Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing
Abstract
:1. Introduction
2. Data, Study Site and Methods
2.1. Data and Study Site
Data Type | Acquisition date | Precipitation before acquisition date (mm) * | |
---|---|---|---|
1 | Landsat TM | 13 May 1990 | 1 |
2 | Landsat TM | 7 September 1992 | 0 (159 the day before) |
3 | Landsat TM | 8 May 1994 | 0 |
4 | Landsat TM | 21 September 1997 | 0 |
5 | Landsat TM | 6 May 1999 | 0 |
6 | Landsat ETM+ | 1 July 1999 | 0 |
7 | Landsat ETM+ | 30 April 2000 | 13 |
8 | Landsat ETM+ | 19 May 2001 | 0 |
9 | Terra ASTER | 4 June 2001 | 0 |
10 | Terra ASTER | 12 June 2004 | 0 |
11 | Terra ASTER | 22 April 2006 | 0 |
12 | Terra ASTER | 8 August 2007 | 68 |
2.2. Estimation of Vegetation Cover
2.2.1. NDVI
2.2.2. Vegetation Abundance
2.2.3. Forest Abundance
2.3. LST Retrieval
2.3.1. Land Surface Emissivity Estimation
2.3.2. LST Calculation from Landsat TM/ETM+ Imagery
2.3.3. LST Calculation from Terra ASTER Images
2.4. Coupling Relationship Analysis
- –
- : , are negative correlations, absolutely negative correlations if ;
- –
- : , are absolutely not correlated;
- –
- : , are in positively correlated, and absolutely positively correlated if ;
3. Results and Discussion
3.1. NDVI and LST
3.2. Urban Vegetation Abundance and LST
- (1).
- Directly based on analysis of all pixels, the value of UVA and LST are linearly fitted and quadratically fitted; Pearson’s correlation coefficients are calculated for all pixel values (and presented in Table 3);
- (2).
- The range of UVA, [0, 100%], is divided into 100 intervals. The mean values of the 100 intervals and the corresponding mean values of LST are also linearly fitted; Pearson’s correlation coefficients are calculated for the mean values (and presented in Table 3).
- (1).
- The monomial coefficients are approximate, with the mean values from 12 images being between −7.1116 and −7.3429, which also show the numeric effect of vegetation in decreasing LST.
- (2).
- The values of differ greatly. For the polynomial fitting for all 12 images, the mean values of are 0.2982 and 0.3055. For the linear fitting and quadratic fitting, the values are much smaller than 0.9448. This also demonstrates that LST is influenced by vegetation, whereas it is also influenced by other factors, including elevation mentioned above.
3.3. Urban Forest Abundance and LST
- (1).
- Based on analysis of all pixels, the values of UFA and LST are linearly fitted and quadratically fitted. Pearson's correlation coefficients are calculated for all pixel values (Table 4);
- (2).
- The range of UFA, [0, 100%], is divided into 100 intervals. The mean values of the 100 intervals and the corresponding mean values of LST are also linearly fitted. Pearson's correlation coefficients are calculated for the mean values (Table 4).
- –
- There is not very much urban forest in the study area;
- –
- Some western areas are mountainous areas covered with forest. So elements other that the UFA, e.g., elevation, soil moisture, also influence LST.
- –
- In the study area, there are various types of trees, which play different roles in decreasing LST;
- –
- There exist some errors in the calculation of UFA;
3.4. Scale Effects
3.4.1. NDVI–LST
3.4.2. UVA–LST
3.4.3. UFA–LST
3.4.4. Summary
Thresholds of NDVI | Fit of LST and NDVI NDVI ∈ (Bare soil, Vegetation cover) | Fit of LST and mean NDVI of each interval NDVI ∈ (Bare soil, Vegetation cover) | Pearson’s correlation coefficients | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Water | Bare Soil | Vegetation Cover | Monomial coefficient | Constant | Monomial coefficient | Constant | All Pixels | NDVI ∈ (Bare soil, Vegetation cover) | |||
1990 TM | −0.45 | −0.09 | 0.56 | –12.2928 | 35.4764 | 0.3408 | –12.4806 | 35.5156 | 0.9867 | –0.6158 | –0.9934 |
1992 TM | −0.2 | –0.05 | 0.58 | –17.9615 | 37.7120 | 0.6989 | –17.9276 | 37.7203 | 0.9790 | –0.8264 | –0.9894 |
1994 TM | −0.32 | –0.1 | 0.42 | –14.7138 | 35.2906 | 0.2798 | –14.8015 | 35.2758 | 0.9951 | –0.4987 | –0.9976 |
1997 TM | –0.8 | –0.15 | 0.74 | –7.9520 | 30.9888 | 0.3002 | –8.0716 | 31.0836 | 0.9491 | –0.5943 | –0.9742 |
1999 TM | –0.7 | –0.05 | 0.78 | –13.7330 | 43.7044 | 0.3765 | –15.5863 | 44.3581 | 0.9313 | –0.5070 | –0.9650 |
1999 ETM+ | –0.3 | –0.14 | 0.34 | –18.6408 | 36.1800 | 0.5177 | –18.2092 | 36.1230 | 0.9812 | –0.7058 | –0.9906 |
2000 ETM+ | –0.8 | –0.33 | 0.32 | –12.2349 | 33.5019 | 0.2319 | –14.3637 | 33.3297 | 0.9702 | –0.3212 | –0.9850 |
2001 ETM+ | –0.58 | –0.32 | 0.2 | –17.1152 | 38.9377 | 0.3141 | –17.2958 | 38.9225 | 0.9902 | –0.4912 | –0.9951 |
2001 ASTER | –0.5 | –0.08 | 0.42 | –24.0389 | 38.5407 | 0.1771 | –25.6857 | 38.5730 | 0.9748 | –0.3923 | –0.9873 |
2004 ASTER | –0.23 | –0.09 | 0.5 | –18.0121 | 35.2307 | 0.0566 | –11.8544 | 35.2114 | 0.4391 | –0.1333 | –0.6626 |
2006 ASTER | –0.2 | –0.09 | 0.45 | –12.6498 | 29.7159 | 0.0347 | –11.3023 | 29.8595 | 0.8687 | –0.1394 | –0.9320 |
2007 ASTER | –0.5 | –0.09 | 0.34 | –21.6386 | 35.4286 | 0.3402 | –21.1473 | 35.3610 | 0.9966 | –0.6307 | –0.9983 |
Mean | −0.47 | −0.13 | 0.47 | −15.9153 | 35.8923 | 0.3057 | −15.7272 | 35.9445 | 0.9218 | −0.4880 | −0.9559 |
Fit of mean of intervals | Linear fit | Quadratic fit | Pearson’s correlation coefficients | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Monomial coefficient | Constant | Monomial coefficient | Constant | Quadratic coefficient | Monomial coefficient | Constant | Pixel value | Mean of intervals | ||||||
1990 TM | −8.0942 | 35.6088 | 0.9781 | −8.1612 | 35.5866 | 0.4100 | −1.3365 | −7.0286 | 35.4868 | 0.4109 | −0.6403 | −0.9890 | ||
1992 TM | −7.4503 | 35.4107 | 0.9744 | −9.0569 | 36.5539 | 0.6626 | 3.8315 | −12.5202 | 36.8455 | 0.6698 | −0.8140 | −0.9871 | ||
1994 TM | −6.7556 | 36.4812 | 0.9936 | −6.5170 | 36.3318 | 0.2760 | −1.5332 | −5.2720 | 36.2340 | 0.2772 | −0.5253 | −0.9968 | ||
1997 TM | −7.5678 | 31.1136 | 0.9717 | −8.2169 | 31.3132 | 0.4133 | 0.0570 | −8.2664 | 31.3178 | 0.4133 | −0.6429 | −0.9858 | ||
1999 TM | −12.2816 | 44.9093 | 0.9340 | −10.2816 | 43.8315 | 0.3177 | −9.4809 | −2.6838 | 43.2458 | 0.3382 | −0.5637 | −0.9665 | ||
1999 ETM+ | −8.2592 | 38.0257 | 0.9845 | −8.0378 | 37.9278 | 0.5256 | 0.0362 | −8.0676 | 37.9303 | 0.5256 | −0.7250 | −0.9922 | ||
2000 ETM+ | −8.4197 | 38.0622 | 0.9466 | −6.0629 | 37.0959 | 0.1504 | −7.5576 | −0.6721 | 36.7461 | 0.1701 | −0.3878 | −0.9730 | ||
2001 ETM+ | −9.3462 | 44.2796 | 0.9772 | −8.8133 | 44.1252 | 0.2892 | 0.0476 | −8.8476 | 44.1275 | 0.2892 | −0.5378 | −0.9885 | ||
2001 ASTER | −6.7738 | 40.2789 | 0.9854 | −6.0567 | 39.8884 | 0.1332 | −4.9580 | −1.9717 | 39.4737 | 0.1409 | −0.3650 | −0.9927 | ||
2004 ASTER | −2.2155 | 36.9150 | 0.7868 | −1.6963 | 36.5617 | 0.0199 | −4.8204 | 2.6790 | 36.0580 | 0.0339 | −0.1409 | −0.8870 | ||
2006 ASTER | −2.9451 | 30.6702 | 0.9169 | −2.8875 | 30.6096 | 0.0236 | −0.8655 | −2.2508 | 30.5558 | 0.0238 | −0.1536 | −0.9576 | ||
2007 ASTER | −8.0054 | 34.8716 | 0.8888 | −9.5506 | 35.5724 | 0.3568 | 7.8842 | −15.9222 | 36.1484 | 0.3725 | −0.5973 | −0.9427 | ||
Mean | −7.3429 | 37.2189 | 0.9448 | −7.1116 | 37.1165 | 0.2982 | −1.5580 | −5.9020 | 37.0141 | 0.3055 | −0.5078 | −0.9716 |
Fit of mean of intervals | Linear fit | Quadratic fit | Pearson’s correlation coefficients | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Monomial coefficient | Constant | Monomial coefficient | Constant | Quadratic coefficient | Monomial coefficient | Constant | Pixel value | Mean of intervals | |||||||
1990 TM | −11.6010 | 34.5226 | 0.8539 | −12.9336 | 35.3560 | 0.4494 | 8.0636 | −18.1931 | 35.6938 | 0.4563 | −0.6704 | −0.9241 | |||
1992 TM | −11.1884 | 36.4250 | 0.9112 | −11.5014 | 36.5410 | 0.6489 | 9.1876 | −18.6565 | 37.1977 | 0.6595 | −0.8055 | −0.9546 | |||
1994 TM | −7.7636 | 33.3574 | 0.7008 | −19.1950 | 36.8026 | 0.4248 | 26.3016 | −32.2491 | 37.5484 | 0.4611 | −0.6517 | −0.8372 | |||
1997 TM | −7.4677 | 27.6790 | 0.7026 | −13.8285 | 30.1439 | 0.3583 | 21.9188 | −29.4157 | 31.1497 | 0.4271 | −0.5986 | −0.8382 | |||
1999 TM | −8.1828 | 38.8291 | 0.2550 | −29.8147 | 43.9045 | 0.3698 | 119.6103 | −77.4715 | 45.8674 | 0.4924 | −0.6081 | −0.5049 | |||
1999 ETM+ | −7.6300 | 36.2626 | 0.7260 | −12.8932 | 37.7325 | 0.3424 | 8.6190 | −17.2400 | 38.0232 | 0.3475 | −0.5851 | −0.8520 | |||
2000 ETM+ | −11.0101 | 37.5955 | 0.7022 | −8.8423 | 37.1371 | 0.1636 | −22.1424 | 2.1104 | 36.6507 | 0.1895 | −0.4044 | −0.8379 | |||
2001 ETM+ | −5.4096 | 41.3349 | 0.6384 | −9.9076 | 43.6218 | 0.2384 | 15.5237 | −21.7775 | 44.2037 | 0.2963 | −0.4882 | −0.7990 | |||
2001 ASTER | −11.3096 | 37.6455 | 0.3905 | −23.9683 | 40.7667 | 0.1445 | −0.3147 | −23.8586 | 40.7600 | 0.1445 | −0.3801 | −0.6249 | |||
2004 ASTER | −10.1165 | 36.0246 | 0.3953 | −12.9336 | 37.4387 | 0.0859 | −18.5385 | −5.1195 | 36.9165 | 0.0901 | −0.2931 | −0.6287 | |||
2006 ASTER | −10.3612 | 30.2757 | 0.9011 | −14.6337 | 31.4104 | 0.1888 | 7.2639 | −18.0127 | 31.5644 | 0.1908 | −0.4345 | −0.9493 | |||
2007 ASTER | −23.4166 | 38.5703 | 0.7096 | −13.6613 | 36.4287 | 0.3683 | 18.8188 | −25.2949 | 37.4774 | 0.3874 | −0.6069 | −0.8424 | |||
Mean | −10.4548 | 35.7102 | 0.6572 | −15.3428 | 37.2737 | 0.3152 | 16.1926 | −23.7649 | 37.7544 | 0.3452 | −0.5439 | −0.7994 |
Resolution | 13 May 1990, Landsat TM | 19 May 2001, Landsat ETM+ | 8 August 2007, ASTER | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Linear Fit, Monomial coefficient | Linear Fit, | Pearson’s correlation coefficients | Linear Fit, Monomial coefficient | Linear Fit, | Pearson’s correlation coefficients | Linear Fit, Monomial coefficient | Linear Fit, | Pearson’s correlation coefficients | ||
NDVI and LST | 30 M | −12.29 | 0.34 | –0.62 | –17.12 | 0.31 | –0.49 | –21.64 | 0.34 | –0.63 |
60 M | −12.92 | 0.30 | –0.58 | –17.37 | 0.30 | –0.36 | –23.06 | 0.36 | –0.55 | |
90 M | –13.25 | 0.25 | –0.54 | –17.55 | 0.31 | –0.18 | –23.65 | 0.38 | –0.39 | |
120 M | –13.16 | 0.20 | –0.49 | –17.63 | 0.31 | –0.02 | –24.15 | 0.39 | –0.26 | |
240 M | –11.57 | 0.09 | –0.32 | –16.96 | 0.28 | 0.37 | –24.11 | 0.39 | 0.16 | |
480 M | –5.95 | 0.01 | –0.12 | –15.92 | 0.24 | 0.66 | –22.74 | 0.38 | 0.55 | |
960 M | 6.89 | 0.01 | 0.09 | –14.87 | 0.23 | 0.83 | –20.38 | 0.33 | 0.77 | |
Vegetation and LST | 30 M | –8.16 | 0.41 | –0.64 | –8.81 | 0.29 | –0.54 | –9.55 | 0.36 | –0.60 |
60 M | –8.35 | 0.35 | –0.59 | –8.99 | 0.23 | –0.48 | –10.14 | 0.37 | –0.61 | |
90 M | –8.62 | 0.29 | –0.54 | –8.84 | 0.17 | –0.41 | –10.40 | 0.33 | –0.57 | |
120 M | –8.64 | 0.24 | –0.49 | –8.56 | 0.12 | –0.35 | –10.50 | 0.29 | –0.54 | |
240 M | –7.53 | 0.10 | –0.32 | –6.79 | 0.04 | –0.20 | –9.57 | 0.16 | –0.40 | |
480 M | –3.35 | 0.01 | –0.10 | –2.12 | 0.00 | –0.04 | –6.19 | 0.04 | –0.19 | |
960 M | 6.53 | 0.02 | 0.13 | –6.36 | 0.04 | –0.19 | 1.11 | 0.00 | 0.02 | |
Forest and LST | 30 M | –12.93 | 0.45 | –0.67 | –9.91 | 0.24 | –0.49 | –13.66 | 0.37 | –0.61 |
60 M | –14.01 | 0.42 | –0.65 | –10.86 | 0.22 | –0.47 | –14.58 | 0.33 | –0.58 | |
90 M | –14.52 | 0.37 | –0.61 | –11.08 | 0.18 | –0.43 | –14.73 | 0.29 | –0.53 | |
120 M | –14.64 | 0.31 | –0.56 | –10.99 | 0.15 | –0.38 | –14.65 | 0.25 | –0.50 | |
240 M | –14.06 | 0.17 | –0.41 | –10.17 | 0.07 | –0.27 | –12.85 | 0.13 | –0.35 | |
480 M | –10.50 | 0.05 | –0.21 | –7.37 | 0.02 | –0.14 | –7.42 | 0.02 | –0.15 | |
960 M | 0.14 | 0.00 | 0.00 | –2.25 | 0.00 | –0.03 | 1.93 | 0.00 | 0.03 |
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Huang, C.; Ye, X. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing. Sustainability 2015, 7, 9478-9504. https://doi.org/10.3390/su7079478
Huang C, Ye X. Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing. Sustainability. 2015; 7(7):9478-9504. https://doi.org/10.3390/su7079478
Chicago/Turabian StyleHuang, Chudong, and Xinyue Ye. 2015. "Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing" Sustainability 7, no. 7: 9478-9504. https://doi.org/10.3390/su7079478
APA StyleHuang, C., & Ye, X. (2015). Spatial Modeling of Urban Vegetation and Land Surface Temperature: A Case Study of Beijing. Sustainability, 7(7), 9478-9504. https://doi.org/10.3390/su7079478