TY - GEN
T1 - Analysing the effects of different land cover types on Land Surface Temperature using satellite data
AU - Şekertekin, A.
AU - Kutoglu, H.
AU - Kaya, S.
AU - Marangoz, A. M.
PY - 2015
Y1 - 2015
N2 - Monitoring Land Surface Temperature (LST) via remote sensing images 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. 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. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 °C lower temperatures than the city center and arid land., LST values change about 10 °C 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 (ÇATES and ZETES) Çatalaǧzi, is about 5 °C higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.
AB - Monitoring Land Surface Temperature (LST) via remote sensing images 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. 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. In this research, mono window algorithm was implemented to Landsat 5 TM image acquired on 28.08.2011. Besides, meteorological data such as humidity and temperature are used in the algorithm. Moreover, high resolution Geoeye-1 and Worldview-2 images acquired on 29.08.2011 and 12.07.2013 respectively were used to investigate the relationships between LST and land cover type. As a result of the analyses, area with vegetation cover has approximately 5 °C lower temperatures than the city center and arid land., LST values change about 10 °C 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 (ÇATES and ZETES) Çatalaǧzi, is about 5 °C higher than city center. Sandbank and agricultural areas have highest temperature due to the land cover structure.
KW - Climate change
KW - Land Surface Temperature
KW - Urbanization
UR - http://www.scopus.com/inward/record.url?scp=84974594034&partnerID=8YFLogxK
U2 - 10.5194/isprsarchives-XL-1-W5-665-2015
DO - 10.5194/isprsarchives-XL-1-W5-665-2015
M3 - Conference contribution
AN - SCOPUS:84974594034
T3 - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SP - 665
EP - 667
BT - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
A2 - Arefi, H.
A2 - Motagh, M.
PB - International Society for Photogrammetry and Remote Sensing
T2 - ISPRS International Conference on Sensors and Models in Remote Sensing and Photogrammetry 2015
Y2 - 23 November 2015 through 25 November 2015
ER -
