Remote Sensing of Forest Fire

Comparasion of Different Vegetation Index in Remote Sensing for Forest Fire in Ljusdal, Sweden Yongqin Zhao for GEOG 7911, 19 fall

INTRODUCTION Forest fire in Ljusdal, Sweden The fire first started on July 14th, 2018 because of lightning, and was finally extinguished in August 9th.

The fire areas are 8400 hectares of forest, according to the National Board of Forestry estimates. This represents about 40 percent of the burned forest land in the country in 2018 The fires have affected about 150 forest owners (mostly private, and three forestry companies). At most, about 200 people evacuated. Approximately 20 - 30 buildings were affected by the fire. The majority involves non-residential buildings.

Approxiamtely 1178 cubic meters of water were used.

METHODOLOGY Landsat 8 level-1 OLI

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20180916

20190802

About Landsat 8 level-1 OLI

About software

11 bands Band 1 Visible (0.43 - 0.45 µm) 30 m Band 2 Visible (0.450 - 0.51 µm) 30 m Band 3 Visible (0.53 - 0.59 µm) 30 m Band 4 Red (0.64 - 0.67 µm) 30 m Band 5 Near-Infrared (0.85 - 0.88 µm) 30 m Band 6 SWIR 1(1.57 - 1.65 µm) 30 m Band 7 SWIR 2 (2.11 - 2.29 µm) 30 m Band 8 Panchromatic (PAN) (0.50 - 0.68 µm) 15 m Band 9 Cirrus (1.36 - 1.38 µm) 30 m Band 10 TIRS 1 (10.6 - 11.19 µm) 100 m Band 11 TIRS 2 (11.5 - 12.51 µm) 100 m

QGIS SCP plugin DOS1 atmospheric correction

METHODOLOGY NBR

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20180916

20190802

About NBR Normalized Burn Ratio is used to identify burned areas and provide a measure of burn severity.

It is calculated as a ratio between the NIR and SWIR values.

(NIR - SWIR) / (NIR + SWIR) dNBR= NBRprefire - NBRpostfireBand 5 measures the near infrared, or NIR, it is especially important for ecology because healthy plants reflect it – the water in their leaves scatters the wavelengths back into the sky.

Band 7 covers different slices of the shortwave infrared, or SWIR, it is useful for telling wet earth from dry earth, and for geology: rocks and soils that look similar in other bands often have strong contrasts in SWIR.

METHODOLOGY dNBR

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20180626-20190802

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Pseduo color

dNBR= NBRprefire - NBRpostfire -0.500 to -0.251 Enhanced Regrowth, High -0.250 to -0.101 Enhanced Regrowth, Low -0.100 to +0.99 Unburned +0.100 to +0.269 Low Severity +0.270 to +0.439 Moderate-low Severity +0.440 to +0.659 Moderate-high Severity +0.660 to +0.1300 High Severity

20180626-20180916

20180626-20190802

20180916-20190802

COMPARASION NDVI

20180626

20180916

20190802

20180626-20190802

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dNDVI

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COMPARASION dNDVI VS dNBR

dNDVI20180916-20190802

dNBR 20180916-20190802

dNDVI20180916-20190802

dNBR 20180916-20190802

CONCLUSION Data dispersion (histgram) NBR can distinguish better and show more sensivity. Especially between the moderate�extreme classes NBR and dNBR are more suitable for detecting different severity levels.

DISCUSSION dNBR-dNDVI(201809-201908) VS dNBR (201806-201809)

dNDVI20180916-20190802

Similar?

dNDVI Pseduo color

dNBR-dNDVI

dNBR 20180626-20180916

REFERENCE https://www.usgs.gov/land-resources/nli/landsat/landsat-normalized-burn-ratio http://www.un-spider.org/advisory-support/recommended-practices/recommended-practice-burn-severity/Step-by-Step/QGIS https://www.usgs.gov/land-resources/nli/landsat/landsat-8 https://www.ljusdalenergi.se/ https://www.ljusdal.se/samhallegator/krisochsakerhet/informationombranderna2018/faktaombranderna.4.12be7f0e165140d0d1895a64.html