Monitoring of Thermal Activity at the Hatchobaru-Otake Geothermal Area in Japan Using Multi-Source Satellite Images - With Comparisons of Methods, and Solar and Seasonal Effects
Monitoring of Thermal Activity at the Hatchobaru-Otake Geothermal Area in Japan Using Multi-Source Satellite Images - With Comparisons of Methods, and Solar and Seasonal Effects
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DOI：
10.3390/rs10091430
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发表时间：
2018-09
期刊：
影响因子：
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通讯作者：
M. Mia;Y. Fujimitsu;J. Nishijima
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文献类型：
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作者：
M. Mia;Y. Fujimitsu;J. Nishijima
八丁原-大竹 (HO) 地热田靠近日本九州的九重火山。目前该地热田内有三座地热发电厂正在运营。在此，我们利用 ASTER 热红外数据探索了 HO 地热区的热状态，以监测 2009 年至 2017 年的热损失。我们根据白天和夜间的 Landsat 热红外图像评估了太阳效应和热损失的季节性变化，并比较了三种传统的地表温度 (LST) 测量方法。采用归一化差异植被指数发射率阈值法、LST 分割窗口算法以及辐射热通量 (RHF) 的 Stefan-Boltzmann 方程来确定研究区域内的热损失。 2009年、2013年和2017年H2O地热田的辐射热损失（RHL）分别为0.36 MW、38.61 MW和29.14 MW。 RHF 异常最高记录于 2013 年，最低异常发生于 2009 年。2013 年（约 31%）和 2017 年（约 78%），大竹的 RHL 高于八丁原热区。基于所有三种 LST 估计方法的 RHL 季节变化具有相似的模式，对于 H2O 地热场的白天图像，春季 RHL 最高（约 383-451 MW），秋季最低（约 10-222 MW）。根据 RHF 的三种 LST 方法，在夜间图像中，秋季 RHL 最高约为 35-67 MW，春季最低约为 1-3 MW。分别分析，八丁原热区的最高 RHL 约为春季（白天）35-42 MW，秋季（夜间）约 3-7 MW。同样，大竹热区的最高 RHL 在春季（白天）约为 22-25 MW，在冬季（夜间）约为 4-5 MW。季节变化受地区环境温度影响较大。我们还观察到云有巨大的影响，LST 和 RHF 的最高值记录在秋季的云层下方。总体而言，在所有季节中，与分割窗口算法相比，改进的单窗口算法在夜间获得了更高的 LST，在白天获得了更低的 LST。根据 LST 夜间热红外数据，改进的单窗口算法的热损失也高于分割窗口算法。考虑到LST方法和Landsat 8 band 11的误差水平，本研究建议使用Landsat 8 band 10数据采用IWM方法进行LST。这项研究还表明，鉴于整个时期的数据可用，夜间 ASTER 和 Landsat 8 热红外数据都可以有效监测 HO 地热区的热状态。
The Hatchobaru–Otake (HO) geothermal field is proximal to the Kuju volcano on Kyushu, Japan. There are currently three geothermal power plants operating within this geothermal field. Herein, we explore the thermal status of the HO geothermal area using ASTER thermal infrared data to monitor heat losses from 2009 to 2017. We assessed the solar effects and seasonal variation on heat losses based on day- and night-time Landsat thermal infrared images, and compared three conventional methods of land surface temperature (LST) measurements. The normalized difference vegetation index threshold method of emissivity, the split window algorithm for LST, and the Stefan–Boltzmann equation for radiative heat flux (RHF) were used to determine the heat loss within the study area. The radiative heat loss (RHL) was 0.36 MW, 38.61 MW, and 29.14 MW in 2009, 2013, and 2017, respectively, from the HO geothermal field. The highest anomaly in RHF was recorded in 2013, while the lowest was in 2009. The RHLs were higher from Otake than from the Hatchobaru thermal area in the year of 2013 (~31%) and 2017 (~78%). The seasonal variation in the RHLs based on all three LST estimation methods had a similar pattern, with the highest RHL (about 383–451 MW) in spring and the lowest (about 10–222 MW) in autumn for the daytime images from the HO geothermal field. In the nighttime images, the highest RHL was about 35–67 MW in autumn and the lowest was about 1–3 MW in spring, based on the three LST methods for RHFs. The highest RHL was about 35–42 MW in spring (day) and 3–7 MW in autumn (night) from the Hatchobaru thermal area, analyzed separately. Similarly, the highest RHL was about 22–25 MW in spring (day) and 4–5 MW in winter (night) from the Otake thermal area. The seasonal variation was greatly influenced by the regional ambient temperature. We also observed that clouds had a huge effect, with the highest values for both LST and RHF recorded below clouds on an autumn day. Overall, we obtained higher LSTs at nighttime and lower LSTs during the day from the improved mono-window algorithm than the split window algorithms for all of the seasons. The heat losses were also higher for the improved mono-window algorithm than the split window algorithms, based on the LST nighttime thermal infrared data. Considering the error level of the LST methods and Landsat 8 band 11, this study recommends the IWM method for LST using the Landsat 8 band 10 data. This study also suggests that both the nighttime ASTER and Landsat 8 thermal infrared data could be effective for monitoring the thermal status of the HO geothermal area, given that data is available for the entire period.