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    Analysis on the long-term variance of surface urban heat island (SUHI) using Landsat thermal infrared: in case of the city of Seoul

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    https://www.riss.kr/link?id=A106171139

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    다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

    Unique heat sources different from peripheral rural areas are formed in urban areas due to impermeable surfaces and thermal peculiarities of absorbance processes. Urban heat island is a symptom that displays higher temperature in urban areas, compared to rural areas. Rural areas surrounding urban areas generate temperature differences. Land surface temperature consisting of two areas is leaded by the pattern of land use and land cover. A Land surface temperature is estimated, and are used as an index to evaluate urban heat island. Accumulated land surface temperature information from long-term studies could be important quantitative data to understand the progress and current situation in urban heat island. In this study, the Landsat thermal infrared sensors of the remote sensing satellite that cover from 1994 to 2015 are utilized to identify long-term changes of the surface urban heat island and its trends in the study area of Seoul, Korea. Each satellite image is used to measure surface temperature, and produce land cover/land use map simultaneously. However, atmospheric mutual responses produced in surface observation with optical satellite remote sensing cause inaccurate results affected by information contamination. In this study, the cosine approximation model atmospheric correction in visible and near infrared bands and single channel algorithm in thermal infrared band are conducted to secure valid information level in the process of surface urban heat island calculation. surface urban heat island in Seoul for 20 years was gradually increased from the results of this study. In case of especially celestial longitude classified from 45 to 120 in the period from May 5 to August 23 every year, surface urban heat island was increased from 2.51 to 3.98. It was identified that its incremental progress has high statistical correlations.
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    Unique heat sources different from peripheral rural areas are formed in urban areas due to impermeable surfaces and thermal peculiarities of absorbance processes. Urban heat island is a symptom that displays higher temperature in urban areas, compared...

    Unique heat sources different from peripheral rural areas are formed in urban areas due to impermeable surfaces and thermal peculiarities of absorbance processes. Urban heat island is a symptom that displays higher temperature in urban areas, compared to rural areas. Rural areas surrounding urban areas generate temperature differences. Land surface temperature consisting of two areas is leaded by the pattern of land use and land cover. A Land surface temperature is estimated, and are used as an index to evaluate urban heat island. Accumulated land surface temperature information from long-term studies could be important quantitative data to understand the progress and current situation in urban heat island. In this study, the Landsat thermal infrared sensors of the remote sensing satellite that cover from 1994 to 2015 are utilized to identify long-term changes of the surface urban heat island and its trends in the study area of Seoul, Korea. Each satellite image is used to measure surface temperature, and produce land cover/land use map simultaneously. However, atmospheric mutual responses produced in surface observation with optical satellite remote sensing cause inaccurate results affected by information contamination. In this study, the cosine approximation model atmospheric correction in visible and near infrared bands and single channel algorithm in thermal infrared band are conducted to secure valid information level in the process of surface urban heat island calculation. surface urban heat island in Seoul for 20 years was gradually increased from the results of this study. In case of especially celestial longitude classified from 45 to 120 in the period from May 5 to August 23 every year, surface urban heat island was increased from 2.51 to 3.98. It was identified that its incremental progress has high statistical correlations.

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    참고문헌 (Reference)

    1 Voogt, J.A., "Thermal remote sensing of urban climates" 86 (86): 370-384, 2003

    2 Lekner, J., "Theory of Reflection of Electromagnetic and Particle Waves" Springer Netherlands 1987

    3 Strahler, A. H., "The use of prior probabilities in maximum likelihood classification of remotely sensed data" 10 (10): 135-163, 1980

    4 Landsberg, H.E., "The urban climate" Academic Press 1981

    5 Hu, L., "The impact of temporal aggregation of land surface temperature data for surface urban heat island (SUHI) monitoring" 134 : 162-174, 2013

    6 Oke, T. R., "The energetic basis of the urban heat island" 108 (108): 1-24, 1982

    7 Markham, B.L., "Spectral characterization of the landsat thematic mapper sensors" 6 (6): 697-716, 1985

    8 Gallo, K.P., "Satellite-Based Adjustments for the Urban Heat Island Temperature Bias" 38 (38): 806-813, 2002

    9 Wan, Z., "New refinements and validation of the collection-6 MODIS land-surface temperature/emissivityproduct" 140 : 36-45, 2014

    10 Yu, X., "Land surface temperature retrieval from landsat 8 TIRS-comparison between radiative transfer equation-based method, split window algorithm andsingle channel method" 6 (6): 9829-9852, 2014

    1 Voogt, J.A., "Thermal remote sensing of urban climates" 86 (86): 370-384, 2003

    2 Lekner, J., "Theory of Reflection of Electromagnetic and Particle Waves" Springer Netherlands 1987

    3 Strahler, A. H., "The use of prior probabilities in maximum likelihood classification of remotely sensed data" 10 (10): 135-163, 1980

    4 Landsberg, H.E., "The urban climate" Academic Press 1981

    5 Hu, L., "The impact of temporal aggregation of land surface temperature data for surface urban heat island (SUHI) monitoring" 134 : 162-174, 2013

    6 Oke, T. R., "The energetic basis of the urban heat island" 108 (108): 1-24, 1982

    7 Markham, B.L., "Spectral characterization of the landsat thematic mapper sensors" 6 (6): 697-716, 1985

    8 Gallo, K.P., "Satellite-Based Adjustments for the Urban Heat Island Temperature Bias" 38 (38): 806-813, 2002

    9 Wan, Z., "New refinements and validation of the collection-6 MODIS land-surface temperature/emissivityproduct" 140 : 36-45, 2014

    10 Yu, X., "Land surface temperature retrieval from landsat 8 TIRS-comparison between radiative transfer equation-based method, split window algorithm andsingle channel method" 6 (6): 9829-9852, 2014

    11 Patz, J. A., "Impact of regional climate change on human health" 438 (438): 310-317, 2005

    12 Dihkan, M., "Evaluation of surface urban heat island (SUHI) effect on coastal zone: The case of Istanbul Megacity" 118 : 309-316, 2015

    13 Jiménez-Muñoz, J.C., "Correction to ‘A generalized single-channel method for retrieving land surface temperature from remote sensing data’ by Juan C. Jiménez-Muñoz and José A. Sobrino" 109 (109): 2004

    14 Snyder, W. C., "Classification-based emissivity for land surface temperature measurement from space" 19 (19): 2753-2774, 1998

    15 Holben, B. N., "Characteristics of maximum-value composite images from temporal AVHRR data" 7 (7): 1417-1434, 1986

    16 Oke, T. R., "Canyon geometry and the nocturnal urban heat island: Comparisonof scale model and field observations" 1 (1): 237-254, 1981

    17 Kuhn, T.S., "Black ‐body Theory and the Quantum Discontinuity" 48 (48): 327-330, 2005

    18 Chavez, P. S., "An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data" 24 (24): 459-479, 1988

    19 Kalkstein, L.S., "An evaluation of climate/mortality relationships in large U.S. cities and the possible impacts of a climate change" 105 (105): 84-93, 1997

    20 Tiangco, M., "ASTER-based study of the night-time urban heat island effect in Metro Manila" 29 (29): 2799-2818, 2008

    21 RIZWAN, A. M., "A review on the generation, determination and mitigation of Urban Heat Island" 20 (20): 120-128, 2008

    22 Zhang, J., "A C++ program for retrieving land surface temperature from the data of Landsat TM/ETM+ band6" 32 (32): 1796-1805, 2006

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    학술지 이력

    학술지 이력
    연월일 이력구분 이력상세 등재구분
    2026 평가 재인증평가 신청대상 (재인증)
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    2013-09-30 학회명변경 영문명 : Korean Association Of Cadastre Information -> The Korean Cadastre Information Association KCI등재
    2013-01-01 등재 등재학술지 유지 (등재유지) KCI등재
    2010-01-01 등재 등재학술지 선정 (등재후보2차) KCI등재
    2009-01-01 등재 등재후보 1차 PASS (등재후보1차) KCI등재후보
    2008-01-01 등재 등재후보 1차 FAIL (등재후보1차) KCI등재후보
    2006-01-01 등재 등재후보학술지 선정 (신규평가) KCI등재후보
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    학술지 인용정보
    기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
    2016 0.58 0.58 0.55
    KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
    0.49 0.44 0.635 0.16
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