Predictive Assessment of Forest Fire Risk in the Hindu Kush Himalaya (HKH) Region Using HIWAT Data Integration
Article
| Article Title | Predictive Assessment of Forest Fire Risk in the Hindu Kush Himalaya (HKH) Region Using HIWAT Data Integration |
|---|---|
| ERA Journal ID | 201448 |
| Article Category | Article |
| Authors | Thapa, Sunil, Maraseni, Tek, Dhonju, Hari Krishna, Shakya, Kiran, Shakya, Bikram, Apan, Armando and Banerjee, Bikram |
| Journal Title | Remote Sensing |
| Journal Citation | 17 (13) |
| Article Number | 2255 |
| Number of Pages | 20 |
| Year | 2025 |
| Publisher | MDPI AG |
| Place of Publication | Switzerland |
| ISSN | 2072-4292 |
| Digital Object Identifier (DOI) | https://doi.org/10.3390/rs17132255 |
| Web Address (URL) | https://www.mdpi.com/2072-4292/17/13/2255 |
| Abstract | Forest fires in the Hindu Kush Himalaya (HKH) region are increasing in frequency and severity, driven by climate variability, prolonged dry periods, and human activity. Nepal, a critical part of the HKH, recorded over 22,700 forest fire events in the past decade, with fire incidence nearly doubling in 2023. Despite this growing threat, operational early warning systems remain limited. This study presents Nepal’s first high-resolution early fire risk outlook system, developed by adopting the Canadian Fire Weather Index (FWI) using meteorological forecasts from the High-Impact Weather Assessment Toolkit (HIWAT). The system generates daily and two-day forecasts using a fully automated Python-based workflow and publishes results as Web Map Services (WMS). Model validation against MODIS, VIIRS, and ground fire records for 2023 showed that over 80% of fires occurred in zones classified as Moderate to Very High risk. Spatiotemporal analysis confirmed fire seasonality, with peaks in mid-April and over 65% of fires occurring in forested areas. The system’s integration of satellite data and high-resolution forecasts improves the spatial and temporal accuracy of fire danger predictions. This research presents a novel, scalable, and operational framework tailored for data-scarce and topographically complex regions. Its transferability holds substantial potential for strengthening anticipatory fire management and climate adaptation strategies across the HKH and beyond. |
| Keywords | forest fire; forest fire prediction; Fire Weather Index (FWI); High-Impact Weather Assessment Toolkit (HIWAT); Hindu Kush Himalaya (HKH); Nepal |
| Contains Sensitive Content | Does not contain sensitive content |
| ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
| 300706. Forestry fire management | |
| Byline Affiliations | Institute for Life Sciences and the Environment |
| Chinese Academy of Sciences, China | |
| Central Queensland University | |
| International Centre for Integrated Mountain Development, Nepal | |
| School of Surveying and Built Environment | |
| University of the Philippines Diliman, Philippines |
https://research.usq.edu.au/item/zyq9y/predictive-assessment-of-forest-fire-risk-in-the-hindu-kush-himalaya-hkh-region-using-hiwat-data-integration
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