@inproceedings{1a0d70e29aea41d086680e0909ee1fd7,
title = "Evaluating Trees Crowns Damage for the 2017 Largest Wildfire in Japan Using Sentinel-2A NDMI",
abstract = "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.",
keywords = "crown damage, fire severity, NDMI, Sentinel-2A, wildfire",
author = "Emang, {Grace Puyang} and Yoshiya Touge and So Kazama",
note = "Funding Information: The authors would like to thank Nomura Foundation for Membrane Structure{\textquoteright}s Technology for their financial assistance and Kamaishi Forestry Association who assisted in the field investigation. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 ; Conference date: 26-09-2020 Through 02-10-2020",
year = "2020",
month = sep,
day = "26",
doi = "10.1109/IGARSS39084.2020.9323345",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6794--6797",
booktitle = "2020 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2020 - Proceedings",
address = "United States",
}