Diversification of land surface temperature change under urban landscape renewal: A case study in the main city of Shenzhen, China

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Abstract

Unprecedented rapid urbanization in China during the past several decades has been accompanied by extensive urban landscape renewal, which has increased the urban thermal environmental risk. However, landscape change is a sufficient but not necessary condition for land surface temperature (LST) variation. Many studies have merely highlighted the correlation between landscape pattern and LST, while neglecting to comprehensively present the spatiotemporal diversification of LST change under urban landscape renewal. Taking the main city of Shenzhen as a case study area, this study tracked the landscape renewal and LST variation for the period 1987-2015 using 49 Landsat images. A decision tree algorithm suitable for fast landscape type interpretation was developed to map the landscape renewal. Analytical tools that identified hot-cold spots, the gravity center, and transect of LST movement were adopted to identify LST changes. The results showed that the spatial variation of LST was not completely consistent with landscape change. The transformation from Green landscape to Grey landscape usually increased the LST within a median of 0.2 °C, while the reverse transformation did not obviously decrease the LST (the median was nearly 0 °C). The median of LST change from Blue landscape to Grey landscape was 1.0 °C, corresponding to 0.5 °C in the reverse transformation. The imbalance of LST change between the loss and gain of Green or Blue landscape indicates the importance of protecting natural space, where the benefits in terms of temperature mitigation cannot be completely substituted by reverse transformation.

Figures

  • Figure 1. Location of the study area.
  • Table 1. Acquisition dates of remote sensing data.
  • Figure 2. Technical flow chart for the decision tree classification.
  • Figure 3. Randomly selected validation points for landscape type interpretation, and transect line locations for detecting landscape and LST changes.
  • Figure 4. Start and end year of landscape transformation portrayed pixel-by-pixel.
  • Figure 5. Changes in hot and cold spots of land surface temperature in the main city of Shenzhen.
  • Figure 6. Movement track of the gravity center of land surface temperature. Figure 6. Movement track of the gravity center of land surface temperature.
  • Figure 7. Correspondence of land surface temperature and landscape type in transects: east-west (EW), north-south (NS), northeast-southwest (NE-SW), and northwest-southeast (NW-SE). Windows a, b, and c highlighted specific landscape-temperature changes.

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APA

Liu, Y., Peng, J., & Wang, Y. (2017). Diversification of land surface temperature change under urban landscape renewal: A case study in the main city of Shenzhen, China. Remote Sensing, 9(9). https://doi.org/10.3390/rs9090919

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