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Landsat-8 시계열 위성영상을 활용한 도심지 확장에 따른 열섬포텐셜 분석 Analysis of Thermal Heat Island Potential by Urbanization Using Landsat-8 Time-Series Satellite Imagery

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Landsat-8 시계열 위성영상을 활용한 도심지 확장에 따른 열섬포텐셜 분석 Analysis of Thermal Heat Island Potential by Urbanization Using Landsat-8 Time-Series Satellite Imagery Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography ISSN 1598-4850(Print) Vol. 36, No. 4, 305-316, 2018 ISSN 2288-260X(Online) https://doi.org/10.7848/ksgpc.2018.36.4.305 Original article Landsat-8 시계열 위성영상을 활용한 도심지 확장에 따른 열섬포텐셜 분석 Analysis of Thermal Heat Island Potential by Urbanization Using Landsat-8 Time-series Satellite Imagery 김태헌1)·이 원 희 2)·한 유 경 3) Kim, Taeheon · Lee, Won Hee · Han, Youkyung Abstract As the urbanization ratio increases, the heat environment in cities is becoming more important due to the urban heat island. In this study, the heat island spatial analysis was calculated and conducted for analysis of urban thermal environment of Sejong city, which was launched in 2012 and has been developed rapidly. To analyze the ratio and change rate of urban area, a multi temporal land cover map (2013 to 2015 and 2017) of study area is generated based on Landsat-8 OLI/TIRS (Operational Land Imager / Thermal Infrared Sensor) satellite imagery. Then, we select an TIR (Thermal Infrared) band from the two TIR bands provided by the Landsat-8, which is used for calculating the heat island potential, through the accuracy evaluation of the brightness temperature and AWS (Automatic Weathering Station) data. Based on the selected band and surface emissivity, land surface temperature is calculated and the estimated heat island potential change is analyzed. As a result, the land surface temperature of the high ratio and change rate of urban area was significantly higher than the surrounding area around 3℃ to 4℃, and the heat island potential was also higher around 4℃ to 5℃. However, the heat island phenomenon was alleviated in urban areas with high rate of change that also show high green area ratio. Therefore, we demonstrated that dense urban area increases the possibility of inducing heat island, but it can mitigate the heat island through green areas. Keywords : Urban Heat Island, Heat Island Potential, Landsat-8 OLI/TIRS, Land Cover Map, Land Surface Temperature 초 록 우리나라의 도시화 비율이 증가함에 따라 도시열섬으로 인한 도시 열 환경의 중요성이 증대되고 있다. 본 연구에 서는 2012년에 출범하여 급속도로 발전을 이룬 세종특별자치시의 도시 열 환경 분석을 위해 열섬포텐셜을 이용하 였다. 우선 도심지의 비율 및 변화율을 분석하기 위해 Landsat-8 OLI/TIRS 위성영상을 기반으로 연구지역의 시계 열 토지피복도(2013년~2015년, 2017년)를 생성하였다. 그리고 취득된 위성영상에서 제공하는 두 가지 열적외선 밴 드에서 산출된 밝기온도와 자동기상관측망 자료와의 정확도 평가를 통해 연구에 활용할 밴드를 선정하였다. 선정 된 밴드와 지표면 방사율을 고려하여 지표면온도를 산출하였으며, 이를 기반으로 산출된 열섬포텐셜 변화분석을 수행하였다. 분석결과, 연구지역의 행정구역별 도심지 변화율이 크게 관측되는 지역의 지표면온도는 주변지역 보다 3℃~4℃ 높고, 열섬포텐셜 또한 4℃~5℃ 높게 관측되었다. 하지만 도심지 변화율이 크고 녹지의 비율이 높은 지역 에서는 열섬현상이 완화되는 경향을 보였다. 이를 통해 면적대비 도심지가 차지하는 비율이 높아지면 열섬을 유발 할 가능성이 증가하지만 녹지를 통해 열섬을 완화 시킬 수 있다는 것을 알 수 있었다. 핵심어 : 도시열섬, 열섬포텐셜, Landsat-8 OLI/TIRS, 토지피복도, 지표면온도 Received 2018. 07. 27, Revised 2018. 08. 09, Accepted 2018. 08. 29 1) Dept. of Geospatial Information, Kyungpook National University (E-mail: [email protected]) 2) Member, School of Convergence & Fusion System Engineering, Kyungpook National University (E-mail: [email protected]) 3) Corresponding Author, Member, School of Convergence & Fusion System Engineering, Kyungpook National University (E-mail: [email protected]) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http:// creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. 305 Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 36, No. 4, 305-316, 2018 1. 서 론 (Ichinose et al., 1994). 지표와 대기간의 현열교환량을 산정 하는 지표인 열섬포텐셜은 다방면에서 활용되고 있으며, 위 과거 산업화가 진행되면서 이촌향도 현상으로 인해 도시로 성영상을 활용하여 산출할 수 있다(Iino and Hoyano, 1996). 인구가 집중되어 급격한 도시화가 진행되었다. 도시화가 진행 Landsat TM 영상을 활용하여 산출된 열섬포텐셜 기반 피복 되면 도시 내에 주거, 상업, 공공시설 등의 인공구조물이 증가 별 열섬발생가능성 분석(Ahn et al., 2007), Landsat ETM+ 영 함으로써 냉각 효과를 담당하는 녹지가 감소하고 인공 열과 상을 활용하여 피복변화에 따른 열섬포텐셜 변화분석(Ahn 대기오염 물질로 인해 도시 상공의 기온이 주변 지역보다 높 et al., 2012), 피복별 열섬포텐셜 분석을 통한 열섬현상 완화 아지는 도시열섬 현상이 발생한다. 도시열섬이란 일반적으로 에 관한 연구(Hashida et al., 2017) 등을 통해 열섬포텐셜은 도심지 번화지역이 주변 교외 지역보다 온도가 높게 측정되는 도시열섬 분석에 효과적으로 활용될 수 있는 지표라는 것이 현상을 말한다(Kim and Yeom, 2012). 도심지를 구성하고 있 증명되었다. 는 아스팔트 및 콘크리트 포장 면은 알베도(albedo)가 낮아 많 기존에 위성영상 기반의 열섬포텐셜을 활용한 연구는 은 양의 태양복사 에너지를 흡수함으로써 지표 부근의 열에 Landsat TM과 Landsat ETM+영상을 기반으로 진행되었다. 너지를 누적시키고, 또한 햇빛을 반사하고 흡수하는 면적이 하지만 Landsat TM 영상은 열적외선(thermal Infrared) 밴드 증가하는 초고층 건물의 증축으로 지표면 온도가 증가하여 영상의 해상도가 120m로 낮고 Landsat ETM+ 영상은 SLC- 열섬현상이 발생한다. 그리고 공장 및 자동차 매연으로 인해 off (Scan Line Corrector Failure) 문제로 인해 데이터로서의 발생하는 스모그가 대기의 열을 저장하여 다시 방출하기 때 활용가치가 떨어진다. 또한 산출된 열섬포텐셜은 지표면 방사 문에 악순환이 반복되며 세계적으로 문제시되고 있는 지구온 율을 고려하지 않아 오차를 포함하고 있다. 위와 같은 문제 난화에도 큰 영향을 미치고 있다. 점을 보완하고 개선하기 위해 본 연구에서는 Landsat-8 OLI/ 도시열섬현상은 인간이 생활함에 있어 전반적으로 큰 영 TIRS (Operational Land Imager / Thermal Infrared Sensor) 향을 미치고 있으며, 이러한 도시열섬의 문제점을 분석하고 영상을 기반으로 도심지 확장에 따른 열섬포텐셜 분석을 진 해결하기 위한 연구가 국내외에서 다양하게 진행되고 있다. 행하였다. 이를 위해, 전처리과정을 거친 영상을 기반으로 토 정규식생지수(NDVI: Normalized Difference Vegetation 지피복도를 생성하였다. 그 후 열적외선 밴드인 Band 10(10.60 Index), 정규수분지수(NDWI: Normalized Difference Water ㎛ - 11.19㎛), Band 11(11.50㎛ - 12.51㎛)에서 각각 산출된 밝 Index)와 지표면온도(LST: Land Surface Temperature)간 기온도와 AWS 자료와의 정확도 분석을 통해 선정된 밴드를 의 상관관계 분석(Weng et al., 2004), IKONOS 영상 기반 기반으로 지표면방사율을 고려하여 지표면온도를 산출하였 의 토지피복도와 Landsat TM/ETM (Thematic Mapper / 다. 생성된 데이터를 바탕으로 열섬포텐셜을 산출 후 도심지 Enhanced Thematic Mapper) 영상기반의 NDVI, 정규시가 확장에 따른 열섬포텐셜과의 관계를 분석하였다. 화지수(NDBI: Normalized Difference Build-up Index) 그리 고 LST와의 관계를 이용한 도시열섬 분석(Chen et al., 2006), 2. 연구지역 및 자료 Landsat 영상 기반의 도시지역지수(UI: Urban Index)와 온도 변동지수(TVI: Temperature Variation Index)를 이용한 도시 대한민국 중앙부에 위치하고 있는 세종특별자치시는 국토 열섬 연구(Kim et al., 2014b)가 진행되었다. 또한 피복별 알베 균형발전의 가치를 실현하고 수도권의 행정중심과밀화를 해 도 분석을 통한 도시열섬원인 분석(Maclachlan et al., 2017), 결하기 위해 충청남도 연기군 전체와 공주시 일부, 충청북도 지표면온도와 자동 기상관측망(AWS: Automated Weather 청원군 일부를 편입하여 2012년 7월에 출범한 행정중심복합 Station) 자료를 함께 활용하여 밴드별 지상기온분포도를 제 도시이며 행정구역은 1읍 9면 14동 125리로 구성되어있다. 출 작(Ku, 2014), 녹지 주차장를 활용한 도시열섬 완화에 관한 범 이후 급격한 도시개발로 인해 도심지가 증가하여 그 결과 연구(Onishi et al., 2010), 열섬 현상 완화를 위한 도심지를 구 출범 당시의 인구는 약 11만 명이었지만 급속도로 인구가 유입 성하고 있는 건축 자재 및 건물 외관에 다양한 녹지를 적용방 되어 2018년 측정 기준 약 30만 명을 달성하였다(Sejong City, 안에 대한 연구(Aflaki et al., 2017) 등이 있다. 2018). 앞에서 언급한 내용을 비추어 볼 때 지속적인 인구유 도시열섬 현상에 관한 심도 깊은 연구를 위해 토지피복 입이 예상되며 단기간 도시개발로 인한 도심지증가로 열섬현 특성에 따라 열섬발생 가능성을 정량적으로 평가하기 위한 상이 심화될 것으로 판단되어 연구대상지를 세종특별자치시 열섬포텐셜(HIP: Heat Island Potential) 개념이 제안되었다 로 선정하였다(Fig. 1). 306 Analysis of Thermal Heat Island Potential by Urbanization Using Landsat-8 Time-series Satellite Imagery 자료를 취득하였다. 취득된 정보는 Table 2와 같으며 온도 측 Table 1. Information of Landsat-8 imagery used in the study Acquisition Acquisition Cloud cover Path/ date time rate(%) Row Datum 2013.06.05 11:07:04 2.97 115/35 2014.05.30 11:10:22 0.46 116/35 WGS 84 2015.05.26 11:04:04 0.09 115/35 2017.05.22 11:10:41 3.36 116/35 Fig. 1. Study area in Sejong city 정시간은 Table 1에 나와 있는 위성영상 취득 시간과 동일한 시간에 측정된 온도를 활용하였다. 본 연구에서는 2013년 2월 11일에 발사되어 운용 중 인 Landsat-8 OLI/TIRS 위성영상을 활용하였다. Landsat 3. 연구 방법 ETM+ 위성과는 달리 Landsat-8 위성은 OLI와 TIRS의 두 개의 센서가 장착되어 VNIR (Visible and Near Infrared) 및 영상을 활용함에 있어 지표면의 특성에 따라 방사되는 에 TIR 대역의 위성영상을 제공한다. 그리고 가시광선 파장대역 너지, 센서의 오차와 조도 및 대기의 조건에서 발생하는 노이 의 공간해상도는 기존의 Landsat ETM+에서 제공하는 가시 즈를 보정하기 위해 반사 및 방사보정을 수행 후 시계열 토지 광선 파장대역의 공간해상도(30m)와 동일하며 열적외선 파 피복도를 구축하였다. 그리고 Landsat-8 OLI/TIRS의 열적외 장대역의 영상의 공간해상도는 100m로 Landsat ETM+에서 선 밴드인 Band 10, Band 11을 기반으로 지표면온도를 산출 제공하는 열적외선 파장대역의 공간해상도인 60m에 비해 줄 하였고, 데이터의 효율성을 높이기 위해 AWS 자료와 지표면 어들었지만, Band가 2개로 증가하였다. 온도간의 평균제곱근오차(RMSE: Root Mean Square Error) 일반적으로 도시열섬 연구는 냉방기 및 인공구조물의 특 를 활용한 정확도 평가를 통해 밴드를 선정하였다. 그 후 정확 성으로 인해 도시열섬 현상이 가장 두드러지는 여름철 데이 도가 높은 밴드를 선별하여 열섬포텐셜 산출 후 분석하였다. 터를 기반으로 진행되었다. 하지만 여름뿐만 아니라 봄, 가을, 겨울에도 도시열섬이 발생하며(Kim et al., 2014a), 본 연구에 3.1 영상의 전처리 및 토지피복분류 서는 구름이 연구지역을 덮고 있는 시기의 영상은 제외 하였 취득된 영상은 지표의 특성 및 센서의 오차가 보정되지 다. 그 결과 5월 말에서 6월 초의 시계열 영상을 바탕으로 연 않아 오차를 포함하고 있는 DN (Digital Number)값으로 구를 진행하였다(Table 1). 표현된다. 이러한 취득된 영상의 DN 값을 전처리 과정을 거 기상청에서 제공하는 AWS 자료는 도시 열 환경 분석 및 쳐 보정된 반사도 값으로 변환하기 위해 NASA (National 다양한 분야에서 기초자료로써 활용되고 있다.
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