Investigation of the Relationship between Land Surface Temperature with Vegetation and Surface Moisture in the Land Use of Zahak Area of Sistan Plain Using Landsat Satellite Images

Document Type : Original Article


1 Ph.D. Student in Desert Management and Control, Faculty of Natural Resources and Desert Studies, Yazd University

2 Associate Prof. of Desert Management and Control, Faculty of Natural Resources and Desert Studies, Yazd University

3 Assistant Prof. of Desert Management and Control, Faculty of Natural Resources and Desert Studies, Yazd University


Land surface temperature is considered a key parameter in the physic processes of land surface at all scales of local to global. In this study, the relationship between land surface temperature with vegetation and soil surface moisture in land uses of Zahak plain of Sistan area was investigated. In order to, Landsat TM (1987), TM (2001) and OLI (2018) satellite imagery were used. After the preprocessing and image processing steps, the extraction of land use maps was performed based on the monitored classification method and through maximum probability algorithm for a period of 30 years. Also, land surface temperature was evaluated statistically by separate window method and the relationship between land surface temperature with vegetation and soil moisture. The results showed that the accuracy of classification by maximum probability method through geomorphic facts data, TM and OLI images in terms of kappa coefficient of 0.89, 0.95 and 0.84, respectively, based on the overall accuracy of 91.8, 96.45 and 87.89% was obtained. During 1987, 2001 and 2018, average of the land surface temperature indices were 38.13, 45.73 and 41.14 ° C, the normalized difference vegetation index was -0.11, -0.13 and -0.16, and the normalized difference moisture index was estimated 0.64, 0.63 and 0.58. The relationship between land surface temperature and normalized difference of vegetation index was no correlative. The correlation between land surface temperature and the normalized difference of humidity index was also inverted and negative. Plant regeneration and growth was decreased owing to factors including hydrological drought and Climatic conditions due to reduced rainfall, rising air temperature and Dust storms. Therefore, due to the lack of suitable vegetation, vegetation is not effective in reducing the surface temperature of the study area.


Agam, N., Kustas, W.P., Anderson, M.C., Li, F., Neale, C.M.U., 2007, A Vegetation Index Based Technique for Spatial Sharpening of Thermal Imagery, Remote Sensing Environment, 107: 545-558.
Alavipanah, S. K., 2018, Thermal Remote Sensing and its Application in the Earth Sciences, University of Tehran Press, Tehran.
Chi, Y., Sun, J., Sun, Y., Liu, S., Fu, Z., 2020, Multi-Temporal Characterization of Land Surface Temperature and its Relationships with Normalized Difference Vegetation Index and Soil Moisture Content in the Yellow River Delta, China, Global Ecology and Conservation, 23: 1-16.
Comprehensive Consulting Engineers of Iran, 2004, Comprehensive Studies on Desertification and Coping with Wind Erosion in Sistan plain- Surface Water Resources (Hydrology), Forests, Rangelands and Watershed Management Organization.
Das,S., Angadi, D., 2020, Land use-land cover (LULC) Transformation and its Relation with Land Surface Temperature Changes: A Case Study of Barrackpore Subdivision, West Bengal, India, Remote Sensing Applications: Society and Environment, 19: 1-28.
Ghorbnnia Kheybari, V., Mirsanjari, M. M., Liaghati, H., Armin, M., 2017, Land Surface Temperature Estimation of Land Use and land Cover in Dena Country Using Single Window Algorithm and Data of Landsat 8 Satellite, Environmental Sciences, 15: 55-74.
Herb, W.R., Janke, B., Mohseni, O., Stefan, H.G., 2008, Ground Surface Temperature Simulation for Different Land Covers, Journal of Hydrology, 356: 327-343.
Hereher, M., 2017, Effect of Land Use/Cover Change on Land Surface Temperatures – The Nile Delta, Egypt, Journal of African Earth Sciences, 126: 75-83.
Khazaei, S., Raeini Sarjaz, M., Valizadeh, E., Ghorbani, Kh., 2017, Estimation of Surface Soil Moisture Using Vegetation and Thermal Indices from MODIS Images (Case study: Gonbad-e Qavus), Iranian Journal of Irrigation and Drainage, 11: 151-162.
Kaviani, A., Sohrabi, T., Daneshkar Araste, P., 2013, Estimation of Land Surface Temperature Using NDVI in MODIS and Landsat ETM+ Imageries, Journal of Agricultural Meteorology, 1: 14-25.
Khorchani, M., Vicente-Serrano, S.M., Azorin-Molina, C., Garcia, M., Martin-Hernandez, N., Pena-Gallardoa, M., El Kenawy, A., Dominguez-Castro, F., 2018, Trends in LST over the Peninsular Spain as Derived from the AVHRR Imagery Data, Global and Planetary Change, 166: 75-93.
Owen, T.W., Carlson, T.N., Gillies, R.R., 1998, An Assessment of Satellite Remotely Sensed Land Cover Parameters in Quantitatively Describing the Climatic Effect of Urbanization, International Journal of Remote. Sensing, 19:1663-1681.
Pirnazar, M., Zandkarimi, A., 2015, Application Guide for ENVI Software and Satellite Image Processing, Nagous Publication, Tehran.
Reutter, H., Olesen, F. S., Fischer, H., 1994, Distribution of the Brightness Temperature of Land Surfaces Determined from AVHRR Data, International Journal of Remote Sensing, 15: 95-104.
Rouse, J., Haas, R., Schell, J., Deering, D., Harlan, J., 1974, Monitoring the Vernal Advancements and Retrogradation (Green Wave Effect) of Natural Vegetation, NASA/GSFC,Greenbelt, MD, USA, Final Report: 1–137.
Sommers, L.E., Gilmour, C.M., Wildung, R.E., Beck, S.M, 1981, The Effect of Water Potential on Decomposition Processes in Soils, Water Potential Relations in Soil Microbiology, 9:97-117.
Townshend, J.R.G., Justice, C.O., 2007, Analysis of the Dynamics of African Vegetation Using the Normalized Difference Vegetation Index. International Journal of Remote Sensing, 7: 1435–1445.
Urqueta, H., Jodar, J., Herrera, C., Wilke, H.G., Medina, A., Urrutia, J., Custodio, E., Rodríguez, J., 2018, Land Surface Temperature as an Indicator of the Unsaturated Zone Thickness: a Remote Sensing Approach in the Atacama Desert, Science of Total Environment, 612:1234-1248.
Vali, A., Ranjbar, A., Mokarram, M., Taripanah, F., 2019, An Investigation of the Relationship between Land Surface Temperatures, Geographical and Environmental Characteristics, and Biophysical Indices from Landsat Images, RS & GIS for Natural Resources, 10: 35-58.
Wan, Z., Zhang, Y., Ma, X., King, M.,  Myers, J., Li, X, 1999, Vicarious Calibration of the Moderate Resolution Imaging Spectro-radiometer Airborne Simulator thermal-infrared channels, Applied Optics, 38: 6294-6306.
Wei, L., Jean-Daniel, M.S., Thomas, W.G., 2015, Acomparison of the Economic Benefits of Urban Green Spaces Estimated with NDVI and with High-Resolution Land Cover Data, Landscape Urban Planning, 133: 105-117.
Weng, Q., Lu, D., Schubring, J., 2004, Estimation of  Land Surface Temperature- Vegetation Abundance Relationship for Urban Heat Island Studies. Remote Sensing and Environmrnt, 89:  467–483.
Wilson, E., Sader, S., 2002, Detection of Forest Harvest Type Using Multiple Dates of Landsat TM Imagery. Remote Sensing Environment, 80: 385–396.
Yue, W., Xu, J., Tan, W., Xu, L., 2007, The Relationship Between Land Surface Temperature and NDVI with Remote Sensing: Application to Shanghai Landsat 7 ETM+ Data, International Journal of Remote Sensing, 28: 3205–3226.
Zhang, F., Kung, H., Johnson, V. C., Maimaitiyiming, M., Zhou, M., Wang, J., 2016, Dynamics of Land Surface Temperature (LST) in Response to Land Use and Land Cover (LULC) Changes in the Weigan and Kuqa River Oasis, Xinjiang, China, Arab Journal Geosciences, 9:1-14