Advanced search
Publication Cover
Big Earth Data Volume 5, 2021 - Issue 4: Big Data in Support of the Sustainable Development Goals (Part B): A celebration of the establishment of the International Research Center of Big Data for Sustainable Development Goals (CBAS)
Submit an article Journal homepage
1,635
Views
2
CrossRef citations to date
0
Altmetric
Original Research Article

Evaluation of county-level poverty alleviation progress by deep learning and satellite observations

Yanxiao Jianga State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, ChinaView further author information
,
Liqiang Zhanga State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, ChinaCorrespondence[email protected] [email protected]
View further author information
,
Yang Lia State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, ChinaView further author information
,
Jintai Linb Laboratory for Climate and Ocean-Atmosphere Studies, Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, ChinaView further author information
,
Jingwen Lic Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guangxi, ChinaView further author information
,
Guoqing Zhouc Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guangxi, ChinaView further author information
,
Suhong Liua State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, ChinaView further author information
,
Jing Caod School of Economics and Management, Tsinghua University, Beijing, ChinaView further author information
&
Zhiqiang Xiaoa State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, ChinaView further author information
 show all
Pages 576-592 | Received 10 Jun 2021, Accepted 04 Aug 2021, Published online: 12 Oct 2021

References

  • Bapna, M. (2012). World poverty: Sustainability is key to development goals. Nature, 489(7416), 367.
  • Dai, Z., Hu, Y., & Zhao, G. (2017). The suitability of different nighttime light data for GDP estimation at different spatial scales and regional levels. Sustainability, 9(2), 305.
  • Ge, Y., Yuan, Y., Hu, S., Ren, Z., & Wu, Y. (2017). Space-time variability analysis of poverty alleviation performance in China’s poverty-stricken areas. Spatial Statistics, 21, 460–474.
  • Gou, X., & Yang, J. (2019). Application of Benford’s law in data quality evaluation of department final accounts. Public Finance Research, (2), 26–42.
  • He, K., Zhang, X., Ren, S., & Sun, J. (2016). Deep residual learning for image recognition. IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, NV, USA. doi: https://doi.org/10.1109/CVPR.2016.90
  • Hu, J., Shen, L., & Sun, G. (2018). Squeeze-and-Excitation Networks. IEEE Conference on Computer Vision and Pattern Recognition, Salt Lake City, UT, USA, 7132–7141. doi: https://doi.org/10.1109/TPAMI.2019.2913372
  • Huang, X., Wang, C., & Lu, J. (2019). Understanding the spatiotemporal development of human settlement in hurricane-prone areas on the US Atlantic and Gulf coasts using nighttime remote sensing. Natural Hazards and Earth System Sciences, 19(10), 2141–2155.
  • Jean, N., Burke, M., Xie, M., Davis, W. M., Lobell, D. B., & Ermon, S. (2016). Combining satellite imagery and machine learning to predict poverty. Science, 353(6301), 790–794.
  • Judge, G., & Schechter, L. (2009). Detecting problems in survey data using Benford’s Law. Journal of Human Resources, 44(1), 1–24.
  • Lin, W. (2018). Discussion on subtle central-local economic relations and their reshaping and adjustment from the phenomenon of data falsification. China Market, 973(18), 28–30.
  • Liu, Y., Liu, J., & Zhou, Y. (2017). Spatio-temporal patterns of rural poverty in China and targeted poverty alleviation strategies. Journal of Rural Studies, 52, 66–75.
  • Pokhriyal, N., & Jacques, D. C. (2017). Combining disparate data sources for improved poverty prediction and mapping. Proceedings of the National Academy of Sciences, 2017, 114(46): E9783-E9792.
  • Sun, J., Di, L., Sun, Z., Wang, J., Wu, Y. (2020). Estimation of GDP using deep learning with NPP-VIIRS imagery and land cover data at the county-level in CONUS. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 99, 1–1. doi:https://doi.org/10.1109/JSTARS.2020.2983331
  • Tollefson, J. (2015). Can randomized trials eliminate global poverty? Nature, 524(7564), 15–153.
  • United Nations. (2015). The Millennium Development Goals Report 2015. New York.
  • Wang, H., & Zheng, K. Y. (2018). Analysis for recent adjustment of statistical data in some provinces. China Market, (36), 10–12. doi:https://doi.org/10.1080/10130950.2009.9676265
  • Westmore, B. (2018). Do government transfers reduce poverty in China? Micro evidence from five regions. China Economic Review, 51, 59–69.
  • Xiao, Z., Liang, S., Wang, J., Xiang, Y., Zhao, X., & Song, J. (2016). Long-time-series global land surface satellite leaf area index product derived from MODIS and AVHRR surface reflectance. IEEE Transactions on Geoscience and Remote Sensing, 54(9), 5301–5318.
  • Xu, Z., Chau, S. N., Chen, X., Zhang, J., Li, Y., Dietz, T., … Liu, J. (2020). Assessing progress towards sustainable development over space and time. Nature, 577(7788), 74–78.
  • Xue, L., & Weng, L. (2017). The policy opportunities and challenges in China’s implementation of 2030 sustainable development goals. China Soft Science, 1, 1–12.
  • Yeh, C., Perez, A., Driscoll, A., Azzari, G., Tang, Z., Lobell, D., … Burke, M. (2020). Using publicly available satellite imagery and deep learning to understand economic well-being in Africa. Nature Communications, 11(1), 2583.
  • Zhang, H., Xu, Z., Sun, C., & Elahi, E. (2018). Targeted poverty alleviation using photovoltaic power: Review of Chinese policies. Energy Policy, 120, 550–558.
  • Zhou, Y., Guo, Y., Liu, Y., Wu, W., & Li, Y. (2018). Targeted poverty alleviation and land policy innovation: Some practice and policy implications from China. Land Use Policy, 74, 53–65.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.