Detection of Urban Heat Island (the urban heat island) with remote sensing data








The process of urbanization that occurred in large cities to result in an increase in the population. As a result of the urbanization process is the existence of land-uses of land not built to land up. The impact of process-quality urbaniasi environmental conditions in addition to affecting change is the microclimate in which the conditions of urban air temperature is higher than the surrounding air temperature (Lo and Quattrochi, 2003; Chen et al., 2006). This phenomenon is often referred to as the Urban Heat Island effect (UHI). UHI is a phenomenon or event increase in air temperature in urban areas compared to the surrounding area up to 3-10 ° C. This condition is caused by objects in the urban areas is largely a land up, and materials that are waterproof generally will result in absorption of heat capacity and high thermal conductivity. According Tursilowati (2007) building materials such as asphalt, cement, and concrete absorbing and storing solar heat. Coupled with the use of heating, air conditioning, and power plants that generate waste heat.UHI is formed if the majority of plants (vegetation) is replaced by asphalt and concrete for roads, buildings and other structures necessary to accommodate the increasing human population. Surface soil was replaced to absorb more solar heat as well as more reflecting, causing surface temperatures and the ambient temperature rises. Replacement of shrubs and trees causing shelter and exchange of air through evapotranspiration is reduced so that more humid air is lost (Nowak, 2000).The study of the UHI is very important because it affects the air quality, human health and affect energy use. An increase UHI is also one of the factors that cause global climate change. In this study performed the analysis using remote sensing data and geographic information systems. Advantages of remote sensing in providing spatial data accuracy as well as meetings with a wide range of areas has been demonstrated by Lo et al. (1997), Streutker (2002), and Chen et al. (2006).

All the studies reveal the potential use of remote sensing to analyze the phenomenon of UHI get good results and accurate, although it must be supported by field observation data at climatological stations as reference data. Limited number of conventional weather stations are spatially can be covered with the use of remote sensing.Utilization of data to detect distant pengideraan urban surface temperatures have been carried out in many places and regions. The main basis of the utilization of remote sensing data is the ability to provide data of land surface temperature (land surface temperature) for a wide area and with a high level of data kerapan (1200 m2). This situation can only be done by remote sensing data. However, as detected by remote sensing data is land surface temperature (the object that is on the surface of land) and NOT the air temperature at the surface. The first study on UHI with remote sensing data is done by Rao (1972) by using a sensor Scanning Radiometer (SR), which has a spatial resolution of 7.4 km that is on-1 satellite ITOs in New York City, USA and beyond. Furthermore Carlson et al. (1977) and Matson et al. (1978) continued the study with a more detailed satellite spatial resolution (1 km) in Los Angeles and Washington. The results of the analysis concluded that remote sensing data can be used to examine the effect of UHI in urban areas.After these studies, the utilization of remote sensing data for mapping of UHI area continues to grow. With the remote sensing data with a more detailed spatial resolution such as Landsat and Aster causes the UHI more detail the detection region. Liu and Zhang (2011) using Landsat and Aster to see the UHI in Hong Kong, Streutker (2002) only make use of NOAA Advanced Very High Resolution Radiometer (AVHRR) in the study of UHI in Houston, Texas; and Chen et al. (2006) make use of Landsat 5 and Landsat ETM + to detect the effects of land use change on UHI to correlate with indices of remote sensing. In Indonesia, Tusilowati (2005) tried to assess changes in land use in urban temperature changes in Bandung and Bogor. In addition, Tursilowati (2007) also examines the UHI in the three other major cities, namely Bandung, Semarang and Surabaya. While Effendy (2007) studied the effects of green open spaces of the UHI phenomenon in the greater Jakarta area.The incorporation of remote sensing and GIS analysis in studies of the UHI been done by Aniello et al. (1995). The results of the analysis show that the incorporation of a GIS can clarify the distribution of the location of UHI. On the other hand, Lo et al. (1997) utilize data from the thermal infrared sensor to study the UHI aircraft and mengabungkannya with GIS to obtain more detailed information. In theory the GIS is helpful to clarify the distribution of the location of the UHI through additions to the GIS data layers such as data paths, streams and distribution buildings. by combining remote sensing data and GIS is expected to provide precise information of the spatial distribution of UHI sector in the region.