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STUDY OF THE RELATIONSHIPS BETWEEN URBAN LAND USE MOSAIC AND LAND SURFACE TEMPERATURE: CASE STUDY OF YAZD CITY

Zareie, Sajad, Panidi, Evgeny

First published: 2016-06-28https://doi.org/10.5593/sgem2016/b22/s10.128View metrics

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Title
STUDY OF THE RELATIONSHIPS BETWEEN URBAN LAND USE MOSAIC AND LAND SURFACE TEMPERATURE: CASE STUDY OF YAZD CITY
Authors
Zareie, Sajad, Panidi, Evgeny
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 16th International Multidisciplinary Scientific GeoConference SGEM2016, Informatics, Geoinformatics and Remote Sensing
Publisher
Stef92 Technology
Year
2016
Pages
1003-1010
ISSN
1314-2704
ISBN
978-619-7105-59-9
Language
en
Publication type
Conference Paper
References26

  1. Chander G., Markham B. Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, Issue 11, pp. 2674-2677, 2003.

  2. Eckert S., Hüsler F., Linigera H., Hodela E. Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia. Journal of Arid Environments, Vol. 113, pp. 16-28, 2015. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org 16th International Multidisciplinary Scientific GeoConference SGEM 2016

  3. Fu B., Burgher I. Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater. Journal of Arid Environments, Vol. 113, pp. 59- 68, 2015.

  4. Guo G., Wu Z., Xiao R., Chen Y., Liu X., Zhang X. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape and Urban Planning, Vol. 135, pp. 1-10, 2015.

  5. Mao D., Wang Z., Luo L., Ren C. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation, Vol. 18, pp. 528- 536, 2012.

  6. Salisbury J.W., D'Aria D.M. Emissivity of terrestrial materials in the 8- 14 μm atmospheric window. Remote Sensing of Environment, Vol. 42, Issue 2, pp. 83-106, 1992.

  7. Salisbury J.W., D'Aria, D.M. Emissivity of terrestrial materials in the 3- 5 μm atmospheric window. Remote Sensing of Environment, Vol. 47, Issue 3, pp. 345-361, 1994.

  8. Schultz P.A., Halpert M.S. Global correlation of temperature, NDVI and precipitation. Advances in Space Research, Vol. 13, Issue 5, pp. 277-280, 1993.

  9. Sobrino J.A., Jiménez-Muñoz J.C., Paolini L. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment. Vol. 90, Issue 4, pp. 434-440, 2004.

  10. Story M., Congalton, R.G. Accuracy assessment: A user's perspective. Photogrammetric Engineering and Remote Sensing, Vol. 52, pp. 397−399, 1986.

  11. Wei Li, Saphores J.-D.M., Gillespie T.W. A comparison of the economic benefits of urban green spaces estimated with NDVI and with high-resolution land cover data. Landscape and Urban Planning, Vol. 133, pp. 105-117, 2015.

  12. Weng Q., Lu D., Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, Vol. 89, Issue 4, pp. 467-483, 2004.

  13. Zheng B., Myint S.W., Thenkabail P.S., Aggarwal R.M.. A support vector machine to identify irrigated crop types using time-series Landsat NDVI data. International Journal of Applied Earth Observation and Geoinformation, Vol. 34, pp. 103-112, 2015. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

  14. Chander G., Markham B. Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing, Vol. 41, Issue 11, pp. 2674-2677, 2003.

  15. Eckert S., Hüsler F., Linigera H., Hodela E. Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia. Journal of Arid Environments, Vol. 113, pp. 16-28, 2015. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org 16th International Multidisciplinary Scientific GeoConference SGEM 2016

  16. Fu B., Burgher I. Riparian vegetation NDVI dynamics and its relationship with climate, surface water and groundwater. Journal of Arid Environments, Vol. 113, pp. 59- 68, 2015.

  17. Guo G., Wu Z., Xiao R., Chen Y., Liu X., Zhang X. Impacts of urban biophysical composition on land surface temperature in urban heat island clusters. Landscape and Urban Planning, Vol. 135, pp. 1-10, 2015.

  18. Mao D., Wang Z., Luo L., Ren C. Integrating AVHRR and MODIS data to monitor NDVI changes and their relationships with climatic parameters in Northeast China. International Journal of Applied Earth Observation and Geoinformation, Vol. 18, pp. 528- 536, 2012.

  19. Salisbury J.W., D'Aria D.M. Emissivity of terrestrial materials in the 8- 14 μm atmospheric window. Remote Sensing of Environment, Vol. 42, Issue 2, pp. 83-106, 1992.

  20. Salisbury J.W., D'Aria, D.M. Emissivity of terrestrial materials in the 3- 5 μm atmospheric window. Remote Sensing of Environment, Vol. 47, Issue 3, pp. 345-361, 1994.

  21. Schultz P.A., Halpert M.S. Global correlation of temperature, NDVI and precipitation. Advances in Space Research, Vol. 13, Issue 5, pp. 277-280, 1993.

  22. Sobrino J.A., Jiménez-Muñoz J.C., Paolini L. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment. Vol. 90, Issue 4, pp. 434-440, 2004.

  23. Story M., Congalton, R.G. Accuracy assessment: A user's perspective. Photogrammetric Engineering and Remote Sensing, Vol. 52, pp. 397−399, 1986.

  24. Wei Li, Saphores J.-D.M., Gillespie T.W. A comparison of the economic benefits of urban green spaces estimated with NDVI and with high-resolution land cover data. Landscape and Urban Planning, Vol. 133, pp. 105-117, 2015.

  25. Weng Q., Lu D., Schubring J. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, Vol. 89, Issue 4, pp. 467-483, 2004.

  26. Zheng B., Myint S.W., Thenkabail P.S., Aggarwal R.M.. A support vector machine to identify irrigated crop types using time-series Landsat NDVI data. International Journal of Applied Earth Observation and Geoinformation, Vol. 34, pp. 103-112, 2015. 16th International Multidisciplinary Scientific GeoConference SGEM2016 www.sgem.org

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