Quantitative-spatial relationships between air and surface temperature, a proxy for microclimate studies in fine-scale intra-urban areas?

2022 ◽  
Vol 77 ◽  
pp. 103584
Author(s):  
Majid Amani-Beni ◽  
Yang Chen ◽  
Mariia Vasileva ◽  
Biao Zhang ◽  
Gao-di Xie
Keyword(s):  
Surface Temperature ◽  
Urban Areas ◽  
Spatial Relationships ◽  
Fine Scale

scholarly journals Ecological Connectivity in Agricultural Green Infrastructure:  Suggested Criteria for Fine Scale Assessment and Planning

Land ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 807
Author(s):  
Simone Valeri ◽  
Laura Zavattero ◽  
Giulia Capotorti
Keyword(s):  
Land Cover ◽  
Green Infrastructure ◽  
Rural Areas ◽  
Urban Areas ◽  
Landscape Heterogeneity ◽  
Agricultural Landscapes ◽  
Spatial Pattern Analysis ◽  
Fine Scale ◽  
Unique Type

In promoting biodiversity conservation and ecosystem service capacity, landscape connectivity is considered a critical feature to counteract the negative effects of fragmentation. Under a Green Infrastructure (GI) perspective, this is especially true in rural and peri-urban areas where a high degree of connectivity may be associated with the enhancement of agriculture multifunctionality and sustainability. With respect to GI planning and connectivity assessment, the role of dispersal traits of tree species is gaining increasing attention. However, little evidence is available on how to select plant species to be primarily favored, as well as on the role of landscape heterogeneity and habitat quality in driving the dispersal success. The present work is aimed at suggesting a methodological approach for addressing these knowledge gaps, at fine scales and for peri-urban agricultural landscapes, by means of a case study in the Metropolitan City of Rome. The study area was stratified into Environmental Units, each supporting a unique type of Potential Natural Vegetation (PNV), and a multi-step procedure was designed for setting priorities aimed at enhancing connectivity. First, GI components were defined based on the selection of the target species to be supported, on a fine scale land cover mapping and on the assessment of land cover type naturalness. Second, the study area was characterized by a Morphological Spatial Pattern Analysis (MSPA) and connectivity was assessed by Number of Components (NC) and functional connectivity metrics. Third, conservation and restoration measures have been prioritized and statistically validated. Notwithstanding the recognized limits, the approach proved to be functional in the considered context and at the adopted level of detail. Therefore, it could give useful methodological hints for the requalification of transitional urban–rural areas and for the achievement of related sustainable development goals in metropolitan regions.

scholarly journals Identificação de Ilhas de Calor na Cidade de Campina Grande-PB Utilizando Sensoriamento Remoto (Identification of Heat Islands in Campina Grande City-PB Using Remote Sensing)

2016 ◽  
Vol 9 (2) ◽  
pp. 614 ◽  
Author(s):  
Elânia Daniele Silva Araújo
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Rural Areas ◽  
Urban Areas ◽  
Spatial And Temporal Variability ◽  
Heat Islands ◽  
Social Nature ◽  
Spatial Changes ◽  
Remote Sensing Techniques ◽  
The City

A intensa urbanização causa diversos problemas de natureza ambiental, climática e social. O crescimento não planejado da população urbana e a remoção da vegetação são fatores que intensificam estes problemas. As temperaturas na cidade são significativamente mais quentes do que as suas zonas rurais circundantes devido às atividades humanas. As intensas mudanças espaciais em áreas urbanas, promovem significativo aumento na temperatura, causando o chamado efeito de Ilha de Calor Urbano (ICU). Campina Grande é uma cidade de tamanho médio que experimentou um crescimento desordenado, desde o tempo do comércio de algodão e, como qualquer cidade de grande ou médio porte, sofre alterações em seu espaço. Dessa forma, este estudo teve por objetivo analisar a variabilidade espaço-temporal da temperatura da superfície (Ts) e detectar ICU, através de técnicas de sensoriamento remoto. Para o efeito, foram utilizadas imagens dos satélites Landsat 5 e 8, dos anos de 1995, 2007 e 2014. Aumentos da Ts foram bem evidentes e foram detectadas duas ICU. Campina Grande mostra um padrão de tendência: o crescimento urbano não planejado é responsável por mudanças no ambiente físico e na forma e estrutura espacial da cidade, o que se reflete sobre o microclima e, em última análise, na qualidade de vida das pessoas.   ABSTRACT The intense urbanization causes several problems of environmental, climate and social nature. The unplanned growth of urban population and the vegetation removal are factors that deepen these problems. Temperatures in the city are significantly warmer than its surrounding rural areas due to human activities. Large spatial changes in urban areas promote significant increase in temperature, causing the so-called Urban Heat Island effect (UHI). Campina Grande is a medium-sized town that experienced an uncontrolled growth since the time of the cotton trade and like any large or medium-sized city, undergoes changes in its space. Therefore, this study aimed to analyze surface temperature spatial and temporal variability and to detect potential UHI, through remote sensing techniques. Spectral images from Landsat 5 and 8 satellites were used. Using images from years 1995, 2007 and 2014, considerable increases in temperature were identified and two UHI were recognize. Campina Grande shows a trend pattern: the urban unplanned growth is responsible for changes in the physical environment and in the form and spatial structure of the city, reflecting on people quality of life. Keywords: change detection, surface temperature, heat islands, urbanization.   

scholarly journals Impact of Multitemporal Land Use and Land Cover Change on Land Surface Temperature Due to Urbanization in Hefei City, China

2021 ◽  
Vol 10 (12) ◽  
pp. 809
Author(s):  
Jing Sun ◽  
Suwit Ongsomwang
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Decomposition Analysis ◽  
Lulc Change ◽  
Main Components ◽  
The Impact

Land surface temperature (LST) is an essential parameter in the climate system whose dynamics indicate climate change. This study aimed to assess the impact of multitemporal land use and land cover (LULC) change on LST due to urbanization in Hefei City, Anhui Province, China. The research methodology consisted of four main components: Landsat data collection and preparation; multitemporal LULC classification; time-series LST dataset reconstruction; and impact of multitemporal LULC change on LST. The results revealed that urban and built-up land continuously increased from 2.05% in 2001 to 13.25% in 2020. Regarding the impact of LULC change on LST, the spatial analysis demonstrated that the LST difference between urban and non-urban areas had been 1.52 K, 3.38 K, 2.88 K and 3.57 K in 2001, 2006, 2014 and 2020, respectively. Meanwhile, according to decomposition analysis, regarding the influence of LULC change on LST, the urban and built-up land had an intra-annual amplitude of 20.42 K higher than other types. Thus, it can be reconfirmed that land use and land cover changes due to urbanization in Hefei City impact the land surface temperature.

scholarly journals Quantifying the Effects of Urban Form on Land Surface Temperature in Subtropical High-Density Urban Areas Using Machine Learning

2019 ◽  
Vol 11 (8) ◽  
pp. 959 ◽  
Author(s):  
Yanwei Sun ◽  
Chao Gao ◽  
Jialin Li ◽  
Run Wang ◽  
Jian Liu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Form ◽  
Urban Areas ◽  
Thermal Environment ◽  
High Density ◽  
Cooling Effects ◽  
Urban Thermal Environment ◽  
The Impact

It is widely acknowledged that urban form significantly affects urban thermal environment, which is a key element to adapt and mitigate extreme high temperature weather in high-density urban areas. However, few studies have discussed the impact of physical urban form features on the land surface temperature (LST) from a perspective of comprehensive urban spatial structures. This study used the ordinary least-squares regression (OLS) and random forest regression (RF) to distinguish the relative contributions of urban form metrics on LST at three observation scales. Results of this study indicate that more than 90% of the LST variations were explained by selected urban form metrics using RF. Effects of the magnitude and direction of urban form metrics on LST varied with the changes of seasons and observation scales. Overall, building morphology and urban ecological infrastructure had dominant effects on LST variations in high-density urban centers. Urban green space and water bodies demonstrated stronger cooling effects, especially in summer. Building density (BD) exhibited significant positive effects on LST, whereas the floor area ratio (FAR) showed a negative influence on LST. The results can be applied to investigate and implement urban thermal environment mitigation planning for city managers and planners.

scholarly journals Validation of ASTER Surface Temperature Data withIn SituMeasurements to Evaluate Heat Islands in Complex Urban Areas

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Bonggeun Song ◽  
Kyunghun Park
Keyword(s):  
Surface Temperature ◽  
Urban Areas ◽  
Thermal Emission ◽  
Temperature Data ◽  
Spatial Characteristics ◽  
Heat Islands ◽  
Land Covers ◽  
Surface Temperature Data ◽  
City Park

This study compared Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) surface temperature data within situmeasurements to validate the use of ASTER data for studying heat islands in urban settings with complex spatial characteristics. Eight sites in Changwon, Korea, were selected for analyses. Surface temperature data were extracted from the thermal infrared (TIR) band of ASTER on four dates during the summer and fall of 2012, and correspondingin situmeasurements of temperature were also collected. Comparisons showed that ASTER derived temperatures were generally 4.27°C lower than temperatures collected byin situmeasurements during the daytime, except on cloudy days. However, ASTER temperatures were higher by 2.23–2.69°C on two dates during the nighttime. Temperature differences between a city park and a paved area were insignificant. Differences between ASTER derived temperatures and onsite measurements are caused by a variety of factors including the application of emissivity values that do not consider the complex spatial characteristics of urban areas. Therefore, to improve the accuracy of surface temperatures extracted from infrared satellite imagery, we propose a revised model whereby temperature data is obtained from ASTER and emissivity values for various land covers are extracted based onin situmeasurements.

scholarly journals Response of Near-Surface Meteorological Conditions to Advection under Impact of the Green Roof

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 759
Author(s):  
Haochen Tan ◽  
Pallav Ray ◽  
Mukul Tewari ◽  
James Brownlee ◽  
Ajaya Ravindran
Keyword(s):  
Surface Temperature ◽  
Urban Areas ◽  
Green Roof ◽  
Wrf Model ◽  
Single Layer ◽  
Meteorological Conditions ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Budget Analysis ◽  
The Impact

Due to rapid urbanization, the near-surface meteorological conditions over urban areas are greatly modulated. To capture such modulations, sophisticated urban parameterizations with enhanced hydrological processes have been developed. In this study, we use the single-layer urban canopy model (SLUCM) available within the Weather Research and Forecasting (WRF) model to assess the response of near-surface temperature, wind, and moisture to advection under the impact of the green roof. An ensemble of simulations with different planetary boundary layer (PBL) schemes is conducted in the presence (green roof (GR)) and absence (control (CTL)) of green roof systems. Our results indicate that the near-surface temperature is found to be driven primarily by the surface heat flux with a minor influence from the zonal advection of temperature. The momentum budget analysis shows that both zonal and meridional momentum advection during the evening and early nighttime plays an important role in modulating winds over urban areas. The near-surface humidity remains nearly unchanged in GR compared to CTL, although the physical processes that determine the changes in humidity were different, in particular during the evening when the GR tends to have less moisture advection due to the reduced temperature gradient between the urban areas and the surroundings. Implications of our results are discussed.

Reconciling the Spatial Distribution of the Surface Temperature Trends in the Southeastern United States

2012 ◽  
Vol 25 (10) ◽  
pp. 3610-3618 ◽  
Author(s):  
V. Misra ◽  
J.-P. Michael ◽  
R. Boyles ◽  
E. P. Chassignet ◽  
M. Griffin ◽  
...  
Keyword(s):  
United States ◽  
South Carolina ◽  
Surface Temperature ◽  
Spatial Heterogeneity ◽  
Rural Areas ◽  
Urban Areas ◽  
Summer Season ◽  
Boreal Summer ◽  
Temperature Trends ◽  
Linear Trends

Abstract This study attempts to explain the considerable spatial heterogeneity in the observed linear trends of monthly mean maximum and minimum temperatures (Tmax and Tmin) from station observations in the southeastern (SE) United States (specifically Florida, Alabama, Georgia, South Carolina, and North Carolina). In a majority of these station sites, the warming trends in Tmin are stronger in urban areas relative to rural areas. The linear trends of Tmin in urban areas of the SE United States are approximately 7°F century−1 compared to about 5.5°F century−1 in rural areas. The trends in Tmax show weaker warming (or stronger cooling) trends with irrigation, while trends in Tmin show stronger warming trends. This functionality of the temperature trends with land features also shows seasonality, with the boreal summer season showing the most consistent relationship in the trends of both Tmax and Tmin. This study reveals that linear trends in Tmax in the boreal summer season show a cooling trend of about 0.5°F century−1 with irrigation, while the same observing stations on an average display warming trends in Tmin of about 3.5°F century−1. The seasonality and the physical consistency of these relationships with existing theories may suggest that urbanization and irrigation have a nonnegligible influence on the spatial heterogeneity of the surface temperature trends over the SE United States. The study also delineates the caveats and limitations of the conclusions reached herein due to the potential influence of perceived nonclimatic discontinuities (which incidentally could also have a seasonal cycle) that have not been taken into account.

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