Investigating urban heat island through spatial analysis of New York City streetscapes

Shaker, Richard R.; Altman, Yaron; Deng, Chengbin; Vaz, Eric; Forsythe, K. Wayne

doi:10.1016/j.jclepro.2019.05.389

Cited by 73 publications

(36 citation statements)

References 115 publications

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“…Cities are increasingly becoming complex systems of social, economic and ecological subsystems [ 1 ], in which land plays an important role in urban production and life [ 2 ]. Human ever increasing demand driven by rapid urbanization exerts pressure on natural resources and induces consequent degradation of land quality and ecosystems [ 3 ], thereby reducing the high quality of urban development [ 4 ]. How to meet the requirement of high-quality urban development with limited land is becoming a global challenge [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Econometric Analysis of Urban Land Use Efficiency in China from the Perspective of Natural Resources Input and Undesirable Outputs: A Case Study of 287 Cities in China

Han

An-lu

Yin-ying

2020

IJERPH

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The rapid urbanization in China has had a huge impact on land use and the scarcity of land resources has become a constraint for sustainable urban development. As urban land is an indispensable material basis in economic development, measuring its use efficiency and adopting effective policies to improve urban land use efficiency (ULUE) are important links in maintaining sustainable economic growth. By establishing a comprehensive ULUE evaluation index system that emphasizes on incorporating the natural resources input and the undesirable output, ULUE from 2010 to 2016 was calculated based on super efficiency SBM model, and its potential influencing factors were explored using a spatial econometric model. The results show that: (1) temporally, the overall ULUE in China is upward growing, and the gap among regions is becoming gradually convergent. (2) Spatially, the ULUE of Chinese cities are positively correlated. (3) Economic agglomeration and industrial structure significantly improve ULUE in China, but the intensity of energy consumption has a negative impact on ULUE. We suggest that: (1) differentiated industrial development strategies should be formulated; (2) the economic growth pattern should be changed from energy-consuming to energy-saving; (3) priority should be given to innovation on science and education, so as to increase in clean energy input and cleaner production.

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Section: Introductionmentioning

confidence: 99%

Spatio-Econometric Analysis of Urban Land Use Efficiency in China from the Perspective of Natural Resources Input and Undesirable Outputs: A Case Study of 287 Cities in China

Han

An-lu

Yin-ying

2020

IJERPH

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“…Produced from high-resolution QuickBird (Digital Globe) satellite imagery, combined with planimetric data, this land cover raster layer has 0.6 m (1.9685 ft) pixels allowing for single tree detection [93]. Although accuracy details for this data file could not be found, the same research group and methods applied to New York City rendered an overall classification accuracy of 96% [14,94]. This high-resolution land cover data set was classified into eight land cover categories: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, (7) other paved surfaces, and (8) agriculture ( Figure 3).…”

Section: Streetscape Configuration and Diversitymentioning

confidence: 99%

“…This is important as urban development lacking urban greenspace and subsequently tree canopy can have many social and physical health implications [122]. Furthermore, preserving urban tree canopy is important as it can also counter urban heat island effect, improve air quality, reduce the needs for heating and cooling of residential homes, and mitigate urban noise pollution [14,123]. Tree canopy COHESION and SHDI were also negatively associated.…”

Section: Importance Of Relationshipsmentioning

confidence: 99%

“…Tree canopy COHESION was negatively associated with premature mortality. As tree canopy becomes more connected streetscapes become cooler, local oxygen levels increase, and phytoremediation lessens toxic gasses and particulate matter reducing negative health effects [14]. Premature mortality experienced a positive correlation to COHESION of buildings and roads, and SHDI.…”

Section: Importance Of Relationshipsmentioning

confidence: 99%

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Showcasing Relationships between Neighborhood Design and Wellbeing Toronto Indicators

et al. 2020

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Cities are the keystone landscape features for achieving sustainability locally, regionally, and globally. With the increasing impacts of urban expansion eminent, policymakers have encouraged researchers to advance or invent methods for managing coupled human–environmental systems associated with local and regional sustainable development planning. Although progress has been made, there remains no universal instrument for attaining sustainability on neither regional nor local planning scales. Previous sustainable urbanization studies have revealed that landscape configuration metrics can supplement other measures of urban well-being, yet few have been included in public data dashboards or contrasted against local well-being indicators. To advance this sector of sustainable development planning, this study had three main intentions: (1) to produce a foundational suite of landscape ecology metrics from the 2007 land cover dataset for the City of Toronto; (2) to visualize and interpret spatial patterns of neighborhood streetscape patch cohesion index (COHESION), Shannon’s diversity index (SHDI), and four Wellbeing Toronto indicators across the 140 Toronto neighborhoods; (3) to quantitatively assess the global collinearity and local explanatory power of the well-being and landscape measures showcased in this study. One-hundred-and-thirty landscape ecology metrics were computed: 18 class configuration metrics across seven land cover categories and four landscape diversity metrics. Anselin Moran’s I-test was used to illustrate significant spatial patterns of well-being and landscape indicators; Pearson’s correlation and conditional autoregressive (CAR) statistics were used to evaluate relationships between them. Spatial “hot-spots” and/or “cold-spots” were found in all streetscape variables. Among other interesting results, Walk Score® was negatively related to both tree canopy and grass/shrub connectedness, signifying its lack of consideration for the quality of ecosystem services and environmental public health—and subsequently happiness—during its proximity assessment of socioeconomic amenities. In sum, landscape ecology metrics can provide cost-effective ecological integrity addendum to existing and future urban resilience, sustainable development, and well-being monitoring programs.

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“…Computed correlation coefficients in the GWR model quantitatively express the spatial relationships at each location. Geographically weighted regression models are widely used in urban landscape pattern analysis [35,37,38], PM 2.5 concentration estimation [39], carbon emissions [40], and ecosystem services [41,42]. Sawut et al [43] also estimated the heavy metal arsenic (As) contents of an open-pit coal mine in soil on the basis of GWR.…”

Section: Introductionmentioning

confidence: 99%

Spatial Heterogeneity of Vegetation Response to Mining Activities in Resource Regions of Northwestern China

Xie

Wang

et al. 2020

Remote Sensing

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Aggregated mining development has direct and indirect impacts on vegetation changes. This impact shows spatial differences due to the complex influence of multiple mines, which is a common issue in resource regions. To estimate the spatial heterogeneity of vegetation response to mining activities, we coupled vegetation changes and mining development through a geographically weighted regression (GWR) model for three cumulative periods between 1999 and 2018 in integrated resource regions of northwestern China. Vegetation changes were monitored by Sen’s slope and the Mann–Kendall test according to a total of 72 Landsat images. Spatial distribution of mining development was quantified, due to four land-use maps in 2000, 2005, 2010, and 2017. The results showed that 80% of vegetation in the study area experienced different degrees of degradation, more serious in the overlapping areas of multiple mines and mining areas. The scope of influence for single mines on vegetation shrunk by about 48%, and the mean coefficients increased by 20%, closer to mining areas. The scope of influence for multiple mines on vegetation gradually expanded to 86% from the outer edge to the inner overlapping areas of mining areas, where the mean coefficients increased by 92%. The correlation between elevation and vegetation changes varied according to the average elevation of the total mining areas. Ultimately, the available ecological remediation should be systematically considered for local conditions and mining consequences.

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Investigating urban heat island through spatial analysis of New York City streetscapes

Cited by 73 publications

References 115 publications

Spatio-Econometric Analysis of Urban Land Use Efficiency in China from the Perspective of Natural Resources Input and Undesirable Outputs: A Case Study of 287 Cities in China

Spatio-Econometric Analysis of Urban Land Use Efficiency in China from the Perspective of Natural Resources Input and Undesirable Outputs: A Case Study of 287 Cities in China

Showcasing Relationships between Neighborhood Design and Wellbeing Toronto Indicators

Spatial Heterogeneity of Vegetation Response to Mining Activities in Resource Regions of Northwestern China

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