{"title":"基于热遥感的大海得拉巴城市热岛季节分析","authors":"N. Sridhar, V. Bhole","doi":"10.37591/.V9I1.61","DOIUrl":null,"url":null,"abstract":"Urban areas are characterized by densely built-up area. Due to urbanization and consequent urban growth, green spaces, water bodies and other land use changes are resulting in several environmental issues and concerns. One such urban environmental issue is the emergence of Urban Heat Island. An Urban Heat Island (UHI) is the characteristics of elevated temperaturere of both atmosphere and land surface in urban areas as compared with the un-urbanized surrounding or rural areas. In this work, the Land Surface Temperature (LST) of mega city of Hyderabad is extracted with the help of remote sensing data. For the present study, Moderate-resolution Imaging Spectroradiometer ( MODIS) data pertaining to the year 2015 is used. The main objective this study is to identify and map Urban Heat Island. Seasonal variations in the Land Surface Temperature (LST) are analyzed for the month of May and December. It is seen from the analysis of Land Surface Temperature (LST) that, the urban areas have recorded higher temperature as compared to its rural counterpart. It is also seen that emergence of Urban Heat Island is very conspicuous during the night time. The temperature variation between urban-rural surroundings varies between 29.11 and 21.69°C in the month of May (summer) whereas it ranged between 23.71 and 16.14°C in the month of December (winter). The variations in the night temperature is maximum during summer season. Keywords: Urbanization, remote sensing, land surface temperature, urban heat island Cite this Article Sridhar N, Vijaya Bhole. Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing. Journal of Remote Sensing & GIS. 2018; 9(1): 49–56p.","PeriodicalId":427440,"journal":{"name":"Journal of Remote Sensing & GIS","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing\",\"authors\":\"N. Sridhar, V. Bhole\",\"doi\":\"10.37591/.V9I1.61\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Urban areas are characterized by densely built-up area. Due to urbanization and consequent urban growth, green spaces, water bodies and other land use changes are resulting in several environmental issues and concerns. One such urban environmental issue is the emergence of Urban Heat Island. An Urban Heat Island (UHI) is the characteristics of elevated temperaturere of both atmosphere and land surface in urban areas as compared with the un-urbanized surrounding or rural areas. In this work, the Land Surface Temperature (LST) of mega city of Hyderabad is extracted with the help of remote sensing data. For the present study, Moderate-resolution Imaging Spectroradiometer ( MODIS) data pertaining to the year 2015 is used. The main objective this study is to identify and map Urban Heat Island. Seasonal variations in the Land Surface Temperature (LST) are analyzed for the month of May and December. It is seen from the analysis of Land Surface Temperature (LST) that, the urban areas have recorded higher temperature as compared to its rural counterpart. It is also seen that emergence of Urban Heat Island is very conspicuous during the night time. The temperature variation between urban-rural surroundings varies between 29.11 and 21.69°C in the month of May (summer) whereas it ranged between 23.71 and 16.14°C in the month of December (winter). The variations in the night temperature is maximum during summer season. Keywords: Urbanization, remote sensing, land surface temperature, urban heat island Cite this Article Sridhar N, Vijaya Bhole. Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing. 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引用次数: 0
摘要
城市地区的特点是密集的建成区。由于城市化和随之而来的城市增长,绿地、水体和其他土地利用的变化导致了一些环境问题和关注。其中一个城市环境问题就是城市热岛的出现。城市热岛(Urban Heat Island, UHI)是指城市地区的大气和地表温度与未城市化的周边地区或农村地区相比升高的特征。本文利用遥感数据提取了海得拉巴特大城市的地表温度(LST)。在本研究中,使用了2015年的中分辨率成像光谱仪(MODIS)数据。本研究的主要目的是识别和绘制城市热岛。分析了5月和12月地表温度的季节变化。从陆地表面温度(LST)的分析中可以看出,城市地区的温度高于农村地区。城市热岛在夜间的出现也非常明显。5月(夏季)城乡温差在29.11 ~ 21.69°C之间,12月(冬季)城乡温差在23.71 ~ 16.14°C之间。夏季夜间气温变化最大。关键词:城市化遥感地表温度城市热岛基于热遥感的大海得拉巴城市热岛季节分析遥感与地理信息系统学报。2018;9 (1): 49-56p。
Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing
Urban areas are characterized by densely built-up area. Due to urbanization and consequent urban growth, green spaces, water bodies and other land use changes are resulting in several environmental issues and concerns. One such urban environmental issue is the emergence of Urban Heat Island. An Urban Heat Island (UHI) is the characteristics of elevated temperaturere of both atmosphere and land surface in urban areas as compared with the un-urbanized surrounding or rural areas. In this work, the Land Surface Temperature (LST) of mega city of Hyderabad is extracted with the help of remote sensing data. For the present study, Moderate-resolution Imaging Spectroradiometer ( MODIS) data pertaining to the year 2015 is used. The main objective this study is to identify and map Urban Heat Island. Seasonal variations in the Land Surface Temperature (LST) are analyzed for the month of May and December. It is seen from the analysis of Land Surface Temperature (LST) that, the urban areas have recorded higher temperature as compared to its rural counterpart. It is also seen that emergence of Urban Heat Island is very conspicuous during the night time. The temperature variation between urban-rural surroundings varies between 29.11 and 21.69°C in the month of May (summer) whereas it ranged between 23.71 and 16.14°C in the month of December (winter). The variations in the night temperature is maximum during summer season. Keywords: Urbanization, remote sensing, land surface temperature, urban heat island Cite this Article Sridhar N, Vijaya Bhole. Seasonal Analysis of Urban Heat Island of Greater Hyderabad Using Thermal Remote Sensing. Journal of Remote Sensing & GIS. 2018; 9(1): 49–56p.