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Land Surface Temperature (LST) is an important indicator for the study of climate change, urban environment, heat balance studies, hydrological and agricultural process, and urban land use and land cover as well as user input for climate models. LANDSAT data is utilized for the number of applications such as environment study, digester and resource...
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Citations
... In Table 2, the details of urban vegetation classes and NDVI value are provided [39]: Equation (2) was used to calculate the proportion of vegetation (PV) [40]. ...
... Equation (3) calculates the LSE [40]. ...
... Finally, Equation (4) was used to determine the LST [40]. ...
Research on the temporal and spatial changes of the urban heat island effect can help us better understand how urbanization, climate change, and the environment are interconnected. This study uses a spatiotemporal analysis method that couples the Emerging Hot Spot Analysis (EHSA) technique with the Mann-Kendall technique. The method is applied to determine the intensity of the heat island effect in humid subtropical climates over time and space. The data used in this research include thermal bands, red band (RED) and near-infrared band (NIR), and Landsat 7 and 8 satellites, which were selected from 2000 to 2022 for the city of Sari, an Iranian city on the Caspian Sea. Pre-processed spectral bands from the 'Google Earth Engine' database were used to estimate the land surface temperature. The land surface temperature difference between the urban environment and the outer buffer (1500 m) was modeled and simulated. The results of this paper show the accuracy and novelty of using Emerging Hotspot Analysis to evaluate the effect of vegetation cover on the urban heat island intensity. Based on the Normalized Difference Vegetation Index (NDVI), the city's land surface temperature increased by approximately 0.30 • C between 2011 and 2022 compared to 2001 to 2010. However, the intensity of the urban heat island decreased during the study period, with r = −0.42, so an average −0.031 • C/decade decrease has been experienced. The methodology can be transferred to other cities to evaluate the role of urban green spaces in reducing heat stress and to estimate the heat budget based on historical observations.
... SUHI mapping was performed through emissivity retrieval using the Normalized Difference Vegetation Index (NDVI). This process involved applying a series of algorithms and fixed parameters extracted from the image metadata file, following the methodology outlined by Sharma and Bisht (2019). ...
The paper is available for free download for 50 days at: https://authors.elsevier.com/a/1iXIi7s%7EEVwj6o
... In recent times, various researchers have focused on relationship between LST and various land indices, such as Normal Difference Vegetation Index (NDVI), Normal Difference Built-up Index (NDBI), Enhanced Bare and Built-up Index (EBBI) and how their dynamics influence and alter the environment of the landscape in different Indian cities, like Kolkata (Ghosh et al. 2018), Delhi and Mumbai (Grover and Singh 2015), Hyderabad (Chakraborti et al. 2019), Lucknow (Sarif and Gupta 2019), Noida , Chandigarh (Sultana and Satyanarayana 2020), ten metropolitan cities of India (Sultana and Satyanarayana 2018). Sharma and Bisht (2019) explored the spatial analysis of Land Use/Land Cover (LU/LC), LST and NDVI in Agra City. The authors carried out spatial distribution of LST based on LU/LC for the year of 1999 and 2017. ...
Growth of populations coupled with industrial and economic development has led to conversion of natural environment to urbanized regions of high built-up areas and infrastructure. The natural space is transforming to built-up set up rigorously which is not only intensifying the thermal state but also changing the climate dynamics. This has resulted in an increase in Land Surface Temperature (LST) leading to critical consequences on the climate and human life. In this study, spatiotemporal imageries of Landsat (1992–2019) are analysed for carrying out the analysis of land indices [Normalised Difference Vegetation Index (NDVI), Normalised Difference Built-up Index (NDBI) and Enhanced Built-up Bareness Index (EBBI)], LST and surface urban heat Island (SUHI) formation for Agra City in India using summer season (April–May) data. The main focus of the present work is the study of spatial pattern of LST and land indices (i.e. NDVI, NDBI and EBBI) and their interrelationship dynamics over the city landscape in directional profiling. The results of SUHI reveal that city center has experienced 0.5–3.5 °C of higher LST than urban periphery. The NDVI vs. LST relationship is found negative, whereas both NDBI vs. LST and EBBI vs. LST relationships are found positive in selected four summer time points of 1992, 2000, 2010, and 2019. The NDVI dynamics results indicate that the forest area (viz. 3–4 km and 10–12 km from city center) experienced 3–5 °C lower LST than other parts of the city landscape. The NDBI dynamics results indicate that in built-up area (from city center to 7 km in all eight directions) experienced 2–4 °C higher LST than other parts of the city landscape (except barren soils area). The EBBI dynamics results indicate that barren soils (viz. 8–10 km of North-East direction, 14–15 km of North–West direction and 7–9 km of South–West direction) have experienced 2–5 °C of higher LST than other part of the city landscape. The purpose of is to help in enriching the knowledge base for not only understanding the dynamics of the thermal state but also in knowing the composition of the landscape for enhancing environmental sustainability and carrying capacity for Agra city.
... The UHI effect has been studied through the retrieval of LST from satellite remote sensing data (Voogt & Oke, 2003;Mirzaei & Haghighat, 2010;Ngie et al., 2014;Abutaleb et al., 2015;Ngie et al., 2016;Sharma & Bisht, 2019). Landsat TM and ETM+ have a single thermal band (band 6) which is the thermal infrared (TIR) channel that records radiation within a 10.4-12.5μm ...
Urban Heat Island (UHI) is among some of the challenges plaguing urban environments. There is increase human population within urban environments especially in the developing world, which is a need to understand the climates for their wellbeing. The use of multispectral satellite remote sensing to investigate the climatic conditions through radiation measurement is applied across the two major South African cities. The thermal remote sensing technique applied for this study is the direct determination of land surface temperatures (LST) using multispectral thermal imagery (ETM+). In addition, meteorological data which included air temperature and relative humidity for the same satellite image dates were used. The LST values obtained showed Johannesburg has many micro heat islands scattered across the metro than in Cape Town. These areas of heat islands corresponded to areas of human settlement and more so the unplanned as opposed to the planned ones. The estimated LST values and observed air temperature values with an R2 of 0.9. It could be concluded that expansion of urban areas in South Africa has led to increased thermal radiation of land surface in densely populated areas.
