86,000 square metres of land slipped away, show satellite images | Bengaluru News – Times of India

86,000 square metres of land slipped away, show satellite images | Bengaluru News – Times of India



BENGALURU: Satellite tv for pc photographs from Nationwide Distant Sensing Centre (NRSC), a key centre beneath Isro, have unveiled the intensive injury and destruction brought on by the landslides in Kerala’s Wayanad district.
Excessive-resolution before-and-after photographs captured by Risat (whose radar can penetrate clouds) and Cartosat-3 (superior optical satellite tv for pc) present round 86,000 sq. metres of land slipped away, and the ensuing particles movement travelled about 8km alongside the Iruvanjippuzha river, devastating cities and settlements in its path.
The report reads: “A significant particles movement was triggered by heavy rainfall in and across the Chooralmala city of Wayanad. Very excessive decision Risat SAR (artificial aperture radar) photographs of July 31 reveals the whole extent of the particles movement from crown to finish of runout zone. The approximate size of the movement is round 8km. The crown zone is a reactivation of an older landslide.”
“… Dimension of important scarp of the landslide is 86,000 sq m. The particles movement has widened the course of Iruvanjippuzha river, inflicting breach of its banks. Homes and different infrastructure alongside the banks have been broken by the particles movement,” it added.
In Feb 2023, Isro had launched the Landslide Atlas of India, which documented round 80,000 landslides throughout 17 states and two UTs within the Himalayas and Western Ghats from 1998 to 2022. It consists of seasonal, event-based, and route-wise inventories, utilizing high-resolution satellite tv for pc and aerial imagery.
The atlas, which coated main occasions from the previous, equivalent to Kedarnath catastrophe and Sikkim earthquake, had ranked 147 districts based mostly on landslide publicity and socio-economic components. Wayanad was positioned among the many susceptible districts. The database was partially field-validated and consists of superior strategies for landslide detection, modelling and prediction.







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