Improved Boreal Forest Wildfire Fuel Type Mapping in Interior Alaska Using AVIRIS-NG Hyperspectral Data

Christopher William Smith,Uma Suren Bhatt,Franz J Meyer,Santosh K Panda

doi:10.3390/rs13050897

Christopher William Smith, Uma Suren Bhatt + Show 2 more

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Journal: Remote Sensing	Publication Date: Feb 27, 2021
Citations: 11	License type: CC BY 4.0

Affiliation: University of Alaska Fairbanks

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In Alaska the current wildfire fuel map products were generated from low spatial (30 m) and spectral resolution (11 bands) Landsat 8 satellite imagery which resulted in map products that not only lack the granularity but also have insufficient accuracy to be effective in fire and fuel management at a local scale. In this study we used higher spatial and spectral resolution AVIRIS-NG hyperspectral data (acquired as part of the NASA ABoVE project campaign) to generate boreal forest vegetation and fire fuel maps. Based on our field plot data, random forest classified images derived from 304 AVIRIS-NG bands at Viereck IV level (Alaska Vegetation Classification) had an 80% accuracy compared to the 33% accuracy of the LANDFIRE’s Existing Vegetation Type (EVT) product derived from Landsat 8. Not only did our product more accurately classify fire fuels but was also able to identify 20 dominant vegetation classes (percent cover >1%) while the EVT product only identified 8 dominant classes within the study area. This study demonstrated that highly detailed and accurate fire fuel maps can be created at local sites where AVIRIS-NG is available and can provide valuable decision-support information to fire managers to combat wildfires.

Highlights

Spectral resolution (11 bands) Landsat 8 satellite imagery which resulted in map products that lack the granularity and have insufficient accuracy to be effective in fire and fuel management at a local scale
The LF geospatial products for Alaska, vegetation and fuel maps, lack the granularity and accuracy to be effective in wildfire and fuel management at local scale as these products are derived from coarser spatial and spectral resolution Landsat 8 satellite images [4]
We produced a significantly improved and detailed vegetation and fuel type map products of Bonanza Creek Experimental Forest (BCEF) and CPCRW using AVIRIS-NG hyperspectral data coupled with the Arctic DEM and field data

Summary

Introduction

Spectral resolution (11 bands) Landsat 8 satellite imagery which resulted in map products that lack the granularity and have insufficient accuracy to be effective in fire and fuel management at a local scale. In this study we used higher spatial and spectral resolution AVIRIS-NG hyperspectral data (acquired as part of the NASA ABoVE project campaign) to generate boreal forest vegetation and fire fuel maps. This study demonstrated that highly detailed and accurate fire fuel maps can be created at local sites where AVIRIS-NG is available and can provide valuable decision-support information to fire managers to combat wildfires. The LF geospatial products for Alaska, vegetation and fuel maps, lack the granularity and accuracy to be effective in wildfire and fuel management at local scale as these products are derived from coarser spatial and spectral resolution Landsat 8 satellite images [4].

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