2-s2.0-85091861978

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[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2020, International Association for Mathematical Geosciences.Identifying physical properties of geothermal features such as surface temperature and roughness is crucial for geothermal assessment, hydrology, and environmental studies. Surface temperature and roughness-related rock properties strongly influence the thermal infrared and back-scattering intensities, respectively, of synthetic aperture radar (SAR) images. This study aimed to identify geothermal steam spots based on the surface temperature and roughness of altered surfaces, mud pools, and hot springs in tropical conditions. The thermal emissivity separation method was adopted to calculate kinetic temperature using the thermal infrared (TIR) of the advanced spaceborne thermal emission and reflection radiometer (ASTER) data as well as ground temperature data. Surface temperatures calculated by the thermal emissivity separation method were corrected using measured ground temperatures to eliminate the effects of atmospheric absorption, thermal inertia of materials, and/or diurnal temperature in the images. In addition, the linear fitting method was applied to obtain the final surface roughness model based on the calculated determination coefficient (R2) between the initial surface roughness model derived by Sentinel-1A SAR and field data. The highest R2 between surface roughness values from Sentinel-1A SAR and field data were selected to calculate spatially the surface roughness of the Wayang Windu Geothermal Field, West Java, Indonesia. The satellite imagery and field measurements showed that surface temperature and roughness features correlate with each other, and high and low thermal features correlate with high and low surface roughness values, respectively. Accordingly, we integrated the TIR and SAR data to propose the thermal resistivity index (TRI) as an indicator of the hydrothermal fluid paths to the surface. Low TRI was encountered at geothermal features and intersections of subsurface faults, which indicated weak zones that radiate heat from the subsurface to the surface.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Geothermal,Radar,Roughness,Sentinel-1A,Thermal[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text]The authors wish to express their gratitude to the Beneficial and Advanced Geothermal Use System (BAGUS) Project within the framework of SATREPS for providing the field and laboratory equipment, RISTEK and LPPM ITB for the funding support of the field surveys, and Star Energy Geothermal, Ltd., for their great collaborative research assistance.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1007/s11053-020-09754-9[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]