Investigating spatial and seasonal variations of urban heat island effect over Jaipur city and its relationship with vegetation, urbanization and elevation parameters

Mathew, Aneesh; Khandelwal, Sumit; Kaul, Nivedita

doi:10.1016/j.scs.2017.07.013

Cited by 130 publications

(66 citation statements)

References 36 publications

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“…As a crucial factor in achieving urban sustainability, the dynamics of urban environment have attracted considerable attention from researchers in the remote sensing community during the past several years [36]. The previous researches have shown that VC and LST were two important indicators of environmental conditions [36,37]. To explore the urbanization effects on the local environment of China's megacities, the dynamics of VC and LST in both pre-grown urban lands in 2000 ("R1" hereinafter) and newly expanded urban lands during 2000-2018 ("R2" hereinafter) were calculated by using Formula (5).…”

Section: Vegetation Coverage (Vc) and Land Surface Temperature (Lst)mentioning

confidence: 99%

Assessing Interannual Urbanization of China’s Six Megacities Since 2000

Zhang

Liu

et al. 2019

Remote Sensing

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As a large and populous developing country, China has entered the rapid urbanization stage since 2000. Until 2018, China has accounted for nearly 1/5 of global megacities. Understanding their urbanization processes is of great significance. Given the deficiencies of existing research, this study explored the interannual urbanization process of China's six megacities during 2000-2018 from four aspects, namely, the basic characteristics of urban land expansion, expansion types, cotemporary evolution of urban land-population-economy, and urbanization effects on the local environment. Results indicated that (1) urban lands in China's six megacities increased by 153.27%, with distinct differences across megacities; (2) all of six megacities experienced the expansion processes from high-speed to low-speed, but they varied greatly in detail; (3) the speeds of urban land expansion in China's megacities outpaced the population growth but lagged behind in GDP increase; and (4) urbanization has triggered an environmental crisis, which is represented by the decline in vegetation coverage and the increase in land surface temperature in newly expanded urban lands. This study enriched the content of urbanization, supplemented the existing materials of megacities, and provided a scientific reference for designing rational urban planning.Despite conducting denser social activities and causing more drastic urban sprawl effects than other medium-and small-sized cities [9], megacities must face more serious eco-environment problems, such as air pollution [10,11], flood disaster [12,13], and cropland losses [14], which have been proven to reflect the urbanization characteristics of a country or region better [15].Urbanization hotspots are expected to emerge in developing countries in the next several decades of the 21st century [1]. As a large and populous developing country with nearly 1/5 of the megacities worldwide, China has experienced significant urbanization at an increasing rate of 232.48% since the implementation of the Reform and Opening-up Policy in 1978 and the country has entered into the rapid expansion stage since 2000 [16]. Therefore, China is a good research area for investigating the urbanization process. During the past decades, urban expansion in China has been thoroughly investigated by using remote sensing technology. These studies have identified the following features. (1) Research objects ranged from a single city (i.e., Beijing [5], Shanghai [17], Harbin [18], Guangzhou [19], Nanjing [20], etc.) to urban aggregations (i.e., Beijing-Tianjin-Hebei [21], Pearl River Delta [22], Yangtze River Delta [23], etc.). However, limited investigations have been conducted on China's six megacities.(2) Research approaches included but not limited to various classification models (i.e., supervised or unsupervised classification, artificial neural network, etc.) and analysis methods (i.e., spatiotemporal dynamics, sprawl patterns, etc.). However, urbanization is a comprehensive process involving both physical morphology and ...

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Section: Vegetation Coverage (Vc) and Land Surface Temperature (Lst)mentioning

confidence: 99%

Assessing Interannual Urbanization of China’s Six Megacities Since 2000

Zhang

Liu

et al. 2019

Remote Sensing

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“…Bounded by the Arabian Sea from the west, and located at tropics, temperatures in Mumbai do not fluctuate much throughout the year. The mean maximum and minimum temperatures of the Mumbai are 31 °C and 21.5 °C, respectively (Saha et al 2017), while in the case of Jaipur, Rajasthan, the climate is semiarid that characteristically has scorching summers and short spans of mild-warm winters (Mathew et al 2017). Figure 2 shows the variation of temperature and the growth curve of the COVID-19 among the selected regions from May 9, 2020, until May 27, 2020.…”

Section: Introductionmentioning

confidence: 99%

Coronavirus pandemic versus temperature in the context of Indian subcontinent: a preliminary statistical analysis

Meraj

Farooq

Singh

et al. 2020

Environ Dev Sustain

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The novel coronavirus (COVID-19) has unleashed havoc across different countries and was declared a pandemic by the World Health Organization. Since certain evidences indicate a direct relationship of various viruses with the weather (temperature in particular), the same is being speculated about COVID-19; however, it is still under investigation as the pandemic is advancing the world over. In this study, we tried to analyze the spread of COVID-19 in the Indian subcontinent with respect to the local temperature regimes from March 9, 2020, to May 27, 2020. To establish the relation between COVID-19 and temperature in India, three different ecogeographical regions having significant temperature differences were taken into consideration for the analysis. We observed that except Maharashtra, Rajasthan and Kashmir showed a significantly positive correlation between the number of COVID-19 cases and the temperature during the period of study. The evidences based on the results presented in this research lead us to believe that the increasing temperature is beneficial to the COVID-19 spread, and the cases are going to rise further with the increasing temperature over India. We, therefore, conclude that the existing data, though limited, suggest that the spread of COVID-19 in India is not explained by the variation of temperature alone and is most likely driven by a host of other factors related to epidemiology, socioeconomics and other climatic factors. Based on the results, it is suggested that temperature should not be considered as a yardstick for planning intervention strategies for controlling the COVID-19 pandemic.

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“…The result of the increase in land uses is one of the causes that decreases in the amount of vegetation and land covers, that are green space (Zhang et al, 2010;Mathew et al, 2017;Ursu, 2019). Vegetation and green space can help reduce air temperature or the rate of UHI formation in urban areas effectively from water release of trees (Kophim, 2013), including reduction of flux values and heat radiation of buildings that accumulate heat energy from solar radiation throughout daytime, will result in the change in atmospheric temperature after sunset (Takebayashi & Moriyama, 2009;Perini & Magliocco, 2014;Yang et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

The Relationship Between Normalized Difference Vegetation Index and Canopy Temperature That Affects the Urban Heat Island Phenomenon

Prohmdirek¹,

Chunpang²,

Laosuwan³

2020

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The objective of this research is to analyze the relationship between Normalized Difference Vegetation Index (NDVI) and canopy temperature that affects the Urban Heat Island (UHI) phenomenon in Mueang Maha Sarakham Municipality. The operational methods were divided into three main steps: 1) Analyzing NDVI by using Landsat 8 OLI satellite data 2) Monitoring canopy temperature with mobile traverses installed with digital thermometer and auto-record GPS receiver 3) Analyzing the relationship between NDVI and canopy temperature that passed through the spatial interpolation process using the kriging method. The results of the operational methods indicated that the trend of average atmospheric temperature in the urban area was higher than the outer area. Mueang Maha Sarakham Municipality had the highest UHI in the atmosphere at 4.65 o C. And from the buffer zone with a distance of 800 m around the centroid point, the highest UHI in the atmosphere was 5.08 o C. From the regression analysis between NDVI and the atmospheric temperature, it could be found a negative relationship between the data with a significance level of 0.01 and the decision coefficient (R 2) of 0.9392. This can be explained that if the area from the buffer zone decreased towards the centroid point, the value of NDVI decreased as well. In addition, when the equation set from the regression analysis was brought to predict the difference in atmospheric temperature in the area of Mueang Maha Sarakham Municipality and the surrounding area, the UHI sizes at all periods (16.00-20.00 hrs.) increased in accordance with the decreases of NDVI values. Meanwhile, considering the tendency between the changes in UHI size in the atmosphere in each period and NDVI values with the polynomial regression analysis (degree 4), it was found that the maximum formation of UHI was during 18.00-19.00 hrs.'. The decreases in NDVI values resulted in a higher UHI size in each period. In addition, when the NDVI values in Mueang Maha Sarakham Municipality were less than 0.302, the largest size of UHI in the atmosphere will change at the time approaching 19.00 hrs.

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Investigating spatial and seasonal variations of urban heat island effect over Jaipur city and its relationship with vegetation, urbanization and elevation parameters

Cited by 130 publications

References 36 publications

Assessing Interannual Urbanization of China’s Six Megacities Since 2000

Assessing Interannual Urbanization of China’s Six Megacities Since 2000

Coronavirus pandemic versus temperature in the context of Indian subcontinent: a preliminary statistical analysis

The Relationship Between Normalized Difference Vegetation Index and Canopy Temperature That Affects the Urban Heat Island Phenomenon

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