SPLIT-WINDOW ALGORİTMASI KULLANARAK UYDU GÖRÜNTÜLERİNDEN YER YÜZEY SICAKLIĞININ HESAPLANMASI
Yıl 2010,
Cilt: 14 Sayı: 1, 57 - 66, 21.02.2014
Bekir Yıldız
Ozan Şenkal
,
Vedat Peştemalcı
Öz
Yer yüzey sıcaklığı (LST) dünyanın enerji döngüsünün önemli bir etmeni olduğu gibi bölgesel ve global ölçekler deki atmosfer-yüzey etkileşiminde rol alan anahtar bir parametredir. Bu çalışmada, atmosferik değişkenlere ve yer yayınırlığına bağlı Split-Window (SW) algoritması ve NOAA uydusu verileri kullanılarak Ankara bölgesinin yer yüzey sıcaklığı değerleri hesaplanmıştır. Bölgesel atmosferik veriler kullanılarak Valencia üniversitesi (UVM) adlı Split- Window modelinin katsayıları yeniden hesaplanmış ve çalışma bölgesi için 24 adet yeni algoritma üretilmiştir. UVM algoritmasının en önemli atmosferik parametresi olan Precipitable water (PW) değerleri Wyoming üniversitesi üst atmosfer veri bankasından alınmıştır. Çalışmada Ankara bölgesinin1990-2007 yıllarına ait PW değerleri kullanılmıştır. Oluşturulan yeni algoritma ile hesaplanan yer yüzey sıcaklığı değerleri Ankara meteoroloji istasyonunu değerleri ile
karşılaştırılmış ve MBE (Mean Bias Error) 1.64 oK. RMSE (Root Mean Square Error) 2.81 0K olarak bulunmuştur. Bu sonuçlar genel olarak yer yüzey sıcaklığı hesaplamaları için makul değerlerdir.
Kaynakça
- Bhattacharya, B.K., ve Dadhwal, V.K. 2005. land surface temperature retrıeval and ıts valıdatıon usıng NOAA AVHRR thermal data. Journal of the Indian Society of Remote Sensing, 33: No. 2
- Becker, F., Li, Z.L. 1990. Towards a local split window method over land surface. International Journal of Remote Sensing, 3: 369- 393. surface emissivity and temperature determination in the whole HAPEX– Sahel area from AVHRR data. International Journal of Remote Sensing, 18: 1009–1027.
- Cartalis, C., Chrysoulakis, N. 1997. “Estimation of Precipitable Water in Greece on the Basis of Radiosondes and Satellite Data”. Toxicological and Environmental Chemistry, 58: 163- 171.
- Coll, C., Caselles, V., Sobrino, J.A., Valor, E. 1994. On the atmospherie dependence of the split window equation for land surface temperature. International Journal of Remote Sensing, 15(1): 105-122.
- Chrysoulakis, N., Cartalis, C. 2002. Improving the estimation of land surface temperature for the region of Greece: adjustment of a split window algorithm to distribution of precipitable water. International Journal of Remote Sensing, 23(5): 871-880. for the
- Humes, K.S., Kustas, W.P., Moran, M.S. 1994.Variability of emissivity and surface temperature over a sparsely vegetated surface. Water Resources Research, 30: 1299-1310.
- Liang, S. 2004.Quantative Remote Sensing. Wiley Interscience publication, USA, 534 s.
- Lim, A., Liev, S.C., Kwah, L.K. 2004. Retrival Of Land Surface Temperature İn The Humid Tropics From Modis Data By Modelling The Atmosphere Transmission And Thermel Emission. IEEE Transactions On Geoscıence And Remote Sensıng, 2: 248-257.
- NOAA KLM User Guide 2001.
- Sobrino, J.A., Coll, C., ve Caselles, V. 1991. Atmospheric Correction for Land Surface Temperature Using NOAA-11 AVHRR Channels 4 and 5. Remote Sensing of Environment, 38 (1): 19- 34.
- Schanda, E. 1976. “Ecological Studies” Remote Sensing for Environmental Sciences, 18.
- Qin, Z., Karnieli, A. 1999. Process in the remote sensing of land surface temperature and ground emissivitiy using NOAA-AVHRR data. International Journal of Remote Sensing 20(12):2367-2393.
- Vogt, J.V. 1996. Land surface temperature retrieval from NOAA AVHRR data. in Advances in the use of NOAA AVHRR data for land applications. Kluwer Academic Publishers, Dordrecht.
- Wan, Z. 1999. MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD). Institute for Computational Earth System Science, Santa Barbara.
- Iqbal, M. 1983. An Introduction to Solar Radiation. Academic Press. Vancouver. British Columbia, 374s.
ESTIMATION OF LAND SURFACE TEMPERATURE USING SPLIT-WINDOW ALGORITHM FROM SATELLITE IMAGES
Yıl 2010,
Cilt: 14 Sayı: 1, 57 - 66, 21.02.2014
Bekir Yıldız
Ozan Şenkal
,
Vedat Peştemalcı
Öz
The Land surface temperature (LST) is a good indicator of the energy balance at the earth's surface and is a key parameters in the physics of atmosphere-surface processes on a
regional as well as global scales. In this study, The National Oceanographic and Atmospheric Administration's (NOAA) satellite data were used to calculate LST using a Split-Window(SW)
algorithm which belongs to the atmospheric variables and surface emissivity. Using regional atmospheric data we have recalculated Universty of Valencia (UVW) model Split-Window
algorithm coefficients and have generated 24 new algorthms. Precipitable Water(PW) values of Ankara. which are the most important atmospheric parameter of UVM model. was estimated from the Wyoming University upper-air radiosonde database during the years of 1990-2007. As a result of this study. comparing the calculated LST values with Ankara meteorology station values. mean bias error was found 1.64 o K and RMS error was found as 2.81 o K. The results are genarally reasonable for land surface calculations.
Kaynakça
- Bhattacharya, B.K., ve Dadhwal, V.K. 2005. land surface temperature retrıeval and ıts valıdatıon usıng NOAA AVHRR thermal data. Journal of the Indian Society of Remote Sensing, 33: No. 2
- Becker, F., Li, Z.L. 1990. Towards a local split window method over land surface. International Journal of Remote Sensing, 3: 369- 393. surface emissivity and temperature determination in the whole HAPEX– Sahel area from AVHRR data. International Journal of Remote Sensing, 18: 1009–1027.
- Cartalis, C., Chrysoulakis, N. 1997. “Estimation of Precipitable Water in Greece on the Basis of Radiosondes and Satellite Data”. Toxicological and Environmental Chemistry, 58: 163- 171.
- Coll, C., Caselles, V., Sobrino, J.A., Valor, E. 1994. On the atmospherie dependence of the split window equation for land surface temperature. International Journal of Remote Sensing, 15(1): 105-122.
- Chrysoulakis, N., Cartalis, C. 2002. Improving the estimation of land surface temperature for the region of Greece: adjustment of a split window algorithm to distribution of precipitable water. International Journal of Remote Sensing, 23(5): 871-880. for the
- Humes, K.S., Kustas, W.P., Moran, M.S. 1994.Variability of emissivity and surface temperature over a sparsely vegetated surface. Water Resources Research, 30: 1299-1310.
- Liang, S. 2004.Quantative Remote Sensing. Wiley Interscience publication, USA, 534 s.
- Lim, A., Liev, S.C., Kwah, L.K. 2004. Retrival Of Land Surface Temperature İn The Humid Tropics From Modis Data By Modelling The Atmosphere Transmission And Thermel Emission. IEEE Transactions On Geoscıence And Remote Sensıng, 2: 248-257.
- NOAA KLM User Guide 2001.
- Sobrino, J.A., Coll, C., ve Caselles, V. 1991. Atmospheric Correction for Land Surface Temperature Using NOAA-11 AVHRR Channels 4 and 5. Remote Sensing of Environment, 38 (1): 19- 34.
- Schanda, E. 1976. “Ecological Studies” Remote Sensing for Environmental Sciences, 18.
- Qin, Z., Karnieli, A. 1999. Process in the remote sensing of land surface temperature and ground emissivitiy using NOAA-AVHRR data. International Journal of Remote Sensing 20(12):2367-2393.
- Vogt, J.V. 1996. Land surface temperature retrieval from NOAA AVHRR data. in Advances in the use of NOAA AVHRR data for land applications. Kluwer Academic Publishers, Dordrecht.
- Wan, Z. 1999. MODIS Land-Surface Temperature Algorithm Theoretical Basis Document (LST ATBD). Institute for Computational Earth System Science, Santa Barbara.
- Iqbal, M. 1983. An Introduction to Solar Radiation. Academic Press. Vancouver. British Columbia, 374s.