Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China

Shen, Huanfeng; Huang, Liwen; Zhang, Liangpei; Wu, Penghai; Zeng, Chao

doi:10.1016/j.rse.2015.11.005

Cited by 298 publications

(186 citation statements)

References 64 publications

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“…Both data have their advantages and disadvantages. We used the MODIS LCD to generate the urban areas in WH and there were no large variations of urban areas between 2001 and 2013 ( Figure 2a,b and Figure 3a,b), which does not meet the actual characteristics of rapid urbanization in WH in past decades [46]. This suggested that the MODIS LCD is not suitable for studying the inter-annual urbanization.…”

Section: Extraction Of Urban Areamentioning

confidence: 98%

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

et al. 2017

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Abstract:In the context of rapid urbanization, systematic research about temporal trends of urbanization effects (UEs) on urban environment is needed. In this study, MODIS (Moderate Resolution Imaging Spectroradiometer) land surface temperature (LST) data and enhanced vegetation index (EVI) data were used to analyze the temporal trends of UEs on vegetation and surface urban heat islands (SUHIs) at 10 big cities in Yangtze River Basin (YRB), China during 2001-2016. The urban and rural areas in each city were derived from MODIS land cover data and nighttime light data. It was found that the UEs on vegetation and SUHIs were increasingly significant in YRB, China. The ∆EVI (the UEs on vegetation, urban EVI minus rural EVI) decreased significantly (p < 0.05) in 9, 7 and 5 out of 10 cities for annual, summer and winter, respectively. The annual daytime and nighttime SUHI intensity (SUHII; urban LST minus rural LST) increased significantly (p < 0.05) in 10 and 4 out of 10 cities, respectively. The increasing rate of daytime SUHII and the decreasing rate of ∆EVI in old urban areas were much less than the whole urban area (0.034 • C/year vs. 0.077 • C/year for annual daytime SUHII; 0.00209/year vs. 0.00329/year for ∆EVI). The correlation analyses indicated that the annual and summer daytime SUHII were significantly negatively correlated with ∆EVI in most cities. The decreasing ∆EVI may also contribute to the increasing nighttime SUHII. In addition, the significant negative correlations (r < −0.5, p < 0.1) between inter-annual linear slope of ∆EVI and SUHII were observed, which suggested that the cities with higher decreasing rates of ∆EVI may show higher increasing rates of SUHII.

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Section: Extraction Of Urban Areamentioning

confidence: 98%

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

et al. 2017

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“…Over recent decades, most cities have experienced dramatic increases in population and rapid expansion of their urban areas [2]. Such unprecedented development of modern cities has led to the emergence of some important urban problems, e.g., urban heat islands [3], transportation congestion [4], and urban villages [5]. Effective monitoring of urban areas is urgently needed for their sustainable development.…”

Section: Introductionmentioning

confidence: 99%

Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data

Jia

Ling

et al. 2018

Remote Sensing

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Land use is of great importance for urban planning, environmental monitoring, and transportation management. Several methods have been proposed to obtain land use maps of urban areas, and these can be classified into two categories: remote sensing methods and social sensing methods. However, remote sensing and social sensing approaches have specific disadvantages regarding the description of social and physical features, respectively. Therefore, an appropriate fusion strategy is vital for large-area land use mapping. To address this issue, we propose an efficient land use mapping method that combines remote sensing imagery (RSI) and mobile phone positioning data (MPPD) for large areas. We implemented this method in two steps. First, a support vector machine was adopted to classify the RSI and MPPD. Then, the two classification results were fused using a decision fusion strategy to generate the land use map. The proposed method was applied to a case study of the central area of Beijing. The experimental results show that the proposed method improved classification accuracy compared with that achieved using MPPD alone, validating the efficacy of this new approach for identifying land use. Based on the land use map and MPPD data, activity density in key zones during daytime and nighttime was analyzed to illustrate the volume and variation of people working and living across different regions.

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“…In recent years, with the development of remote sensing technology, thermal infrared (TIR) remote sensing has become popular in urban climate and environment studies. It has become a powerful research tool for UHI studies [20][21][22][23]. Land surface temperature (LST), one of the most important variables measured by TIR, is considered the skin temperature of the Earth.…”

Section: Introductionmentioning

confidence: 99%

Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China

Yang

Yan

et al. 2017

Sustainability

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Abstract:The spatio-temporal patterns of land use/land cover changes (LUCC) can significantly affect the distribution and intensity of the urban heat island (UHI) effect. However, few studies have mapped a clear picture of the influence of LUCC on UHI. In this study, both qualitative and quantitative models are employed to explore the effect of LUCC on UHI. UHI and LUCC maps were retrieved from Landsat data acquired from 1984, 1992, 2000, 2007, and 2014 to show their spatio-temporal patterns. The results showed that: (1) both the patterns of LUCC and UHI have had dramatic changes in the past 30 years. The urban area of Changchun increased more than four times, from 143.15 km 2 in 1984 to 577.45 km 2 in 2014, and the proportion of UHI regions has increased from 15.27% in 1984 to 29.62% in 2014; (2) the spatiotemporal changes in thermal environment were consistent with the process of urbanization. The average LST of the study area has been continuously increasing as many other land use types have been transformed to urban regions. The mean temperatures were higher in urban regions than rural areas over all of the periods, but the UHI intensity varied based on different measurements; and (3) the thermal environment inside the city varied widely even within a small area. The LST possesses a very strong positive relationship with impervious surface area (ISA), and the relationship has become stronger in recent years. The UHI we employ, specifically in this study, is SUHI (surface urban heat island).

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Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multi-temporal and multi-sensor remote sensed data: A 26-year case study of the city of Wuhan in China

Cited by 298 publications

References 64 publications

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

Urbanization Effects on Vegetation and Surface Urban Heat Islands in China’s Yangtze River Basin

Urban Land Use Mapping by Combining Remote Sensing Imagery and Mobile Phone Positioning Data

Mapping the Influence of Land Use/Land Cover Changes on the Urban Heat Island Effect—A Case Study of Changchun, China

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