Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network

Open Access. Powered by Scholars. Published by Universities.®

Environmental Sciences

PDF

Chapman University

2019

Wildfire

Articles 1 - 2 of 2

Full-Text Articles in Entire DC Network

A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee Dec 2019

A Feasibility Study On The Application Of Tvdi On Accessing Wildfire Danger In The Korean Peninsula, Kwang Nyun Kim, Seung Hee Kim, Myoung Soo Won, Keun Chang Jang, Won Jun Choi, Yun Gon Lee

Mathematics, Physics, and Computer Science Faculty Articles and Research

Wildfire is a major natural disaster affecting socioeconomics and ecology. Remote sensing data have been widely used to estimate the wildfire danger with an advantage of higher spatial resolution. Among the several wildfire related indices using remote sensing data, Temperature Vegetation Dryness Index (TVDI) assesses wildfire danger based on both Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). Although TVDI has physical advantages by considering both weather and vegetation condition, previous studies have shown TVDI does not performed well compare to other wildfire related indices over the Korean Peninsula. In this study we have attempted multiple modification to …


Estimating Live Fuel Moisture Using Smap L-Band Radiometer Soil Moisture For Southern California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Menas Kafatos Jul 2019

Estimating Live Fuel Moisture Using Smap L-Band Radiometer Soil Moisture For Southern California, Usa, Shenyue Jia, Seung Hee Kim, Son V. Nghiem, Menas Kafatos

Mathematics, Physics, and Computer Science Faculty Articles and Research

Live fuel moisture (LFM) is a field-measured indicator of vegetation water content and a crucial observation of vegetation flammability. This study presents a new multi-variant regression model to estimate LFM in the Mediterranean ecosystem of Southern California, USA, using the Soil Moisture Active Passive (SMAP) L-band radiometer soil moisture (SMAP SM) from April 2015 to December 2018 over 12 chamise (Adenostoma fasciculatum) LFM sites. The two-month lag between SMAP SM and LFM was utilized either as steps to synchronize the SMAP SM to the LFM series or as the leading time window to calculate the accumulative SMAP SM. …