References
- Brown, L. R. 1997. Who Will Feed China? Wake-up Call for a Small Planet. Vol. 5. New York: WW Norton & Company.
- Bryan, B. A., Y. Yanqiong, J. Zhang, and J. D. Connor. 2018. “Land-use Change Impacts on Ecosystem Services Value: Incorporating the Scarcity Effects of Supply and Demand Dynamics.” Ecosystem Services 32: 144–157. doi:https://doi.org/10.1016/j.ecoser.2018.07.002.
- Buchhorn, M., M. Lesiv, N.-E. Tsendbazar, M. Herold, L. Bertels, and B. Smets. 2020. “Copernicus Global Land Cover Layers—Collection 2.” Remote Sens 12 (6): 1044. doi:https://doi.org/10.3390/rs12061044
- Calderón-Loor, M., M. Hadjikakou, and B. A. Bryan. 2021. “High-resolution Wall-to-wall Land-cover Mapping and Land Change Assessment for Australia from 1985 to 2015.” Remote Sens. Environ 252: 112148. doi:https://doi.org/10.1016/j.rse.2020.112148.
- Cao, S., H. Deyong, W. Zhao, M. You, Y. Chen, and Y. Zhang. 2019. “Monitoring Changes in the Impervious Surfaces of Urban Functional Zones Using Multisource Remote Sensing Data: A Case Study of Tianjin, China.” GIScience & Remote Sensing 56 (7): 967–987. doi:https://doi.org/10.1080/15481603.2019.1600110.
- Chai, B., and L. Peijun. 2018. “Annual Urban Expansion Extraction and Spatio-Temporal Analysis Using Landsat Time Series Data: A Case Study of Tianjin, China.” IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens 11 (8): 2644–2656. doi:https://doi.org/10.1109/JSTARS.2018.2829525.
- Chen, G., L. Xia, X. Liu, Y. Chen, X. Liang, J. Leng, X. Xiaocong, et al. 2020. “Global Projections of Future Urban Land Expansion under Shared Socioeconomic Pathways.” Nature Communications 11 (1): 537. doi:https://doi.org/10.1038/s41467-020-14386-x.
- Chen, J., P. Jönsson, M. Tamura, Z. Gu, B. Matsushita, and L. Eklundh. 2004. “A Simple Method for Reconstructing A High-quality NDVI Time-series Data Set Based on the Savitzky–Golay Filter.” Remote Sensing of Environment 91 (3–4): 332–344. doi:https://doi.org/10.1016/j.rse.2004.03.014.
- Christina, A. F., M. Pesaresi, P. Politis, and V. Syrris. 2018. “GHS Built-up Grid, Derived from Landsat, Multitemporal (1975-1990-2000-2014), R2018A.” doi:https://doi.org/10.2905/JRC-GHSL-10007./rs12061044
- Clarke, K. C., and J. M. Johnson. 2020. “Calibrating SLEUTH with Big Data: Projecting California’s Land Use to 2100.” Computers, Environment and Urban Systems 83: 101525. doi:https://doi.org/10.1016/j.compenvurbsys.2020.101525.
- de Beurs, K. M., and G. M. Henebry. 2004. “Land Surface Phenology, Climatic Variation, and Institutional Change: Analyzing Agricultural Land Cover Change in Kazakhstan.” Remote Sens. Environ 89 (4): 497–509. doi:https://doi.org/10.1016/j.rse.2003.11.006.
- Deng, C., and Z. Zhu. 2020. “Continuous Subpixel Monitoring of Urban Impervious Surface Using Landsat Time Series.” Remote Sens. Environ 238: 110929. doi:https://doi.org/10.1016/j.rse.2018.10.011.
- Elmore, A. J., S. M. Guinn, B. J. Minsley, and A. D. Richardson. 2012. “Landscape Controls on the Timing of Spring, Autumn, and Growing Season Length in mid-Atlantic Forests.” Global Change Biol 18 (2): 656–674. doi:https://doi.org/10.1111/j.1365-2486.2011.02521.x.
- Fang, C., X. Cui, L. Guangdong, C. Bao, Z. Wang, M. Haitao, S. Sun, H. Liu, K. Luo, and Y. Ren. 2019. “Modeling Regional Sustainable Development Scenarios Using the Urbanization and Eco-Environment Coupler: Case Study of Beijing-Tianjin-Hebei Urban Agglomeration, China.” The Science of the Total Environment 689: 820–830. doi:https://doi.org/10.1016/j.scitotenv.2019.06.430.
- Filazzola, A., N. Shrestha, J. S. MacIvor, and M. Stanley. 2019. “The Contribution of Constructed Green Infrastructure to Urban Biodiversity: A Synthesis and Meta‐analysis.” Journal of Applied Ecology 56 (9): 2131–2143. doi:https://doi.org/10.1111/1365-2664.13475.
- Foga, S., P. L. Scaramuzza, S. Guo, R. D. Zhe Zhu, T. B. Dilley, G. L. Schmidt, J. L. Dwyer, L. Brady, B. Laue, and B. Laue. 2017. “Cloud Detection Algorithm Comparison and Validation for Operational Landsat Data Products.” Remote Sensing of Environment 194: 379–390. doi:https://doi.org/10.1016/j.rse.2017.03.026.
- Friedl, M., D. Sulla-Menashe. 2019. “MCD12Q1 MODIS/Terra+Aqua Land Cover Type Yearly L3 Global 500m SIN Grid V006. 2019, distributed by NASA EOSDIS Land Processes DAAC.” doi:https://doi.org/10.5067/MODIS/MCD12Q1.006
- Fu, Y., L. Jiufeng, Q. Weng, Q. Zheng, S. D. Le Li, B. Guo, and B. Guo. 2019. “Characterizing the Spatial Pattern of Annual Urban Growth by Using Time Series Landsat Imagery.” Science of the Total Environment 666: 274–284. doi:https://doi.org/10.1016/j.scitotenv.2019.02.178.
- Gong, P., L. Xuecao, J. Wang, Y. Bai, B. Chen, H. Tengyun, X. Liu, et al. 2020. “Annual Maps of Global Artificial Impervious Area (GAIA) between 1985 and 2018.” Remote Sens. Environ 236. doi:https://doi.org/10.1016/j.rse.2019.111510.
- Gong, P., L. Xuecao, and W. Zhang. 2019. “40-Year (1978–2017) Human Settlement Changes in China Reflected by Impervious Surfaces from Satellite Remote Sensing.” Sci. Bull. (Science Bulletin) 64 (11): 756–763. doi:https://doi.org/10.1016/j.scib.2019.04.024.
- Gorelick, N., M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore. 2017. “Google Earth Engine: Planetary-scale Geospatial Analysis for Everyone.” Remote Sensing of Environment 202: 18–27. doi:https://doi.org/10.1016/j.rse.2017.06.031.
- Guo, W., L. Guiying, N. Wenjian, Y. Zhang, and L. Dengsheng. 2018. “Exploring Improvement of Impervious Surface Estimation at National Scale through Integration of Nighttime Light and Proba-V Data.” GIScience & Remote Sensing 55 (5): 699–717. doi:https://doi.org/10.1080/15481603.2018.1436425.
- He, C., Z. Liu, S. Gou, Q. Zhang, J. Zhang, and X. Linlin. 2019. “Detecting Global Urban Expansion over the Last Three Decades Using a Fully Convolutional Network.” Environmental Research Letters 14 (3): 3. doi:https://doi.org/10.1088/1748-9326/aaf936.
- He, J., K. Yang, W. Tang, L. Hui, J. Qin, Y. Chen, and L. Xin. 2020. “The First High-Resolution Meteorological Forcing Dataset for Land Process Studies over China.” Scientific Data 7 (1): 25. doi:https://doi.org/10.1038/s41597-020-0369-y.
- Hopkins, F. M., J. R. Ehleringer, S. E. Bush, R. M. Duren, C. E. Miller, C.-T. Lai, Y.-K. Hsu, V. Carranza, and J. T. Randerson. 2016. “Mitigation of Methane Emissions in Cities: How New Measurements and Partnerships Can Contribute to Emissions Reduction Strategies.” Earth’s Future 4 (9): 408–425. doi:https://doi.org/10.1002/2016ef000381.
- Hou, X., L. Feng, J. Tang, X.-P. Song, J. Liu, Y. Zhang, J. Wang, et al. 2020. “Anthropogenic Transformation of Yangtze Plain Freshwater Lakes: Patterns, Drivers and Impacts.” Remote Sensing of Environment 248 :111998. doi:https://doi.org/10.1016/j.rse.2020.111998.
- Jin, G., K. Chen, P. Wang, B. Guo, Y. Dong, and J. Yang. 2019. “Trade-offs in Land-use Competition and Sustainable Land Development in the North China Plain.” Technological Forecasting and Social Change 141: 36–46. doi:https://doi.org/10.1016/j.techfore.2019.01.004.
- Jönsson, P., Z. Cai, E. Melaas, M. Friedl, and L. Eklundh. 2018. “A Method for Robust Estimation of Vegetation Seasonality from Landsat and Sentinel-2 Time Series Data.” Remote Sensing 10 (4): 635. doi:https://doi.org/10.3390/rs10040635.
- Jun, C., Y. Ban, and S. Li. 2014. “China: Open Access to Earth Land-Cover Map.” Nature 514 (7523): 434. doi:https://doi.org/10.1038/514434c
- Ke, X., J. van Vliet, P. H. Ting Zhou, W. Z. Verburg, X. Liu, and X. Liu. 2018. “Direct and Indirect Loss of Natural Habitat Due to Built-up Area Expansion: A Model-based Analysis for the City of Wuhan, China.” Land Use Policy 74: 231–239. doi:https://doi.org/10.1016/j.landusepol.2017.12.048.
- Kuang, W., A. Liu, Y. Dou, L. Guiying, and L. Dengsheng. 2019. “Examining the Impacts of Urbanization on Surface Radiation Using Landsat Imagery.” GIScience & Remote Sensing 56 (3): 462–484. doi:https://doi.org/10.1080/15481603.2018.1508931.
- Lamb, W. F., F. Creutzig, M. W. Callaghan, and J. C. Minx. 2019. “Learning about Urban Climate Solutions from Case Studies.” Nature Climate Change 9 (4): 279–287. doi:https://doi.org/10.1038/s41558-019-0440-x.
- Li, G., C. Jiang, J. Du, Y. Jia, and J. Bai. 2020a. “Spatial Differentiation Characteristics of Internal Ecological Land Structure in Rural Settlements and Its Response to Natural and Socio-Economic Conditions in the Central Plains, China.” Science of the Total Environment 709: 135932. doi:https://doi.org/10.1016/j.scitotenv.2019.135932.
- Li, G., L. Longwei, L. Dengsheng, W. Guo, and W. Kuang. 2020b. “Mapping Impervious Surface Distribution in China Using Multi-Source Remotely Sensed Data.” GIScience & Remote Sensing 57 (4): 543–552. doi:https://doi.org/10.1080/15481603.2020.1744240.
- Li, S., F. A. Suzana Dragicevic, M. S. Castro, S. Winter, A. Coltekin, C. Pettit, C. Pettit, et al. 2016. “Geospatial Big Data Handling Theory and Methods: A Review and Research Challenges.” ISPRS Journal of Photogrammetry and Remote Sensing 115 (2): 119–133. doi:https://doi.org/10.1016/j.isprsjprs.2015.10.012.
- Li, X., and P. Gong. 2016. “An “Exclusion-inclusion” Framework for Extracting Human Settlements in Rapidly Developing Regions of China from Landsat Images.” Remote Sensing of Environment 186: 286–296. doi:https://doi.org/10.1016/j.rse.2016.08.029.
- Li, X., P. Gong, and L. Liang. 2015. “A 30-year (1984–2013) Record of Annual Urban Dynamics of Beijing City Derived from Landsat Data.” Remote Sensing of Environment 166: 78–90. doi:https://doi.org/10.1016/j.rse.2015.06.007.
- Li, X. C., Y. Y. Zhou, Z. Y. Zhu, L. Liang, B. L. Yu, and W. T. Cao. 2018. “Mapping Annual Urban Dynamics (1985-2015) Using Time Series of Landsat Data.” Remote Sensing of Environment 216: 674–683. doi:https://doi.org/10.1016/j.rse.2018.07.030.
- Liu, C., Q. Zhang, H. Luo, S. H. Qi, S. Q. Tao, H. Z. Y. Xu, and Y. Yao. 2019. “An Efficient Approach to Capture Continuous Impervious Surface Dynamics Using Spatial-Temporal Rules and Dense Landsat Time Series Stacks.” Remote Sensing of Environment 229: 114–132. doi:https://doi.org/10.1016/j.rse.2019.04.025.
- Liu, Y., L. Liu, A.-X. Zhu, C. Lao, H. Guohua, and H. Yueming. 2020. “Scenario Farmland Protection Zoning Based on Production Potential: A Case Study in China.” Land Use Policy 95: 104581. doi:https://doi.org/10.1016/j.landusepol.2020.104581.
- National Bureau of Statistics of China. 2019a. “Announcement of the 2019 Grain Output.” Accessed 20 December 2020 http://www.gov.cn/xinwen/2019-12/07/content_5459250.htm
- National Bureau of Statistics of China. 2019b. “China Statistical Yearbook.” Beijing: China Statistics Press. Accessed November 06: 2020.
- Nations, U. 2019. “World Urbanization Prospects 2018: Highlights.” Population Division, United Nations 32. doi:https://doi.org/10.18356/6255ead2-en.
- Odenweller, J. B., and K. I. Johnson. 1984. “Crop Identification Using Landsat Temporal-spectral Profiles.” Remote Sensing of Environment 14 (1–3): 39–54. doi:https://doi.org/10.1016/0034-4257(84).90006-3.
- Poursanidis, D., N. Chrysoulakis, and Z. Mitraka. 2015. “Landsat 8 Vs. Landsat 5: A Comparison Based on Urban and Peri-urban Land Cover Mapping.” International Journal of Applied Earth Observation and Geoinformation 35: 259–269. doi:https://doi.org/10.1016/j.jag.2014.09.010.
- Roodposhti, M. S., J. Aryal, and B. A. Bryan. 2019. “A Novel Algorithm for Calculating Transition Potential in Cellular Automata Models of Land-use/cover Change.” Environmental Modelling and Software 112: 70–81. doi:https://doi.org/10.1016/j.envsoft.2018.10.006.
- Schneider, A., and C. M. Mertes. 2014. “Expansion and Growth in Chinese Cities, 1978–2010.” Environmental Research Letters 9 (2): 24008. doi:https://doi.org/10.1088/1748-9326/9/2/024008.
- Shi, L., F. Ling, G. Yong, G. Foody, L. Xiaodong, L. Wang, Y. Zhang, and D. Yun. 2017. “Impervious Surface Change Mapping with an Uncertainty-Based Spatial-Temporal Consistency Model: A Case Study in Wuhan City Using Landsat Time-Series Datasets from 1987 to 2016.” Remote Sensing 9 (11): 1148. doi:https://doi.org/10.3390/rs9111148.
- Shrivastava, M., M. O. Andreae, H. M. Paulo Artaxo, J. Barbosa, L. K. Berg, J. Brito, J. Ching, et al. 2019. “Urban Pollution Greatly Enhances Formation of Natural Aerosols over the Amazon Rainforest.” Nature Communications 10 (1): 1046. doi:https://doi.org/10.1038/s41467-019-08909-4.
- Song, W., and X. Deng. 2015. “Effects of Urbanization-Induced Cultivated Land Loss on Ecosystem Services in the North China Plain.” Energies 8 (6): 5678–5693. doi:https://doi.org/10.3390/en8065678.
- Song, X. P., J. O. Sexton, C. Q. Huang, S. Channan, and J. R. Townshend. 2016. “Characterizing the Magnitude, Timing and Duration of Urban Growth from Time Series of Landsat-Based Estimates of Impervious Cover.” Remote Sensing of Environment 175: 1–13. doi:https://doi.org/10.1016/j.rse.2015.12.027.
- Stehman, S. V., and G. M. Foody. 2019. “Key Issues in Rigorous Accuracy Assessment of Land Cover Products.” Remote Sens. Environ 231. doi:https://doi.org/10.1016/j.rse.2019.05.018.
- Tallis, H. T., T. Ricketts, A. D. Guerry, E. Nelson, D. Ennaanay, S. Wolny, N. Olwero, K. Vigerstol, D. Pennington, and G. Mendoza. 2011. InVEST 2.1 Beta User’s Guide. The Natural Capital Project.California: Stanford.
- Tang, J., J. Zeng, Q. Zhang, R. Zhang, S. Leng, Y. Zeng, W. Shui, X. Zhanghua, and Q. Wang. 2020. “Self-Adapting Extraction of Cropland Phenological Transitions of Rotation Agroecosystems Using Dynamically Fused NDVI Images.” International Journal of Biometeorology 64 (8): 1273–1283. doi:https://doi.org/10.1007/s00484-020-01904-1.
- Wang, C., L. Jing, Q. Liu, B. Zhong, W. Shanlong, and C. Xia. 2017. “Analysis of Differences in Phenology Extracted from the Enhanced Vegetation Index and the Leaf Area Index.” Sensors (Basel, Switzerland) 17 (9): 1982. doi:https://doi.org/10.3390/s17091982.
- Wang, J., Q. Zhang, T. Gou, M. Jianbing, Z. Wang, and M. Gao. 2018. “Spatial-temporal Changes of Urban Areas and Terrestrial Carbon Storage in the Three Gorges Reservoir in China.” Ecological Indicators 95: 343–352. doi:https://doi.org/10.1016/j.ecolind.2018.06.036.
- Wang, S., G. Azzari, and D. B. Lobell. 2019. “Crop Type Mapping without Field-Level Labels: Random Forest Transfer and Unsupervised Clustering Techniques.” Remote Sensing of Environment 222: 303–317. doi:https://doi.org/10.1016/j.rse.2018.12.026.
- Ye, Y., B. A. Bryan, J. D. Jia’en Zhang, L. C. Connor, Z. Qin, H. Mingqian, and M. He. 2018. “Changes in Land-use and Ecosystem Services in the Guangzhou-Foshan Metropolitan Area, China from 1990 to 2010: Implications for Sustainability under Rapid Urbanization.” Ecological Indicators 93: 930–941. doi:https://doi.org/10.1016/j.ecolind.2018.05.031.
- Yue, H., H. Chunyang, Q. Huang, D. Yin, and B. A. Bryan. 2020. “Stronger Policy Required to Substantially Reduce Deaths from PM2.5 Pollution in China.” Nature Communications 11 (1): 1462. doi:https://doi.org/10.1038/s41467-020-15319-4.
- Zeng, L., B. D. Wardlow, D. Xiang, H. Shun, and L. Deren. 2020. “A Review of Vegetation Phenological Metrics Extraction Using Time-series, Multispectral Satellite Data.” Remote Sens. Environ 237. doi:https://doi.org/10.1016/j.rse.2019.111511.
- Zhang, X., L. Liu, C. Wu, X. Chen, Y. Gao, S. Xie, and B. Zhang. 2020. “Development of a Global 30 m Impervious Surface Map Using Multisource and Multitemporal Remote Sensing Datasets with the Google Earth Engine Platform.” Earth System Science Data 12 (3): 1625–1648. doi:https://doi.org/10.5194/essd-12-1625-2020.
- Zhong, C., H. Ruifa, M. Wang, W. Xue, and H. Linfeng. 2020. “The Impact of Urbanization on Urban Agriculture: Evidence from China.” Journal of Cleaner Production 276: 122686. doi:https://doi.org/10.1016/j.jclepro.2020.122686.