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Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data.

K. Shi, B. Yu, Y. Huang, Y. Hu, B. Yin, Z. Chen, L. Chen, und J. Wu. Remote. Sens., 6 (2): 1705-1724 (2014)

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Zhanjun Shi

Jian Shi

Renhu Shi

Huili Shi

Lei Shi

Weitere Publikationen von Autoren mit dem selben Namen

Identifying and Quantifying Urban Polycentric Development in China From DMSP-OLS Data and Urban Land Data Sets.K. Shi, J. Shen, Y. Wu, und X. Tang. IEEE Geosci. Remote. Sens. Lett., (2022)Exploring Spatial and Temporal Connection Patterns among the Districts in Chongqing Based on Highway Passenger Flow.Y. Huang, K. Shi, H. Zong, T. Zhou, und J. Shen. Remote Sensing, 12 (1): 27 (2020)The potential of nighttime light remote sensing data to evaluate the development of digital economy: A case study of China at the city level.Z. Chen, Y. Wei, K. Shi, Z. Zhao, C. Wang, B. Wu, B. Qiu, und B. Yu. Comput. Environ. Urban Syst., (2022)Carbon dioxide (CO2) emissions from the service industry, traffic, and secondary industry as revealed by the remotely sensed nighttime light data.K. Shi, J. Shen, Y. Wu, S. Liu, und L. Li. Int. J. Digit. Earth, 14 (11): 1514-1527 (2021)Remote Sensing of Wetland Flooding at a Sub-Pixel Scale Based on Random Forests and Spatial Attraction Models.L. Li, Y. Chen, T. Xu, K. Shi, R. Liu, C. Huang, B. Lu, und L. Meng. Remote. Sens., 11 (10): 1231 (2019)Evaluating the Ability of NPP-VIIRS Nighttime Light Data to Estimate the Gross Domestic Product and the Electric Power Consumption of China at Multiple Scales: A Comparison with DMSP-OLS Data.K. Shi, B. Yu, Y. Huang, Y. Hu, B. Yin, Z. Chen, L. Chen, und J. Wu. Remote. Sens., 6 (2): 1705-1724 (2014)Estimating and Interpreting Fine-Scale Gridded Population Using Random Forest Regression and Multisource Data.Y. Zhou, M. Ma, K. Shi, und Z. Peng. ISPRS Int. J. Geo Inf., 9 (6): 369 (2020)Enhanced Super-Resolution Mapping of Urban Floods Based on the Fusion of Support Vector Machine and General Regression Neural Network.L. Li, Y. Chen, T. Xu, K. Shi, C. Huang, R. Liu, B. Lu, und L. Meng. IEEE Geosci. Remote. Sens. Lett., 16 (8): 1269-1273 (2019)Rapid Socioeconomic Growth in Southeast Asia: Evidence From Nighttime Light Observations.Y. Cui, R. Zhao, M. Zhang, L. Wang, Y. Yuan, X. Duan, und K. Shi. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2024)Does China's City-Size Distribution Present a Flat Distribution Trend? A Socioeconomic and Spatial Size Analysis From DMSP-OLS Nighttime Light Data.K. Shi, Y. Wu, und S. Liu. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2021)

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