Effects of Urban Vegetation on Mitigating Exposure of Vulnerable Populations to Excessive Heat in Cleveland, Ohio

2016 ◽  
Vol 8 (4) ◽  
pp. 507-524 ◽  
Author(s):  
Juan Declet-Barreto ◽  
Kim Knowlton ◽  
G. Darrel Jenerette ◽  
Alexander Buyantuev
Keyword(s):  
Health Risks ◽  
Vulnerable Populations ◽  
Land Surface ◽  
Global Climate ◽  
Potential Temperature ◽  
High Heat ◽  
Tree Canopy ◽  
Urban Heat Islands ◽  
Effect Of Temperature ◽  
Cleveland Ohio

Abstract Hot weather is a threat to human health, especially in cities, where urban heat islands (UHIs) are elevating temperatures already on the rise from global climate change. Increased vegetation can help reduce temperatures and exposure to heat hazards. Here, an ensemble of geographically weighted regressions (GWR) on land surface temperature (LST) is conducted for May–October to estimate potential LST reductions from increased vegetation and to assess the effect of temperature reductions among vulnerable populations in Cleveland, Ohio. Possible tree canopy increases are applied to the results, and it is found that LST reductions can range from 6.4° to 0.5°C for May–October and are strongest from May to July. Potential LST reductions vary spatially according to possible canopy increases and are highest in suburban fringe neighborhoods and lower in downtown areas. Among populations at high heat-related health risks, the percentage of the population 65 years of age or older in Cleveland is negatively associated with LST, while percentages of Hispanics and those with low educational achievement are most positively associated with higher LST. The areas that have a high percentage of Hispanic also have the lowest potential temperature reductions from increased vegetation. Neighborhoods with the highest potential temperature reductions had the highest percentages of whites. Three subpopulations associated with high heat health risks are negatively correlated (African Americans and the elderly) or not correlated (persons living in poverty) with LST, and the relationships to LST reduction potential for all three are not statistically significant. Estimates of the effect of vegetation increases on LST can be used to target specific neighborhoods for UHI mitigation under possible and achievable policy-prescribed tree canopy scenarios in Cleveland.

scholarly journals MODIS Summer SUHI Cross-sections Anomalies over the Megacities of the Monsoon Asia Region and Global Trends

2017 ◽  
Vol 11 (1) ◽  
pp. 121-136 ◽  
Author(s):  
Hofit Itzhak-Ben-Shalom ◽  
Pinhas Alpert ◽  
Oded Potchter ◽  
Rana Samuels
Keyword(s):  
Cross Sections ◽  
Land Surface ◽  
Energy Use ◽  
Global Climate ◽  
Daily Basis ◽  
Urban Heat Islands ◽  
Anthropogenic Factors ◽  
City Center ◽  
Temperature Variations ◽  
The City

Background:Evidence has accumulated in recent years regarding the scope of local and global climate changes attributed to exacerbating anthropogenic factors such as accelerating population growth, urbanization, industrialization, traffic and energy use. Remote space monitoring, unlike ground-based measurements, has the advantage of providing global coverage on a daily basis.Methods:MODIS (Moderate Resolution Imaging Spectroradiometer) Aqua and Terra 1°×1° spatial resolution as well as the 1 km higher resolution of Aqua-MODIS were investigated for a global overview of megacities temperature variations, as well as the recent trends of the 10 largest Monsoon Asian megacities.Results:The average Land Surface Temperature (LST) cross-sections of the 10 Asian megacities were examined for June-August 2002-2014. Temperature variations fit a spatial bell-shaped curve, with a pronounced maximum over the city center. Nighttime data indicated sharp LST decreases with distance from the city center, particularly in the coldest cities, those of Tokyo, Seoul, Osaka and Beijing.Conclusion:Daytime latitudinal (E-W) and longitudinal (N-S) Surface Urban Heat Islands (SUHI) have steeper gradients than for nighttime data. During daytime, the SUHI gradients are largest in Tokyo, Seoul, Osaka and Beijing with values reaching 15oC followed by the cities of Shanghai and Guangzhou with ~11oC, and Karachi with ~5oC SUHI. Nighttime SUHIs were more moderate, 4-6oC in Tokyo, Seoul ~5oC, Osaka 5-7oC and Beijing ~7oC. Only in the three largest megacities,i.e., Tokyo, Guangzhou and Shanghai, did the nighttime LST trends decline.

Impact of LULC Changes on LST in Rajshahi District of Bangladesh: A Remote Sensing Approach

2020 ◽  
Vol 3 (1) ◽  
pp. 11-23 ◽  
Author(s):  
Abdulla Al Kafy ◽  
Abdullah Al-Faisal ◽  
Mohammad Mahmudul Hasan ◽  
Md. Soumik Sikdar ◽  
Mohammad Hasib Hasan Khan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface ◽  
Agricultural Land ◽  
Global Climate ◽  
Urban Expansion ◽  
Water Bodies ◽  
Landsat 8 ◽  
Lulc Changes ◽  
The Impact

Urbanization has been contributing more in global climate warming, with more than 50% of the population living in cities. Rapid population growth and change in land use / land cover (LULC) are closely linked. The transformation of LULC due to rapid urban expansion significantly affects the functions of biodiversity and ecosystems, as well as local and regional climates. Improper planning and uncontrolled management of LULC changes profoundly contribute to the rise of urban land surface temperature (LST). This study evaluates the impact of LULC changes on LST for 1997, 2007 and 2017 in the Rajshahi district (Bangladesh) using multi-temporal and multi-spectral Landsat 8 OLI and Landsat 5 TM satellite data sets. The analysis of LULC changes exposed a remarkable increase in the built-up areas and a significant decrease in the vegetation and agricultural land. The built-up area was increased almost double in last 20 years in the study area. The distribution of changes in LST shows that built-up areas recorded the highest temperature followed by bare land, vegetation and agricultural land and water bodies. The LULC-LST profiles also revealed the highest temperature in built-up areas and the lowest temperature in water bodies. In the last 20 years, LST was increased about 13ºC. The study demonstrates decrease in vegetation cover and increase in non-evaporating surfaces with significantly increases the surface temperature in the study area. Remote-sensing techniques were found one of the suitable techniques for rapid analysis of urban expansions and to identify the impact of urbanization on LST.

scholarly journals A Review of Reconstructing Remotely Sensed Land Surface Temperature under Cloudy Conditions

2021 ◽  
Vol 13 (14) ◽  
pp. 2838
Author(s):  
Yaping Mo ◽  
Yongming Xu ◽  
Huijuan Chen ◽  
Shanyou Zhu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Spatial Scales ◽  
Remotely Sensed ◽  
Urban Heat Islands ◽  
Reconstruction Algorithms ◽  
Gap Filling ◽  
Practical Applications ◽  
Data Gaps

Land surface temperature (LST) is an important environmental parameter in climate change, urban heat islands, drought, public health, and other fields. Thermal infrared (TIR) remote sensing is the main method used to obtain LST information over large spatial scales. However, cloud cover results in many data gaps in remotely sensed LST datasets, greatly limiting their practical applications. Many studies have sought to fill these data gaps and reconstruct cloud-free LST datasets over the last few decades. This paper reviews the progress of LST reconstruction research. A bibliometric analysis is conducted to provide a brief overview of the papers published in this field. The existing reconstruction algorithms can be grouped into five categories: spatial gap-filling methods, temporal gap-filling methods, spatiotemporal gap-filling methods, multi-source fusion-based gap-filling methods, and surface energy balance-based gap-filling methods. The principles, advantages, and limitations of these methods are described and discussed. The applications of these methods are also outlined. In addition, the validation of filled LST values’ cloudy pixels is an important concern in LST reconstruction. The different validation methods applied for reconstructed LST datasets are also reviewed herein. Finally, prospects for future developments in LST reconstruction are provided.

scholarly journals Spatiotemporal Influence of Land Use/Land Cover Change Dynamics on Surface Urban Heat Island: A Case Study of Abuja Metropolis, Nigeria

2021 ◽  
Vol 10 (5) ◽  
pp. 272
Author(s):  
Auwalu Faisal Koko ◽  
Wu Yue ◽  
Ghali Abdullahi Abubakar ◽  
Akram Ahmed Noman Alabsi ◽  
Roknisadeh Hamed
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Urban Expansion ◽  
Urban Heat Islands ◽  
Sustainable Land Use ◽  
Land Use Land Cover ◽  
Urban Centers ◽  
Rapid Urbanization ◽  
Urban Heat

Rapid urbanization in cities and urban centers has recently contributed to notable land use/land cover (LULC) changes, affecting both the climate and environment. Therefore, this study seeks to analyze changes in LULC and its spatiotemporal influence on the surface urban heat islands (UHI) in Abuja metropolis, Nigeria. To achieve this, we employed Multi-temporal Landsat data to monitor the study area’s LULC pattern and land surface temperature (LST) over the last 29 years. The study then analyzed the relationship between LULC, LST, and other vital spectral indices comprising NDVI and NDBI using correlation analysis. The results revealed a significant urban expansion with the transformation of 358.3 sq. km of natural surface into built-up areas. It further showed a considerable increase in the mean LST of Abuja metropolis from 30.65 °C in 1990 to 32.69 °C in 2019, with a notable increase of 2.53 °C between 2009 and 2019. The results also indicated an inverse relationship between LST and NDVI and a positive connection between LST and NDBI. This implies that urban expansion and vegetation decrease influences the development of surface UHI through increased LST. Therefore, the study’s findings will significantly help urban-planners and decision-makers implement sustainable land-use strategies and management for the city.

scholarly journals Land surface model photosynthesis and parameter calibration for boreal sites with adaptive population importance sampler

2019 ◽  
Author(s):  
Jarmo Mäkelä ◽  
Jürgen Knauer ◽  
Mika Aurela ◽  
Andrew Black ◽  
Martin Heimann ◽  
...  
Keyword(s):  
Stomatal Conductance ◽  
Land Surface ◽  
Carbon Fixation ◽  
Gross Primary Production ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Surface Model ◽  
Drought Event ◽  
Forest Site ◽  
Delayed Effect

Abstract. We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the Boreal zone. The parameter posterior distributions were generated by adaptive population importance sampler and the optimal values by a simple stochastic optimisation algorithm. The observations used to constrain the model are evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. We were able to improve the coefficient of determination and the model bias with all stomatal conductance formulations. There was no clear candidate for the best stomatal conductance model, although certain versions produced better estimates depending on the examined variable (ET, GPP) and the used metric. We were also able to significantly enhance the model behaviour during a drought event in a Finnish Scots pine forest site. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity. This modification enabled the model to correctly time and replicate the springtime increase in GPP (and ET) for conifers throughout the measurements sites used in this study.

Evaluation of Land Surface Temperature Retrieved from MODIS Data

2013 ◽  
Vol 785-786 ◽  
pp. 1333-1336
Author(s):  
Xiao Feng Yang ◽  
Xing Ping Wen
Keyword(s):  
Surface Temperature ◽  
Brightness Temperature ◽  
Land Surface Temperature ◽  
Global Climate Change ◽  
Land Surface ◽  
Global Climate ◽  
Average Temperature ◽  
Profile Line ◽  
Weather Stations ◽  
Temperature Retrieval

Land surface temperature (LST) is important factor in global climate change studies, radiation budgets estimating, city heat and others. In this paper, land surface temperature of Guangzhou metropolis was retrieved from two MODIS imageries obtained at night and during the day respectively. Firstly, pixel values were calibrated to spectral radiances according to parameters from header files. Then, the brightness temperature was calculated using Planck function. Finally, The brightness temperature retrieval maps were projected and output. Comparing two brightness temperature retrieval maps, it is concluded that the brightness temperature retrieval are more accurate at night than during the day. Comparing the profile line of brightness temperature from north to south, the brightness temperature increases from north to south. Temperature different from north to south is larger at night than during the day. The average temperature nears 18°C at night and the average temperature nears 26°C during the day, which is consistent with the surface temperature observed by automatic weather stations.

scholarly journals Halogenated Greenhouse Gases Made Global Warming Primarily

2022 ◽  
Author(s):  
Qing-Bin Lu
Keyword(s):  
Sea Ice ◽  
Greenhouse Gases ◽  
Land Surface ◽  
Southern Oscillation ◽  
Theoretical Calculations ◽  
Global Climate ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Snow Cover Extent

Abstract Time-series observations of global lower stratospheric temperature (GLST), global land surface air temperature (LSAT), global mean surface temperature (GMST), sea ice extent (SIE) and snow cover extent (SCE), together with observations reported in Paper I, combined with theoretical calculations of GLSTs and GMSTs, have provided strong evidence that ozone depletion and global climate changes are dominantly caused by human-made halogen-containing ozone-depleting substances (ODSs) and greenhouse gases (GHGs) respectively. Both GLST and SCE have become constant since the mid-1990s and GMST/LSAT has reached a peak since the mid-2000s, while regional continued warmings at the Arctic coasts (particularly Russia and Alaska) in winter and spring and at some areas of Antarctica are observed and can be well explained by a sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free warming theory of halogenated GHGs show an excellent agreement with the observed GMSTs after the natural El Niño southern oscillation (ENSO) and volcanic effects are removed. These results provide a convincing mechanism of global climate change and will make profound changes in our understanding of atmospheric processes. This study also emphasizes the critical importance of continued international efforts in phasing out all anthropogenic halogenated ODSs and GHGs.

scholarly journals An ensemble of AMIP simulations with prescribed land surface temperatures

2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models ◽  
Solar Constant ◽  
Surface Temperatures ◽  
Co2 Concentrations ◽  
Land Surface Temperatures ◽  
Intercomparison Project

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

scholarly journals Response of Spatio-Temporal Differentiation Characteristics of Habitat Quality to Land Surface Temperature in a Fast Urbanized City

Forests ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1668
Author(s):  
Yongge Hu ◽  
Enkai Xu ◽  
Gunwoo Kim ◽  
Chang Liu ◽  
Guohang Tian
Keyword(s):  
Surface Temperature ◽  
Habitat Quality ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Northern Region ◽  
Urban Heat Islands ◽  
Urban Habitat ◽  
Rural Settlements ◽  
Quality Model ◽  
High Type

The degradation and loss of global urban habitat and biodiversity have been extensively studied as a global issue. Urban heat islands caused by abnormal land surface temperature (LST) have been shown to be the main reason for this problem. With the accelerated urbanization process and the increasing possibility of abnormal temperatures in Zhengzhou, China, more and more creatures cannot adapt and survive in urban habitats, including humans; therefore, Zhengzhou was selected as the study area. The purpose of this study is to explore the response of urban habitat quality to LST, which provides a basis for the scientific protection of urban habitat and biodiversity in Zhengzhou from the perspective of alleviating heat island effect. We used the InVEST-Habitat Quality model to calculate the urban habitat quality, combined with GIS spatial statistics and bivariate spatial autocorrelation analysis, to explore the response of habitat quality to LST. The results show the following: (1) From 2000 to 2015, the mean value of urban habitat quality gradually decreased from 0.361 to 0.304, showing a downward trend as a whole. (2) There was an obvious gradient effect between habitat quality and LST. Habitat quality’s high values were distributed in the central and northern built-up area and low values were distributed in the high-altitude western forest habitat and northern water habitat. However, the distribution of LST gradient values were opposite to the habitat quality to a great extent. (3) There were four agglomeration types between LST and habitat quality at specific spatial locations: the high-high type was scattered mainly in the western part of the study area and in the northern region; the high-low type was mainly distributed in the densely populated and actively constructed central areas; the low-low type was mainly distributed in the urban-rural intersections and small and medium-sized rural settlements; and the low-high type was mainly distributed in the western mountainous hills and the northern waters.

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