Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Acquisition and Treatment of Climatic Data
2.3. Estimation of Urban Biomass in Lisbon
- NIR corresponds to near-infrared band and;
- Red represents the red band.
2.4. Estimation of Cooling Potential of Green Spaces
- On a first attempt, the correlation between AGB and the temperature differences at Gulbenkian’s Garden was tested and turned out not statistically significant for both seasons (R = 0.6).
- On a second and final attempt, the linear regression model incorporated a map with the density of vegetation produced from green volume estimations of the city instead of AGB. This parameter was calculated for both winter and summer (Figure 4) using the Kernel density, which estimates the magnitude of green mass per area.
3. Results
3.1. Biomass in Lisbon
3.2. The Cooling Potential of Green Spaces in Lisbon
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Measuring Points | Air Temperature Anomalies (Δ)(°C) | ||||||
---|---|---|---|---|---|---|---|
24/04 | 20/05 | 18/06 | 25/06 | 07/07 | 09/07 | 23/07 | |
I1 | 4.6 | 6.0 | 3.8 | 6.8 | 2.6 | 0.4 | 2.2 |
I2 | 1.5 | 4.3 | 2.6 | 6.3 | 5.6 | 3.4 | 4.9 |
I3 | 0.7 | 3.7 | 1.9 | 4.8 | 3.4 | 1.2 | 2.2 |
I4 | 1.2 | 2.4 | 0.0 | 3.8 | 2.4 | 0.2 | 0.9 |
I5 | 2.4 | 4.0 | 0.3 | 5.8 | 3.4 | 1.2 | 0.7 |
I6 | 4.4 | 6.0 | 3.9 | 5.1 | 3.4 | 1.2 | 1.0 |
I7 | 4.5 | 7.4 | 3.4 | 7.6 | 4.8 | 2.6 | 2.3 |
I8 | 3.0 | 4.7 | 3.2 | 6.1 | 4.8 | 2.6 | 3.5 |
N1 | 1.7 | 3.9 | 1.4 | 2.2 | 3.3 | 3.4 | 0.5 |
N2 | 4.6 | 7.2 | 1.2 | 2.8 | 2.7 | 3.2 | 1.8 |
N3 | 4.4 | 6.9 | 1.1 | 2.5 | 1.6 | 1.4 | 0.6 |
W1 | 3.9 | 1.0 | 2.5 | 7.6 | 3.1 | 2.6 | 0.7 |
W2 | 7.7 | 1.0 | 6.2 | 8.2 | 4.7 | 8.0 | 2.9 |
W3 | 5.1 | 3.5 | 5.0 | 7.8 | 5.6 | 7.8 | 3.6 |
S1 | 5.2 | 6.5 | 2.8 | 3.8 | 4.6 | 5.0 | 2.6 |
S2 | 6.8 | 8.4 | 4.1 | 5.5 | 3.1 | 2.3 | 3.0 |
S3 | 5.0 | 7.8 | 5.4 | 8.5 | 1.8 | 1.1 | 2.1 |
E1 | 4.9 | 5.1 | 3.9 | 4.2 | 4.3 | 4.5 | 4.5 |
E2 | 10.0 | 6.6 | 4.7 | 6.1 | 5.9 | 4.8 | 2.7 |
E3 | 9.0 | 8.9 | 5.6 | 8.4 | 6.9 | 5.3 | 2.8 |
E4 | 7.1 | 9.2 | 6.3 | 7.2 | 5.4 | 3.5 | 4.5 |
Source | Equation |
---|---|
Pereira et al.; 1995 [47] | Biomass (ton/ha) = −2.923 + 21.486 * NDVI |
Filella et al.; 2004 [46] | Biomass (kg/m2) = 0.856 (NDVI) + 0.183 |
Chang & Shoshany, 2016 [48] | Biomass (kg/m2) = 0.148 + 1.735 * NDVI |
Winter (5 February 2016) | Summer (17 July 2017) | |||||||
---|---|---|---|---|---|---|---|---|
Whole City | Green Spaces | Street Trees | Whole City | Green Spaces | Street Trees | |||
ᾱ (kg/m2) | Total (ton) | ᾱ (kg/m2) | ᾱ (kg/m2) | ᾱ (kg/m2) | Total (ton) | ᾱ (kg/m2) | ᾱ (kg/m2) | |
[46] | 0.6 | 10.2 | 0.7 | 0.4 | 0.5 | 21.1 | 0.6 | 0.5 |
[47] | 0.7 | 19.4 | 0.9 | 0.3 | 0.5 | 35.9 | 0.6 | 0.3 |
[48] | 1.0 | 47.1 | 1.1 | 0.7 | 0.8 | 57.5 | 0.9 | 0.7 |
Average Biomass | 0.7 | 23.1 | 0.9 | 0.5 | 0.6 | 37.4 | 0.7 | 0.5 |
Variables | Results |
---|---|
Equation | Y = 19.2162 − 0.0249 * x (P < 0.001) |
Correlation Coefficient (R) | −0.74 |
Determination Coefficient (R2) | 0.55 |
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Reis, C.; Lopes, A. Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon. Sustainability 2019, 11, 2480. https://doi.org/10.3390/su11092480
Reis C, Lopes A. Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon. Sustainability. 2019; 11(9):2480. https://doi.org/10.3390/su11092480
Chicago/Turabian StyleReis, Cláudia, and António Lopes. 2019. "Evaluating the Cooling Potential of Urban Green Spaces to Tackle Urban Climate Change in Lisbon" Sustainability 11, no. 9: 2480. https://doi.org/10.3390/su11092480