@inproceedings{3827f23fe422488aa749496a18715546,
title = "Estimation and monitoring heat discharge rates using Landsat ETM+ thermal infrared data: A case study in Unzen geothermal field, Kyushu, Japan",
abstract = "The Unzen geothermal field, our study area is active fumaroles, situated in Shimabara Peninsula of Kyushu Island in Japan. Our prime objectives were (1) to estimate radiative heat flux (RHF), (2) to calculate approximately heat discharge rate (HDR) using the relationship of radiative heat flux with the total heat loss derived from two geothermal field studies and (3) finally, to monitor RHF as well as HDR in our study area using seven sets of Landsat 7 ETM+ images from 2000 to 2009. We used the NDVI (Normalized differential vegetation index) method for spectral emissivity estimation, the mono-window algorithm for land surface temperature (LST) and the Stefan-Boltzmann equation analyzing those satellite TIR images for RHF. We obtained a desired strong correlation of LST above ambient with RHF using random samples. We estimated that the maximum RHF was about 251 W/m2 in 2005 and minimum was about 27 W/m2in 2001. The highest total RHF was about 39.1 MW in 2005 and lowest was about 12 MW in 2001 in our study region. We discovered that the estimated RHF was about 15.7 % of HDR from our studies. We applied this percentage to estimate heat discharge rate in Unzen geothermal area. The monitoring results showed a single fold trend of HDR from 2000 to 2009 with highest about 252 MW in 2005 and lowest about 78 MW in 2001. In conclusion, TIR remote sensing is thought as the best option for monitoring heat losses from fumaroles with high efficiency and low cost..",
author = "Mia, {Md Bodruddoza} and Yasuhiro Fujimitsu and Bromely, {Chris J.}",
year = "2012",
doi = "10.1117/12.974475",
language = "English",
isbn = "9780819492630",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
booktitle = "Land Surface Remote Sensing",
address = "United States",
note = "Land Surface Remote Sensing ; Conference date: 29-10-2012 Through 02-11-2012",
}