Project Funding: 2013 - 2016

NRA: 2012 NASA: Pre-ABoVE: Terrestrial Ecology   

Funded by NASA

Abstract:
The greatest rise in global temperature is occurring in High Northern Latitudes (HNL) above 60°N and this recent warming trend is projected to continue. Wildfire is the main disturbance agent in this ecosystem and a major emerging issue identified by the North Slope Science Initiative. Although much research has been done in the forested areas of HNL in the recent decade, little is still known about fire patterns in transitional forest/tundra ecotone and tundra ecosystems. The proposed project falls under all three types of proposals solicited under the current Terrestrial Ecology (TE) call. First and foremost, the proposed work will develop a consistent data set in support of the planned NASA arctic-boreal ecosystems vulnerability experiment (ABOVE) field campaign. Within this project we will develop and implement a new approach to produce moderate resolution (30m) records of fire disturbances guided by coarse resolution datasets. We will use active fire detections and burned area products from a succession of coarse resolution sensors, including Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imager Radiometer Suite (VIIRS), to guide the selection and archival of clear surface Landsat images in order to produce moderate resolution fire perimeter and fire impact characterization maps across HNL. Within this project we will provide the first formal assessment of VIIRS and the Landsat Data Continuity Mission (LDCM) capabilities for fire detection and mapping burned areas in HNL thus establishing the continuation of fire mapping in HNL using a consistent algorithm into the future. The proposed project will also take advantage of the opportunities offered by Synthetic Aperture Radar (SAR) sensors to characterize burns in HNL. Past research in boreal forests and current evaluation in Alaskan tundra shows that SAR data can be used successfully to map burned area perimeters and distinguish burned and unburned areas within the perimeter over a longer period of time than optical sensors. However, it is presently unclear whether SAR data can provide complimentary burn severity information to the metrics extracted from optical and thermal data. We will use our field-collected observations of burn severity in tundra fires, obtained under the previously funded NASA TE project, to compare the capabilities offered by SAR (ERS, Envisat and Radarsat-2) and optical data (Landsat) in characterizing burn severity. The proposed project will also be a successor study in the areas of remote sensing science solicited as the third type of proposal under the current call. This project will present a continuation of the currently funded NASA TE project #NNX10AF41G (PI - French) aimed at investigating fire impacts on North American tundra. We will build on our previous findings and developed methods for coarse resolution burned area mapping in HNL by extending them to include both a consistent moderate resolution data record and burn severity characterization. Moreover, we will continue the development of remotely-sensed metrics for fire impact characterization using the field data we collected under the currently funded project. Finally, the resultant dataset and associated in situ data will present a reference/validation dataset for use in evaluation of coarse resolution Essential Climate Variables (specifically fire disturbances) included under the second type of projects solicited within this TE call. We will develop and test the algorithm over North American HNL during year 1. In year 2 we will finalize the algorithm and implement it over North American HNL between 1984 and 2015 and scope out the feasibility of extending the mapping method to complete the circumpolar coverage into Northern Eurasia. In year 3 we will extend the mapping activity to cover Northern Eurasia.

Publications:

Chen, D., Fu, C., Hall, J. V., Hoy, E. E., Loboda, T. V. 2021. Spatio-temporal patterns of optimal Landsat data for burn severity index calculations: Implications for high northern latitudes wildfire research. Remote Sensing of Environment. 258, 112393. DOI: 10.1016/j.rse.2021.112393

Chen, D., Loboda, T. V., Hall, J. V. 2020. A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems. ISPRS Journal of Photogrammetry and Remote Sensing. 159, 63-77. DOI: 10.1016/j.isprsjprs.2019.11.011

Chen, D., Shevade, V., Baer, A., Loboda, T. V. 2021. Missing Burns in the High Northern Latitudes: The Case for Regionally Focused Burned Area Products. Remote Sensing. 13(20), 4145. DOI: 10.3390/rs13204145

Loboda, T.V., J.V. Hall, D. Chen, A. Hoffman-Hall, V.S. Shevade, F. Argueta, and X. Liang. 2024. Arctic Boreal Annual Burned Area, Circumpolar Boreal Forest and Tundra, V2, 2002-2022. ORNL DAAC, Oak Ridge, Tennessee, USA. DOI: 10.3334/ORNLDAAC/2328

Barrett, K., Loboda, T., McGuire, A. D., Genet, H., Hoy, E., Kasischke, E. 2016. Static and dynamic controls on fire activity at moderate spatial and temporal scales in the Alaskan boreal forest. Ecosphere. 7(11). DOI: 10.1002/ecs2.1572

Jenkins, L., Bourgeau-Chavez, L., French, N., Loboda, T., Thelen, B. 2014. Development of Methods for Detection and Monitoring of Fire Disturbance in the Alaskan Tundra Using a Two-Decade Long Record of Synthetic Aperture Radar Satellite Images. Remote Sensing. 6(7), 6347-6364. DOI: 10.3390/rs6076347

French, N. H. F., Jenkins, L. K., Loboda, T. V., Flannigan, M., Jandt, R., Bourgeau-Chavez, L. L., Whitley, M. 2015. Fire in arctic tundra of Alaska: past fire activity, future fire potential, and significance for land management and ecology. International Journal of Wildland Fire. 24(8), 1045. DOI: 10.1071/WF14167

More details may be found in the following project profile(s):

• NASA Terrestrial Ecology (TE) Project Profile
• North American Carbon Program (NACP) Project Profile
• NASA Arctic-Boreal Vulnerability Experiment (ABoVE) Project Profile