Detecting and analyzing the evolution of subsidence due to coal fires in Jharia coalfield, India using Sentinel-1 SAR data
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-236703
- Public safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequentlyPublic safety and socio-economic development of the Jharia coalfield (JCF) in India is critically dependent on precise monitoring and comprehensive understanding of coal fires, which have been burning underneath for more than a century. This study utilizes New-Small BAseline Subset (N-SBAS) technique to compute surface deformation time series for 2017–2020 to characterize the spatiotemporal dynamics of coal fires in JCF. The line-of-sight (LOS) surface deformation estimated from ascending and descending Sentinel-1 SAR data are subsequently decomposed to derive precise vertical subsidence estimates. The most prominent subsidence (~22 cm) is observed in Kusunda colliery. The subsidence regions also correspond well with the Landsat-8 based thermal anomaly map and field evidence. Subsequently, the vertical surface deformation time-series is analyzed to characterize temporal variations within the 9.5 km\(^2\) area of coal fires. Results reveal that nearly 10% of the coal fire area is newly formed, while 73% persisted throughout the study period. Vulnerability analyses performed in terms of the susceptibility of the population to land surface collapse demonstrate that Tisra, Chhatatanr, and Sijua are the most vulnerable towns. Our results provide critical information for developing early warning systems and remediation strategies.…
Autor(en): | Moidu Jameela Riyas, Tajdarul Hassan Syed, Hrishikesh Kumar, Claudia Kuenzer |
---|---|
URN: | urn:nbn:de:bvb:20-opus-236703 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Philosophische Fakultät (Histor., philolog., Kultur- und geograph. Wissensch.) / Institut für Geographie und Geologie |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Remote Sensing |
ISSN: | 2072-4292 |
Erscheinungsjahr: | 2021 |
Band / Jahrgang: | 13 |
Heft / Ausgabe: | 8 |
Aufsatznummer: | 1521 |
Originalveröffentlichung / Quelle: | Remote Sensing (2021) 13:8, 1521. https://doi.org/10.3390/rs13081521 |
DOI: | https://doi.org/10.3390/rs13081521 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 5 Naturwissenschaften und Mathematik / 52 Astronomie / 526 Mathematische Geografie |
5 Naturwissenschaften und Mathematik / 55 Geowissenschaften, Geologie / 550 Geowissenschaften | |
Freie Schlagwort(e): | InSAR; SBAS; coal; coal fire; interferometry; remote sensing; subsidence |
Datum der Freischaltung: | 12.07.2022 |
Datum der Erstveröffentlichung: | 15.04.2021 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |