서울의 도심 녹지가 주변 기온에 미치는 영향 = (The)influence of urban green areas on ambient air temperature in seoul

다국어 초록 (Multilingual Abstract)

Urban green areas represent a unique environment in the human-modified urban climate. It has been well known that a park is relatively cooler than its densely built-up surroundings because it lowers the air temperature in the surrounding urban areas. During the last few decades, focuses have been put on the role of parks for sustainable urban development. So even if the importance of parks has always been commonly acknowledged, research on its possibilities for the improvement of the urban environment is relatively new in Korea.
The main purpose of this dissertation is to examine the influence of parks on
local climate of cities. The specific objectives are to examine:
1) the relationships between land-use types and the air condition around parks analyzing AWS (Automatic Weather Station) data of Seoul from KMA (Korea Meteorological Administration). The distribution of air temperature by land-use type has been influenced by the different heating rates and cooling rates.
2) the influence of different factors and variables on the magnitude of air temperature differences between park and built-up area (ΔTu-p) and the air temperature pattern in and around a park;
3) the influences of urban green areas on built-up area, based on the analysis of the thermal band of Landsat Enhanced Thematic Mapper (ETM) at September 4, 2000.
4) the magnitude and the extension of the cool island formed by urban green area in the built-up area and the spatial pattern of the air temperature in and around an urban park during both daytime and nighttime through case studies. The pattern of air temperature in urban parks and their surrounding built-up area was analyzed from September to November 2000 and from June to August, 2001, measuring maximum and minimum temperatures with fixed sensor (maximum and minimum thermometer) and real temperature by means of car traverse.
The results of this study are followings:
1) The difference of heating rates by land-use type was largest at 2~3 h after sunrise and the difference of cooling rates was largest from 2 h before sunset to 2 h after sunset with its maximum at sunset.
The difference of cooling rates is greatest in a clear and calm weather situation and the difference of cooling rates between the green areas and built-up area is up to 1.5 ℃ h-1. In season, the difference of cooling rates is largest in fall and in turn spring, winter and summer. In a cloudy or rainy day, the difference in heating and cooling rates by land-use type is not distinct but the tendency is similar to a clear day.
2) The local distribution of air temperature is influenced by land-use type, pressure system, wind-speed, wind-direction and topography. In the spatial distribution of anomaly in maximum and minimum temperature, the maximum temperature is not related to air condition or wind-speed.
The distribution of minimum temperature tends to be lower at northeast and to be higher at southwest due to the flow of cold air in Seoul. The maximum temperature is more influenced by land cover than air condition, but the minimum temperature is more influenced by air condition and topography than land cover.
3) In this study, the author took a theoretical model of NASA to estimate the surface temperature from Landsat ETM thermal band data at September 4, 2000. The correlation coefficient between Air Temperature (AT) of AWS and Brightness Temperature (BT) is 0.85 and the relationship may be expressed by the regression; y(AT) = 0.537x(BT) + 16.83. The characteristics of the spatial distribution of the air temperature in Seoul were analyzed using the data of surface temperature from Landsat. In the horizontal distribution of air temperature, warm area appears in the densely built-up commercial or industrial region of the city.
4) The influence of small urban parks on surrounding air temperature was examined in and around Changkyeong palace, Changdeok palace and Jongmyo, Jongro-gu, Seoul.
In daytime of fall with light winds and clear skies, the spatial distribution of temperature depends largely on the land-use and the distance from the park border. There is a magnitude of 1~2 ℃ over a distance of 100 m, 2~3 ℃ over a distance of 300 m, 3~4 ℃ over a distance of 400 m and 5~6 ℃ over a distance of 600 m from the park borders. In maximum temperature, the lowest value appeared on the green area within parks and the highest value on the built-up area, far from the green area. The maximum temperature difference between parks and built-up areas was up to 7.3 ℃. In the built-up area, the maximum temperature of commercial areas was 1~2 ℃ higher than residential areas. In the case of calm and clear daytime, the wind direction affected both the spatial pattern and the magnitude of ΔTu-p.
In daytime of summer with light winds and clear skies, the spatial distribution of temperature depends on the land-use and the distance from the park border.
There is a magnitude of 0.5~1℃ over a distance of 100 m, 1~1.5℃ over a distance of 300 m and 1.5~2℃ over a distance of 500 m from the park borders.
In nighttime, land-use as well as topography and air condition is important for the spatial distribution of temperature because of the cold airflow from adjacent hills.
The horizontal temperature profile by mobile measurement is also related to land-use and to the distance from the park borders during calm and clear day. In Changdeok palace (green ratio is 100 %), there is a magnitude of 1 ℃ over a distance of 200 m and 3~4 ℃ over a distance of 400 m from the park borders.
The major findings and conclusions in this study may be summarized as follows;
1) The temperature difference is related to the distance from the park border. In the case of clear and calm days, the urban green area with a size of about 0.86 ㎢ can lower the air temperature over a distance of 600 m from the park border.
2) The extension of the cooling effect due to the influence of urban green area in the built-up area has increased with the size of park.
3) If the algorithm which can estimate the surface temperature from Landsat ETM thermal data by land-use type, is developed, it might be regarded as one of the most effective methods to analyze the cooling effect with satellite image data.

목차 (Table of Contents)

• 목차
• 그림목차 = iii
• 표목차 = vi
• Abstract = 1
• 제1장 서론 = 5
• 1. 문제의 제기 및 연구 목적 = 5
• 2. 연구 동향 = 6
• 제2장 연구 지역, 자료 및 방법 = 12
• 1. 연구 지역 = 12
• 2. 연구 자료 = 21
• 3. 연구 방법 = 23
• 제3장 토지이용 유형과 기온 특성 = 28
• 1. 토지이용 유형 분류 = 28
• 2. 토지이용 유형별 기온 변화 특성 = 34
• 3. 토지이용과 기상 상태별 기온 분포 = 43
• 제4장 위성 자료를 사용한 녹지 주변의 기온 분포 = 59
• 1. 위성 자료로부터 지표 온도 추출 = 59
• 2. 위성영상 자료에서 추정된 녹지 주변의 기온 분포 = 65
• 제5장 도시 녹지가 주변 시가지 기온에 미치는 영향 = 71
• 1. 건조한 계절의 기온 분포 특성 = 72
• 2. 습윤한 계절의 기온 분포 특성 = 86
• 제6장 결론 = 94
• 참고문헌 = 97
• <부록 1> 서울시 토지이용 현황도 유형과 재분류 목록 = 107
• <부록 2> 자동기상관측 지점별 반경 1 km 내의 토지이용 비율 = 108
• <부록 3> 자동기상관측 지점별 반경 1.5 km 내의 토지이용 비율 = 109
• <부록 4> 자동기상관측 지점별 반경 2 km 내의 토지이용 비율 = 110