Investigation of Land Surface Temperature Trends Relative to Land Use Changes in Dust Sources of South East Ahwaz Using Landsat 8 Satellite Data

Document Type : Research Paper

Authors

Department of Soil Sciences, Faculty of Agriculture, University of Khuzestan Agricultural Sciences and Natural Resources, Mollasani, Iran.

Abstract

Dust storms are known as one of the most important environmental hazards that affects various parts of the world. Following the intensification of dust storms in Khuzestan province, the internal sources of dust storms in Khuzestan province have been introduced in form of seven areas that southeast of Ahwaz was identified as the No.4 internal dust sources with the first priority of control and rehabilitation practices and the necessary executive measures for land reclamation in this region, including: management practices, biological operation and water distribution were on the agenda. The aim of this study was to investigate the land surface temperature (LST) changes and its relationship with land use changes as effective factors in creating a dust sources in south east Ahwaz. For this purpose, the Landsat 8 satellite data during the (2016-2020) were used and the land use maps of the study area were extracted using support vector machine (SVM) method and Split-Window method was used to extract the land surface temperature (LST) of the study area. The results showed that the area of barren land has been increased from 98.97% in 2016 to 99.81% in 2017 and has been reduced to 76.68% in 2020. The lowest areas of moderate vegetation, good vegetation and water bodies were corresponded to year 2017 which were equal to 0.05%, 0.01% and 0.03%, respectively. The highest areas of moderate vegetation and good vegetation were corresponded to year 2020 which were equal to 13.29% and 3.26%, respectively. The highest area of water body was corresponded to year 2019 which was equal to 7.73%. The results of mean LST estimation during 2016-2017 period showed 3.85℃ increase (from 32.62℃ to 36.47℃) and during 2017-2020 period showed 10.31℃ decrease, which reached to 26.16 ℃ in 2020. This trend has been affected by the land use changes, improved rainfall and the positive effects of modified measures taken to restore the vegetation of the study area.

Keywords

References

Abdul Athick, A. S. M., Shankar, K., & Raja Naqvi, H. (2019). Data on time series analysis of land surface temperature variation in response to vegetation indices in Twelve Wereda of Ethiopia using mono window, split window algorithm and spectral radiance model. Journal of Data in Brief, 27, 1-12.
Ahmadi, B., Ghorbani, A., Safarrad, T., & Sobhani, B. (2015). Evaluation of surface temperature in relation to land use/cover using remote sensing data. Journal of RS & GIS for Natural Resources, 6(1), 61-77. (In Farsi)
Alemu, M. M. (2019). Analysis of spatio-temporal land surface temperature and normalized difference vegetation index changes in the Andassa Watershed, Blue Nile Basin, Ethiopia. Journal of Resources and Ecology, 10(1), 77-86.
Asghari Sarasekanrood, S., & Emami H. (2019). Monitoring the earth surface temperature and relationship land use with surface temperature using of oli and tirs images. Researches in Geographical Sciences, 19(53), 195-215. (In Farsi)
Azhdari, A., Heidarian, P., Fathtabar, S., Salehi, H., & Fuladi, A. (2017). Prioritizing the dust sources in khuzestan province. Ministry of Industry, Mine and Trade Geological Survey of Iran South West Regional Center, pp. 1-66. (In Farsi)
Azhdari A., Heidarian, P., Joudaki, M., Darvishi Khatoni, J., & Shahbazi R. (2015). Recognized dust sources in khuzestan province. Ministry of Industry, Mine and Trade Geological Survey of Iran South West Regional Center, pp. 1-73. (In Farsi)
Bayat, R., Iranmanesh, F., & Kazemi, R. (2021). Investigating effect of dust storms on the vegetation of Shadegan Wetland. Environment Water Engineering, 7(1), 1–13. (In Farsi)
Bevel, A., & Korme, T. (2020). Monitoring land surface temperature in Bahir Dar city and its surrounding using landsat images. The Egyptian Journal of Remote Sensing and Space Sciences, 23(3), 371-386.
Choudhury, D., Kalikinkar, D., & Arijit, D. (2019). Assessment of land use land cover changes and its impact on variations of land surface temperature in Asansol-Durgapur development region. The Egyptian Journal of Remote Sensing and Space Sciences, 22(2), 203–218.
Das, N., and Angadi, D. P. (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, 10322.
 Das, N., Mondal, p., Sutradhar, S., & Ghosh, R. (2020). Assessment of variation of land use/land cover and its impact on land surface temperature of Asansol subdivision. The Egyptian Journal of Remote Sensing and Space Sciences, 24(1), 131-149.
Ebrahimi, A., Motamedvaziri, B., Nazemosadat, S. M. J., & Ahmadi H. (2020). Assessing the relationship between land surface temperature with vegetation and water area change in Arsanjan country, Iran. Journal of RS & GIS for Natural Resources, 11(4), 65-86. (In Farsi)
Entezari, A., Amir Ahnadi, A., Aliabadi, K., Khosravian, M., & Ebrahimi M. (2016). Monitoring land surface temperature and evaluating change detection land use (case study: Parishan Lake Basin). Journal of Hydrogeomorphology, 3(8), 113-139. (In Farsi)
Fayaz, M. (2017). The combat dust project in internal dust sources of Khuzestan province, final report, dust surces of south-east ahwaz. Research Lnstitute of Forestes and Ranglands, pp.1-263. (In Farsi)
Ghorbani, M., Nazari Katooli, M., & Aslani, S. (2020). Investigating the relationship between agronomic change and surface temperature using remote sensing data (case study: zabol). Geographical Planning of Quarterly Journal, 10(37), 143-156. (In Farsi)
Ghorbannia Kheybari, V., Mirsanjari, M., Liaghati, H., & Armin M. (2017). Estimating land surface temperature of land use and land cover in Dena country using single window algorithm and landsat 8 satellite data. Environmental Sciences, 15(2), 55-74. (In Farsi)
Govil, H., Guha, S., Diwan, P., Gill, N., & Dey, A. (2020). Analyzing linear relationships of lst with ndvi and mndisi using various resolution levels of landsat 8 oli and tirs data. Data Management, Analytics and Innovation, 1, 171-184.
Guha, S., & Govil, H. (2020). An assessment on the relationship between land surface temperature and normalized difference vegetation index. Environment, Development and Sustainability, 23, 1944-1963.
He, J., Zhao, W., Li, A, Wen, F., & Yu, D. (2019). The impact of the terrain effect on land surface temperature variation based on Landsat-8 observations in mountainous areas. International Journal of Remote Sensing, 40 (5-6), 1808-1827.
Huete, A.R., Liu, H.Q., Batchily, K., & Vanleeuwen, W. (1997). A comparison of vegetation indices global set of TM images for EOS-MODIS. Remote Sensing of Environment, 59, 440–451.
Huete, A. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295–309.
Jamali, Z., Ownegh, M., & Salman Mahini, A. R. (2019). Investigation the relationship between surface temperature and land use and normalized difference vegetation index in Gorgan plain. The Journal of Spatial Planning, 23(3), 175-194. (In Farsi)
Kaffash, M., & Sanaei Nejad, S. H. (2020). Fusion of MODIS and Landsat-8 land surface temperature images using spatio-temporal image fusion model. Iranian Journal of Soil and Water Research, 15(3), 763-773. (In Farsi)
Kakehmami, A., Ghorbani, A., Asghari Sarasekanrood, S., Ghale, E., & Ghafari, S. (2020). Study of the relationship between land use and vegetation changes with the land surface temperature in Namin County. Journal of RS & GIS for Natural Resources, 11(2), 27-48. (In Farsi)
Khandelwal, S., Goyal, R., Nivedita, K., & Aneesh, M. (2018). Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India. The Egyptian Journal of Remote Sensing and Space Sciences, 21, 87–94.
Kianisalmi, E., & Ebrahimi, A. (2019). Assessing the impact of urban expansion and land cover changes on land surface temperature in Shahrekord city. Journal of RS & GIS for Natural Resources, 9(4), 102-118. (In Farsi)
Liu, L., & Yuanzhi, Z. (2011). Urban heat island analysis using the landsat tm data and aster data: a case study in hong kong. Remote Sensing, (3), 1535-1552.
Liu, H., Zhang, Y., & Zhang, X. (2018). Monitoring vegetation coverage in Tongren from 2000 to 2016 based on Landsat 7 ETM+ and Landsat 8. Annals of the Brazilian Academy of Sciences, 90(3), 2721-2730.
Mckee, T. B., Doesken N.J., and Kleist J. (1993). The relationship of drought frequency and duration to time scales. Proceeding of the Eighth Conference of Applied Climatology, 17-22 jan., Anaheim, California, pp. 1-6.
Mijani, N., Hamzeh, S., & Karimi Firozjaei, M. (2019). Quantifying the effect of surface parameters and climatic conditions on land surface temperature using reflective and thermal remote sensing data. Journal of RS & GIS for Natural Resources, 10(1), 36-59. (In Farsi)
Nadizadeh Shorabeh, S., Hamzeh, S., Kiavarz, M., & Afsharipoor, S. K. (2018). Effects of spatial and temporal land use changes and urban development on the increase of land surface temperature using landsat multi-temporal images (case study: Gorgan city). Geographical Urban Planning Research, 6(3), 545-568. (In Farsi)
Nikam, B. R., Ibragimov, F., Chouksey, A., Vaibhav, G., & Aggarwal, S.P. (2016). Retrieval of land surface temperature from landsat 8 tirs for the command area of mula irrigation project. Environmental Earth Sciences, 75, 1-17.
Norouzi, A., Ansari, M. R., Moazami, M., & Asghari Pour Dasht Bozorg, N. (2019). Land Use Changes in Dust Sources of South and South-East Ahwaz. Journal of Water and Soil Science (Science and Technology of Agriculture and Natural Resources), 23(3), 341-354. (In Farsi)
Qin, Z., and Karnieli, A. (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.
Rahdari, V., Soffianian, A., Khajaldin., S. J., & Maleki Najafabadi, S. (2014). Identification of Satellite image ability for vegetation cover crown percentage mapping in arid and semi arid region (case study: Mouteh wild life sanctuary). Journal of environmental Science and Technology, 4(4), 43-54. (In Farsi)
Rajeshwari, A., & Mani N. D. (2014). Estimation of land surface temperature of Dindigul district using landsat 8 data. International Journal of Research in Engineering and Technology, 3(5), 122-126.
Ranjbar, A., Valia, A., Mokarramb, M., & Taripanahc. (2020). Analyzing of the spatio-temporal changes of vegetation and its response to environmental factors in north of Fars province, Iran. Iranian Remote Sensing & GIS, 11(4), 61-82. (In Farsi)
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(14), 1-19.
Rusta, Z., Monavvari, S. M., Darvishi, M., & Falahati, F. (2012). Application of remote sensing and geographic information system in extraction of Shiraz land use maps. Town and Country Planning, 4(6), 149-164. (In Farsi)
Sekertekin, A., & Zadbagher, E. (2021). Simulation of future land surface temperature distribution and evaluating surface urban heat island based on impervious surface area. Ecological Indicators, 122, 1-11.
Thakur, P.K., & Gosavi V. E. (2018). Estimation of Temporal Land surface temperature using thermal remote sensing of landsat-8 (oli) and landsat-7 (etm+): a study in Sainj river basin, himachal pradesh, India. Society for Environment and Development, 13, 29-45.
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8, 127–150.
Ullah, S., Ahmad, K., Sajjad, R. U., Abbasi, A. M., Nazzer, A., & Tahir, A. A. (2019). Analysis and simulation of land cover changes and their impacts on land surface temperature in a lower Himalayan region. Journal of Environmental Management, 245, 348-357.
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. Journal of RS & GIS for Natural Resources, 10(3), 35-58. (In Farsi)
Wang, M., He, G., Zhang, Z., Wang, G., Wang, Z., Yin, R., Cui, S., Wu, Z., & Cao, X. (2019). A radiance-based split-window algorithm for land surface temperature retrieval: Theory and application to MODIS data. International Journal of Applied Earth Observation and Geoinformation, 76, 204–217.
Wang, R., & Murayama, Y. (2020). Geo-simulation of land use/cover scenarios and impacts on land surface temperature in sapporo, japan. Sustainable Cities and Society, 63, 1-11.
Weng, Q., Karimi firozjaei, M., Kiavarz, M., Alavipanah S. K., & Hamzeh, S. (2019). Normalizing land surface temperature for environmental parameters in mountainous and urban areas of a cold semi-arid climate. Science of the Total Environment, 650, 515-529.
Zhu, Y., Zhang, J., Zhang, Y., Qin, S., Shao, Y., & Gao, Y. (2019). Responses of vegetation to climatic variations in the desert region of northern China, Catena, 175, 27–36.
 
Iranian Journal of Soil and Water Research
Volume 52, Issue 7
October 2021
Pages 1825-1840

Files

Share

How to cite

Statistics