The Burn Area Mapper (BAM) is an automated, self-supervised framework for near-real-time wildfire mapping at 30-meter resolution. It utilizes the novel Automated Temporal Burn Index (ATBI) and SREM atmospheric correction to retrieve high-precision burn perimeters even through heavy smoke and haze. By employing a self supervised learning machine learning paradigm, BAM eliminates the need for manual training labels and outperforms coarse-resolution baselines like MODIS in fragmented landscapes. It provides a scalable, open-source solution for rapid disaster response and precise post-fire ecological assessment.
Developed by Mirza Waleed
Contact: waleedgeo@outlook.com
Portfolio: https://waleedgeo.com/
This app is prepared to visualize the results of Bahawalpur land-use classification results.
Paper available at: https://www.mdpi.com/2071-1050/15/2/1416
Global Flood Susceptibility Map (GFSM v1) Explorer
The GFSM App is a high-resolution geospatial tool designed to identify areas inherently prone to flooding based on terrain, hydrology, meteorology, and anthropogenic factors.
Unlike traditional hazard models that predict specific flood events, this app highlights the landscape’s natural propensity for inundation at a 30 m spatial resolution.
Image Dates Acquisition Tool (IDAT) is a tool to access and visualize the available satellite images for given duration and AOI. Satellites incldue S1,S2,L8, and L9.
The application hosts the data produced by the recent study titled "Urbanization-led land cover change impacts terrestrial carbon storage capacity: A high-resolution remote sensing-based nation-wide assessment in Pakistan (1990–2020)", available at: https://doi.org/10.1016/j.eiar.2023.107396.
Through this app, users can visualize any area within Pakistan and can quickly analyze its spatiotemporal changes in carbon storage between 1990 and 2020.
The application hosts the data produced by the recent study titled "Urbanization-led land cover change impacts terrestrial carbon storage capacity: A high-resolution remote sensing-based nation-wide assessment in Pakistan (1990–2020)", available at: https://doi.org/10.1016/j.eiar.2023.107396.
Through this app, users can visualize any area within Pakistan and can quickly analyze its spatiotemporal changes in land cover between 1990 and 2020.
