accurate site selection and resource assessment. It was emphasized that remote sensing techniques allow obtaining detailed spatial information over a wide geographic area, offering valuable input for evaluating potential hydropower facilities. Satellite images in combination with DEM allow accurate mapping of elevation fluctuations, watershed boundaries, and river networks. This spatial data helps identify areas with favorable hydraulic conditions and sufficient water flow, which is critical for assessing the feasibility and energy potential of small hydropower projects. In parallel, SPARQL queries are used to retrieve structured data from Resource Description Framework (RDF) datasets containing hydrological and geographic information. SPARQL's semantic query capabilities allow you to retrieve relevant data points such as river flow rates, drainage areas, and proximity to existing infrastructure. This semantic approach supports decision-making processes by providing an understanding of site suitability criteria derived from both remote sensing data and hydrological measurements.