@2024 Afarand., IRAN
ISSN: 2538-4384 Geographical Researches 2021;36(2):191-203
ISSN: 2538-4384 Geographical Researches 2021;36(2):191-203
Detection of Surface Temperature Changes Using Satellite Images and Real Data and its Relationship with the Covered Vegetation in the Southern Part of the Lake Urmia
ARTICLE INFO
Article Type
Original ResearchAuthors
Mikaili HajiKandi Kh. (1)Sobhani B. (*1)
Vramesh S. (2)
(1) Department of Geography, Faculty of Social Sciences, Mohaghegh Ardabili University, Ardabil, Iran
(2) Department of Science and Forest Engineering, Faculty of Agriculture and Natural Resource, University of Mohaghegh Ardabili, Ardabil, Iran
Correspondence
Address: Department of Geography, Faculty of social Sciences, Mohaghegh Ardabili University, Daneshgah Street, Ardabil, Iran. Postal Code: 5619911367Phone: +98 (45) 33596107
Fax: +98 (45) 31505981
sobhani@uma.ac.ir
Article History
Received: November 9, 2020Accepted: January 25, 2021
ePublished: June 16, 2021
ABSTRACT
Aims & Backgrounds
Today, the use of remote sensing methods for measuring land surface temperature has got more popular. Because remote sensing provides the opportunity to estimate the temperature in every region accurately. This study aimed to estimate land surface temperature using remote sensing in the south of Urmia Lake, compare them with observed data, and analyze the relationship between estimated land surface temperature and vegetation cover.
Methodology Changes in temperature of the surface of the earth were investigated from 2000 to 2017 as well as their relationship with changes in vegetation and land use in agricultural regions. Then, thermal bands of Landsat 7 and OLI were used for measuring land surface temperature and converting DN to radians and brightness temperature. Moreover, NDVI was used for calculating emissivity and determining land use based using an object-oriented method. Then, the relationship between vegetation and land surface temperature was investigated using regression analysis.
Findings The results showed that the observed and estimated land surface temperature had increased from 2000 to 2017 due to the changes in land use and vegetation cover. According to the results of linear regression analysis, there is a significant relationship between estimated and observed land surface temperature (R2 = 0.72). Furthermore, there is a significant negative relationship between land surface temperature and vegetation cover.
Conclusion The results showed that remote sensing methods provide accurate results in estimating the surface temperature. Understanding the surface temperature and its relationship with various land uses helps planners and experts to make managerial decisions to protect natural resources and agricultural lands.
Methodology Changes in temperature of the surface of the earth were investigated from 2000 to 2017 as well as their relationship with changes in vegetation and land use in agricultural regions. Then, thermal bands of Landsat 7 and OLI were used for measuring land surface temperature and converting DN to radians and brightness temperature. Moreover, NDVI was used for calculating emissivity and determining land use based using an object-oriented method. Then, the relationship between vegetation and land surface temperature was investigated using regression analysis.
Findings The results showed that the observed and estimated land surface temperature had increased from 2000 to 2017 due to the changes in land use and vegetation cover. According to the results of linear regression analysis, there is a significant relationship between estimated and observed land surface temperature (R2 = 0.72). Furthermore, there is a significant negative relationship between land surface temperature and vegetation cover.
Conclusion The results showed that remote sensing methods provide accurate results in estimating the surface temperature. Understanding the surface temperature and its relationship with various land uses helps planners and experts to make managerial decisions to protect natural resources and agricultural lands.
CITATION LINKS
[1]Afzan Buyadi S N, Naim W-M, Misni A (2013). Impact of land use changes on the surface temperature distribution of area surrounding the national botanic garden. Shah Alam. Procedia-Social and Behavioral Sciences. 101:516-525.
[2]Akbari E, Ebrahimi M, Fiezizadeh B, Nezhadsoleimani H (2016). Evaluating land surface temperature related to the land use change detection by satellite image (Case study: Taleghan Basin). Geography and Environmental Planning Journal. 4(60):151-170. [Persian]
[3]Ansari M, Noori Gh, Fotoohi S (2016). Investigation of temperature precipitation and flow trend using nonparametric mankendall (Case study: Kaju River in Sistan and Baluchestan). Journal of Watershed Management Research. 7(14): 152-158. [Persian]
[4]Arvin A (2019). Land surface temperature detection using of satellite images. Journal of Natural Environmental Hazards. 8(19):91-102. [Persian]
[5]Aslami F, Ghorbani A, Sobhani B, Panahandeh M (2015). Comparing artificial neural network, support vector machine and object-based methods in preparation land use/cover mapsusing landSat-8 images. RS and GIS for Natural Resources. 6(3):1-14. [Persian]
[6]Asgarzadeh P, Darvishi Boloorani A, Bahrami H.A, Hamzeh S (2016). Comparison between land surface temperature estimation in single and multi-channel method using landsat images 8. Journal of Rs and Gis for Natural Resources. 7(3):18-29. [Persian]
[7]Ayanlade A, Howarda M T (2019). Land surface temperature and heat fluxes over three cities in Niger Delta, Journal of African Earth Sciences. 151:54-66.
[8]Chaudhuri G, Mishra N B (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.
[9]Chen X L, Zhao H M, Li P X, Yin Z Y (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment. 104(2):133-146.
[10]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 Sciences. 22(2):203-218.
[11]Feizizadeh B, Didehban Kh, Gholamnia Kh (2016). Extraction of land surface temperature (LST) based on lndsat satellite images and split window algorithm. Study area: Mahabad Catchment. Journal of Geographical Data (SEPEHR). 25(98):171-181. [Persian]
[12]Ghorbannia Kheybari V, Mirsanjari M, Liaghati H, Armin M (2017). Estimating land surface temperature of land use and land cover in dena county using single window algorithm and landsat 8 satellite data. Environmental Sciences Journal. 15(2):55-74. [Persian]
[13]Hejazizadeh Z, Ziaeian P, Shirkhani A (2013). Estimation of Surface temperature using thermal-band data in west of Tehran province and Qazvin. Geography. 11(38):33-49. [Persian]
[14]Hengl T, Heuvelink G B M, Tadic M P (2012). Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images. Theoretical and Applied Climatology. 107:265-277.
[15]Jahandideh M, Shirvani A (2012). Trend analysis for precipitation time sub-series in Fars province. Water Engineering Journal. 5(12):73-84. [Persian]
[16]Jouybari Moghaddam Y, Akhoondzadeh M, Saradjian M R (2015). A novel method for retrieving land surface emissivity from landsat-8 satellite data based on vegetation index. Jurnal of geomatics science and technology. 5(1):175-187. [Persian]
[17]Kazemi Garajeh M, Salmani B, Feizizadeh B (2020). Evaluating the types of split window algorithms for calculating the land surface temperature to determine the best algorithm for MODIS sensor images. RS and GIS for Natural Resources. 11(2-39):106-127. [Persian]
[18]khoshhal dastjerdi J, ghavidel Rahimi Y (2008). Application of Mann-Kendall nonparametric test in estimating temperature changes, Geographic Space. 8(22): 21-38. [Persian]
[19]Klok L, Zwart S J, Verhagen H, Mauri E (2012). The surface heat island of Rotterdam and its relationship with urban surface characteristics. Resources, Conservation and Recycling Journal. 64:23-29.
[20]Meng X, Li H, Du Y, Liu Q, Zhu J, Sun L (2016). Retrieving land surface temperature from landsat 8 TIRS data using RTTOV and ASTER GED. IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 4302-4305.
[21]Morawitz D F, Blewett T M, Cohen A, Alberti M (2006). Using NDVI to assess vegetative land cover change in central Puget sound. Environmental Monitoring and Assessment Journal. 114(1-3):85-106.
[22]Nichol J E, Hang T P (2012). Temporal characteristics of thermal satellite images for urban heat stress and heat land mapping, ISPRS Journal of Photogrammetry and Remote Sensing. 74:153-162.
[23]Rogan J, Ziemer M, Martin D, Ratick S, Cuba N, De Lauer V (2013). The impact of tree cover loss on land surface temperature: A case study of central Massachusetts using landsat thematic mapper thermal data. Applied Geography Journal. 45:49-57.
[24]Solanky V, singh S, katiyar S (2018). Land Surface Temperature Estimation Using Remote Sensing Data. Hidrologic Modeling Journal. 343-351.
[25]Syvitski J P (2008). Deltas at risk. Sustainability Science Journal. 3(1):23-32.
[26]Weng Q, Lu D (2008). A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States. International Journal of Applied Earth Observation and Geoinformation. 10(1):68-83.
[27]Xiong Y, Huang Sh, Chen F, Ye H, Wang C, Zhu C (2012). The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou. South China. Remote Sensing Journal. 4(7):2033-2056.
[28]Yue W, Xu J, Tan W (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(15): 3205-3226.
[2]Akbari E, Ebrahimi M, Fiezizadeh B, Nezhadsoleimani H (2016). Evaluating land surface temperature related to the land use change detection by satellite image (Case study: Taleghan Basin). Geography and Environmental Planning Journal. 4(60):151-170. [Persian]
[3]Ansari M, Noori Gh, Fotoohi S (2016). Investigation of temperature precipitation and flow trend using nonparametric mankendall (Case study: Kaju River in Sistan and Baluchestan). Journal of Watershed Management Research. 7(14): 152-158. [Persian]
[4]Arvin A (2019). Land surface temperature detection using of satellite images. Journal of Natural Environmental Hazards. 8(19):91-102. [Persian]
[5]Aslami F, Ghorbani A, Sobhani B, Panahandeh M (2015). Comparing artificial neural network, support vector machine and object-based methods in preparation land use/cover mapsusing landSat-8 images. RS and GIS for Natural Resources. 6(3):1-14. [Persian]
[6]Asgarzadeh P, Darvishi Boloorani A, Bahrami H.A, Hamzeh S (2016). Comparison between land surface temperature estimation in single and multi-channel method using landsat images 8. Journal of Rs and Gis for Natural Resources. 7(3):18-29. [Persian]
[7]Ayanlade A, Howarda M T (2019). Land surface temperature and heat fluxes over three cities in Niger Delta, Journal of African Earth Sciences. 151:54-66.
[8]Chaudhuri G, Mishra N B (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.
[9]Chen X L, Zhao H M, Li P X, Yin Z Y (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment. 104(2):133-146.
[10]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 Sciences. 22(2):203-218.
[11]Feizizadeh B, Didehban Kh, Gholamnia Kh (2016). Extraction of land surface temperature (LST) based on lndsat satellite images and split window algorithm. Study area: Mahabad Catchment. Journal of Geographical Data (SEPEHR). 25(98):171-181. [Persian]
[12]Ghorbannia Kheybari V, Mirsanjari M, Liaghati H, Armin M (2017). Estimating land surface temperature of land use and land cover in dena county using single window algorithm and landsat 8 satellite data. Environmental Sciences Journal. 15(2):55-74. [Persian]
[13]Hejazizadeh Z, Ziaeian P, Shirkhani A (2013). Estimation of Surface temperature using thermal-band data in west of Tehran province and Qazvin. Geography. 11(38):33-49. [Persian]
[14]Hengl T, Heuvelink G B M, Tadic M P (2012). Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images. Theoretical and Applied Climatology. 107:265-277.
[15]Jahandideh M, Shirvani A (2012). Trend analysis for precipitation time sub-series in Fars province. Water Engineering Journal. 5(12):73-84. [Persian]
[16]Jouybari Moghaddam Y, Akhoondzadeh M, Saradjian M R (2015). A novel method for retrieving land surface emissivity from landsat-8 satellite data based on vegetation index. Jurnal of geomatics science and technology. 5(1):175-187. [Persian]
[17]Kazemi Garajeh M, Salmani B, Feizizadeh B (2020). Evaluating the types of split window algorithms for calculating the land surface temperature to determine the best algorithm for MODIS sensor images. RS and GIS for Natural Resources. 11(2-39):106-127. [Persian]
[18]khoshhal dastjerdi J, ghavidel Rahimi Y (2008). Application of Mann-Kendall nonparametric test in estimating temperature changes, Geographic Space. 8(22): 21-38. [Persian]
[19]Klok L, Zwart S J, Verhagen H, Mauri E (2012). The surface heat island of Rotterdam and its relationship with urban surface characteristics. Resources, Conservation and Recycling Journal. 64:23-29.
[20]Meng X, Li H, Du Y, Liu Q, Zhu J, Sun L (2016). Retrieving land surface temperature from landsat 8 TIRS data using RTTOV and ASTER GED. IEEE International Geoscience and Remote Sensing Symposium (IGARSS). 4302-4305.
[21]Morawitz D F, Blewett T M, Cohen A, Alberti M (2006). Using NDVI to assess vegetative land cover change in central Puget sound. Environmental Monitoring and Assessment Journal. 114(1-3):85-106.
[22]Nichol J E, Hang T P (2012). Temporal characteristics of thermal satellite images for urban heat stress and heat land mapping, ISPRS Journal of Photogrammetry and Remote Sensing. 74:153-162.
[23]Rogan J, Ziemer M, Martin D, Ratick S, Cuba N, De Lauer V (2013). The impact of tree cover loss on land surface temperature: A case study of central Massachusetts using landsat thematic mapper thermal data. Applied Geography Journal. 45:49-57.
[24]Solanky V, singh S, katiyar S (2018). Land Surface Temperature Estimation Using Remote Sensing Data. Hidrologic Modeling Journal. 343-351.
[25]Syvitski J P (2008). Deltas at risk. Sustainability Science Journal. 3(1):23-32.
[26]Weng Q, Lu D (2008). A sub-pixel analysis of urbanization effect on land surface temperature and its interplay with impervious surface and vegetation coverage in Indianapolis, United States. International Journal of Applied Earth Observation and Geoinformation. 10(1):68-83.
[27]Xiong Y, Huang Sh, Chen F, Ye H, Wang C, Zhu C (2012). The impacts of rapid urbanization on the thermal environment: A remote sensing study of Guangzhou. South China. Remote Sensing Journal. 4(7):2033-2056.
[28]Yue W, Xu J, Tan W (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(15): 3205-3226.