Quantitative assessment of spatio-temporal dynamics of land use/land cover and land surface temperature using different algorithms and landsat imagery

Document Type : Research Paper


Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Iran.



Human-induced land use land cover changes have resulted in adverse impacts on the environment at various spatial and temporal scales. Land surface temperature (LST) is an important indicator associated with strong spatio-temporal variability in complex Earth Patterns. Remote sensing is the primary source for various types of thematic data critical to land analysis, including land use data and land surface temperature changes. In this study, first, to analyze the spatial-temporal land surface temperature changes, LST maps were prepared using Radiative Transfer Equation, Single Channel Algorithm, Split Window Algorithm and Two Mono Window Algorithm. Then the performance of Land Surface Temperature (LST) retrieval methods was evaluated. Land use and land cover maps were prepared to investigate the contribution and role of each land use class on the changes of the LST.  Also, the effects Normalized Difference Vegetation Index, Normalized Difference Built-up Index and elevation on LST variability were investigated. There was a positive correlation of LST with Normalized Difference Built-up Index and a negative correlation with Normalized Difference Vegetation Index and elevation for all years. Spatio-temporal analysis shows a 6.64°C increase in LST from 1989 to 2021. The results clearly showed the moderating role of vegetation, regardless of its type, on LST. The findings of the present study serve as basic information for future studies to investigate the impact of different policies on LULC change in the region. Also, the obtained results reveal the importance of studying and examining the mentioned changes in order to achieve sustainable development.


Aboelnour, M., Engel, B., 2018. Application of remote sensing techniques and geographic information systems to analyze land surface temperature in response to land use/land cover change in Greater Cairo Region, Egypt. Journal of Geographic Information System 10: 57-88.
Almeida, C.R., Teodoro, A.C., Gonçalves, A., 2021. Study of the Urban Heat Island (UHI) using remote sensing data/techniques: A Systematic Review. Environments 8(10), 105.
Arab, N., Salmanmahiny, A., Mikaeili Tabrizi, A.R., Houet, T., 2022. Investigation and analysis of land use dynamics and its impact on urban Heat islands(Case study: Mashhad). Journal of Natural Environment 75(3), 384-398.
Chaudhuri, G., Mishra, N., 2016. Spatio-temporal dynamics of land cover and land surface temperature in Ganges-Brahmaputra delta: A comparative analysis between India and Bangladesh. Applied Geography 68, 68-83.
Cristóbal, J., Jiménez-Muñoz, J.C., Prakash, A., Mattar, C., Skoković, D., Sobrino, J.A., 2018. An improved single-channel method to retrieve land surface temperature from the Landsat-8 thermal band. Remote Sensing 10(3), 431.
Diaz, L.R., Santos, D.C., Käfer, P.S., Rocha, N.S., Costa, S.T., Kaiser, E.A., Rolim, S.B., 2021. Land surface temperature retrieval using high-resolution vertical profiles simulated by WRF model. Atmosphere 12(11), 1436.
Feng, Y., Gao, C., Tong, X., Chen, S., Lei, Z., Wang, J., 2019. Spatial patterns of land surface temperature and their influencing factors: a case study in Suzhou, China. Remote Sensing 11(2), 182.
Garcia-Santos, V., Cuxart, J., Villagrasa, D., Jiménez, M., Simó, G., 2018. Comparison of three methods for estimating Land Surface Temperature from Landsat 8-TIRS sensor data. Remote Sensing 10, 1450.
Guha, S., Govil, H., Dey, A., Gill, N., 2018. Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing 51, 667-678.
Guo, A., Yang, J., Sun, W., Xiao, X., Xia Cecilia, J., Jin, C., Li, X., 2020. Impact of urban morphology and landscape characteristics on spatiotemporal heterogeneity of land surface temperature. Sustainable Cities and Society 63, 102443.
Hulley, G.C., Ghent, D., Göttsche, F.M., Guillevic, P.C., Mildrexler, D.J., Coll, C., 2019. 3 - Land Surface Temperature. In G. C. Hulley & D. Ghent (Eds.), Taking the Temperature of the Earth.  57-127.
Imen, G., Halima, G., Djamel, A., 2022. relationship between the LULC characteristic and LST, based on remote sensing and GIS, Case study Guelma (Algeria). Romanian Journal of Geography 65(2), 203-222.
Isaya Ndossi, M., Avdan, U., 2016. Application of Open Source Coding Technologies in the Production of Land Surface Temperature (LST) Maps from Landsat: A PyQGIS Plugin. Remote Sensing 8(5), 413.
Jimenez-Munoz, J., Sobrino, J.A., 2008. Split-Window Coefficients for Land Surface Temperature Retrieval From Low-Resolution Thermal Infrared Sensors. IEEE Geoscience and Remote Sensing Letters 5(4), 806-809.
Jiménez-Muñoz, J.C., Sobrino, J.A., 2003. A generalized single-channel method for retrieving land surface temperature from remote sensing data. Journal of Geophysical Research: Atmospheres 108(D22), 4688.
Martinelli, L., Matzarakis, A., 2017. Influence of height/width proportions on the thermal comfort of courtyard typology for Italian climate zones. Sustainable Cities and Society 29, 97-106.
Mathew, A., Khandelwal, S., Kaul, N., 2017. Investigating spatial and seasonal variations of urban heat island effect over Jaipur city and its relationship with vegetation, urbanization and elevation parameters. Sustainable Cities and Society 35, 157-177.
Parvar, Z., Mohammadzadeh, M., Saeidi, S., 2022. Effects of land use and land morphology on land surface temperature: a case study for Bojnourd City, North Khorasan. Journal of RS and GIS for Natural Resources In Press.
Parvar, Z., SalmanMahini, A.R., 2023. A python-based application for retrieving Land Surface Temperature (LST) from landsat imagery. Journal of RS and GIS for Natural Resources, in Press.
Punia, M., Joshi, P.K., Porwal, M.C. 2011. Decision tree classification of land use land cover for Delhi, India using IRS-P6 AWiFS data. Expert Systems with Applications 38(5), 5577-5583.
Qin, Z., Karnieli, A., Berliner, P., 2001. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. International Journal of Remote Sensing 22(18), 3719-3746.
Rongali, G., Keshari, A.K., Gosain, A., Khosa, R., 2017. A mono-window algorithm for land surface temperature estimation from landsat 8 thermal infrared sensor data. Conference: 4th International Conference on Recent Developments in Science, Engineering & Technology (REDSET 2017), October 13–14, 2017, Goenka University, Gurgaon, New Delhi, India.
Rongali, G., Keshari, A.K., Gosain, A.K., Khosa, R., 2018. Split-Window algorithm for retrieval of Land Surface Temperature using landsat 8 thermal infrared data. Journal of Geovisualization and Spatial Analysis 2(2), 14.
Rwanga, S. and Ndambuki, J. 2017. Accuracy assessment of land use/land cover classification using remote sensing and GIS. International Journal of Geosciences 08, 611-622.
Sobrino, J.A., Jimenez-Munoz, J.C., Soria, G., Romaguera, M., Guanter, L., Moreno, J., Plaza, A., Martinez, P., 2008. Land Surface Emissivity Retrieval From Different VNIR and TIR Sensors. IEEE Transactions on Geoscience and Remote Sensing 46(2), 316-327.
Torres, P., Augusto, M., Neves, C., 2022. Value dimensions of gamification and their influence on brand loyalty and word-of-mouth: Relationships and combinations with satisfaction and brand love. Psychology & Marketing 39(1), 59-75.
Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A., Zhao, S., 2015. An Improved Mono-Window Algorithm for Land Surface Temperature Retrieval from Landsat 8 Thermal Infrared Sensor Data. Remote Sensing 7(4), 4268-4289.
Yeneneh, N., Elias, E., Feyisa, G.L., 2022. Detection of land use/land cover and land surface temperature change in the Suha watershed, North-Western highlands of Ethiopia. Environmental Challenges 7, 100523.