[1] Bagheri B, Tousi S N, 2018. An explanation of urban sprawl phenomenon in Shiraz Metropolitan Area (SMA). Cities, 73: 71–90. doi:  10.1016/j.cities.2017.10.011
[2] Barbosa J A, Bragança L, Mateus R, 2015. Assessment of land use efficiency using Bsa tools: development of a new index. Journal of Urban Planning and Development, 141: 04014020. doi:  10.1061/(ASCE)UP.1943-5444.0000208
[3] Chen W, Ning S Y, Chen W J et al., 2020. Spatial-temporal characteristics of industrial land green efficiency in China: evidence from prefecture-level cities. Ecological Indicators, 113: 106256. doi:  10.1016/j.ecolind.2020.106256
[4] Chen Xiaohui, Guo Zijian, Zhong Rui, 2019. Reflections and prospect of interactions between development zones and urbanization: a case study of Jiangsu. Urban Planning Forum, (1): 68–73. (in Chinese)
[5] Chen Y, Chen Z G, Xu G L et al., 2016. Built-up land efficiency in urban China: insights from the General Land Use Plan (2006–2020). Habitat International, 51: 31–38. doi:  10.1016/j.habitatint.2015.10.014
[6] De Vos J, Witlox F, 2013. Transportation policy as spatial planning tool; reducing urban sprawl by increasing travel costs and clustering infrastructure and public transportation. Journal of Transport Geography, 33: 117–125. doi:  10.1016/j.jtrangeo.2013.09.014
[7] Ding C R, Lichtenberg E, 2011. Land and urban economic growth in China. Journal of Regional Science, 51(2): 299–317. doi:  10.1111/j.1467-9787.2010.00686.x
[8] Gao J L, Yuan F, 2017. Economic transition, firm dynamics, and restructuring of manufacturing spaces in urban China: empirical evidence from Nanjing. The Professional Geographer, 69(3): 504–519. doi:  10.1080/00330124.2016.1268059
[9] González M, López-Espín J J, Aparicio J et al., 2015. Using genetic algorithms for maximizing technical efficiency in data envelopment analysis. Procedia Computer Science, 51: 374–383. doi:  10.1016/j.procs.2015.05.257
[10] Guo S, Shen G Q, Chen Z M et al., 2014. Embodied cultivated land use in China 1987–2007. Ecological Indicators, 47: 198–209. doi:  10.1016/j.ecolind.2014.05.019
[11] He S W, Yu S, Li G D et al., 2020. Exploring the influence of urban form on land-use efficiency from a spatiotemporal heterogeneity perspective: evidence from 336 Chinese cities. Land Use Policy, 95: 104576. doi:  10.1016/j.landusepol.2020.104576
[12] Hegazy I R, Kaloop M R, 2015. Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. International Journal of Sustainable Built Environment, 4(1): 117–124. doi:  10.1016/j.ijsbe.2015.02.005
[13] Huang Muyi, Yue Wenze, He Xiang, 2018. Decoupling relationship between urban expansion and economic growth and its spatial heterogeneity in the Yangtze Economic Belt. Journal of Natural Resources, 33(2): 219–232. (in Chinese)
[14] Huang Z J, He C F, Zhu S J, 2017. Do China’s economic development zones improve land use efficiency? The effects of selection, factor accumulation and agglomeration. Landscape and Urban Planning, 162: 145–156. doi:  10.1016/j.landurbplan.2017.02.008
[15] Jin G, Chen K, Wang P et al., 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:  10.1016/j.techfore.2019.01.004
[16] Katkovnik V, Shmulevich I, 2002. Kernel density estimation with adaptive varying window size. Pattern Recognition Letters, 23(14): 1641–1648. doi:  10.1016/S0167-8655(02)00127-7
[17] Kaur H, Garg P, 2019. Urban sustainability assessment tools: a review. Journal of Cleaner Production, 210: 146–158. doi:  10.1016/j.jclepro.2018.11.009
[18] Kuang B, Lu X H, Zhou M et al., 2020. Provincial cultivated land use efficiency in China: empirical analysis based on the SBM-DEA model with carbon emissions considered. Technological Forecasting and Social Change, 151: 119874. doi:  10.1016/j.techfore.2019.119874
[19] Lee J H, Lim S, 2018. The selection of compact city policy instruments and their effects on energy consumption and greenhouse gas emissions in the transportation sector: the case of South Korea. Sustainable Cities and Society, 37: 116–124. doi:  10.1016/j.scs.2017.11.006
[20] Liu H W, Zhang Y, Zhu Q Y et al., 2017. Environmental efficiency of land transportation in China: a parallel slack-based measure for regional and temporal analysis. Journal of Cleaner Production, 142: 867–876. doi:  10.1016/j.jclepro.2016.09.048
[21] Liu S C, Xiao W, Li L L et al., 2020. Urban land use efficiency and improvement potential in China: a stochastic frontier analysis. Land Use Policy, 99: 105046. doi:  10.1016/j.landusepol.2020.105046
[22] Liu Y, Fan P L, Yue W Z et al., 2018. Impacts of land finance on urban sprawl in China: the case of Chongqing. Land Use Policy, 72: 420–432. doi:  10.1016/j.landusepol.2018.01.004
[23] Lu L L, Weng Q H, Guo H D et al., 2019. Assessment of urban environmental change using multi-source remote sensing time series (2000–2016): a comparative analysis in selected megacities in Eurasia. Science of the Total Environment, 684: 567–577. doi:  10.1016/j.scitotenv.2019.05.344
[24] Lu X H, Kuang B, Li J, 2018. Regional difference decomposition and policy implications of China’s urban land use efficiency under the environmental restriction. Habitat International, 77: 32–39. doi:  10.1016/j.habitatint.2017.11.016
[25] Luo J J, Xing X S, Wu Y Z et al., 2018. Spatio-temporal analysis on built-up land expansion and population growth in the Yangtze River Delta Region, China: from a coordination perspective. Applied Geography, 96: 98–108. doi:  10.1016/j.apgeog.2018.05.012
[26] Masoudi M, Tan P Y, Fadaei M, 2021. The effects of land use on spatial pattern of urban green spaces and their cooling ability. Urban Climate, 35: 100743. doi:  10.1016/j.uclim.2020.100743
[27] Miller J D, Brewer T, 2018. Refining flood estimation in urbanized catchments using landscape metrics. Landscape and Urban Planning, 175: 34–49. doi:  10.1016/j.landurbplan.2018.02.003
[28] Ministry of Housing and Urban-Rural Construction of China (MHURC), 2000–2018. China Urban Construction Statistical Yearbook. Beijing: China Planning Press. (in Chinese)
[29] Mohajerani A, Bakaric J, Jeffrey-Bailey T, 2017. The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete. Journal of Environmental Management, 197: 522–538. doi:  10.1016/j.jenvman.2017.03.095
[30] Muscat A, De Olde E M, Candel J J L et al., 2022. The Promised Land: contrasting frames of marginal land in the European Union. Land Use Policy, 112: 105860. doi:  10.1016/j.landusepol.2021.105860
[31] National Bureau of Statistics of China (NBSC), 2000–2018. China City Statistical Yearbook 2000−2018. Beijing: China Statistics Press. (in Chinese)
[32] National Bureau of Statistics of China (NBSC), 2019. China Statistical Yearbook 2019. Beijing: China Statistics Press. (in Chinese)
[33] Otto S A C, Gernaat D E H J, Isaac M et al., 2015. Impact of fragmented emission reduction regimes on the energy market and on CO2 emissions related to land use: a case study with China and the European Union as first movers. Technological Forecasting and Social Change, 90: 220–229. doi:  10.1016/j.techfore.2014.01.015
[34] Sciara G C, 2020. Implementing regional smart growth without regional authority: the limits of information for nudging local land use. Cities, 103: 102661. doi:  10.1016/j.cities.2020.102661
[35] Tan M H, Li X B, Xie H et al., 2005. Urban land expansion and arable land loss in China—a case study of Beijing-Tianjin-Hebei region. Land Use Policy, 22(3): 187–196. doi:  10.1016/j.landusepol.2004.03.003
[36] Tone K, 2001. A slacks-based measure of efficiency in data envelopment analysis. European Journal of Operational Research, 130(3): 498–509. doi:  10.1016/S0377-2217(99)00407-5
[37] Wang Jianlin, Zhao Jiajia, Song Malin, 2017. Analysis of urban land use efficiency in China based on endogenous directional distance function model. Geographical Research, 36(7): 1386–1398. (in Chinese)
[38] Wei Y D, Li H, Yue W Z, 2017. Urban land expansion and regional inequality in transitional China. Landscape and Urban Planning, 163: 17–31. doi:  10.1016/j.landurbplan.2017.02.019
[39] Williams T M, Ben-David M, Noren S et al., 2002. Running energetics of the North American river otter: do short legs necessarily reduce efficiency on land? Comparative Biochemistry and Physiology Part A:Molecular & Integrative Physiology, 133(2): 203–212. doi:  10.1016/S1095-6433(02)00136-8
[40] Xie Hualin, Wang Wei, 2015. Spatiotemporal differences and convergence of urban industrial land use efficiency for China’s major economic zones. Journal of Geographical Sciences, 25(10): 1183–1198. doi:  10.1007/s11442-015-1227-2
[41] Xu X Y, Yan Z, Xu S L, 2015. Estimating wind speed probability distribution by diffusion-based kernel density method. Electric Power Systems Research, 121: 28–37. doi:  10.1016/j.jpgr.2014.11.029
[42] Yang Liangjie, Wu Wei, Su Qin et al., 2013. Evaluation of road transport efficiency in China during 1997–2010 based on SBM-Undesirable model. Progress in Geography, 32(11): 1602–1611. (in Chinese)
[43] Yang Qingke, Duan Xuanjun, Ye Lei et al., 2014. Efficiency evaluation of city land utilization in the Yangtze River Delta using a SBM-undesirable model. Resources Science, 36(4): 712–721. (in Chinese)
[44] Yu J Q, Zhou K L, Yang S L, 2019. Land use efficiency and influencing factors of urban agglomerations in China. Land Use Policy, 88: 104143. doi:  10.1016/j.landusepol.2019.104143
[45] Yuan Peng, Tang Xin, Peng Wenwu et al., 2020. The spatial connection of potential innovation factor synergy and its relation with the upgrading of high-tech industry in Yangtze River Delta. Economic Geography, 40(6): 1–14. (in Chinese)
[46] Zhao R, Liu S L, Liu Y Y et al., 2018a. A safety vulnerability assessment for chemical enterprises: a hybrid of a data envelopment analysis and fuzzy decision-making. Journal of Loss Prevention in the Process Industries, 56: 95–103. doi:  10.1016/j.jlp.2018.08.018
[47] Zhao Z, Bai Y P, Wang G F et al., 2018b. Land eco-efficiency for new-type urbanization in the Beijing-Tianjin-Hebei Region. Technological Forecasting and Social Change, 137: 19–26. doi:  10.1016/j.techfore.2018.09.031
[48] Zhu X H, Zhang P F, Wei Y G et al., 2019. Measuring the efficiency and driving factors of urban land use based on the DEA method and the PLS-SEM model—a case study of 35 large and medium-sized cities in China. Sustainable Cities and Society, 50: 101646. doi:  10.1016/j.scs.2019.101646