Modelling Future Land Surface Temperature: A Comparative Analysis between Parametric and Non-Parametric Methods
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection and Preprocessing
2.3. Classification of Land Use/Land Cover (LULC)
2.4. Calculating Land Surface Temperature
2.5. Selection of Variables for LST Estimation
2.6. LST Modeling Algorithm
2.7. Evaluation of LST Estimates
3. Results
3.1. Evaluation of LST Fitting Results
3.2. Comparative Analysis of Estimated LST over Time
3.3. Future LST Prediction in Beijing
4. Discussion
4.1. The Spatial Reoslution of Future LST Prediction
4.2. The Performance of Fitting Results
4.3. Temporal Stability in Prediction Accuracy
4.4. Advantages and Limitations
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Year | Landsat and Daily MODIS (Reference Data) | 8-Day Daytime MODIS at Predicted Time (tp) | |||
---|---|---|---|---|---|
First Pair (tm) | Second Pair (tn) | June | July | August | |
2006 | 29 October 2005 | 28 May 2007 | 06/10–06/17 | 07/20–07/27 | 08/13–08/20 |
2012 | 26 July 2011 | 29 April 2014 | 06/09–06/16 | 07/11–07/18 | 08/20–08/27 |
2018 | 04 August 2018 | 17 October 2018 | 06/10–06/17 | 07/28–08/04 | 08/13–08/20 |
Variables | Description | Calculation |
---|---|---|
Percentage of impervious surface (%) | The ratio of impervious surface area to block area | PIS = Ai/Ab, where Ai is the area of impervious surfaces in block, and Ab is the block area. |
Percentage of barren land (%) | The ratio of barren land area to block area | PBL = Abl/Ab, where Abl is the area of barren land in block, and Ab is the block area. |
Percentage of water (%) | The ratio of water bodies to block area | PW = Aw/Ab, where Aw is the area of water in block, and Ab is the block area. |
Average DEM | The mean of DEM in block area | , where Vdi is the value of dem i, and n is the number of pixels in a block. |
Average LST | The mean of LST in block area | , where Vti is the value of LST i, and n is the number of pixels in a block. |
Year | MLR | GWR | ANN | RF | ||||
---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | |
2006 | 0.78 | 1.88 | 0.90 | 1.17 | 0.81 | 1.9 | 0.93 | 1.41 |
2012 | 0.79 | 1.47 | 0.88 | 1.18 | 0.72 | 1.7 | 0.92 | 1.42 |
2018 | 0.75 | 1.49 | 0.85 | 1.20 | 0.70 | 1.7 | 0.90 | 1.46 |
Year | MLR | GWR | ANN | RF | ||||
---|---|---|---|---|---|---|---|---|
R2 | RMSE | R2 | RMSE | R2 | RMSE | R2 | RMSE | |
2006–2012 | 0.79 | 1.47 | 0.73 | 1.87 | 0.71 | 2.15 | 0.72 | 1.85 |
2012–2018 | 0.75 | 2.40 | 0.70 | 2.97 | 0.70 | 2.58 | 0.69 | 2.69 |
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Gao, Y.; Li, N.; Gao, M.; Hao, M.; Liu, X. Modelling Future Land Surface Temperature: A Comparative Analysis between Parametric and Non-Parametric Methods. Sustainability 2024, 16, 8195. https://doi.org/10.3390/su16188195
Gao Y, Li N, Gao M, Hao M, Liu X. Modelling Future Land Surface Temperature: A Comparative Analysis between Parametric and Non-Parametric Methods. Sustainability. 2024; 16(18):8195. https://doi.org/10.3390/su16188195
Chicago/Turabian StyleGao, Yukun, Nan Li, Minyi Gao, Ming Hao, and Xue Liu. 2024. "Modelling Future Land Surface Temperature: A Comparative Analysis between Parametric and Non-Parametric Methods" Sustainability 16, no. 18: 8195. https://doi.org/10.3390/su16188195