Evaluating Trees Crowns Damage for the 2017 Largest Wildfire in Japan Using Sentinel-2A NDMI

The study shows the use of Normalized Difference Moisture Index (NDMI) acquired by the Sentinel 2A in evaluating the trees crowns damage in Japan largest wildfire in 2017. Ground truth used was from field-collected data on scorch crowns of trees from the burned area. Our results show that difference...

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Bibliographic Details
Published inIGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium pp. 6794 - 6797
Main Authors Emang, Grace Puyang, Touge, Yoshiya, Kazama, So
Format Conference Proceeding
LanguageEnglish
Published IEEE 26.09.2020
Subjects
crown damage
fire severity
Fires
Forestry
Indexes
NDMI
Reflectivity
Remote sensing
Sentinel-2A
Vegetation
Vegetation mapping
wildfire
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Summary:The study shows the use of Normalized Difference Moisture Index (NDMI) acquired by the Sentinel 2A in evaluating the trees crowns damage in Japan largest wildfire in 2017. Ground truth used was from field-collected data on scorch crowns of trees from the burned area. Our results show that difference NDMI (dNDMI) of pre and post-fire images was the best spectral index among Normalize Burn Ratio (NBR), NBR2, Normalize Difference Vegetation Index (NDVI), difference NBR (dNBR), difference NBR2 (dNBR2) and difference NDVI (dNDVI) for spectral sensitivity in differentiating unburned and burned areas. The estimates area for tree crowns damage due to high severity was the largest at 147 hectares (33.1%) and the total calculated burned area was 445.02 hectares which exceed less than 8% of the total burned area reported. This study is needed for Japan because of the different ecosystem and climate with other fire studies conducted in different regions.
ISSN:2153-7003
DOI:10.1109/IGARSS39084.2020.9323345