Analysis of Land Use Change and Expansion of Surface Urban Heat Island in Bogor City by Remote Sensing

Bogor as one of the satellite cities of Jakarta Metropolitan experiences rapid population growth and urban development. The urban landscape that is changed by urban development affects the city expansion, the increase of land surface temperature (LST), and the urban heat island (UHI). Objectives of this study are to analyze the city expansion, to analyze the LST characteristic of each land use type, and to examine the correlation between LST change and land use change that is affected by the city expansion. We examined the development of the UHI through the city expansion and the increasing of LST. Landsat 5 TM in 1990, 1997, 2007, and Landsat 8 OLI/TIRS in 2017 were used in this study. For the land used classification, we used Local Climate Zone (LCZ) classification system. The result shows that Bogor has experienced city expansion in the last 27 years. According to the rate of city expansion in the different period, the highest city expansion occurred in 1997–2007 by 8213.7 ha in the analyzed area. In the analysis of relationship between LST and LCZ, there are differences of LSTs among LCZ categories. We also found the area that shows a high LST value expanded broadly towards suburban area with urban development. The temperature differences between urban and suburban were 1.36 °C in 1990, 2.33 °C in 1997, 2.97 °C in 2007, and 2.26 °C in 2017. We defined urban change degree to quantify the land use change, and it is compared with LST change. By the analysis, strong influence of urban expansion on the distribution of surface UHI was observed.

[1]  Y. Murayama,et al.  Classification and change detection of built-up lands from Landsat-7 ETM+ and Landsat-8 OLI/TIRS imageries: A comparative assessment of various spectral indices , 2015 .

[2]  D. Lu,et al.  Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies , 2004 .

[3]  J. Rhee,et al.  Relationship between land cover patterns and surface temperature in urban areas , 2014 .

[4]  Maria Antonia Brovelli,et al.  CENSUS of Cities: LCZ Classification of Cities (Level 0) – Workflow and Initial Results from Various Cities , 2015 .

[5]  Yuji Murayama,et al.  An urban heat island study in Nanchang City, China based on land surface temperature and social-ecological variables , 2017 .

[6]  B. Dousseta,et al.  Satellite multi-sensor data analysis of urban surface temperatures and landcover , 2003 .

[7]  J. A. Voogta,et al.  Thermal remote sensing of urban climates , 2003 .

[8]  Lin Liu,et al.  Urban Heat Island Analysis Using the Landsat TM Data and ASTER Data: A Case Study in Hong Kong , 2011, Remote. Sens..

[9]  Raymond L. Czaplewski,et al.  Variance Estimates and Confidence Intervals for the Kappa Measure of Classification Accuracy , 1997 .

[10]  Nathaniel A. Brunsell,et al.  Seasonal and Diurnal Characteristics of Land Surface Temperature and Major Explanatory Factors in Harris County, Texas , 2017 .

[11]  Swades Pal,et al.  Detection of land use and land cover change and land surface temperature in English Bazar urban centre , 2017 .

[12]  Christopher S. Galletti,et al.  Landscape configuration and urban heat island effects: assessing the relationship between landscape characteristics and land surface temperature in Phoenix, Arizona , 2013, Landscape Ecology.

[13]  M. Bauer,et al.  Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery , 2007 .

[14]  W. Emery,et al.  Satellite-derived urban heat islands from three coastal cities and the utilization of such data in urban climatology , 1989 .

[15]  T. Oke,et al.  Local Climate Zones for Urban Temperature Studies , 2012 .

[16]  D. Streutker A remote sensing study of the urban heat island of Houston, Texas , 2002 .

[17]  Manjula Ranagalage,et al.  An Urban Heat Island Study of the Colombo Metropolitan Area, Sri Lanka, Based on Landsat Data (1997-2017) , 2017, ISPRS Int. J. Geo Inf..

[18]  R. Leemans,et al.  Comparing global vegetation maps with the Kappa statistic , 1992 .

[19]  Yuanzhi Zhang,et al.  Surface Urban Heat Island Analysis of Shanghai (China) Based on the Change of Land Use and Land Cover , 2017 .

[20]  Xu Chen,et al.  Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China , 2017 .

[21]  Benjamin Bechtel,et al.  Multitemporal Landsat data for urban heat island assessment and classification of local climate zones , 2011, 2011 Joint Urban Remote Sensing Event.

[22]  Giles M. Foody,et al.  On the compensation for chance agreement in image classification accuracy assessment, Photogram , 1992 .

[23]  Xiaoling Chen,et al.  Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes , 2006 .

[24]  S. Myint,et al.  Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of Southeast Asia. , 2017, The Science of the total environment.