Spatial Variation of Land Use/Cover Composition and Impact on Surface Urban Heat Island in a Tropical Sub-Saharan City of Accra, Ghana

Patterns and drivers of surface cooling effect of urban trees across global cities

Urban trees offer a promising strategy to mitigating rising heat stress in cities globally. However, the spatial distribution and influencing factors of the tree cooling effect across urban surfaces worldwide are not thoroughly understood. Here we quantified the surface cooling effect during the summer season across 1016 cities globally using two key metrics simultaneously - cooling intensity and cooling distance - primarily based on Landsat-8 land surface temperature data. We then investigated the impact of various drivers on the surface cooling effect, including tree attributes at the small scale (e.g., area and landscape shape index), urban characteristic at the medium scale (e.g., city population), and background climate at the large scale (e.g., air temperature and precipitation). Furthermore, the combined effects of urban and climatic contexts on the regulation of tree attributes on the surface cooling effect were examined. Our findings reveal that the global average cooling intensity is 1.67 ± 1.13 °C, while the global average cooling distance is 136.86 ± 60.44 m. Cooling intensity is mainly regulated by tree attributes (88 %), followed by background climate (9 %) and urban characteristic (3 %). The variable that explains the most variation in cooling intensity is the NDVI of trees at the small scale. Similarly, the cooling distance is primarily influenced by tree attributes (73 %), background climate (22 %), and urban characteristic (5 %). The area of trees at the small scale is the primary factor contributing to the variation in cooling distance. Additionally, the impact of tree attributes on cooling effect is jointly moderated by urban characteristic and background climate. In cities with larger populations or higher air temperatures, the area of trees and the landscape shape index exert a less pronounced impact on the cooling effect. This implies that the presence of small, widely dispersed tree cover in such urban areas can effectively provide the cooling intensity. Our study provides a crucial baseline for formulating tree cooling strategies and managing urban tree cover across global cities.

LST-R: A method for assessing land surface temperature reduction in urban, hot and semi-arid Global South

Over the next 30 years, temperatures are expected to increase in hot semi-arid zones. Despite increasing studies on urban heat, cooling measures suitable for this climate zone remain poorly investigated. The proposed method is innovative because it focuses on significant landscape metrics for determining the land surface temperature (LST) and evaluating cooling measures. Recurrence of warm spells was identified analysing the daily air temperatures. Daytime and night-time LST data acquired from space were correlated with landscape metrics extracted from very high-resolution satellite imagery. Stepwise linear regression was used to identify the significant metrics that affected it. Cooling measures were selected considering implementation leeway; performance of existing measures; strengths, weaknesses, opportunities, and threats, equity analyses. Although the method was tested in Niamey, Niger, it can be applied to any city or town in hot semi-arid Global South, requiring decision-making support on cooling policies.•Landscape metrics are consistent with development standard and general requirements.•Evaluation of measures to reduce land surface temperature includes experts... advice.•Equity of measures to reduce land surface temperature is considered.

Quantifying the spatial pattern of urban heat islands and the associated cooling effect of blue-green landscapes using multisource remote sensing data

Surface urban heat islands (SUHIs) are a global concern. Although their spatial pattern and the cooling effect of blue-green landscapes have been documented, exploring more accurate and quantitative results is still necessary. For Hangzhou, we combined nighttime light (NTL) data with LST images to investigate the spatial morphology of SUHIs and analyze the cooling effect of blue-green landscapes. The radiative transfer equation (RTE) method was used to derive the land surface temperature (LST). Then, based on the unique feature of Luojia1-01 NTL data, the concentric zone model (CZM) was proposed to depict the urban spatial structure. The CZM was applied to construct a number of equal-area concentric belts along the urban-rural gradient to determine the SUHI range and the corresponding blue-green landscape cooling effects. Finally, local Moran's I indices were adopted to identify the cold-hot spots of the SUHI and the relationship with land use. The minimum, average and maximum LSTs were 21.81 °C, 32.79 °C and 44.79 °C, respectively. Additionally, 59.16 % of the study area was affected by the SUHI, and the mean LST inside the SUHI was 36.4 °C, clearly higher than that of the rural area. The SUHI hotpots were clustered in regions with intensive human activities, forming archipelagos. Due to the different blue-green landscape densities, the cooling capacity had spatial heterogeneity in different urban rural belts (URBs), and the cooling capacity of URB₁₆ was approximately 71 times that of URB₁. The cooling efficiency increased with blue-green landscape density in general; hence, blue-green landscape density thresholds of 40 % and 70 % were recommended in the urban planning of different urban function zones. Relating the pattern of NTL data to LST images provide meaningful insight into the spatial pattern of SUHIs and the optimization of urban planning.

The relationship between land use land cover and land surface temperature using remote sensing: systematic reviews of studies globally over the past 5 years

The land surface temperature (LST) has been increased worldwide from time to time with the rapid increase of impervious surfaces such as built-up areas, parking lots, and asphalt and concrete roads. Several studies have examined the impacts of spatial dynamics of land use land cover (LULC) on the spatial variability of LST. However, there have not been systematic reviews conducted about the relationship between LULC and LST. Therefore, this study was conducted to investigate the relationship between LULC and LST with the main objective of synthesizing the relationship between LULC and LST using remote sensing data. An extensive literature search was conducted from the most familiar electronic databases such as Science Direct, Scopus, Web of Science, and Google Scholar between 27/08/2021 and 28/08/2021. The studies that are focussed on the relationship between LULC and LST and/or the impacts of LULC change on the LST using remote sensing were included for the analysis. Besides, papers conducted over the last 5 years (January/2016 to August/2021) were selected in this systematic study since this study focused on the most recent studies. In this systematic review, 100 studies were included for the study analysis. Based on the analysis of this study, built-up land has the first highest LST from the thirteen LULC types. Besides, bare land has a higher LST next to built-up land. On the other side, snow cover has the lowest LST among the LULC types. Lastly, waterbodies have a lower LST compared to vegetation cover.

Understanding the Links between LULC Changes and SUHI in Cities: Insights from Two-Decadal Studies (2001–2020)

An urban heat island (UHI) is a serious phenomenon associated with built environments and presents threats to human health. It is projected that UHI intensity will rise to record levels in the following decades due to rapid urban expansion, as two-thirds of the world population is expected to live in urban areas by 2050. Nevertheless, the last two decades have seen a considerable increase in the number of studies on surface UHI (SUHI)—a form of UHI quantified based on land surface temperature (LST) derived from satellite imagery—and its relationship with the land use/cover (LULC) changes. This surge has been facilitated by the availability of freely accessible five-decade archived remotely sensed data, the use of state-of-art analysis methods, and advancements in computing capabilities. The authors of this systematic review aimed to summarize, compare, and critically analyze multiple case studies—carried out from 2001 to 2020—in terms of various aspects: study area characteristics, data sources, methods for LULC classification and SUHI quantification, mechanisms of interaction coupled with linking techniques between SUHI intensity with LULC spatial and temporal changes, and proposed alleviation actions. The review could support decision-makers and pave the way for scholars to conduct future research, especially in vulnerable cities that have not been well studied.

Dynamic Changes of Local Climate Zones in the Guangdong–Hong Kong–Macao Greater Bay Area and Their Spatio-Temporal Impacts on the Surface Urban Heat Island Effect between 2005 and 2015

Local climate zones (LCZs) emphasize the influence of representative geometric properties and surface cover characteristics on the local climate. In this paper, we propose a multi-temporal LCZ mapping method, which was used to obtain LCZ maps for 2005 and 2015 in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA), and we analyze the effects of LCZ changes in the GBA on land surface temperature (LST) changes. The results reveal that: (1) The accuracy of the LCZ mapping of the GBA for 2005 and 2015 is 85.03% and 85.28%, respectively. (2) The built type category showing the largest increase in area from 2005 to 2015 is LCZ8 (large low-rise), with a 1.01% increase. The changes of the LCZs also vary among the cities due to the different factors, such as the economic development level and local policies. (3) The area showing a warming trend is larger than the area showing a cooling trend in all the cities in the GBA study area. The main reasons for the warming are the increase of built types, the enhancement of human activities, and the heat radiation from surrounding high-temperature areas. (4) The spatial morphology changes of the built type categories are positively correlated with the LST changes, and the morphological changes of the LCZ4 (open high-rise) and LCZ5 (open midrise) built types exert the most significant influence. These findings will provide important insights for urban heat mitigation via rational landscape design in urban planning management.

Quantifying the Cooling Effect and Scale of Large Inner-City Lakes Based on Landscape Patterns: A Case Study of Hangzhou and Nanjing

The rapid urbanization worldwide has brought various environmental problems. The urban heat island (UHI) phenomenon is one of the most concerning issues because of its strong relation with daily lives. Water bodies are generally considered a vital resource to relieve the UHI. In this context, it is critical to develop a method for measuring the cooling effect and scale of water bodies in urban areas. In this study, West Lake and Xuanwu Lake, two famous natural inner-city lakes, are selected as the measuring targets. The scatter plot and multiple linear regression model were employed to detect the relationship between the distance to the lake and land surface temperature based on Landsat 8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Sentinel-2 data. The results show that West Lake and Xuanwu Lake massively reduced the land surface temperature within a few hundred meters (471 m for West Lake and 336 m for Xuanwu Lake) and have potential cooling effects within thousands of meters (2900 m for West Lake and 3700 m for Xuanwu Lake). The results provide insights for urban planners to manage tradeoffs between the large lake design in urban areas and the cooling effect demands.

Urban Heat Island Formation in Greater Cairo: Spatio-Temporal Analysis of Daytime and Nighttime Land Surface Temperatures along the Urban–Rural Gradient

An urban heat island (UHI) is a significant anthropogenic modification of urban land surfaces, and its geospatial pattern can increase the intensity of the heatwave effects. The complex mechanisms and interactivity of the land surface temperature in urban areas are still being examined. The urban–rural gradient analysis serves as a unique natural opportunity to identify and mitigate ecological worsening. Using Landsat Thematic Mapper (TM), Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS), Land Surface Temperature (LST) data in 2000, 2010, and 2019, we examined the spatial difference in daytime and nighttime LST trends along the urban–rural gradient in Greater Cairo, Egypt. Google Earth Engine (GEE) and machine learning techniques were employed to conduct the spatio-temporal analysis. The analysis results revealed that impervious surfaces (ISs) increased significantly from 564.14 km2 in 2000 to 869.35 km2 in 2019 in Greater Cairo. The size, aggregation, and complexity of patches of ISs, green space (GS), and bare land (BL) showed a strong correlation with the mean LST. The average urban–rural difference in mean LST was −3.59 °C in the daytime and 2.33 °C in the nighttime. In the daytime, Greater Cairo displayed the cool island effect, but in the nighttime, it showed the urban heat island effect. We estimated that dynamic human activities based on the urban structure are causing the spatial difference in the LST distribution between the day and night. The urban–rural gradient analysis indicated that this phenomenon became stronger from 2000 to 2019. Considering the drastic changes in the spatial patterns and the density of IS, GS, and BL, urban planners are urged to take immediate steps to mitigate increasing surface UHI; otherwise, urban dwellers might suffer from the severe effects of heatwaves.

Impacts of Urbanization on the Muthurajawela Marsh and Negombo Lagoon, Sri Lanka: Implications for Landscape Planning towards a Sustainable Urban Wetland Ecosystem

Urban wetland ecosystems (UWEs) play important social and ecological roles but are often adversely affected by urban landscape transformations. Spatio-temporal analyses to gain insights into the trajectories of landscape changes in these ecosystems are needed for better landscape planning towards sustainable UWEs. In this study, we examined the impacts of urbanization on the Muthurajawela Marsh and Negombo Lagoon (MMNL), an important UWE in Sri Lanka that provides valuable ecosystem services. We used remote sensing data to detect changes in the land use/cover (LUC) of the MMNL over a two-decade period (1997–2017) and spatial metrics to characterize changes in landscape composition and configuration. The results revealed that the spatial and socio-economic elements of rapid urbanization of the MMNL had been the main driver of transformation of its natural environment over the past 20 years. This is indicated by a substantial expansion of settlements (+68%) and a considerable decrease of marshland and mangrove cover (−41% and −21%, respectively). A statistical analysis revealed a significant relationship between the change in population density and the loss of wetland due to settlement expansion at the Grama Niladhari division level (n = 99) (where wetland includes marshland, mangrove, and water) (1997–2007: R2 = 0.435, p = 0.000; 2007–2017: R2 = 0.343, p = 0.000). The findings also revealed that most of the observed LUC changes occurred in areas close to roads and growth nodes (viz. Negombo, Ja-Ela, Wattala, and Katana), which resulted in both landscape fragmentation and infill urban expansion. We conclude that, in order to ensure the sustainability of the MMNL, there is an urgent need for forward-looking landscape and urban planning to promote environmentally conscious urban development in the area which is a highly valuable UWE.