The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season
"> Figure 1
<p>Flowchart of the study framework.</p> "> Figure 2
<p>Location and the distribution of different land covers of the study region: (<b>A</b>) Study region is presented in red spot; (<b>B</b>) Land cover map of the study area (Corine Land Cover 2006).</p> "> Figure 3
<p>(<b>A</b>) Munich area map of mean daytime land surface temperature (LST) (°C) for June, July and August of 2002 to 2012 with spatial resolution of approximately 1 km × 1 km presented in pseudocolor; (<b>B</b>) Proportion of urban vegetation in each grid cell with spatial resolution of approximately 1 km × 1 km presented in percent’s.</p> "> Figure 4
<p>LST pattern of pixels completely covered with built-up area (100 percent) and pixels covered fully with urban vegetation (100 percent). Every year consists of June, July and August only. Urban vegetation cover shows cooler LST values than the built-up areas in range, as well as in maximum, upper quartile, median, lower quartile and minimum values. However, year 2003, due to strong European heat wave, shows higher LST values. Year 2003, for both built-up area and urban vegetation, shows a statistically significant difference (shown with <b>*</b>) to other years.</p> "> Figure 5
<p>Relationship between the LST and the ratio of urban vegetation cover within each pixel. All figures illustrate a decreasing and a negative temperature trend with the increase of urban vegetation in each pixel. This figure compares the hottest and the coldest warm period of the years from 2002 to 2012 as the summary of all results. All the graphs from the years 2002 to 2012 are available in <a href="#app1-sustainability-07-04689" class="html-app">supplementary materials</a>.</p> "> Figure 5 Cont.
<p>Relationship between the LST and the ratio of urban vegetation cover within each pixel. All figures illustrate a decreasing and a negative temperature trend with the increase of urban vegetation in each pixel. This figure compares the hottest and the coldest warm period of the years from 2002 to 2012 as the summary of all results. All the graphs from the years 2002 to 2012 are available in <a href="#app1-sustainability-07-04689" class="html-app">supplementary materials</a>.</p> "> Figure 6
<p>The LST fluctuation for fully urbanized pixels (red boxplots) and pixels covered 50 to 100 percent with urban vegetation (green spectrum) from June, July and August of 2002 to 2012. Urban vegetation shows cooler LST values than the built-up areas in range, as well as in maximum, upper quartile, median, lower quartile and minimum values. Increase in the proportion of urban vegetation within each pixel shows a non-linear trend in the cooling effect of the urban vegetation.</p> "> Figure 7
<p>Difference between medians of LSTs for pixels covered fully with built-up areas and pixels covered more than 50 percent with urban vegetation. The median of the LSTs has been computed for June, July and August from 2002 to 2012. Different proportions of urban vegetation are presented in five groups. Pixels containing urban vegetation with a stronger cooling effect are highlighted in grey.</p> ">
Abstract
:1. Introduction
2. Methodology
2.1. Study Area
2.2. Land Cover Data
CLC Classes | Homogenous Class | ||
---|---|---|---|
Level 1 | Level 2 | Level 3 | Built-up area |
1. Artificial surface | 11. Urban fabric | 111. Continuous urban fabric 112. Discontinuous urban fabric | |
12. Industrial, commercial and transport units | 121. Industrial or commercial units 122. Road and rail networks and associated land 124. Airport | ||
13. Mine, dump and construction sites | 132. Dump sites 133. Construction sites | ||
14. Artificial, non-agricultural vegetated areas | 141. Green urban areas 142. Sport and leisure facilities | Urban vegetation | |
3. Forest and semi natural areas | 31. Forest | 311. Broad-leaved forest 312. Coniferous forest 313. Mixed forest | |
32. Scrub and/or herbaceous vegetation associations | 321. Natural grasslands |
2.3. Land Surface Temperature Data
2.4. Statistical Methods
3. Results
3.1 Relationship between LST and the Ratio of Urban and/or Urban Vegetation
3.2 Built-Up Area and Urban Vegetation LST Patterns
4. Discussion
5. Conclusions
Supplementary Materials
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Alavipanah, S.; Wegmann, M.; Qureshi, S.; Weng, Q.; Koellner, T. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season. Sustainability 2015, 7, 4689-4706. https://doi.org/10.3390/su7044689
Alavipanah S, Wegmann M, Qureshi S, Weng Q, Koellner T. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season. Sustainability. 2015; 7(4):4689-4706. https://doi.org/10.3390/su7044689
Chicago/Turabian StyleAlavipanah, Sadroddin, Martin Wegmann, Salman Qureshi, Qihao Weng, and Thomas Koellner. 2015. "The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season" Sustainability 7, no. 4: 4689-4706. https://doi.org/10.3390/su7044689