Assessing the role of urban green vegetation in mitigating land surface temperature in Naples (Italy) using Landsat-9 and GIS techniques

Urban vegetation can help decrease Land surface temperature (LST) to mitigate urban heat island (UHI) effects. The relationship between LST and urban vegetation amount has been extensively documented. However, few studies have examined the relationship between LST and urban vegetation configuration and particularly whether the relationship changes across scales. In this study, LST in Changchun, China was obtained from Landsat-5 Thematic Mapper (TM) data and then correlated to urban vegetation amount and configuration information derived from high-spatial-resolution SPOT satellite data to uncover the relationship between urban vegetation configuration and LST. These results suggest that not only by increasing the amounts of urban vegetation, but also by optimizing their spatial pattern of urban vegetation can decrease LST. Given a fixed amount of urban vegetation, LST can be significantly decreased or increased by different configuration of urban vegetation. Besides the relationship between LST and urban vegetation configuration is complex and scale dependant and spatial scales should be considered when we try to explore the relationship between them. These findings can deepen the understanding of their interactions between LST and urban vegetation and provide useful information for urban planners about how to arrange urban vegetation at the landscape level to improve urban thermal environment.

AN ASSESSMENT OF SPATIAL VARIATION OF LAND SURFACE CHARACTERISTICS OF MINNA, NIGER STATE NIGERIA FOR SUSTAINABLE URBANIZATION USING GEOSPATIAL TECHNIQUES

Land cover change and climate change lead to rising land surface temperaturesLandsurface temperatures. An abundance of research demonstrates that urban vegetationUrban vegetation, known asInfrastructuregreen green infrastructureGreen infrastructure, can reduce land surface temperatures. However, there is little research determining how the spatial structureSpatial structure and pattern of urban vegetationUrban vegetation affects land surface temperatureLandsurface temperatures. This research focuses on investigating the effects of urban vegetationUrban vegetation patterns on land surface temperaturesLandsurface temperatures by comparing classification maps, spatial patternsSpatial pattern of vegetation, and the land surface temperature contour maps. Eight areas that have similar land cover ratios but different spatial patterns have been selected. The results show that large vegetation patches reduce surface temperature better than small vegetation patches. A large vegetation patch has the ability to decrease surface temperature only in the patch itself, and at a distance of 60–120 m surrounding the patch. However, built-up and bare soil areas that reside next to the green patch still retain a high surface temperature. On the other hand, the maximum temperature of areas comprising the small vegetation patches is lower than the large patch. Overall, small, scattered vegetation patches reduce the surface temperature not only on the patches themselves but also in a wider area. It seems that small, scattered vegetation patches benefit the urban areas by reducing land surface temperatureLandsurface temperatures more than a large vegetation patch. However, both large and small, scattered vegetation patches should be combined to most efficiently decreasing urban land surface temperatureLandsurface temperatures. The findings of the research can be applied to Bangkok’sBangkok, Thailand green infrastructureGreen infrastructure planningInfrastructuregreen to improve the quality of lifeQuality of Life for the people and make the city more resilient.

The coupling relationship between urban vegetation and land surface temperature (LST) has been of great interest to a variety of environmental studies. This paper retrieves the urban vegetation and LST utilizing Terra ASTER imagery in the year 2007, and analyzes their coupling relationships accordingly, so as to provide the basis for decision making of ecological planning and environment protection. It turns out that NDVI, urban vegetation abundance (UVA) and urban forest abundance (UFA) are all in negative correlation with land surface temperature (LST), so that Urban vegetation and urban forest are both capable in decreasing LST. The influence of urban vegetation and urban forest varies with pixel aggregation, and peaks around 90 m ~ 120 m resolution. At the end of this paper, some future efforts on the analysis are pointed out.

With continuing global warming and urbanization, it is increasingly important to understand the resilience of urban vegetation to extreme high temperatures, but few studies have examined urban vegetation at large scale or both concurrent and delayed responses. In this study, we performed an urban-rural comparison using the Enhanced Vegetation Index and months that exceed the historical 90th percentile in mean temperature (referred to as "hot months") across 85 major cities in the contiguous United States. We found that hot months initially enhanced vegetation greenness but could cause a decline afterwards, especially for persistent (≥4 months) and intense (≥+2 °C) episodes in summer. The urban responses were more positive than rural in the western United States or in winter, but more negative during spring-autumn in the eastern United States. The east-west difference can be attributed to the higher optimal growth temperatures and lower water stress levels of the western urban vegetation than the rural. The urban responses also had smaller magnitudes than the rural responses, especially in deciduous forest biomes, and least in evergreen forest biomes. Within each biome, analysis at 1 km pixel level showed that impervious fraction and vegetation cover, local urban heat island intensity, and water stress were the key drivers of urban-rural differences. These findings advance our understanding of how prolonged exposure to warm extremes, particularly within urban environments, affects vegetation greenness and vitality. Urban planners and ecosystem managers should prioritize the long and intense events and the key drivers in fostering urban vegetation resilience to heat waves.

The coupling relationship between urban vegetation and land surface temperature (LST) has been heatedly debated in a variety of environmental studies. This paper studies the urban vegetation information and LST by utilizing a series of remote sensing imagery covering the period from 1990 to 2007. Their coupling relationship is analyzed, in order to provide the basis for ecological planning and environment protection. The results show that the normalized difference vegetation index (NDVI), urban vegetation abundance (UVA) and urban forest abundance (UFA) are negatively correlated with LST, which means that both urban vegetation and urban forest are capable in decreasing LST. The apparent influence of urban vegetation and urban forest on LST varies with the spatial resolution of the imagery, and peaks at the resolutions ranging from 90 m to 120 m.

Interpreting the relationship between urban heat island (UHI) and urban vegetation is a basis for understanding the impacts of underlying surfaces on UHI. The calculation of UHI intensity (UHII) requires observations from paired stations in both urban and rural areas. Due to the limited number of paired meteorological stations, many studies have used remotely sensed land surface temperature, but these time-series land surface temperature data are often heavily affected by cloud cover and other factors. These factors, together with the algorithm for inversion of land surface temperature, lead to accuracy problems in detecting the UHII, especially in cities with weak UHII. Based on meteorological observations from the Oklahoma Mesonet, a world-class network, we quantified the UHII and trends in eight cities of the Great Plains, USA, where data from at least one pair of urban and rural meteorological stations were available. We examined the changes and variability in urban temperature, UHII, vegetation condition (as measured by enhanced vegetation index, EVI), and evapotranspiration (ET). We found that both UHI and urban cold islands (UCI) occurred among the eight cities during 2000–2014 (as measured by impervious surface area). Unlike what is generally considered, UHII in only three cities significantly decreased as EVI and ET increased (p<0.1), indicating that the UHI or UCI cannot be completely explained simply from the perspective of the underlying surface. Increased vegetative cover (signaled by EVI) can increase ET, and thereby effectively mitigate the UHI. Each study station clearly showed that the underlying surface or vegetation affects urban-rural temperature, and that these factors should be considered during analysis of the UHI effect over time.

The term urban heat island (UHI) effect arises from the temperature variations between built-up areas and their surroundings which is also popular in Dhaka Metropolitan Area (DMA). The study evaluates the impact of UHI by estimating land surface temperature (LST) in the DMA area using quantitative multi-temporal thermal remote sensing images and GIS techniques. The study aims to analyse the trend of land use/land cover (LULC) and LST change for the year 1991, 2001, 2011 and 2019, and to predict the future LST (2029) using the artificial neural network-based cellular automata (ANN-CA) algorithm. Series of Landsat 4-5 TM/8 OLI images of DMA areas are used to monitor the relationship between LULC change and LST from 1991 to 2019. The normalized difference built-up index (NDBI) and normalized difference vegetation index (NDVI) are used to predict the LST, which helps to determine the quantitative future UHI effects in the DMA area. The results indicate that LSTs have an average increase of 3 to 5 degrees Celsius over 28 years. The results also show that UHIs can be mainly linked to urban expansion. The highest UHI impact in 2019 was 99.72 per cent, suggesting a risky present and future. The built-up area is expanded from 30 per cent (1991) to more than 90 per cent (2019) of the study area which indicates unbalanced urbanization between the built-up and unbuilt city regions. This study thus draws the city’s attention to the importance of environmental comprehensiveness in policymaking and strategic planning to assure sustainable urban development.

The Urban Heat Island (UHI) is the phenomenon of altered increased temperatures in urban areas compared to their rural surroundings. UHIs grow and intensify under extreme hot periods, such as during heat waves, which can affect human health and also increase the demand for energy for cooling. This study applies remote sensing and land use/land cover (LULC) data to assess the cooling effect of varying urban vegetation cover, especially during extreme warm periods, in the city of Munich, Germany. To compute the relationship between Land Surface Temperature (LST) and Land Use Land Cover (LULC), MODIS eight-day interval LST data for the months of June, July and August from 2002 to 2012 and the Corine Land Cover (CLC) database were used. Due to similarities in the behavior of surface temperature of different CLCs, some classes were reclassified and combined to form two major, rather simplified, homogenized classes: one of built-up area and one of urban vegetation. The homogenized map was merged with the MODIS eight-day interval LST data to compute the relationship between them. The results revealed that (i) the cooling effect accrued from urban vegetation tended to be non-linear; and (ii) a remarkable and stronger cooling effect in terms of LST was identified in regions where the proportion of vegetation cover was between seventy and almost eighty percent per square kilometer. The results also demonstrated that LST within urban vegetation was affected by the temperature of the surrounding built-up and that during the well-known European 2003 heat wave, suburb areas were cooler from the core of the urbanized region. This study concluded that the optimum green space for obtaining the lowest temperature is a non-linear trend. This could support urban planning strategies to facilitate appropriate applications to mitigate heat-stress in urban area.

Predicting land use dynamics, surface temperature and urban thermal field variance index in mild cold climate urban area of Pakistan

Urbanization has led to one of the most important climatic issues i.e., the Urban Heat Island (UHI) phenomenon. In Chennai Metropolitan Area (CMA), the overall distribution of the green cover has gradually succumbed to urbanization whereas the temperatures have soared by 1.3 deg C in the past six decades. Urban vegetation provides shade and protects the buildings from direct solar exposure, thus reduces the UHI. Further, it also sequester large quantities of carbon, reduce storm water runoff and function as noise filters and pollutant traps. In comparison with the international UHI studies, the studies concerning Indian UHI are limited. Hence, the aim of the current research work is to understand the seasonal relationship between Land Surface Temperature (LST) and the Normalised Difference Vegetation Index (NDVI) of CMA using LANDSAT 4, 5, 7 and 8 images captured during the years 1988, 1991, 1996, 2000, 2008, 2013 and 2016. The results are discussed under three parts namely, Part-A, Part-B, and Part-C. Part-A results infer that the CMA is covered predominantly by minimum LST values (9 deg C to 25 deg C) and maximum LST values (25 deg C to 50 deg C) during Monsoon and Summer/Post-Monsoon seasons, respectively. The mean LST of the CMA is between 18 deg C to 31 deg C throughout the year. In Part B analysis results, the study establishes a moderate seasonal correlation between LST and the NDVI values (r-values between -0.2648 and 0.3604). According to Part C results, ‘High Vegetation’ (NDVI values 0.5 to 1) has a significant role in maintaining the average LST during all four seasons. Further, it also has the potential to reduce the LST values during the summer season in CMA. However, due to a moderate correlation, the urban vegetation may reduce the LST value only as an outcome of reducing the rest of the UHI contributors.

This research aims to analyze temperatures for periods of heat waves using the Earth's surface temperature index (LST) and linking it to the vegetation density index data (NDV), using GIS techniques, and using the data of the LANDSAT 8 satellite visuals represented by Band 10 - Thermal Infrared (TIRS) to estimate the temperature The temperature of brightness, and the two bands Band 4 - Red and Band 5 - Near infrared (NIR) were used during the heat waves in July, August and September of 2020. The study concluded that the surface temperature of the earth ranged between 40-48 m and constituted approximately 70% of the area The totality, which was recorded during the months of August and September, while the surface temperature, which ranged between 27-43 degrees, constituted approximately 30% of the total area, which was recorded during the month of July. As for the NDVI vegetation index, it turned out that the negative values are low compared to the positive values, which indicates the existence of lands with moderate vegetation cover. Thus, the rise in temperatures affects the open areas with no vegetation cover more than the areas with vegetation cover. Keywords: Land Surface Temperature (LST), Land Surface Emissivity (LSE), Normalized Difference Vegetation Index (NDVI), Remote sensing, Irbid governorate, Heat waves.

A study of urban heat island effects using remote sensing and GIS techniques in Kancheepuram, Tamil Nadu, India

This study examines the spatio-temporal variations of Land Surface Temperature (LST) in Taraba Central Senatorial District, Nigeria, from 1987 to 2022, using remote sensing and GIS techniques. The research assesses LST trends in relation to land use/land cover (LULC) changes, highlighting the impact of deforestation, agricultural expansion, and urbanization on surface temperature dynamics. Landsat satellite imagery was analyzed to retrieve LST values and detect patterns of thermal variation across different land-use types. The findings reveal a significant increase in LST over time, with a notable reduction in cooler temperature zones and an expansion of hotter areas, particularly in built-up and deforested regions. Vegetated areas maintained lower LST, underscoring the role of natural land cover in temperature regulation. These results emphasize the need for sustainable land management strategies, afforestation programs, and climate adaptation policies to mitigate rising temperatures and promote environmental sustainability. The study demonstrates the effectiveness of geospatial techniques in monitoring LST variations and provides critical insights for policymakers and environmental planners in addressing climate-related challenges in the region..

Large and comparatively compact European cities such as Bucharest and Leipzig struggle with considerable urban heat island (UHI) effects characterized by heat and drought together with high concentrations of air pollutants (NO2, SO2, O3, CO2). However, a healthy urban green infrastructure is necessary to reduce the impacts of UHI on human health. Therefore, continuous monitoring schemes are required for green infrastructure in order to improve human life in such cities. Satellite remote sensing can provide the means for monitoring urban vegetation status. In this study, vegetation indices, mostly based on the spectral bands located in the red-edge region, were computed from Sentinel-2 imagery, and land surface temperature (hereafter LST) was estimated from Landsat 8 data. The aim was to assess the individual and cumulative effects of both vicinity to roads and estimated LST on tree vegetation health in urban parks using analysis of variance. Vegetation indices indicated stressed vegetation. However, tracking urban tree health required a combination of indices, and therefore of spectral ranges, rather than one specific index alone, as the effect sizes varied between parks, cities and along the centre-periphery gradient. Therefore, spaceborne data can provide spatially-explicit indicators for stressed urban vegetation and, thus, decreasing ecosystem services delivery. Future studies are encouraged to decipher further the relation the spatial configuration of urban systems and remote sensing based stress indicators of urban trees using publicly available datasets to enable comparative studies.