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Identifying Potential Patterns of Wildfires in California in Relation to Soil Moisture using Remote Sensing

Link, Adam John
http://rave.ohiolink.edu/etdc/view?acc_num=bgsu158646328387007

Abstract Details

2020, Master of Science (MS), Bowling Green State University, Geology.
The purpose of this study is determining a potential correlation between soil moisture and burn severity as well as examining potential correlations between slope, elevation, wind speed, wind direction and Normalized Difference Vegetation Index (NDVI) value and burn severity within the Mendocino Complex Fire, California, which occurred in 2018. A time-series of the difference Normalized Burn Ratio (dNBR), the difference between pre- and intra-fire NBR values, was calculated via Sentinel-2, soil moisture was mapped using SMAP, and the Digital Elevation Model (DEM) from ASTER was used to derive elevation and slope values. The imagery was obtained from USGS and USDA websites. Images were processed and reprojected to the same spatial resolution (60 m) and projection (UTM Zone 10N, WGS-87). dNBR imagery was subdivided in newly burned areas for each consecutive day for ten days from 29 July 2018 to 31 August 2018. The findings suggested that there was no strong correlation trend consistently found over the proposed period of time between dNBR values and soil moisture content (R ≈ -0.20 to 0.39), slope (R ≈ -0.35 to 0.46), elevation (R ≈ -0.24 to 0.56), wind speed (R ≈ -0.15 to 0.36), and wind direction (R ≈ -0.42 to 0.24). However, a positive correlation between NDVI values and dNBR values was found to be strong and consistent (R ≈ -0.48 to 0.57). This implies that burn severity increased more significantly and frequently with NDVI, a surrogate for vegetation biomass and leaf area index. It can be surmised that soil moisture must reach some higher values before having a possible impact upon burn severity. Considering that the summer of 2018 was one of the warmest and driest summers in the study area’s recent history, soil moisture content was relatively low while, simultaneously, vegetation was dry and more prone to burning.
Anita Simic Milas, Ph.D. (Advisor)
Yuning Fu, Ph.D. (Committee Member)
Ganming Liu, Ph.D. (Committee Member)
87 p.
Environmental Geology; Geography; Geology; Remote Sensing; Statistics
remote sensing; Sentinel-2; ASTER; DEM; WindNinja; ArcMap; ArcGIS; ENVI; Python; SNAP; NDVI; dNBR; NBR; elevation; slope; wind speed; wind direction; multiple regression; Mendocino Complex Fire; 2018; Ranch Fire; River Fire; California; Lake County

Recommended Citations

Citations

  • Link, A. J. (2020). Identifying Potential Patterns of Wildfires in California in Relation to Soil Moisture using Remote Sensing [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu158646328387007

    APA Style (7th edition)

  • Link, Adam. Identifying Potential Patterns of Wildfires in California in Relation to Soil Moisture using Remote Sensing. 2020. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu158646328387007.

    MLA Style (8th edition)

  • Link, Adam. "Identifying Potential Patterns of Wildfires in California in Relation to Soil Moisture using Remote Sensing." Master's thesis, Bowling Green State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu158646328387007

    Chicago Manual of Style (17th edition)

bgsu158646328387007
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This open access ETD is published by Bowling Green State University and OhioLINK.