تعداد نشریات | 31 |
تعداد شمارهها | 748 |
تعداد مقالات | 7,112 |
تعداد مشاهده مقاله | 10,246,115 |
تعداد دریافت فایل اصل مقاله | 6,899,808 |
Land surface temperature assessment in relation to land-use/land-cover (A case study: Isfahan City, Central Iran) | ||
Caspian Journal of Environmental Sciences | ||
دوره 21، شماره 3، مهر 2023، صفحه 725-735 اصل مقاله (1.33 M) | ||
نوع مقاله: Research Paper | ||
شناسه دیجیتال (DOI): 10.22124/cjes.2023.6959 | ||
نویسندگان | ||
Sayyad Asghari Saraskanrood* ؛ Bahareh Asadi,؛ Ehsan Ghale | ||
Department of Physical Geography, Faculty of Social Sciences, University of Mohaghegh Ardabili, Ardabil, Iran | ||
چکیده | ||
Most of critical issues such as increase in pollution levels, sudden climatic changes and the rise of temperature in the urban area, leading to the formation of Urban Heat Islands (UHI), have been resulted from urbanization. As population density increases, most terrestrial areas become cities, and cities grow very fast. The reason to do the current study is to compare Single-Channel, SEBAL and Split-Window methods and then choose the best method for estimating land surface temperature. The objectives are as follows: Three independent studies were conducted using a series of Landsat data: (i) to land-use/land-cover (LU/LC) classification by object-oriented method and change detection; (ii) to understand the connection between particular LU/LC class and Land Surface Temperature(LST); and (iii) LST recovery using Single-Channel, SEBAL and Split-Window, as well as comparing these methods together. The results of land-use classification and change detection indicated that urban areas have increased, while agriculture has declined. The results of validation of the three temperature recovery methods demonstrated that due to using two thermal bands simultaneously, the Split-Window method functions better and in these three algorithms, water bodies and wet soils exhibit minimum surface temperatures. Due to less vegetation, areas such as deserts, saline soils and residential area display a higher surface temperature. Vegetation has always been an obstacle for heat input and inversely related to surface heat. In addition, due to fuel pollution of machinery and factory, urban areas experience high temperatures. The only gap of this study was the utilizing 5-cm surface temperature data, which was only available at airports and was not available. | ||
کلیدواژهها | ||
Single-channel؛ SEBAL؛ Split-window algorithm؛ Object-oriented | ||
مراجع | ||
Ameer Abbas, GA 2022, Assessment of land sensitivity to desertification for Al-Mussaib project using MEDALUS approach. Caspian Journal of Environmental Sciences, 20: 177-196.
Blaschke, T, & Strobl, J 2001, What’s wrong with pixels some recent development interfacing remote sensing and GIS. GeoBIT/GIS, 14: 12-17.
Buyantuyev, A & Jianguo, W 2010, Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landscape Ecology, 25: 17-33.
Gao, Y, Mas, JF, Maathuis, BHP, Zhang, X, & Van Dijk, PM 2006, Comparison of pixel-based and object oriented image classification approaches-a case study in a coal fire area, Wuda, Inner Mongolia, China. International Journal of Remote Sensing, 27: 4039-4055.
Gholizadeh, M, Rezvani, SA & Zibaei, M 2021, Effects of land use change on macroinvertebrate community composition in upper reaches of the Chehel-Chai catchment, Iran. Caspian Journal of Environmental Sciences, 19: 523-533
Jain, S, Sannigrahi, S, Sen, S, Bhatt, S, Chakraborti, S, & Rahmat, S 2020, Urban heat island intensity and its mitigation strategies in the fast-growing urban area. Journal of Urban Management, 9: 54-66.
Jiménez‐Muñoz, JC, & Sobrino, JA 2003, A generalized single‐channel method for retrieving land surface temperature from remote sensing data, Journal of Geophysical Research: Atmospheres, 108(22): 19-31.
Kamran, K.V, Pirnazar, M, & Bansouleh, V.F 2015, Land surface temperature retrieval from Landsat 8 TIRS: comparison between split window algorithm and SEBAL method, In Third International Conference on Remote Sensing and Geoinformation of the Environment, pp. 9535-9550.
Liu, K, Xueling, W, & Young, M 2014, Effect of bentonite/potassium sorbate coatings on the quality of mangos in storage at ambient temperature. Journal of Food Engineering, 137: 16-22.
McMillin, L.M 1975, Estimation of sea surface temperatures from two infrared window measurements with different absorption. Journal of Geophysical Research, 80(36): 5113-5117.
Pongrácz, R, Bartholy, J, & Dezső, Z 2010, Application of remotely sensed thermal information to urban climatology of Central European cities. Physics and Chemistry of the Earth, 35: 95-99.
Qian, J, Zhou, Q, & Hou, Q 2007, Comparison of pixel-based and object-oriented classification methods for extracting built-up areas in arid zone, In ISPRS Workshop on Updating Geo-spatial Databases with Imagery & the 5th ISPRS workshop on DMGISs, 36: 163-171.
Ramezani, H & Ramezani, F 2021, Status and trend analysis in landscape pattern through field-based sampling data Caspian Journal of Environmental Sciences, 19: 469-481.
Sekertekin, A, & Bonafoni, S 2020, Land surface temperature retrieval from Landsat 5, 7, and 8 over rural areas: assessment of different retrieval algorithms and emissivity models and toolbox implementation, Remote Sensing, 12(29): 1-32
Sobrino, J.A, Jimenez-Munoz, J.C, El-Kharraz, J, Gómez, M, Romaguera, M, & Soria, G, 2004, Single-channel and two-channel methods for land surface temperature retrieval from DAIS data and its application to the Barrax site, International Journal of Remote Sensing, 25: 215-230.
Surya Suamba, IB, Anom Wiryasa, NM, Acwin Dwijendra, NK, Agung Diasana Putra, IDG 2022, Characteristics and deviation patterns of agricultural land use in tourism area of Canggu, Bali, Indonesia. Caspian Journal of Environmental Sciences, 20: 423-430.
Trigo, I, Freitas, S, Bioucas-Dias, J, Barroso, C, Monteiro, I, & Viterbo, P 2009, Algorithm theoretical basis document for land surface temperature (LST)(SAF/LAND/IM/ATBD_LST/1.0), EUMETSAT, 14: 34-53.
Ulivieri, C, Castronuovo, M, Francioni, R, & Cardillo, A 1994, A split window algorithm for estimating land surface temperature from satellites. Advances in Space Research, 14: 59-65.
Wan, Z 2014, New refinements and validation of the collection-6 MODIS land-surface temperature/emissivity product. Remote sensing of Environment, 140: 36-45.
Wan, Z, & Dozier, J 1996, A generalized split-window algorithm for retrieving land surface temperature from space, IEEE Transactions on Geoscience and Remote Sensing, 34: 892-905.
Wang, W, Kai, L, Rong, T, & Shudong, W 2019, Remote sensing image-based analysis of the urban heat island effect in Shenzhen, China. Physics and Chemistry of the Earth, 110: 168-175.
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: 68-83.
Zhang, Y, Odeh, I.O, & Han, C 2009, Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. International Journal of Applied Earth Observation and Geoinformation, 11: 256-264.
Zhou, Y, Zhi, Z, Feng, Y, Yao, Y, & Xiaohong, X 2017, Urban morphology on heat island and building energy consumption, Procedia Engineering, 20: 2401-2406. | ||
آمار تعداد مشاهده مقاله: 295 تعداد دریافت فایل اصل مقاله: 442 |