Remote Sensing for Wildfire Management

Santosh K. Panda serves as Associate Professor of GIS and Remote Sensing at the University of Alaska Fairbanks, where he holds joint appointments with the Geophysical Institute and the Institute of Agriculture, Natural Resources and Extension. His research focuses on understanding Arctic landscape dynamics, particularly permafrost response to climate change and its effects on Arctic systems. After completing his PhD in Geology from UAF, he has pioneered high-resolution permafrost modeling across Alaska's national parks and developed innovative approaches to mapping boreal forest wildfire patterns using hyperspectral remote sensing. His work includes significant community engagement, notably building capacity for permafrost monitoring in native villages of Telida and Nikolai, and mapping Colville River bathymetry to support safe river navigation. As principal investigator for the Alaska NSF EPSCoR Fire and Ice project, he leads research on improving boreal wildfire fuel mapping. His publications have garnered over 795 citations, with significant contributions to permafrost dynamics modeling, remote sensing applications, and Arctic landscape change analysis. Beyond research, he maintains an active teaching role in remote sensing and GIS at both undergraduate and graduate levels while advancing the application of spatial technologies to understand Arctic environmental changes.

Dr. Anushree Badola serves as Postdoctoral Researcher at the Institute of Agriculture, Natural Resources and Extension, University of Alaska Fairbanks, where she specializes in hyperspectral remote sensing and machine learning applications for forestry and agriculture. Her groundbreaking research includes developing novel methods to simulate AVIRIS-NG hyperspectral imagery from Sentinel-2 data for improved vegetation and wildfire fuel mapping in boreal Alaska. After earning her Master's in Geoinformatics from the University of Twente and IIRS, ISRO, Dehradun, she completed her PhD at UAF's Geophysical Institute. Her work with the Alaska NSF EPSCoR Fire and Ice project has significantly advanced boreal forest monitoring techniques, achieving improved classification accuracies from 77.8% with Sentinel-2 to 94.4% with AVIRIS-NG data. Her research portfolio includes innovative approaches to tree species mapping in tropical forests, sub-pixel needleleaf cover fraction estimation in boreal forests, and development of spectral reconstruction methods for vegetation mapping. As a skilled programmer in Python and R with expertise in various GIS tools including QGIS, ArcGIS, ENVI, and Erdas Imagine, she continues to advance the field of remote sensing while focusing on improving wildfire fuel mapping technologies for better forest management.

Christopher Smith currently serves as Lead GIS Analyst at the Municipality of Anchorage, following his role as Geospatial Data Analyst at the Geographic Information Network of Alaska (GINA). His research focuses on improving wildfire fuel mapping techniques using hyperspectral remote sensing data. His groundbreaking work demonstrated that AVIRIS-NG hyperspectral imagery could achieve 80% accuracy in vegetation classification compared to 33% accuracy with traditional Landsat-based products. After completing his MS in Geosciences from the University of Alaska Fairbanks, he has contributed significantly to understanding boreal forest fire behavior through advanced remote sensing applications. His expertise spans multiple geospatial platforms including ArcGIS, ENVI, ERDAS Imagine, QGIS, and Trimble Business Center. Through his work with GINA, he has played a crucial role in analyzing and sharing geospatial data tools while maintaining involvement in earth science education as a teaching assistant for courses on glaciers, earthquakes, and volcanoes. His research has significantly advanced the field of wildfire fuel mapping in Alaska's boreal forests, providing valuable decision-support information for fire managers.