Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China
Abstract
:1. Introduction
2. Materials
2.1. Study Area
2.2. Data Sources
3. Methods
3.1. Calibration of the NPP-VIIRS Data
3.2. Extraction and Accuracy Assessment of Urban and Rural Areas
3.3. Construction of the REPC Model
3.4. EPC Spatialization
4. Results
5. Discussion
5.1. EPC of Ethnic Minorities
5.2. Influence of Terrain on Distribution of REPC
5.3. Innovation and Limitation
6. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Data | Data Description | Year | Source |
---|---|---|---|
NPP-VIIRS | Annual composites | 2015 and 2016 | NOAA/NGDC (https://www.ngdc.noaa.gov/eog/viirs/download_dnb_composites.html) |
Monthly composites | 2012, 2013, 2014, 2017 | ||
POI | Points-of-interest | 2017 | BigeMap (http://www.bigemap.com/) |
Toponym | Results of the second national Toponymic census of China | 2019 | National Database for Geographical Names of China (http://dmfw.mca.gov.cn/) |
REPC | Annual statistical data of REPC (unit: 104 kW·h) | 2012–2017 (Except 2016) | China’s Economic and Social Big Data Research Platform (http://data.cnki.net/) |
Boundaries | Shapefile of DH prefecture and counties | 2017 | National Geomatics Center of China (http://www.ngcc.cn/ngcc/) |
DEM | digital elevation model | 2015 | Geospatial Data Cloud (http://www.gscloud.cn/) |
Statistical Classification Index | Urban Central Areas | Suburb Areas | Rural Areas | Natural Areas |
---|---|---|---|---|
precision | 0.91 | 0.77 | 0.68 | 0.66 |
recall | 0.87 | 0.89 | 0.8 | 0.41 |
F1 score | 0.89 | 0.82 | 0.73 | 0.5 |
Year | Ruili | Mangshi | Lianghe | Yingjiang | Longchuan |
---|---|---|---|---|---|
2012 | 43,757 | 105,419 | 35,843 | 129,793 | 60,050 |
2013 | 44,529 | 108,576 | 35,721 | 130,127 | 60,074 |
2014 | 44,979 | 107,738 | 35,651 | 129,832 | 60,210 |
2015 | 44,557 | 106,523 | 35,644 | 129,654 | 60,488 |
2017 | 43,988 | 105,757 | 35,494 | 129,549 | 62,121 |
Year | Ruili | Mangshi | Lianghe | Yingjiang | Longchuan |
---|---|---|---|---|---|
2012 | 4917 | 4119 | 1100 | 1648 | 1302 |
2013 | 4975 | 4117 | 967 | 1698 | 1373 |
2014 | 4997 | 4278 | 900 | 1695 | 1603 |
2015 | 4988 | 4292 | 862 | 1626 | 1652 |
2017 | 4803 | 4218 | 835 | 1746 | 1653 |
Year | Ruili | Mangshi | Lianghe | Yingjiang | Longchuan |
---|---|---|---|---|---|
2012 | 22,514 | 41,526 | 16,169 | 38,625 | 24,910 |
2013 | 22,917 | 43,236 | 16,003 | 38,317 | 24,435 |
2014 | 23,400 | 42,771 | 16,067 | 38,429 | 24,608 |
2015 | 23,058 | 42,139 | 16,103 | 38,356 | 24,782 |
2017 | 22,983 | 42,274 | 16,179 | 38,840 | 26,619 |
Region | Year | REPCcal (104 kW·h) | REPCreal (104 kW·h) | RE | ARE |
---|---|---|---|---|---|
Ruili | 2012 2013 2014 2015 2017 | 38,347 39,694 41,310 40,166 39,915 | 25,026 7371 15,075 7294 12,068 | 0.53 4.39 1.74 4.51 2.31 | 2.69 |
Mangshi | 2012 2013 2014 2015 2017 | 101,923 107,641 106,086 103,973 104,424 | 114,691 110,567 103,295 118,332 93,842 | 0.11 0.03 0.03 0.12 0.11 | 0.08 |
Lianghe | 2012 2013 2014 2015 2017 | 17,129 16,574 16,788 16,908 17,163 | 18,480 17,077 29,310 39,676 25,982 | 0.07 0.03 0.43 0.57 0.34 | 0.29 |
Yingjing | 2012 2013 2014 2015 2017 | 92,222 91,192 91,567 91,322 92,941 | 69,357 95,717 102,437 89,363 94,850 | 0.33 0.05 0.11 0.02 0.02 | 0.11 |
Longchuan | 2012 2013 2014 2015 2017 | 46,359 44,771 45,349 45,931 52,074 | 52,334 60,406 74,599 72,950 51,600 | 0.11 0.26 0.39 0.37 0.01 | 0.23 |
Region | Year | TEPCi (104 kW·h) | EPCi (104 kW·h) | Ki |
---|---|---|---|---|
Ruili | 2012 2013 2014 2015 2017 | 25,026 7371 15,075 7294 12,068 | 38,347 39,694 41,310 40,166 39,915 | 0.65 0.19 0.36 0.18 0.30 |
Mangshi | 2012 2013 2014 2015 2017 | 114,691 110,567 103,295 118,332 93,842 | 101,923 107,641 106,086 103,973 104,424 | 1.13 1.03 0.97 1.14 0.90 |
Lianghe | 2012 2013 2014 2015 2017 | 18,480 17,077 29,310 39,676 25,982 | 17,129 16,574 16,788 16,908 17,163 | 1.08 1.03 1.75 2.35 1.51 |
Yingjing | 2012 2013 2014 2015 2017 | 69,357 95,717 102,437 89,363 94,850 | 92,222 91,192 91,567 91,322 92,941 | 0.75 1.05 1.12 0.98 1.02 |
Longchuan | 2012 2013 2014 2015 2017 | 52,334 60,406 74,599 72,950 51,600 | 46,359 44,771 45,349 45,931 52,074 | 1.13 1.35 1.64 1.59 0.99 |
Region | Real REPC (104 kW·h) | Total EPC (104 kW·h) | Urban Center EPC (104 kW·h) |
---|---|---|---|
Ruili | 12,068 | 14,381 | 2313 |
Mangshi | 93,842 | 104,491 | 10,649 |
Lianghe | 25,982 | 27,483 | 1501 |
Yingjiang | 94,850 | 100,902 | 6052 |
Longchuan | 51,600 | 54,148 | 2548 |
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Zhao, F.; Ding, J.; Zhang, S.; Luan, G.; Song, L.; Peng, Z.; Du, Q.; Xie, Z. Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China. Remote Sens. 2020, 12, 2836. https://doi.org/10.3390/rs12172836
Zhao F, Ding J, Zhang S, Luan G, Song L, Peng Z, Du Q, Xie Z. Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China. Remote Sensing. 2020; 12(17):2836. https://doi.org/10.3390/rs12172836
Chicago/Turabian StyleZhao, Fei, Jieyu Ding, Sujin Zhang, Guize Luan, Lu Song, Zhiyan Peng, Qingyun Du, and Zhiqiang Xie. 2020. "Estimating Rural Electric Power Consumption Using NPP-VIIRS Night-Time Light, Toponym and POI Data in Ethnic Minority Areas of China" Remote Sensing 12, no. 17: 2836. https://doi.org/10.3390/rs12172836