Next Article in Journal
Monitoring the Response of Roads and Railways to Seasonal Soil Movement with Persistent Scatterers Interferometry over Six UK Sites
Next Article in Special Issue
Impacts of Urbanization on Vegetation Phenology over the Past Three Decades in Shanghai, China
Previous Article in Journal
Self-Learning Based Land-Cover Classification Using Sequential Class Patterns from Past Land-Cover Maps
Previous Article in Special Issue
“Kill Two Birds with One Stone”: Urban Tree Species Classification Using Bi-Temporal Pléiades Images to Study Nesting Preferences of an Invasive Bird
Article Menu
Issue 9 (September) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(9), 919; doi:10.3390/rs9090919

Diversification of Land Surface Temperature Change under Urban Landscape Renewal: A Case Study in the Main City of Shenzhen, China

1
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
2
Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
*
Author to whom correspondence should be addressed.
Received: 21 June 2017 / Revised: 8 August 2017 / Accepted: 31 August 2017 / Published: 2 September 2017
(This article belongs to the Special Issue Remote Sensing of Urban Ecology)
View Full-Text   |   Download PDF [9763 KB, uploaded 2 September 2017]   |  

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. View Full-Text
Keywords: landscape transformation; temperature mitigation; decision tree; urbanization landscape transformation; temperature mitigation; decision tree; urbanization
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Liu, Y.; Peng, J.; Wang, Y. Diversification of Land Surface Temperature Change under Urban Landscape Renewal: A Case Study in the Main City of Shenzhen, China. Remote Sens. 2017, 9, 919.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top