Relation between urban volume and land surface temperature: A comparative study of planned and traditional cities in Japan

The horizontal two-dimensional (2D) urban land use approach is not sufficient to trace rapid changes in urban environment. Hence, a three-dimensional (3D) approach that is different from the traditional geographical method is necessary to understand the mechanism of compound urban diversity. Using remote sensing data captured in 2010/2011 and geospatial tools and techniques, we quantified the urban volume (UV, consisting of urban built volume (UBV) and urban green volume (UGV)) and retrieved and mapped the land surface temperature (LST) of two cities in Japan (Tsukuba, a planned city, and Tsuchiura, a traditional city). We compared these two cities in terms of (1) UBV and UGV and their relationships with mean LST; and (2) the relationship of the UGV–UBV ratio with mean LST. Tsukuba had a total UBV of 74 million m3, while Tsuchiura had a total of 89 million m3. In terms of UGV, Tsukuba had a total of 52 million m3, while Tsuchiura had a total of 29 million m3. In both cities, UBV had a positive relationship with mean LST (Tsukuba: R2 = 0.31, p < 0.001; Tsuchiura: R2 = 0.42, p < 0.001), and UGV had a negative relationship with mean LST (Tsukuba: R2 = 0.53, p < 0.001; Tsuchiura: R2 = 0.19, p < 0.001). Tsukuba also had a higher UGV–UBV ratio of 54.9% in comparison with Tsuchiura, with 28.7%. Overall, the results indicate that mean LST was more intense in the traditional city (Tsuchiura). This could have been due to the difference in urban spatial structure. As a planned city, Tsukuba is still a relatively young city that has more dispersed green spaces and a well-spread (so far) built-up area

ANÁLISE ESPAÇO-TEMPORAL DA EVOLUÇÃO DO IBI E NDVI NA ZONA OESTE DA CIDADE DO RIO DE JANEIRO/RJ ENTRE 2001 E 2020

A Zona Oeste (ZO) da cidade do Rio de Janeiro compõe um cenário heterogêneo, contendo áreas urbanizadas, vegetadas e de transição entre o uso urbano e o de vegetação. O sensoriamento remoto fornece dados que viabilizam o cálculo de índices temáticos, que são aplicados como ferramentas de mensuração e análise dessas contrastantes realidades. Este trabalho tem como objetivo analisar a variação espacial dos índices temáticos Índice de Vegetação por Diferença Normalizada (NDVI) e do Índice de Área Construída (IBI) na Zona Oeste da cidade do Rio de Janeiro entre os anos de 2021 e 2020 com base nas imagens de satélite Landsat 5, 7 e 8. Por meio de código em linguagem computacional C foram corrigidas as imagens, calculados os índices e gerados quatro mapas para cada um dos índices a cada cinco anos a partir da Composição de Máximo Valor (CMV). O IBI descreve as áreas com maior densidade urbana, enquanto o NDVI destaca áreas vegetadas. Como resultado das análises nas Regiões Administrativas (RAs), há uma nítida expansão urbana nas regiões da Barra da Tijuca e Jacarepaguá com a presença de novos empreendimentos. As RAs Bangu e Realengo mantiveram seus padrões altamente urbanos nas áreas centrais, concentrando os espaços de vegetação nos limites administrativos com as cidades adjacentes e nos maciços costeiros como Pedra Branca e Mendanha. A RA de Campo Grande, Santa Cruz e Guaratiba apresentaram alterações pontuais destacadas por manchas nos mapas de IBI e NDVI como aumento da área urbana, sendo principalmente devido à implantação de áreas industriais. A RA Cidade de Deus mostrou altos valores de IBI e baixo NDVI, indicando um padrão mais urbano em toda sua extensão. Conclui-se que o estudo dos índices IBI e NDVI se complementam nas análises e destacam de forma oposta os fenômenos de evolução urbana nas áreas observadas. As análises podem ser aplicadas para estudos ambientais, direcionamento de recursos, manutenção de áreas de conservação/preservação contribuindo para políticas públicas

Quantifying Surface Urban Heat Island Formation in the World Heritage Tropical Mountain City of Sri Lanka

Presently, the urban heat island (UHI) phenomenon, and its adverse impacts, are becoming major research foci in various interrelated fields due to rapid changes in urban ecological environments. Various cities have been investigated in previous studies, and most of the findings have facilitated the introduction of proper mitigation measures to overcome the negative impact of UHI. At present, most of the mountain cities of the world have undergone rapid urban development, and this has resulted in the increasing surface UHI (SUHI) phenomenon. Hence, this study focuses on quantifying SUHI in Kandy City, the world heritage tropical mountain city of Sri Lanka, using Landsat data (1996 and 2017) based on the mean land surface temperature (LST), the difference between the fraction of impervious surfaces (IS), and the fraction of green space (GS). Additionally, we examined the relationship of LST to the green space/impervious surface fraction ratio (GS/IS fraction ratio) and the magnitude of the GS/IS fraction ratio. The SUHI intensity (SUHII) was calculated based on the temperature difference between main land use/cover categories and the temperature difference between urban-rural zones. We demarcated the rural zone based on the fraction of IS recorded, <10%, along with the urban-rural gradient zone. The result shows a SUHII increase from 3.9 °C in 1996 to 6.2 °C in 2017 along the urban-rural gradient between the urban and rural zones (10 < IS). These results relate to the rapid urban expansion of the study areas from 1996 to 2017. Most of the natural surfaces have changed to impervious surfaces, causing an increase of SUHI in Kandy City. The mean LST has a positive relationship with the fraction of IS and a negative relationship with the fraction of GS. Additionally, the GS/IS fraction ratio shows a rapid decline. Thus, the findings of this study can be considered as a proxy indicator for introducing proper landscape and urban planning for the World Heritage tropical mountain city of Kandy in Sri Lanka

Land use change and climate variation in the Three Gorges Reservoir Catchment from 2000 to 2015 based on the Google Earth Engine

Possible environmental change and ecosystem degradation have received increasing attention since the construction of Three Gorges Reservoir Catchment (TGRC) in China. The advanced Google Earth Engine (GEE) cloud-based platform and the large number of Geosciences and Remote Sensing datasets archived in GEE were used to analyze the land use and land cover change (LULCC) and climate variation in TGRC. GlobeLand30 data were used to evaluate the spatial land dynamics from 2000 to 2010 and Landsat 8 Operational Land Imager (OLI) images were applied for land use in 2015. The interannual variations in the Land Surface Temperature (LST) and seasonally integrated normalized difference vegetation index (SINDVI) were estimated using Moderate Resolution Imaging Spectroradiometer (MODIS) products. The climate factors including air temperature, precipitation and evapotranspiration were investigated based on the data from the Global Land Data Assimilation System (GLDAS). The results indicated that from 2000 to 2015, the cultivated land and grassland decreased by 2.05% and 6.02%, while the forest, wetland, artificial surface, shrub land and waterbody increased by 3.64%, 0.94%, 0.87%, 1.17% and 1.45%, respectively. The SINDVI increased by 3.209 in the period of 2000-2015, while the LST decreased by 0.253 °C from 2001 to 2015. The LST showed an increasing trend primarily in urbanized area, with a decreasing trend mainly in forest area. In particular, Chongqing City had the highest LST during the research period. A marked decrease in SINDVI occurred primarily in urbanized areas. Good vegetation areas were primarily located in the eastern part of the TGRC, such as Wuxi County, Wushan County, and Xingshan County. During the 2000–2015 period, the air temperature, precipitation and evapotranspiration rose by 0.0678 °C/a, 1.0844 mm/a, and 0.4105 mm/a, respectively. The climate change in the TGRC was influenced by LULCC, but the effect was limited. What is more, the climate change was affected by regional climate change in Southwest China. Marked changes in land use have occurred in the TGRC, and they have resulted in changes in the LST and SINDVI. There was a significantly negative relationship between LST and SINDVI in most parts of the TGRC, especially in expanding urban areas and growing forest areas. Our study highlighted the importance of environmental protection, particularly proper management of land use, for sustainable development in the catchment

Influence of Permeable Interlocking Concrete Paver Performance on Infiltration and Temperature in and Urban Watershed

Urbanization is a form of land use change that typically results in an expansion of impervious surfaces and increased soil compaction. These urban-induced changes in watershed hydrology can result in stream channel erosion, degraded water quality and stream aquatic habitat, increased ambient air temperatures, and increased peak flows, all of which pose challenges to stormwater management. Recent efforts to improve stormwater treatment have included the implementation of green stormwater infrastructure (GSI), which include a range of measures that use plant or soil systems, permeable surfaces or other features to store, infiltrate, or evapotranspire stormwater and reduce flows to storm sewer systems and surface waters. Permeable Interlocking Concrete Pavers (PICP) are one type of GSI implemented in urban settings to reduce runoff through infiltration of stormwater at its source. Over the past decade, East Carolina University has been implementing GSI on their Greenville, NC East Campus, and has installed approximately 0.3 hectares (3,000 square meters) of PICPs, to reduce flooding and ponding and urban stormwater impacts to local streams. Surface infiltration rates were measured at 18 PICP, 10 forested, 21 campus lawn, and 12 fractured asphalt locations to evaluate the effectiveness of PICPs on campus. Infiltration rates between the groups were significantly different (p < 0.05). The median infiltration rate of PICP sites was 587.41 cm/h and it was estimated that peak discharge to local streams may be reduced by approximately 11.47 cubic feet per second (cfs) with current PICP installations. Regular asphalt (RA) sites were tested for infiltration where fractures in the pavement intersected, with a median infiltration rate of 3.8 cm/h; however, there were not enough data to draw conclusions on the secondary permeability of fractured asphalt in this study. Forested and campus lawn soils had median infiltration rates of 5.46 cm/h and 0.95 cm/h, respectively. A total of 93 soil cone index values (kPa) were taken at campus lawn (n = 63) and forested (n = 30) sites to determine the effect of existing surface conditions on infiltration rates. There was a significant difference between infiltration rates (p = 0.007) and maximum compaction values (p = 0.000) for forested and campus lawn sites. Surface temperatures were taken at each PICP site and RA parking lots for comparison. Recorded surface temperatures for both asphalt and PICP were lowest between 9 pm and 6 am, with the median temperature of asphalt being 1.64 °C warmer. Data collected and analyzed from this study showed that fractured asphalt and campus lawns had significantly lower infiltration rates compared to forested soils and PICP installations. Moreover, relative to PICPs, asphalt displayed elevated surface temperatures for longer periods of time that contribute to local environmental warming. The results in this study indicate that PICPs are effective in sandy soils for the management of stormwater runoff in urban settings as an alternative or addition to traditional gray infrastructure (pipes, ditches, concrete curbs, and culverts), and PICPs have the potential to minimize effects of the UHI by maintaining lower nighttime temperatures and shorter periods of peak temperatures

Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

The urban heat island (UHI) effect resulting from rapid urbanization generally has a negative impact on urban residents. Shijiazhuang, the capital of Hebei Province in China, was selected to assess surface thermal patterns and its correlation with Land Cover Types (LCTs). This study was conducted using Landsat TM images on the mesoscale level and airborne hyperspectral thermal images on the microscale level. Land surface temperature (LST) was retrieved from four scenes of Landsat TM data in the summer days to analyze the thermal spatial patterns and intensity of surface UHI (SUHI). Surface thermal characteristics were further examined by relating LST to percentage of imperious surface area (ISA%) and four remote sensing indices (RSIs), the Normalized Difference Vegetation Index (NDVI), Universal Pattern Decomposition method (VIUPD), Normalized Difference Built-up Index (NDBI) and Biophysical Composition Index (BCI). On the other hand, fives scenes of airborne TASI (Thermal Airborne Spectrographic Imager sensor) images were utilized to describe more detailed urban thermal characteristics of the downtown of Shijiazhuang city. Our results show that an obvious surface heat island effect existed in the study area during summer days, with a SUHI intensity of 2–4 °C. The analyses reveal that ISA% can provide an additional metric for the study of SUHI, yet its association with LST is not straightforward and this should a focus in future work. It was also found that two physically based indices, VIUPD and BCI, have the potential to account for the variation in urban LST. The results concerning on TASI indicate that diversity of impervious surfaces (rooftops, concrete, and mixed asphalt) contribute most to the SUHI, among all of the land cover features. Moreover, the effect of impervious surfaces on LST is complicated, and the composition and arrangement of land cover features may play an important role in determining the magnitude and intensity of SUHI. Overall, the analysis of urban thermal signatures at two spatial scales complement each other and the use of airborne imagery data with higher spatial resolution is helpful in revealing more details for understanding urban thermal environments

Analysis of the Urban Heat Island Effect in Shijiazhuang, China Using Satellite and Airborne Data

The urban heat island (UHI) effect resulting from rapid urbanization generally has a negative impact on urban residents. Shijiazhuang, the capital of Hebei Province in China, was selected to assess surface thermal patterns and its correlation with Land Cover Types (LCTs). This study was conducted using Landsat TM images on the mesoscale level and airborne hyperspectral thermal images on the microscale level. Land surface temperature (LST) was retrieved from four scenes of Landsat TM data in the summer days to analyze the thermal spatial patterns and intensity of surface UHI (SUHI). Surface thermal characteristics were further examined by relating LST to percentage of imperious surface area (ISA%) and four remote sensing indices (RSIs), the Normalized Difference Vegetation Index (NDVI), Universal Pattern Decomposition method (VIUPD), Normalized Difference Built-up Index (NDBI) and Biophysical Composition Index (BCI). On the other hand, fives scenes of airborne TASI (Thermal Airborne Spectrographic Imager sensor) images were utilized to describe more detailed urban thermal characteristics of the downtown of Shijiazhuang city. Our results show that an obvious surface heat island effect existed in the study area during summer days, with a SUHI intensity of 2–4 °C. The analyses reveal that ISA% can provide an additional metric for the study of SUHI, yet its association with LST is not straightforward and this should a focus in future work. It was also found that two physically based indices, VIUPD and BCI, have the potential to account for the variation in urban LST. The results concerning on TASI indicate that diversity of impervious surfaces (rooftops, concrete, and mixed asphalt) contribute most to the SUHI, among all of the land cover features. Moreover, the effect of impervious surfaces on LST is complicated, and the composition and arrangement of land cover features may play an important role in determining the magnitude and intensity of SUHI. Overall, the analysis of urban thermal signatures at two spatial scales complement each other and the use of airborne imagery data with higher spatial resolution is helpful in revealing more details for understanding urban thermal environments

The use of satellite data, meteorology and land use data to define high resolution temperature exposure for the estimation of health effects in Italy

Introduction. Despite the mounting evidence on heat-related health risks, there is limited evidence in suburban and rural areas. The limited spatial resolution of temperature data also hinders the evidence of the differential heat effect within cities due to individual and area-based characteristics. Methods. Satellite land surface temperature (LST), observed meteorological and spatial and spatio-temporal land use data were combined in mixed-effects regression models to estimate daily mean air temperature with a 1x1km resolution for the period 2000-2010. For each day, random intercepts and slopes for LST were estimated to capture the day-to-day temporal variability of the Ta–LST relationship. The models were also nested by climate zones to better capture local climates and daily weather patterns across Italy. The daily exposure data was used to estimate the effects and impacts of heat on cause-specific mortality and hospital admissions in the Lazio region at municipal level in a time series framework. Furthermore, to address the differential effect of heat within an urban area and account for potential effect modifiers a case cross-over study was conducted in Rome. Mean temperature was attributed at the individual level to the Rome Population Cohort and the urban heat island (UHI) intensity using air temperature data was calculated for Rome. Results. Exposure model performance was very good: in the stage 1 model (only on grid cells with both LST and observed data) a mean R2 value of 0.96 and RMSPE of 1.1°C and R2 of 0.89 and 0.97 for the spatial and temporal domains respectively. The model was also validated with regional weather forecasting model data and gave excellent results (R2=0.95 RMSPE=1.8°C. The time series study showed significant effects and impacts on cause-specific mortality in suburban and rural areas of the Lazio region, with risk estimates comparable to those found in urban areas. High temperatures also had an effect on respiratory hospital admissions. Age, gender, pre-existing cardiovascular disease, marital status, education and occupation were found to be effect modifiers of the temperature-mortality association. No risk gradient was found by socio-economic position (SEP) in Rome. Considering the urban heat island (UHI) and SEP combined, differential effects of heat were observed by UHI among same SEP groupings. Impervious surfaces and high urban development were also effect modifiers of the heat-related mortality risk. Finally, the study found that high resolution gridded data provided more accurate effect estimates especially for extreme temperature intervals. Conclusions. Results will help improve heat adaptation and response measures and can be used predict the future heat-related burden under different climate change scenarios.Open Acces