Synergetic interaction between spatial land cover dynamics and expanding urban heat islands

Dutta, K.; Basu, Debolina; Agrawal, Sonam

doi:10.1007/s10661-021-08969-4

Cited by 31 publications

(16 citation statements)

References 59 publications

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“…There are also studies on the relationship between vegetation and climate response based on remote sensing long-time series data [ 23 , 24 ]. Notably, the mentioned studies concentrated on the temporal and spatial distribution characteristics of vegetation, LST and UHI, as well as the impact of urban landscape on the surface thermal environment [ 25 , 26 , 27 , 28 ]. Accordingly, what is the corresponding relationship between FVC and LST in a single surface cover area, and whether the distribution pattern of LST will show diversity characteristics?…”

Section: Introductionmentioning

confidence: 99%

“…They are vital places for animal husbandry activities, as well as relatively serious desertification-prone areas in Eurasia. In the study of desertification, vegetation coverage can reflect the variations of surface ecological environment directly and underpin the division of different stages of desertification [ 25 , 26 , 27 , 28 , 29 , 30 ]. The vegetation in semi-arid sandy area is sparse and mostly distributed in patches, which is obviously different from the urban area [ 31 , 32 ].…”

Section: Introductionmentioning

confidence: 99%

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Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

Qiao

Dong

et al. 2021

Sensors

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Sandy range land refers to a major component of grassland area types in the semi-arid area of northern China. Monitoring of vegetation and land surface temperature (LST) using remote sensing technology can help determine the degree of desertification in a regional and/or sub regional scale, as in the Horqin Sandy Land selected in this study. Correlation analysis was performed to examine the relationship between the fractional vegetation coverage (FVC) and the LST within one growing season (from May to August 2017), at different spatial scales. The results showed that the FVC increased from 0.12 in May to 0.29 in August, and the LST increased first and then declined. The highest LST was 41.68 °C in July, while the lowest was 28.62 °C in August. At the grid scale, the LST increased first and then declined with the increase of the FVC on 25 May, 10 June, and 29 August; the FVC ranged from 0.29–0.38, 0.27–0.32, and 0.29–0.38 with the preference of the ‘turning point’, respectively. A negative correlation was identified between the FVC and the LST and without any ‘turning point’ in the fitting curve on 28 July. The correlation between FVC and LST complied with the grid scale at the sample area scale. The coupling analysis of landscape pattern expressed by FVC and LST showed that, the landscape evenness, Euclidean nearest neighbor distance, and landscape splitting degree all showed strong coupling correlation in any study period (P). The landscape aggregation of FVC and LST showed a good coupling at the relatively high and low air temperature conditions of P1 and P3. Landscape contagion showed a good coupling between FVC and LST at relatively moderate air temperature condition of P1 and P4. Air temperature conditions and characteristics of vegetation coverage should be considered for a more targeted analysis when analyzing the relationship between FVC and LST and attention should be paid to the timing and type of study area in practical application.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

Qiao

Dong

et al. 2021

Sensors

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“…School campuses are often well planted locations covered with turf grasses that create the Oasis effect (Taha et al, 1997 ). It helps to reduce the impact of urban heat islands (Dutta et al, 2021 ). The LULC of the schools can be studied at the micro scale (schoolyard) or macro scale (neighborhood of schools).…”

Section: Literature Reviewmentioning

confidence: 99%

An evaluation of primary schools and its accessibility using GIS techniques: a case study of Prayagraj district, India

2022

Self Cite

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The spatial analysis of primary schools is needed to ensure that they meet standards set by the Government of India. Therefore, mapping of Prayagraj district primary schools is carried out in this research work. The spatial analysis of schools is performed using various parameters that include: literacy rate, student gender ratio, teacher taught ratio, and students’ toilets ratio. Several problems were revealed in the GIS based analysis of schools by highlighting their locations on the map. The results identify the location of all those schools where there is a need to take corrective measures. Further, the route analysis between home and school is handled in this research work. Sometimes, commutation is the sole criteria in the selection of a school. Therefore, optimal path analysis has been performed based on three parameters, i.e. population density, traveling distance and traveling time. A combined weight function is also given to find the optimal path. This work will help people to select the best possible path based upon their requirements. There is often a requirement to reach all the schools to distribute the goods or other physical monitoring activities. This work gave the optimal route to visit all the schools by using the Travelling Salesman Problem (TSP). School accessibility results obtained in this research through TSP will assist in choosing the best possible route. This will help the government identify locations where new roads need to be constructed to have road connectivity.

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“…In urban areas, zoning determines the density and height of buildings. The types of zoning in urban areas influence temperature in association with those of zoning in adjacent areas [ 26 , 27 , 28 , 29 , 30 ]. Commercial zones show higher UHI intensity than do residential zones [ 27 , 31 ].…”

Section: Control Of Outdoor Temperaturementioning

confidence: 99%

Multidisciplinary Understanding of the Urban Heating Problem and Mitigation: A Conceptual Framework for Urban Planning

Lee

Kim

2022

IJERPH

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With the global acceleration of urbanization, temperatures in cities are rising continuously with global climate change, creating an imminent risk of urban heat islands and urban heating. Although much research has attempted to analyze urban heating from various perspectives, a comprehensive approach to urban planning that addresses the problem is just beginning. This study suggests a conceptual framework for multidisciplinary understanding of urban heating by reviewing 147 selected articles from various fields, published between 2007 and 2021, that discuss urban heating mitigation. From these, we identified several outdoor and indoor temperature-reduction factors and proposed area-based, zoning-based, and point-based approaches to mitigate urban heating.

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Synergetic interaction between spatial land cover dynamics and expanding urban heat islands

Cited by 31 publications

References 59 publications

Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

Spatial Scale Effects of the Relationship between Fractional Vegetation Coverage and Land Surface Temperature in Horqin Sandy Land, North China

An evaluation of primary schools and its accessibility using GIS techniques: a case study of Prayagraj district, India

Multidisciplinary Understanding of the Urban Heating Problem and Mitigation: A Conceptual Framework for Urban Planning

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