ANALYSING THE EFFECTS OF DIFFERENT LAND COVER TYPES ON LAND SURFACE TEMPERATURE USING SATELLITE DATA |
Paper ID : 1058-SMPR-FULL |
Authors: |
Aliihsan Sekertekin *1, Senol Hakan KUTOGLU2, Sinasi KAYA3, Aycan Murat MARANGOZ2 1Bulent Ecevit University
Geomatic Muhendisligi Bolumu 2Bulent Ecevit University 3Istanbul Technical University |
Abstract: |
In recent years, climate change has been one of the most important problems that the ecological system of the world has been encountering. Global warming and climate change have been studied frequently by all disciplines all over the world and Geomatics Engineering also contributes to such studies by means of remote sensing, Global Navigation Satellite System (GNSS) etc. Monitoring Land Surface Temperature (LST) via remote sensing satellites is one of the most important contributions to climatology. LST is an important parameter governing the energy balance on the Earth and it also helps us to understand the behavior of urban heat islands. Urban heat island means that the city is warmer than its surroundings. In other words, urban lands have higher temperature values than the rural ones and urban heat island is one of the most crucial definitions as climate change parameter. There are lots of algorithms to obtain LST by remote sensing techniques. The most commonly used algorithms are split-window algorithm, temperature/emissivity separation method, mono-window algorithm and single channel method. Generally three algorithms are used to obtain LST by using Landsat 5 TM data. These algorithms are radiative transfer equation method, single channel method and mono-window algorithm. Radiative transfer equation method is not applicable because during the satellite pass, atmospheric parameters must be measured in-situ. Single channel method and mono-window algorithm both present satisfying results. However, mono-window algorithm can be implemented simply and practically because of using simulated linear transformation equations for some parameters. In this research, mono window algorithm was implemented to Landsat 5 TM image. Besides, meteorological data such as humidity and temperature are used in the algorithm. Acquisition date of the image is 28.08.2011 and our study area is Zonguldak, Turkey. Moreover, high resolution Geoeye-1 and Worldview-2 satellite images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. In this study, some characteristic areas like industrial regions, city centers, sandbank, arid land, vegetated and forest land were evaluated as different land cover types with regard to LST. As a result of the analyses, area with vegetation cover has approximately 5 ºC lower temperatures than the city center and arid land., LST values change about 10 ºC in the city center because of different surface properties such as reinforced concrete construction, green zones and sandbank. The temperature around some places in thermal power plant region Çatalağzı, is about 5 ºC higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure. Consequently, satellite imagery is an effective method to retrieve LST maps for large areas. Land cover types and the materials used as surface structure affect LST directly. Thus, it should be considered not to use materials in city centers that absorb the sun radiation too much for urban heat island effect. LST maps can be generated periodically by means of satellite images. Thus, it can not only be useful for agricultural activities but also for preparing a substructure especially for regional climate change researches. |
Keywords: |
Land Surface Temperature, Urbanization, Climate Change |
Status : Paper Accepted (Oral Presentation) |