Estimation of radiant flux and radiation balance in the summer months for electricity supply to villages in Chalus Township using Landsat satellite images

Document Type : Origional Article

Authors

1 Assistant Professor, Department of Geography and Rural Planning, University of Mohaghegh Ardabili, Ardabil, Iran

2 PhD student in Geomorphology, University of Mohaghegh Ardabili, Ardabil, Iran

Abstract
Background and Aim: City furniture is actually a manifestation of the aesthetics and identity of a society. Therefore, functional design, appropriate location, and proper and principled use of furniture in the city context are very important. Although city furniture is one of the most important categories of a city, it is not possible to equip and improve the current situation of this important thing at a time and simultaneously in all regions of a city; therefore, a comparative comparison in this regard can be effective and help urban managers perform better and make decisions in accordance with the priority of intervention at the level of each region. On this basis, the present study has been developed with the aim of a comparative study of the regions of Tabriz metropolis based on the components of city furniture.
Methodology: For this purpose, the relevant images were first obtained and the necessary pre-processing was applied to each. Then, the images were modeled. Initially, images from the year 2023 of the Landsat 8 satellite, the OLI sensor and the TIRS sensor, and the Sebal algorithm were used to conduct this research. ENVI software was used for geometric, atmospheric and radiometric corrections of satellite images and also for performing calculations related to the SEBAL model, and ArcGIS software was used for creating a database, spatial analyses, cartographic operations and finally implementing the model.
Results and Findings: The results show that the average of the highest incoming shortwave radiation was 769 watts per square meter in September and the lowest value was in the next month of August with 730 watts per square meter. And the lowest value was in July with 555 watts per square meter. The reason for this difference in radiation power in the amount of net radiation reaching the ground in the study area is due to the difference in the angle of the sun's rays and the number of sunny hours in different months of the year. It can be concluded that solar radiation from the radiation threshold to 1000 watts per square meter is received, it can be concluded that solar radiation and radiation balance in the villages of Chalus Township have the potential to provide electricity in a suitable way.

Keywords

Subjects

Ahmadi, M., Ashurlu, D., and Narangi Fard, M., 2012, Temporal-spatial changes of thermal and applied patterns of Shiraz city using TM and ETM measuring data. Remote sensing and GIS of Iran, 4(4): 55_68.
Akbari, E., Ebrahimi, M., Fiezizadeh, B., and 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, 26(4): 151-170.
Alavi Panah, K., 2009, Thermal Remote Sensing and its Application in Earth Sciences. Second Edition, Tehran, University of Tehran Press.
Amini Bazyani, S., Zare Abyaneh, H., and Akbari, M., 2014, Estimation of Surface Temperature and Cropping Intensity in Hamedan Province Using Remote Sensing Data. Physical Geography Research Quarterly, 46(3): 333-348.
Asghari, S., and Emami, H., 2019, Monitoring the earth surface temperature and relationship land use with surface temperature using of OLI and TIRS Image. Researches in Geographical Sciences, 19(53): 195-215.
Ashraf, B., Faridbhosseini, A., and Mianabadi, A., 2012, The Investigation of Mashhad’s Heat Island Using Satellite Images and Applying Fractal Theory. GEOGRAPHY AND ENVIRONMENTAL HAZARDS, 1(1): 35-48.
Darvishi, S., rashidpour, M., and soleimani, K., 2019, Analysis of Land Use Role in the Formation of Thermal Islets of Marivan Township Using Landsat Satellite Images. Geography and Development Iranian Journal, 17(54): 143-162.
Darvishi, S., Soleimani, K., and Rashidpour, M., 2019, Impact of vegetation indices and urban surface characteristics on land surface temperature changes (Case study: Sanandaj city). Journal of RS and GIS for Natural Resources, 10(1): 17-35.
Faizizadeh, B., and Hilali, H., 2010. Comparison of base pixel, object-oriented and effective parameters in land use coverage classification in West Azarbaijan Province. Geographical Research Journal, 71: 73_84.
Farhanj, F., and Akhoondzadeh, M., 2017, Fusion of _8 Thermal Infrared and Visible Bands with Multi-Resolution Analysis Contour let Methods. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 77-81.
Kakeh Mami, A., Ghorbani, A., Kayvan Behjoo, F., and Mirzaei Mosivand, A., 2017, Comparison of visual and digital interpretation methods of land use/cover mapping in Ardabil province. Journal of RS and GIS for Natural Resources, 8(3): 121-134.
Karenia, C.NS.G., 2016, spatial Geotechnologies and Gis tools for urban planners applied to the Analysis of urban heat island case caracas citevenezuela. 9 th lnternational Conference on Urban Climate jointly with 12 th symposium on the urban Environment, 1-5.
Kaviani, A., Sohrabi, T., and Daneshkar Araste, P., 2013, Estimation of land surface temperature using NDVI in MODIS and Landsat ETM+ imageries. Journal of Agricultural Meteorology, 1(1): 14-25.
Lu, D., and Weng, Q., 2008, A survey of image classification methods and techniques for improving classification performance.
Moradi, M., Salahi, B., and Masoodian, S., 2016, Analysis of land surface temperature gradient of Iran using MODIS Terra and Aqua data. Physical Geography Research Quarterly, 48(4): 517-532.
Pijanowski, B.C., Brown, D.G., Shellito, B.A., and Manik, G.A., 2002, Using neural networks and GIS to forecast land use change; A Land Transformation Model. Computers Environment and Urban Systems, 26: 553-575.
Ronald, C., Estoque, M., and Yuji, M., 2017, Effects  of landscape Composition  and pattern on  land surface temperature An urban heat island  study in  the megacities of Southeast  Asia. National Library  of Medicine, 15(577): 349-359.
Rozensten, O., Qin, Z., Derimian, Y., and Karnieli, A., 2014, Derivation of land surface temperature for landsat – 8 TIRS using a split window algorithm. Sensor, 4(14): 5768-5780.
Shi, Y., Katzschner, L., Ng, E., 2017, Modelling the fine- scale spatiotemporal pattern of urban heat island effect using land use regression approach in a megacity. Science of the Total Environment, 618(15): 891-904.
Valizadeh Kamran, K., Gholamnia, K., Eynali, G., and Moosavi, M., 2017, Estimation land surface temperature and extract heat islands using split window algorithm and multivariate regression analysis (Case Study of Zanjan). Research and urban planning, 8(30), 35-50.
Wang, Y., Ch, B., Hu, s.w., Myint, Ch., feng, Ch., Chow, W.T.L., and Passy, P.F., 2018, Patterns of land change and their potential impacts on land surface temperature change in Yangon Myanmar. Science of the Total Environment, 643: 738-750.
Zhong, X., Huo, X., Ren, C., Labed, J., and Li, Z, L., 2016, Retrieving Land surface temperature from hyperspectral thermal infrared data using a multi-channel method. Sensors, l5(16): 671-687.
 
Volume 6, Issue 4 - Serial Number 22
Winter 2025
Pages 449-459

  • Receive Date 20 January 2025
  • Revise Date 31 March 2025
  • Accept Date 06 May 2025
  • First Publish Date 06 May 2025
  • Publish Date 20 February 2026