Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Buchkapitel |
| DOI | 10.1007/978-3-031-46880-3_21 |
| Titel (primär) | Cloud-based technologies Google Earth Engine for monitoring surface deformation of the Solotvyno agglomeration |
| Titel (sekundär) | Information and communication technologies and sustainable development. ICT&SD 2022 |
| Autor | Hordiienko, O.; Anpilova, Y.
; Yakovliev, Y.; Rogozhin, O. |
| Herausgeber | Dovgyi, S.; Trofymchuk, O.; Ustimenko, V.; Globa, L. |
| Quelle | Lecture Notes in Networks and Systems |
| Erscheinungsjahr | 2023 |
| Department | CHS |
| Band/Volume | 809 |
| Seite von | 337 |
| Seite bis | 353 |
| Sprache | englisch |
| Topic | T5 Future Landscapes |
| Keywords | Google Earth Engine; Remote Sensing; Post-Mining; Surface Deformation; Monitoring; Water Surface Masks |
| Abstract | This study utilized the Google Earth Engine (GEE) service to analyze satellite images, aiming to determine human-induced spatial and temporal changes in the man-made water surface and identify anthropogenic alterations in the Solotvyno salt mine agglomeration. Traditional methods for measuring vertical topography changes using active satellite imagery are complex. GEE enabled efficient processing of large geospatial datasets in the cloud, employing masks and machine learning for a wide range of computational operations. The masking method, using threshold values and image pre-processing, offered a simpler approach to track vertical relief displacements. Additionally, it provided accurate and prompt research results. By employing water surface masks and analyzing Sentinel 1 and Sentinel 2 satellite images, it was observed that the area of land subsidence and water presence above flooded mining areas increased from 2015 to 2023, displaying a tendency for further expansion. These findings can be utilized to identify risk areas, inform decisions regarding ecosystem preservation and sustainable territorial development, and predict potential damage to critical infrastructure. The primary focus is on using threshold masks for active satellite data to detect inundation zones where vertical relief displacements occur, enabling the calculation of their areas and sizes. This approach was compared to passive data, which exhibited a similar trend over the entire time frame. The method offers a quicker and more accessible means of detecting vertical relief displacements compared to methods such as classification and interferometry. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=28367 |
| Hordiienko, O., Anpilova, Y., Yakovliev, Y., Rogozhin, O. (2023): Cloud-based technologies Google Earth Engine for monitoring surface deformation of the Solotvyno agglomeration In: Dovgyi, S., Trofymchuk, O., Ustimenko, V., Globa, L. (eds.) Information and communication technologies and sustainable development. ICT&SD 2022 Lecture Notes in Networks and Systems 809 Springer, Cham, p. 337 - 353 10.1007/978-3-031-46880-3_21 |
|