Improved fire severity mapping in the North American boreal forest using a hybrid composite method
Abstract Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high‐intensity wildfires. Satellite‐derived burn severity maps have been an important tool in these remote landscapes for both fire and resource manag...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-04-01
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| Series: | Remote Sensing in Ecology and Conservation |
| Subjects: | |
| Online Access: | https://doi.org/10.1002/rse2.238 |
| _version_ | 1811299913073426432 |
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| author | Lisa M. Holsinger Sean A. Parks Lisa B. Saperstein Rachel A. Loehman Ellen Whitman Jennifer Barnes Marc‐André Parisien |
| author_facet | Lisa M. Holsinger Sean A. Parks Lisa B. Saperstein Rachel A. Loehman Ellen Whitman Jennifer Barnes Marc‐André Parisien |
| author_sort | Lisa M. Holsinger |
| collection | DOAJ |
| description | Abstract Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high‐intensity wildfires. Satellite‐derived burn severity maps have been an important tool in these remote landscapes for both fire and resource management. The conventional methodology to produce satellite‐inferred fire severity maps generally involves comparing imagery from 1 year before and 1 year after a fire, yet environmental conditions unique to the boreal have limited the accuracy of resulting products. We introduce an alternative method – the ‘hybrid composite’ – based on deriving mean severity over time on a per‐pixel basis within the cloud‐computing environment of Google Earth Engine. It constructs the post‐fire image from satellite data composited from all valid images (i.e., clear‐sky and snow‐free) acquired in the time period immediately after fire through the early growing season of the following year. We compare this approach to paired‐scene and composite approaches where the post‐fire time period is from the growing season 1 year after fire. Validation statistics based on field‐derived data for 52 fires across Alaska and Canada indicate that the hybrid composite method outperforms the other approaches. This approach presents an efficient and cost‐effective means to monitor and explore trends and patterns across broad spatial domains, and could be applied to fires in other regions, especially those with frequent cloud cover or rapid vegetation recovery. |
| first_indexed | 2024-04-13T06:43:36Z |
| format | Article |
| id | doaj.art-2a8a1bce637049d6b18fc2a54a5a9163 |
| institution | Directory Open Access Journal |
| issn | 2056-3485 |
| language | English |
| last_indexed | 2024-04-13T06:43:36Z |
| publishDate | 2022-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Remote Sensing in Ecology and Conservation |
| spelling | doaj.art-2a8a1bce637049d6b18fc2a54a5a91632022-12-22T02:57:40ZengWileyRemote Sensing in Ecology and Conservation2056-34852022-04-018222223510.1002/rse2.238Improved fire severity mapping in the North American boreal forest using a hybrid composite methodLisa M. Holsinger0Sean A. Parks1Lisa B. Saperstein2Rachel A. Loehman3Ellen Whitman4Jennifer Barnes5Marc‐André Parisien6Aldo Leopold Wilderness Research Institute Rocky Mountain Research Station US Forest Service 790 E. Beckwith Ave. Missoula Montana 59801USAAldo Leopold Wilderness Research Institute Rocky Mountain Research Station US Forest Service 790 E. Beckwith Ave. Missoula Montana 59801USAUS Fish and Wildlife Service 1011 E. Tudor Rd. Anchorage Alaska 99503USAUS Geological Survey, Alaska Science Center University Drive Anchorage Alaska 99503USANatural Resources Canada Canadian Forest Service Northern Forestry Centre 6520‐122 Street Edmonton Alberta T6H 3S5 CanadaNational Park Service, Alaska Regional Office 4175 Geist Rd. Fairbanks Alaska 99709USANatural Resources Canada Canadian Forest Service Northern Forestry Centre 6520‐122 Street Edmonton Alberta T6H 3S5 CanadaAbstract Fire severity is a key driver shaping the ecological structure and function of North American boreal ecosystems, a biome dominated by large, high‐intensity wildfires. Satellite‐derived burn severity maps have been an important tool in these remote landscapes for both fire and resource management. The conventional methodology to produce satellite‐inferred fire severity maps generally involves comparing imagery from 1 year before and 1 year after a fire, yet environmental conditions unique to the boreal have limited the accuracy of resulting products. We introduce an alternative method – the ‘hybrid composite’ – based on deriving mean severity over time on a per‐pixel basis within the cloud‐computing environment of Google Earth Engine. It constructs the post‐fire image from satellite data composited from all valid images (i.e., clear‐sky and snow‐free) acquired in the time period immediately after fire through the early growing season of the following year. We compare this approach to paired‐scene and composite approaches where the post‐fire time period is from the growing season 1 year after fire. Validation statistics based on field‐derived data for 52 fires across Alaska and Canada indicate that the hybrid composite method outperforms the other approaches. This approach presents an efficient and cost‐effective means to monitor and explore trends and patterns across broad spatial domains, and could be applied to fires in other regions, especially those with frequent cloud cover or rapid vegetation recovery.https://doi.org/10.1002/rse2.238Boreal forestsburn severityComposite Burn IndexdNBR, RBRfire severityGoogle Earth Engine |
| spellingShingle | Lisa M. Holsinger Sean A. Parks Lisa B. Saperstein Rachel A. Loehman Ellen Whitman Jennifer Barnes Marc‐André Parisien Improved fire severity mapping in the North American boreal forest using a hybrid composite method Remote Sensing in Ecology and Conservation Boreal forests burn severity Composite Burn Index dNBR, RBR fire severity Google Earth Engine |
| title | Improved fire severity mapping in the North American boreal forest using a hybrid composite method |
| title_full | Improved fire severity mapping in the North American boreal forest using a hybrid composite method |
| title_fullStr | Improved fire severity mapping in the North American boreal forest using a hybrid composite method |
| title_full_unstemmed | Improved fire severity mapping in the North American boreal forest using a hybrid composite method |
| title_short | Improved fire severity mapping in the North American boreal forest using a hybrid composite method |
| title_sort | improved fire severity mapping in the north american boreal forest using a hybrid composite method |
| topic | Boreal forests burn severity Composite Burn Index dNBR, RBR fire severity Google Earth Engine |
| url | https://doi.org/10.1002/rse2.238 |
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