Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2019, Cilt: 4 Sayı: 1, 16 - 27, 01.02.2019
https://doi.org/10.26833/ijeg.417151

Öz

Kaynakça

  • Avdan, U., Jovanovska, G., (2016) Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data, Journal of Sensors, vol. 2016, Article ID 1480307, 8 pages,. 2016. doi:10.1155/2016/1480307.
  • Bastiaanssen, W. G. M. and Menenti, M. (1998). A remote sensing surface energy balance algorithms for land (SEBAL) 1. Formulation. Journal of Hydrology, 212, 198–212.
  • Brunetti, M., Maugeri, M.,Nanni, T. (2000). Long-Term Trends in Extreme Precipitation Events over the Conterminous United States and Canada. Theoratical and Applied Climatology, 65, 165-175.
  • Cai, G., Xue, Y., Hu, Y., Guo, J., Wang, Y. and Qi, S. (2007). Quantitative study of net radiation from MODIS data in the lower boundary layer in Poyang Lake area of Jiangxi Province, China. International Journal of Remote Sensing, 28, 4381-4389.
  • Chander, G., Markham, B.L., Helder, D.L., (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113, 893–903.
  • Chen, Y.H., Li, X.B., Li, J., Shi, P.J. and Dou, W., (2005). Estimation of daily evapotranspiration using a two-layer remote sensing model. International Journal of Remote Sensing, 26, 1755–1762.
  • Christóbal, J., Ninyerola, M.Andpons, X., (2008). Modeling air temperature through a combination of remote sensing and GIS data. Journal of Geophysical Research, 113, D13106 doi:10.1029/2007JD009318.
  • Coll, C., Caselles, V., Galve, J.M. (2005). Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data. Remote Sensing of Environment, 97, 288-300.
  • Coll, C., Galve, J.M., Sánchez, J.M., Caselles, V., (2010). Validation of landsat-7/ETM+ thermal-band calibration and atmospheric correction with ground-based measurements. IEEE Transactions on Geoscience and Remote Sensing, 48, 547–555.
  • Dash, P., Göttsche, F.M., Olesen,F.S., Andfischer, H., (2002). Land surface temperature and emissivity estimation from passive sensor data: theory and practicecurrent trends. International Journal of Remote Sensing, 23, 2563–2594.
  • Dogdu, M.S., M. M. Toklu,C., Sağnak, 2007, “Examination of Precipitation and Groundw ater Level Values in Konya Closed Basin”,First Turkish Climate Change Congress, (in Turkish), pp. 394–401. 11-12 April 2007, İstanbul.
  • Du,Y., J. Cihlar, J. Beaubien, and R. Latifovic, (2001). “Radiometric Normalization, Compositing, and Quality Control for Satellite High Resolution Image Mosaics over Large Areas,” IEEE Transactions on Geoscience and Remote Sensing, 39, 623-634. [doi:10.1109/36.911119].
  • Durduran, S. S. (2010). Coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey, using multitemporal landsat imagery. Environmental monitoring and assessment, 164(1-4), 453-461.
  • Florio, E.N., Lele, S.R., Chi Chang, Y., Sterner,R. and Glass, G.E., (2004). Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature: a statistical approach. International Journal of Remote Sensing, 25, 2979-2994.
  • Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J.S., Hook,S., Andkahle, A.B., (1998). A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. IEEE Transaction on Geoscience and Remote Sensing, 36, 1113–1126.
  • Jiang, L. and Islam, S. (2001). Estimating of surface evaporation map over southern Great Plains using remote sensing data. Water Resources Research, 37, 329–340.
  • Joshi, J. P., & Bhatt, B. (2012). Estimating temporal land surface temperature using remote sensing: A study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences, 2(1), 123- 130.
  • Kendall, M. G. (1975). Rank Correlation Methods. Griffin, London.
  • Kim, K., Jezek, K. C. and Liu, H. (2007). Orthorectified image mosaic of Antarctica from 1963 Argon satellite photography: image processing and glaciological applications, International Journal of Remote Sensing, 28, 5357-5373.
  • Kundzewicz, Z. W.,Robson, A. J. (2004). Change detection in hydrological records: review of methodology. Hydrological Sciences Journal, 49, 7-19.
  • Kustas,W.P. and Norman, J.M. (1999). Evaluation of soil and vegetation heat flux predictions using a simple twosource model with radiometric temperatures for partial canopy cover. Agricultural and Forest Meteorology, 94, 13–29.
  • Mann, H. B. (1945). Non-Parametric tests against trend. Econometrica, 13, 245-259.
  • Nichol, J.E. and Wong, M.S., (2008). Spatial variability of air temperature and appropriate resolution for satellitederived air temperature estimation. International Journal of Remote Sensing, 29, 7213-7223.
  • Niedźwiedź, T., Twardosz, R., Walanus, A. (2009). Long-term variability of precipitation series in east central Europe in relation to circulation patterns. Theoretical and Applied Climatology, 98, 337-350.
  • Markham, B.L., and Barker, J.L. (1986). Landsat MSS and TM post-calibration dynamic rangers, exoatmospheric reflectance and at-satellite temperatures. EOSAT Landsat Tech. Notes, August, 1986.
  • Norman, J.M., Kustas, W.P. and Humes, K.S. (1995). Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agriculture and Forest Meteorology, 77, 263-293.
  • Orhan, O., Ekercin, S., Dadaser-Celik, F., (2014) Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey, The Scientific World Journal, vol. 2014, Article ID 142939, 11 pages. doi:10.1155/2014/142939
  • Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). Assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization.International Journal of Remote sensing, 19, 1663-1681.
  • Partal, T.,Kahya, E. (2006). Trend analysis in Turkish precipitation data. Hydrological Processes, 20, 2011- 2026.
  • Qin, Z.H. and Karnieli, A. (1999). Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data. International Journal of Remote Sensing, 20, 2367–2393.
  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of American Statistical Association, 39, 1379-1389.
  • Sobrino, J.A. and Raissouni, N. (2000). Towardremotesensing methods for land cover dynamic monitoring: application to Morocco, International Journal of Remote Sensing, vol.21, no. 2, pp. 353–366.
  • Sobrino, J.A., Jimenez-Munoz, J. C., Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90, 434-440.
  • Sobrino, J.A., Jiménez-Muñoz, J.C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J., Martínez, P., (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscience and Remote Sensing, 46, 316–327.
  • Srivastava, P.K., Majumdar, T.J., Bhattacharya, A.K. (2009). Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 43, 1563- 1574.
  • Su, Z., (2002). The surface energy balance system (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Science, 6, 85–99.
  • Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A. Zhao, S., (2015). An improved mono-window algorithm for land surface temper-ature retrieval from landsat 8 thermal infrared sensor data, Remote Sensing, vol. 7, no. 4, pp. 4268–4289.

Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey

Yıl 2019, Cilt: 4 Sayı: 1, 16 - 27, 01.02.2019
https://doi.org/10.26833/ijeg.417151

Öz

The main purpose of this paper is to investigate multi-temporal land surface temperature (LST) changes of Konya Closed Basin (KCB) in Turkey using remotely sensed data. KCB is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six Landsat-5 TM images selected from the 1984- 2011 period were used in the analysis. A real-time field work was performed during the overpass of Landsat-5 satellite on 21/08/2011 over Salt Lake to collect coordinated temperature measurements using a handheld GPS and thermal infrared thermometer. All satellite images were geometrically and radiometrically corrected to relate the image data with in-situ measurements. Thematic LST images were used to evaluate the conditions over the region between 1984 and 2011. The results show that real-time ground temperature and satellite remote sensing data were in good agreement with correlation coefficient (R2) values of 0.94. The remotely sensed and processed satellite images and resulting thematic indices maps show that dramatic land surface temperature changes occurred (about 2°C) in the KCB from 1984 to 2011. Analysis of climatic data supports this finding. Air temperatures and pan evaporation had significant upward trends from 1984 to 2011. Analysis conducted using both LST and climatic data prove that the basin has been experiencing drought in recent years. It is suggested that the use of water supplies, especially ground water should be controlled taking into account particularly summer drought impacts over the basin.

Kaynakça

  • Avdan, U., Jovanovska, G., (2016) Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data, Journal of Sensors, vol. 2016, Article ID 1480307, 8 pages,. 2016. doi:10.1155/2016/1480307.
  • Bastiaanssen, W. G. M. and Menenti, M. (1998). A remote sensing surface energy balance algorithms for land (SEBAL) 1. Formulation. Journal of Hydrology, 212, 198–212.
  • Brunetti, M., Maugeri, M.,Nanni, T. (2000). Long-Term Trends in Extreme Precipitation Events over the Conterminous United States and Canada. Theoratical and Applied Climatology, 65, 165-175.
  • Cai, G., Xue, Y., Hu, Y., Guo, J., Wang, Y. and Qi, S. (2007). Quantitative study of net radiation from MODIS data in the lower boundary layer in Poyang Lake area of Jiangxi Province, China. International Journal of Remote Sensing, 28, 4381-4389.
  • Chander, G., Markham, B.L., Helder, D.L., (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113, 893–903.
  • Chen, Y.H., Li, X.B., Li, J., Shi, P.J. and Dou, W., (2005). Estimation of daily evapotranspiration using a two-layer remote sensing model. International Journal of Remote Sensing, 26, 1755–1762.
  • Christóbal, J., Ninyerola, M.Andpons, X., (2008). Modeling air temperature through a combination of remote sensing and GIS data. Journal of Geophysical Research, 113, D13106 doi:10.1029/2007JD009318.
  • Coll, C., Caselles, V., Galve, J.M. (2005). Ground measurements for the validation of land surface temperatures derived from AATSR and MODIS data. Remote Sensing of Environment, 97, 288-300.
  • Coll, C., Galve, J.M., Sánchez, J.M., Caselles, V., (2010). Validation of landsat-7/ETM+ thermal-band calibration and atmospheric correction with ground-based measurements. IEEE Transactions on Geoscience and Remote Sensing, 48, 547–555.
  • Dash, P., Göttsche, F.M., Olesen,F.S., Andfischer, H., (2002). Land surface temperature and emissivity estimation from passive sensor data: theory and practicecurrent trends. International Journal of Remote Sensing, 23, 2563–2594.
  • Dogdu, M.S., M. M. Toklu,C., Sağnak, 2007, “Examination of Precipitation and Groundw ater Level Values in Konya Closed Basin”,First Turkish Climate Change Congress, (in Turkish), pp. 394–401. 11-12 April 2007, İstanbul.
  • Du,Y., J. Cihlar, J. Beaubien, and R. Latifovic, (2001). “Radiometric Normalization, Compositing, and Quality Control for Satellite High Resolution Image Mosaics over Large Areas,” IEEE Transactions on Geoscience and Remote Sensing, 39, 623-634. [doi:10.1109/36.911119].
  • Durduran, S. S. (2010). Coastline change assessment on water reservoirs located in the Konya Basin Area, Turkey, using multitemporal landsat imagery. Environmental monitoring and assessment, 164(1-4), 453-461.
  • Florio, E.N., Lele, S.R., Chi Chang, Y., Sterner,R. and Glass, G.E., (2004). Integrating AVHRR satellite data and NOAA ground observations to predict surface air temperature: a statistical approach. International Journal of Remote Sensing, 25, 2979-2994.
  • Gillespie, A., Rokugawa, S., Matsunaga, T., Cothern, J.S., Hook,S., Andkahle, A.B., (1998). A temperature and emissivity separation algorithm for Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) images. IEEE Transaction on Geoscience and Remote Sensing, 36, 1113–1126.
  • Jiang, L. and Islam, S. (2001). Estimating of surface evaporation map over southern Great Plains using remote sensing data. Water Resources Research, 37, 329–340.
  • Joshi, J. P., & Bhatt, B. (2012). Estimating temporal land surface temperature using remote sensing: A study of Vadodara urban area, Gujarat. International Journal of Geology, Earth and Environmental Sciences, 2(1), 123- 130.
  • Kendall, M. G. (1975). Rank Correlation Methods. Griffin, London.
  • Kim, K., Jezek, K. C. and Liu, H. (2007). Orthorectified image mosaic of Antarctica from 1963 Argon satellite photography: image processing and glaciological applications, International Journal of Remote Sensing, 28, 5357-5373.
  • Kundzewicz, Z. W.,Robson, A. J. (2004). Change detection in hydrological records: review of methodology. Hydrological Sciences Journal, 49, 7-19.
  • Kustas,W.P. and Norman, J.M. (1999). Evaluation of soil and vegetation heat flux predictions using a simple twosource model with radiometric temperatures for partial canopy cover. Agricultural and Forest Meteorology, 94, 13–29.
  • Mann, H. B. (1945). Non-Parametric tests against trend. Econometrica, 13, 245-259.
  • Nichol, J.E. and Wong, M.S., (2008). Spatial variability of air temperature and appropriate resolution for satellitederived air temperature estimation. International Journal of Remote Sensing, 29, 7213-7223.
  • Niedźwiedź, T., Twardosz, R., Walanus, A. (2009). Long-term variability of precipitation series in east central Europe in relation to circulation patterns. Theoretical and Applied Climatology, 98, 337-350.
  • Markham, B.L., and Barker, J.L. (1986). Landsat MSS and TM post-calibration dynamic rangers, exoatmospheric reflectance and at-satellite temperatures. EOSAT Landsat Tech. Notes, August, 1986.
  • Norman, J.M., Kustas, W.P. and Humes, K.S. (1995). Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature. Agriculture and Forest Meteorology, 77, 263-293.
  • Orhan, O., Ekercin, S., Dadaser-Celik, F., (2014) Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area, Turkey, The Scientific World Journal, vol. 2014, Article ID 142939, 11 pages. doi:10.1155/2014/142939
  • Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). Assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization.International Journal of Remote sensing, 19, 1663-1681.
  • Partal, T.,Kahya, E. (2006). Trend analysis in Turkish precipitation data. Hydrological Processes, 20, 2011- 2026.
  • Qin, Z.H. and Karnieli, A. (1999). Progress in the remote sensing of land surface temperature and ground emissivity using NOAA-AVHRR data. International Journal of Remote Sensing, 20, 2367–2393.
  • Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of American Statistical Association, 39, 1379-1389.
  • Sobrino, J.A. and Raissouni, N. (2000). Towardremotesensing methods for land cover dynamic monitoring: application to Morocco, International Journal of Remote Sensing, vol.21, no. 2, pp. 353–366.
  • Sobrino, J.A., Jimenez-Munoz, J. C., Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 90, 434-440.
  • Sobrino, J.A., Jiménez-Muñoz, J.C., Sòria, G., Romaguera, M., Guanter, L., Moreno, J., Martínez, P., (2008). Land surface emissivity retrieval from different VNIR and TIR sensors. IEEE Transactions on Geoscience and Remote Sensing, 46, 316–327.
  • Srivastava, P.K., Majumdar, T.J., Bhattacharya, A.K. (2009). Surface temperature estimation in Singhbhum Shear Zone of India using Landsat-7 ETM+ thermal infrared data. Advances in Space Research, 43, 1563- 1574.
  • Su, Z., (2002). The surface energy balance system (SEBS) for estimation of turbulent heat fluxes. Hydrology and Earth System Science, 6, 85–99.
  • Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A. Zhao, S., (2015). An improved mono-window algorithm for land surface temper-ature retrieval from landsat 8 thermal infrared sensor data, Remote Sensing, vol. 7, no. 4, pp. 4268–4289.
Toplam 37 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Osman Orhan 0000-0002-1362-8206

Filiz Dadaser-celik 0000-0003-3623-7723

Semih Ekercin 0000-0002-9458-2261

Yayımlanma Tarihi 1 Şubat 2019
Yayımlandığı Sayı Yıl 2019 Cilt: 4 Sayı: 1

Kaynak Göster

APA Orhan, O., Dadaser-celik, F., & Ekercin, S. (2019). Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey. International Journal of Engineering and Geosciences, 4(1), 16-27. https://doi.org/10.26833/ijeg.417151
AMA Orhan O, Dadaser-celik F, Ekercin S. Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey. IJEG. Şubat 2019;4(1):16-27. doi:10.26833/ijeg.417151
Chicago Orhan, Osman, Filiz Dadaser-celik, ve Semih Ekercin. “Investigating Land Surface Temperature Changes Using Landsat-5 Data and Real-Time Infrared Thermometer Measurements at Konya Closed Basin in Turkey”. International Journal of Engineering and Geosciences 4, sy. 1 (Şubat 2019): 16-27. https://doi.org/10.26833/ijeg.417151.
EndNote Orhan O, Dadaser-celik F, Ekercin S (01 Şubat 2019) Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey. International Journal of Engineering and Geosciences 4 1 16–27.
IEEE O. Orhan, F. Dadaser-celik, ve S. Ekercin, “Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey”, IJEG, c. 4, sy. 1, ss. 16–27, 2019, doi: 10.26833/ijeg.417151.
ISNAD Orhan, Osman vd. “Investigating Land Surface Temperature Changes Using Landsat-5 Data and Real-Time Infrared Thermometer Measurements at Konya Closed Basin in Turkey”. International Journal of Engineering and Geosciences 4/1 (Şubat 2019), 16-27. https://doi.org/10.26833/ijeg.417151.
JAMA Orhan O, Dadaser-celik F, Ekercin S. Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey. IJEG. 2019;4:16–27.
MLA Orhan, Osman vd. “Investigating Land Surface Temperature Changes Using Landsat-5 Data and Real-Time Infrared Thermometer Measurements at Konya Closed Basin in Turkey”. International Journal of Engineering and Geosciences, c. 4, sy. 1, 2019, ss. 16-27, doi:10.26833/ijeg.417151.
Vancouver Orhan O, Dadaser-celik F, Ekercin S. Investigating land surface temperature changes using Landsat-5 data and real-time infrared thermometer measurements at Konya Closed Basin in Turkey. IJEG. 2019;4(1):16-27.

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