Analyzing the Relationship between Temporal and Spatial Changes in Daily Surface Temperature and the Spatial Pattern of Land Cover Changes in the Direction of Environmental Sustainability (Case Study: Kashan city_ Iran)

Document Type : Research Paper

Authors

1 Department of Urban Planning, Faculty of Art and Architecture, University of Guilan, Rasht, Iran

2 Department of Geography, Faculty of Humanities, Yazd University, Yazd, Iran.

3 Department of Remote Sensing and GIS, Faculty of Scinence, Agriculture and New Technology, Shiraz Branch, Islamic Azad University, Shiraz, Iran

Abstract

The world is experiencing an unprecedented flow of urbanization. Population growth and urbanization have changed land use in urban areas. One of the consequences of these changes is the increase in the temperature of the earth's surface in urban areas and the formation of a heat island. The main purpose of this research is to monitor the surface temperature of the earth and its relationship with land cover. For this purpose, Landsat 8 and 7 satellite images were taken first. Then, using the supervised classification method - maximum likelihood algorithm, the land cover map was classified into three classes of man-made land, barren land and vegetation and finally, in order to monitor the surface temperature of the earth, the surface temperature map of Kashan city was extracted using single channel algorithm. The analysis of land cover showed that man-made lands increased by 21.05 percent during the years 1385 to 1400, and barren lands and lands with vegetation (with 11.17 percent and 9.88 percent, respectively) has had a decreasing trend. The minimum temperature of the earth's surface has reached from 34.87 degrees Celsius to 42.33 degrees Celsius in 1385 and 1400, respectively. Also, during the 15-year period, the maximum temperature has increased from 59.63 degrees Celsius to 60.70 degrees Celsius. Vegetation has the lowest surface temperature in the studied years. Due to its climatic and spatial nature, the city of Kashan, like other arid and semi-arid regions of Iran, has a lower surface temperature than its surrounding environment, this phenomenon is known as urban cool islands. Moran's spatial autocorrelation analysis at the 99% confidence level showed that the surface temperature data of Kashan city are distributed in clusters. According to the Gi* index, in all the studied years, the maximum temperature belongs to barren lands.
 
Extended Abstract
1-Introduction
The rapid development of cities has had negative effects on the quality of the global environment due to extensive changes in land use and land cover. The change of land cover and land use and the development of urban and agricultural areas and deforestation have changed the regional and local temperature regime. Knowing the Earth's surface temperature significantly contributes to a wide range of geoscience issues such as urban climate, global environmental change, and the study of human-environment interaction. Therefore, investigating the relationship between land cover changes and land surface temperature (LST) is one of the important parameters in urban-regional planning, and it is necessary to plan a new and successful method to achieve better urbanization and reduce environmental effects on cities. A city should be introduced according to the spatial distribution of land surface temperature (LST).
 
2-Materials and Methods
In this study the effect of land use and land cover changes on the formation of hot and cold islands was investigated. In order to investigate the effect of different land covers in the study area on land surface temperature and land use changes over a 15-year period, images were first prepared from the website of the United States Geological Survey (www.usgs.gov). Then, using ENVI 5.3 software, pre-processing operations were performed to apply atmospheric and radiometric corrections, and using the supervised classification method and the maximum likelihood algorithm, the land cover was divided into three categories: man-made, vegetation and bare land. Then, in order to understand the effect of land cover changes on the spatial distribution of urban cool islands, the ground surface temperature was calculated using a single-channel algorithm. The satellite images of Landsat 7 and 8 sensors have been used in the period of 2006 and 2021 to check the land surface temperature of urban area. The image of Landsat 8 satellite was used to extract the land cover map from OLI sensor and TIRS1 sensor. The Landsat ETM+ sensor image was used to extract the land surface temperature and also to prepare the land cover map using visible and infrared bands to extract the land surface temperature. In order to investigate autocorrelation and spatial clustering, hot spot pattern, Moran's I and Getis-Ord GI were used.
 
3- Results and Discussion
The survey of land cover changes during the 15-year period from 2006 to 2021 shows that about 21percent has been added to the built-up area of the city. Following this increase, the extent of barren land and vegetation land has decreased by about 12 percent and 10 percent, respectively. Considering the influence of the land surface temperature on the land cover of urban areas, changes in the land cover in urban areas will cause temperature changes. The results of the study show that barren lands had the highest average temperatures (52.11 and 55.57 degrees Celsius) in both research periods. Also, the results show that during the 15-year period, the vegetation lands have the lowest average surface temperature with 46.21 and 49.62 degrees Celsius. In the areas where the change of land cover from barren and man-made lands to vegetation land has occurred, due to the effect of the greenness index on the temperature of the land surface due to the simultaneous creation of shade and humidity. In these conditions we see a decrease in temperature between 4 and 5 degrees Celsius. During the studied period, after barren lands, man-made lands had the highest temperature with an average temperature of 50.48 in 2006 and 50.34 degrees in 2021. During the day, the land surface temperature in the city center is lower than in the suburbs, and in the parts of the city center, we see urban cool islands. The outcomes of two considered spatial statistics indicated the clustering, pattern for LST of the Kashan city. In addition, there was a good agreement between the results of Getis-Ord GI statistic (hot spots spatial analysis) and the Local Moran's I statistic (spatial autocorrelation) on the spatial pattern of heat and cool clusters.
 
4- Conclusion
The results of the research show that the highest temperature of the land surface in the two studied periods is related to barren lands and the lowest surface temperature belongs to vegetation land. According to the effect of land surface temperature on the land cover of urban areas, based on the results, it can be said that there is a significant relationship between the temperature and the land cover of the region. The pattern of spatial changes in the surface temperature of Kashan city is mostly related to the pattern of spatial changes of vegetation cover and barren lands. Spatial autocorrelation analysis with local Moran indices showed that the land surface temperature in Kashan city has a spatial structure; In other words, high and low temperature cells tend to concentrate or cluster in space. Analysis of hot spots has been a clear confirmation of the clustering of cool urban islands (99% confidence level) at the man-made areas. The results of the research show the importance of planning, managing and preserving areas with vegetation and preventing them from turning into built-up and barren lands in order to maintain the environmental sustainability of urban areas.

Keywords

Main Subjects

References

Abdollahi, A. A., Khabazi, M., & Dorani, z. (2020). Modeling Land Use Change Using Perceptron Neural Network (Case Study: Lahijan City). The Journal of Spatial Planning, 24(1), 49-79 (In Persian).
Abedin, M., Ghale, E., Aghazadeh, N., & Mohamadzadeh Sheshegaran, M. (2022). Monitoring the surface temperature and studying the land use relationship with surface temperature using OLI and TM image sensors (Case study: Meshginshahr city). Journal of Applied researches in Geographical Sciences, 22(67), 375-393 (In Persian).
Ahmadi, A., Akbari, E., Jamalabadi, J., & Alemohammad, M. (2022). Impact of land use and vegetation on the formation of thermal islands Case Study: Qainat City. Journal of Applied researches in Geographical Sciences, 22(64), 79-93 (In Persian).
Ahmadi, M., Farahmand,Q. (2017). Analyzing the spatial changes of the cores of thermal islands in Urmia city, Journal of Urban Development Studies, 1(2), 37-60 (In Persian).
Alavipanah, S. K., Hashemi Darrehbadami, S., & Kazemzadeh, A. (2015). Spatial- Temporal Analysis of Urban Heat- Island of Mashhad City due to Land Use/ Cover Change and Expansion. Geographical Urban Planning Research (GUPR), 3(1), 1-17. doi:10.22059/jurbangeo.2015.54436 (In Persian).
Arabi Ali Abad, F., Zare, M., & Ghafarian Malamiri, H. (2021). Effect of land cover changes on land surface temperature in Yazd plain, Iran. The Journal of Geographical Research on Desert Areas, 9(2), 43-66. Retrieved from (In Persian).
Asadi, M., Oshnooei-Nooshabadi, A., Saleh, S. A., Habibnezhad, F., Sarafraz-Asbagh, S., & Van Genderen, J. L. (2022). Simulation of Urban Sprawl by Comparison Cellular Automata-Markov and ANN.
Asgari, A. (2013). Spatial statistics analysis with Arc gis. Tehran: Publications of Information Technology and Communications Organization of Tehran Municipality. Journal of Urban Social Geography, 6(1), 213-227 (In Persian).
Azadi Mubaraky, M., & Ahmadi, M. (2021). Investigation of urban heat islands of Tabriz metropolis using multi-time data of LANDSAT8 satellite based on hot spot analysis method. Regional Planning, 11(43), 47-63. doi:10.30495/jzpm.2021.3992 (In Persian).
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(5), 893-903.
Choudhury, D., Das, K., & Das, A. (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 Science, 22(2), 203-218.
Foroughifar, A., & Dashti, S. (2020). Land Use Changes Detection Using Satellite Images (Case study: Susa County). Physical Sacial Planning, 7(3), 101-114. doi:10.30473/psp.2020.41954.1476 (In Persian).
Ghiasvand Nanji, H., Tashayo, B., Momeni, M., & Yazdanpanah, H. (2021). Modelling the Effective Factors on Temporal and Thermal Island Distribution of Qom applying Tasseled Cap Transformation (TCP). Geography and Environmental Sustainability, 11(1), 73-91. doi:10.22126/ges.2021.5922.2322 (In Persian).
Gohain, K. J., Mohammad, P., & Goswami, A. (2021). Assessing the impact of land use land cover changes on land surface temperature over Pune city, India. Quaternary International, 575, 259-269.
Hajizade Vadeghani, B., Balist, J., & Karimi, S. (2018). Urban development locating with Fuzzy Logic, weighted linear combination and FANP Decision-Making Technique - Case study: Kashan City. Scientific- Research Quarterly of Geographical Data (SEPEHR), 27(105), 219-232. doi:10.22131/sepehr.2018.31496 (In Persian).
Halabian, A., Parvin, N., & Naghibzadeh, R. (2021). Analysis of the spatial and temporal variations in the thermal patterns of the Arak City in Iran using satellite image processing. Scientific- Research Quarterly of Geographical Data (SEPEHR), 30(119), 121-139. doi:10.22131/sepehr.2021.247885 (In Persian).
Hashemi Darebadami, S., Darvishi Boloorani, A., AlaviPanah, S. K., maleki, M., & Bayat, R. (2019). Investigation of changes in surface urban heat-island (SUHI) in day and night using multi-temporal MODIS sensor data products (Case Study: Tehran metropolitan). Journal of Applied researches in Geographical Sciences, 19(52), 113-128. doi:10.29252/jgs.19.52.113.
Hashemi Dareh Badami, S., Nouraeisefat, I., & Karimi, S., & Nazari, S. (2015). Development Trend Analysis Of Urban Heat Island Regarding Land Use/Cover Changes Using Time Series Of Landsat Images. Journal Of Rs And Gis For Natural Resources (Journal Of Applied Rs And Gis Techniques In Natural Resource Science), 6(3), 15-28 (In Persian).
Heidari, M. A., & Tavakoli, A. (2017). Analyzing of the Relationship Between Land Surface Temperature Temporal Changes and Spatial Pattern of Land Use changes. The Journal of Spatial Planning, 21(3), 119-144 (In Persian).
Imran, H. M., Hossain, A., Islam, A. K. M., Rahman, A., Bhuiyan, M. A. E., Paul, S., & Alam, A. (2021). Impact of land cover changes on land surface temperature and human thermal comfort in Dhaka City of Bangladesh. Earth Systems and Environment, 5(3), 667-693.
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.
Kafy, A.-A., Dey, N. N., Al Rakib, A., Rahaman, Z. A., Nasher, N. R., & Bhatt, A. (2021). Modeling the relationship between land use/land cover and land surface temperature in Dhaka, Bangladesh using CA-ANN algorithm. Environmental Challenges, 4, 100190.
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 and GIS for Natural Resources, 11(2), 27-48. Retrieved (In Persian).
Karimi Firozjaei, M., Kiavarz Mogaddam, M., & Alavi Panah, S. K. (2017). Monitoring and predicting spatial-temporal changes heat island in Babol city due to urban sprawl and land use changes. Journal of Geospatial Information Technology, 5(3), 123-151. doi:10.29252/jgit.5.3.123 (In Persian).
Kazemi, M., Nafarzadegan, A. R., & Mohammadi, F. (2019). Studying changes in heat islands and land uses of the Minab city using the random forest classification approach and spatial autocorrelation analysis. Journal of RS and GIS for Natural Resources, 10(4), 38-56. Retrieved from (In Persian).
Khosravi, Y., Heidari, M. A., Tavakoli, A., & Zamani, A. (2017). Analyzing of the Relationship Between Land Surface Temperature Temporal Changes and Spatial Pattern of Land Use changes. The Journal of Spatial Planning, 21(3), 119-144 (In Persian).
Liu, N., & Morawska, L. (2020). Modeling the urban heat island mitigation effect of cool coatings in realistic urban morphology. Journal of Cleaner Production, 264, 121560.
Mahmoudzadeh, H., Puyanjam, A., & Amanzadeh, F. (2020). Calculation of land surface temperature and thermal island extraction using Landsat 8 satellite imagery and separate window algorithm in Urmia. Geography and Planning, 24(73), 325-348. doi:10.22034/gp.2020.10794 (In Persian).
Maleki, M., Van Genderen, J. L., Tavakkoli-Sabour, S. M., Saleh, S. S., & Babaee, E. (2020). Land use/cover change in Dinevar rural area of West Iran during 2000–2018 and its prediction for 2024 and 2030. Geogr. Tech, 15, 93-105.
Mansourmoghaddam, M., Ghafarian Malamiri, H. R., Arabi Aliabad, F., Fallah Tafti, M., Haghani, M., & Shojaei, S. (2022c). The Separation of the Unpaved Roads and Prioritization of Paving These Roads Using UAV Images. Air, Soil and Water Research, 15, 11786221221086285.
Mansourmoghaddam, M., Ghafarian Malamiri, H. R., Rousta, I., Olafsson, H., & Zhang, H. (2022d). Assessment of Palm Jumeirah Island’s Construction Effects on the Surrounding Water Quality and Surface Temperatures during 2001–2020. Water, 14(4), 634.
Mansourmoghaddam, M., Naghipur, N., Rousta, I., & Ghaffarian, H. R. (2022b). Temporal and Spatial Monitoring and Forecasting of Suspended Dust Using Google Earth Engine and Remote Sensing Data (Case Study: Qazvin Province). Desert Management, 10(1), 77-98.
Mansourmoghaddam, M., Rousta, I., Zamani, M. S., Mokhtari, M. H., Karimi Firoozjaei, M., & Alavipanah, S. K. (2021). Study and prediction of land surface temperature changes of Yazd city: assessing the proximity and changes of land cover. Journal of RS and GIS for Natural Resources, 12(4), 1-27.
Mansourmoghaddam, M., Rousta, I., Zamani, M. S., Mokhtari, M. H., Karimi Firozjaei, M., & Alavipanah, S. K. (2022a). Investigating And Modeling the Effect of The Composition and Arrangement of The Landscapes of Yazd City on The Land Surface Temperature Using Machine Learning and Landsat-8 and Sentinel-2 Data. Iranian Journal of Remote Sensing & GIS, -. doi:10.52547/gisj.2022.223918.1060
Mohammadi, M., & Afifi, M. (2021). Investigation of the occurrence of urban thermal islands phenomenon using ASTER satellite images (Study area: Shiraz city). Journal of Geography and Environmental Studies, 10(37), 21-44. Retrieved from (In Persian).
Mortazavi Asl, S., & Saeeidi Rezvani, N., & REZAEI, M. (2021). The Effect of Land Use on the Spatial Distribution of Cool Islands in Tehran. Journal of Geographical Studies of Mountainous Areas, 2(2 (6) ), 31-50 (In Persian).
Nasir, M. J., Ahmad, W., Iqbal, J., Ahmad, B., Abdo, H. G., Hamdi, R., & Bateni, S. M. (2022). Effect of the Urban Land Use Dynamics on Land Surface Temperature: A Case Study of Kohat City in Pakistan for the Period 1998–2018. Earth Systems and Environment, 6(1), 237-248.
Omidvar,k.,Moayedfar,S.,Fatami,M.,Narengifard,M.(2020). Assessing the relationship between urban land use and thermal islands, Case study: Yazd desert city. Physical Geography Quarterly, 13(47), 1-17. (In Persian).
Pal, S., & Ziaul, S. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban centre. The Egyptian Journal of Remote Sensing and Space Science, 20(1), 125-145.
Rehman, A., Qin, J., Pervez, A., Khan, M. S., Ullah, S., Ahmad, K., & Rehman, N. U. (2022). Land-Use/Land Cover Changes Contribute to Land Surface Temperature: A Case Study of the Upper Indus Basin of Pakistan. Sustainability, 14(2), 934.
Rousta, I., Mansourmoghaddam, M., Olafsson, H., Krzyszczak, J., Baranowski, P., Zhang, H., & Tkaczyk, P. (2022). Analysis of the recent trends in vegetation dynamics and its relationship with climatological factors using remote sensing data for Caspian Sea watersheds in Iran. International Agrophysics, 36(3), 139-153.
Saedpanah, M., Amanoallahi, J., & Ghorbani, F. (2021). Investigating the effect of land use changes on land surface temperature in cold and semi-arid areas (Case study: Central Zone of Sanandaj City). Journal of Natural Environment, 74(1), 69-82. doi:10.22059/jne.2021.314241.2121 (In Persian).
Traore, M., Lee, M. S., Rasul, A., & Balew, A. (2021). Assessment of land use/land cover changes and their impacts on land surface temperature in Bangui (the capital of Central African Republic). Environmental Challenges, 4, 100114.
Wang, M., Zhang, Z., Hu, T., & Liu, X. (2019). A practical single‐channel algorithm for land surface temperature retrieval: application to landsat series data. Journal of Geophysical Research: Atmospheres, 124(1), 299-316.
Zare Naghadehi, S., Asadi, M., Maleki, M., Tavakkoli-Sabour, S. M., Van Genderen, J. L., & Saleh, S. S. (2021). Prediction of Urban Area Expansion with Implementation of MLC, SAM and SVMs’ Classifiers Incorporating Artificial Neural Network Using Landsat Data. ISPRS International Journal of Geo-Information, 10(8), 513.

Files

Share

How to cite

Statistics