地球信息科学学报 ›› 2022, Vol. 24 ›› Issue (2): 299-309.doi: 10.12082/dqxxkx.2022.210079
李军1(), 刘举庆1,*(
), 游林2, 董恒3, 俞艳3, 张晓盼3, 钟文军4, 杨典华5
收稿日期:
2021-02-18
修回日期:
2021-03-28
出版日期:
2022-02-25
发布日期:
2022-04-25
通讯作者:
*刘举庆(1995— ),男,山东临沂人,博士研究生,主要研究方向为地理大数据分析与挖掘。E-mail: liujvq@163.com作者简介:
李 军(1987— ),男,湖北汉川人,副教授,主要从事地理信息科学理论与方法应用研究。E-mail: junli@cumtb.edu.cn
基金资助:
LI Jun1(), LIU Juqing1,*(
), YOU Lin2, DONG Heng3, YU Yan3, ZHANG Xiaopan3, ZHONG Wenjun4, YANG Dianhua5
Received:
2021-02-18
Revised:
2021-03-28
Online:
2022-02-25
Published:
2022-04-25
Supported by:
摘要:
伴随着城镇化的快速推进,城乡建设用地资源日益紧张,但目前土地储备决策缺乏精准科学依据,无法有效地进行资源配置和宏观调控。针对此问题,本文深入剖析土地储备基本业务与决策环节,研究了一套面向土地储备的智能决策模型集,包括存量土地监测模型、收储成本预测模型、出让价格预测模型、储备平衡分析模型、相似地块分析模型、开发时序分析模型及病态地块识别模型,旨在将土地储备决策环节科学化、定量化和模型化,并重点为土地储备总量、效益、规模、结构、布局、时序的统筹安排提供建议。另外,该模型集具有体系化、高效灵活、智能化的特点,能够服务于储备业务全链条,满足即时决策应用需求和实现模型自主更新与进化,保证模型的时效性。最后,该模型集已经工程化应用于宁波市土地储备智能决策支持平台,实践验证了以上决策模型具有较高的准确度和实用性,表明模型集能够为土地储备的科学决策提供理论依据,有利于土地资源的集约利用和高效配置。
李军, 刘举庆, 游林, 董恒, 俞艳, 张晓盼, 钟文军, 杨典华. 多源大数据支持的土地储备智能决策模型集研究[J]. 地球信息科学学报, 2022, 24(2): 299-309.DOI:10.12082/dqxxkx.2022.210079
LI Jun, LIU Juqing, YOU Lin, DONG Heng, YU Yan, ZHANG Xiaopan, ZHONG Wenjun, YANG Dianhua. An Intelligent Decision Model Set for Land Reserve based on Multi-source Big Data[J]. Journal of Geo-information Science, 2022, 24(2): 299-309.DOI:10.12082/dqxxkx.2022.210079
[1] | 国家统计局. 2018年国民经济和社会发展统计公报[EB/OL]. http://www.stats.gov.cn/tjsj/zxfb/201902/t20190228_1651265.html, 2019-02-28. |
[National Bureau of Statistics. 2018 statistical bulletin on national economic and social development[EB/OL]. http://www.stats.gov.cn/tjsj/zxfb/201902/t20190228_1651265.html, 2019-02-28. ] | |
[2] | 夏柱智. 城市化进程中的土地制度改革比较研究—— 基于苏南和珠三角的经验[J]. 社会科学, 2019(2):81-88. |
[ Xia Z Z. A comparative study of land system reform in the process of urbanization: Based on the experience of south of Jiangsu and the Pearl River Delta region[J]. Journal of Social Sciences, 2019(2):81-88. ] DOI: 10.13644/j.cnki.cn31-1112.2019.02.008
doi: 10.13644/j.cnki.cn31-1112.2019.02.008 |
|
[3] |
Sheng X W, Cao Y G, Zhou W, et al. Multiple scenario simulations of land use changes and countermeasures for collaborative development mode in Chaobai River region of Jing-Jin-Ji, China[J]. Habitat International, 2018, 82:38-47. DOI: 10.1016/j.habitatint.2018.10.008
doi: 10.1016/j.habitatint.2018.10.008 |
[4] | 李明超. 城市土地征收、储备、出让改革联动述论[J]. 西部论坛, 2017, 27(5):54-63. |
[ Li M C. Review of urban land expropriation, reserve, transfer and management reform of China[J]. West Forum, 2017, 27(5):54-63. ] DOI: 10.3969/j.issn.1674-8131.2017.05.009
doi: 10.3969/j.issn.1674-8131.2017.05.009 |
|
[5] | 高霞, 朱德米. 中国土地储备政策演进的结构特征[J]. 城市问题, 2017(12):72-80. |
[ Gao X, Zhu D M. Structual features of the evolution of China's land conservation policies[J]. Urban Problems, 2017(12):72-80. ] DOI: 10.13239/j.bjsshkxy.cswt.171210
doi: 10.13239/j.bjsshkxy.cswt.171210 |
|
[6] | 黄海, 祝国瑞. 基于模糊神经网络的土地合理储备量预测研究[J]. 武汉大学学报·信息科学版, 2006, 31(6):561-563. |
[ Huang H, Zhu G R. Application of fuzzy neural networks to land reserve prediction[J]. Geomatics and Information Science of Wuhan University, 2006, 31(6):561-563. ] DOI: 10.3969/j.issn.1671-8860.2006.06.024
doi: 10.3969/j.issn.1671-8860.2006.06.024 |
|
[7] |
Wang Y J, Li L J. Forecasts of urban construction land scale based on driving force analysis[C]//Proceedings of the 2017 5th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering (ICMMCCE 2017). Paris: Atlantis Press, 2017:453-456. DOI: 10.2991/icmmcce-17.2017.86
doi: 10.2991/icmmcce-17.2017.86 |
[8] |
Xiong Y, Chen Y, Peng F, et al. Analog simulation of urban construction land supply and demand in Chang-Zhu-Tan Urban Agglomeration based on land intensive use[J]. Journal of Geographical Sciences, 2019, 29(8):1346-1362. DOI: 10.1007/s11442-019-1663-5
doi: 10.1007/s11442-019-1663-5 |
[9] | 刘鹏, 关丽, 罗晓燕. 基于GIS的城市建设用地资源潜力评价初探[J]. 地理与地理信息科学, 2011, 27(5):69-73. |
[ Liu P, Guan L, Luo X Y. Potential resource evaluation of urban construction land based on GIS[J]. Geography and Geo-information Science, 2011, 27(5):69-73. ] DOI: CNKI:SUN:DLGT.0.2011-05-016
doi: CNKI:SUN:DLGT.0.2011-05-016 |
|
[10] |
Xu Y, Tang Q, Fan J, et al. Assessing construction land potential and its spatial pattern in China[J]. Landscape and Urban Planning, 2011, 103(2):207-216. DOI: 10.1016/j.landurbplan.2011.07.013
doi: 10.1016/j.landurbplan.2011.07.013 |
[11] | 董冠鹏, 张文忠, 武文杰, 等. 北京城市住宅土地市场空间异质性模拟与预测[J]. 地理学报, 2011, 66(6):750-760. |
[ Dong G P, Zhang W Z, Wu W J, et al. Spatial heterogeneity in determinants of residential land price: Simulation and prediction[J]. Acta Geographica Sinica, 2011, 66(6):750-760. ] DOI: 10.11821/xb201106004
doi: 10.11821/xb201106004 |
|
[12] |
Wang Z Y, Fu M C, Yu Y L, et al. Prediction of urban land price based on Grey-Markov model[C]// Proceedings of 2011 International Conference on Computer Science and Network Technology. IEEE, 2011:708-712. DOI: 10.1109/ICCSNT.2011.6182064
doi: 10.1109/ICCSNT.2011.6182064 |
[13] |
Sampathkumar V, Santhi M H, Vanjinathan J. Forecasting the land price using statistical and neural network software[J]. Procedia Computer Science, 2015, 57:112-121. DOI: 10.1016/j.procs.2015.07.377
doi: 10.1016/j.procs.2015.07.377 |
[14] |
Li L B, Chen Y M, Yu C. Study on the price and economic impact of residential land based on system dynamics[C]// ICCREM 2017. Reston, VA: American Society of Civil Engineers, 2017:187-196. DOI: 10.1061/9780784481073.021
doi: 10.1061/9780784481073.021 |
[15] | 李德仁, 马军, 邵振峰. 论时空大数据及其应用[J]. 卫星应用, 2015(9):7-11. |
[ Li D R, Ma J, Shao Z F. Discussion on spatio-temporal big data and its application[J]. Satellite Application, 2015(9):7-11. ] DOI: CNKI:SUN:WXYG.0.2015-09-005
doi: CNKI:SUN:WXYG.0.2015-09-005 |
|
[16] |
Xie H L, He Y F, Xie X. Exploring the factors influencing ecological land change for China's Beijing-Tianjin-Hebei Region using big data[J]. Journal of Cleaner Production, 2017, 142:677-687. DOI: 10.1016/j.jclepro.2016.03.064
doi: 10.1016/j.jclepro.2016.03.064 |
[17] | 吴志峰, 曹峥, 宋松, 等. 粤港澳大湾区湿地遥感监测与评估:现状、挑战及展望[J]. 生态学报, 2020, 40(23):8440-8450. |
[ Wu Z F, Cao Z, Song S, et al. Wetland remote sensing monitoring and assessment in Guangdong-Hong Kong-Macao Greater Bay Area: Current status, challenges and future perspectives[J]. Acta Ecologica Sinica, 2020, 40(23):8440-8450. ] DOI: 10.5846/stxb202004150888
doi: 10.5846/stxb202004150888 |
|
[18] |
Ding L, Shao Z F, Zhang H C, et al. A comprehensive evaluation of urban sustainable development in China based on the TOPSIS-entropy method[J]. Sustainability, 2016, 8(8):746. DOI: 10.3390/su8080746
doi: 10.3390/su8080746 |
[19] | 陈能成, 刘迎冰, 盛浩, 等. 智慧城市时空信息综合决策关键技术与系统[J]. 武汉大学学报·信息科学版, 2018, 43(12):2278-2286. |
[ Chen N C, Liu Y B, Sheng H, et al. Key techniques and system for comprehensive decision-making of spatio-temporal information in smart city[J]. Geomatics and Information Science of Wuhan University, 2018, 43(12):2278-2286. ] DOI: 10.13203/j.whugis20180198
doi: 10.13203/j.whugis20180198 |
|
[20] |
Li J, Li Q Q, Zhu Y, et al. An automatic extraction method of coach operation information from historical trajectory data[J]. Journal of Advanced Transportation, 2019, 2019:1-15. DOI: 10.1155/2019/3634942
doi: 10.1155/2019/3634942 |
[21] |
Tu W, Zhu T T, Xia J Z, et al. Portraying the spatial dynamics of urban vibrancy using multisource urban big data[J]. Computers, Environment and Urban Systems, 2020, 80:101428. DOI: 10.1016/j.compenvurbsys.2019.101428
doi: 10.1016/j.compenvurbsys.2019.101428 |
[22] | 秦萧, 甄峰, 李亚奇, 等. 国土空间规划大数据应用方法框架探讨[J]. 自然资源学报, 2019, 34(10):2134-2149. |
[ Qin X, Zhen F, Li Y Q, et al. Discussion on the application framework of big data in territorial spatial planning[J]. Journal of Natural Resources, 2019, 34(10):2134-2149. ] DOI: 10.31497/zrzyxb.20191010
doi: 10.31497/zrzyxb.20191010 |
|
[23] |
Batty M. Big data, smart cities and city planning[J]. Dialogues in Human Geography, 2013, 3(3):274-279. DOI: 10.1177/2043820613513390
doi: 10.1177/2043820613513390 |
[24] | 李燕萍, 虞虎, 王昊, 等. 面向大数据时代的城市规划研究响应与应对方略[J]. 城市发展研究, 2017, 24(10):1-10. |
[ Li Y P, Yu H, Wang H, et al. The response and countermeasures of urban planning research in the era of big data[J]. Urban Development Studies, 2017, 24(10):1-10. ] DOI: 10.3969/j.issn.1006-3862.2017.10.001
doi: 10.3969/j.issn.1006-3862.2017.10.001 |
|
[25] | 喻文承, 李晓烨, 高娜, 等. 北京国土空间规划“一张图”建设实践[J]. 规划师, 2020, 36(2):59-64,77. |
[ Yu W C, Li X Y, Gao N, et al. “one map” construction in national land-space plan, Beijing[J]. Planners, 2020, 36(2):59-64,77. ] DOI: 10.3969/j.issn.1006-0022.2020.02.009
doi: 10.3969/j.issn.1006-0022.2020.02.009 |
|
[26] | 李满春, 陈振杰, 周琛, 等. 面向“一张图”的国土空间规划数据库研究[J]. 中国土地科学, 2020, 34(5):69-75. |
[ Li M C, Chen Z J, Zhou C, et al. “one map” oriented database investigation for territorial space planning[J]. China Land Science, 2020, 34(5):69-75. ] DOI: 10.11994/zgtdkx.20200514.144131
doi: 10.11994/zgtdkx.20200514.144131 |
|
[27] |
Cai J X, Huang B, Song Y M. Using multi-source geospatial big data to identify the structure of polycentric cities[J]. Remote Sensing of Environment, 2017, 202:210-221. DOI: 10.1016/j.rse.2017.06.039
doi: 10.1016/j.rse.2017.06.039 |
[28] | 蒋希冀, 王静, 王兰. 基于多源数据的城市功能布局优化研究:以上海市宝山区为例[J]. 现代城市研究, 2020, 35(5):2-9,37. |
[ Jiang X J, Wang J, Wang L. Research on optimization of urban functional layout based on multi-source data: A case study of Baoshan district, Shanghai[J]. Modern Urban Research, 2020, 35(5):2-9,37. ] DOI: 10.3969/j.issn.1009-6000.2020.05.001
doi: 10.3969/j.issn.1009-6000.2020.05.001 |
|
[29] | Gao X, Cai J. Optimization analysis of urban function regional planning based on big data and GIS Technology[J]. Boletin Tecnico/Technical Bulletin, 2017, 55(11):344-351. |
[30] |
杨振山, 苏锦华, 杨航, 等. 基于多源数据的城市功能区精细化研究——以北京为例[J]. 地理研究, 2021, 40(2):477-494.
doi: 10.11821/dlyj020200074 |
[ Yang Z S, Su J H, Yang H, et al. Exploring urban functional areas based on multi-source data: A case study of Beijing[J]. Geographical Research, 2021, 40(2):477-494. ] DOI: 10.11821/dlyj020200074
doi: 10.11821/dlyj020200074 |
|
[31] | 屠李, 赵鹏军, 张超荣, 等. 面向新一代人工智能的城市规划决策系统优化[J]. 城市发展研究, 2019, 26(1):54-59. |
[ Tu L, Zhao P J, Zhang C R, et al. Optimization of urban planning decision system based on the new generation of artificial intelligence[J]. Urban Development Studies, 2019, 26(1):54-59. ] DOI: 10.3969/j.issn.1006-3862.2019.01.009
doi: 10.3969/j.issn.1006-3862.2019.01.009 |
|
[32] | 张芳芳, 沈少青, 陈学业, 等. 智慧城市规划云平台的设计与实现[J]. 测绘通报, 2019(1):123-126. |
[ Zhang F F, Shen S Q, Chen X Y, et al. Design and implementation of smart city planning cloud platform[J]. Bulletin of Surveying and Mapping, 2019(1):123-126. ] DOI: 10.13474/j.cnki.11-22 46.2019.0025
doi: 10.13474/j.cnki.11-22 46.2019.0025 |
|
[33] | 李军, 刘举庆, 游林, 等. 时空大数据支持的土地储备智能决策体系与应用研究[J]. 中国土地科学, 2019, 33(9):111-120. |
[ Li J, Liu J Q, You L, et al. Intelligent decision system and application of land reserve supported by spatiotemporal big data[J]. China Land Science, 2019, 33(9):111-120. ] DOI: 10.11994/zgtdkx.20190910.091057
doi: 10.11994/zgtdkx.20190910.091057 |
|
[34] | 卢新海, 邓中明. 对我国城市土地储备制度的评析[J]. 城市规划汇刊, 2004(6):27-33,95. |
[ Lu X H, Deng Z M. Comment on urban land banking system in our country[J]. Urban Planning Forum, 2004(6):27-33,95. ] DOI: 10.M3969/j.issn.1000-3363.2004.06.007
doi: 10.M3969/j.issn.1000-3363.2004.06.007 |
|
[35] | 崔建远, 陈进. 土地储备制度的现状与完善[M]. 北京: 中国人民大学出版社, 2014.12-14. |
[ Cui J Y, Chen J. Land reserve system in China: status in quo and its perfection[M]. Beijing: China Renmin University Press, 2014:12-14. ] | |
[36] | 姜华, 王蔚炫, 毛勇龙, 等. 多规融合导向下宁波土地储备规划方法研究[J]. 规划师, 2018, 34(7):106-109,115. |
[ Jiang H, Wang W X, Mao Y L, et al. Multi-plan integration oriented land reserve planning, Ningbo[J]. Planners, 2018, 34(7):106-109,115. ] DOI: 10.3969/j.issn.1006-0022.2018.07.016
doi: 10.3969/j.issn.1006-0022.2018.07.016 |
|
[37] | 鲍艳, 胡振琪, 王建峰, 等. 层次分析法在土地开发中的适宜性评价[J]. 西安科技大学学报, 2005, 25(2):179-182. |
[ Bao Y, Hu Z Q, Wang J F, et al. Analytical hierarchy process based on GIS assessment of suitability in land exploitation and consolidation[J]. Journal of Xi'an University of Science & Technology, 2005, 25(2):179-182. ] DOI: 10.3969/j.issn.1672-9315.2005.02.012
doi: 10.3969/j.issn.1672-9315.2005.02.012 |
|
[38] |
Cheng E W L, Li H, Ho D C K. Analytic hierarchy process (AHP)[J]. Measuring Business Excellence, 2002, 6(4):33-37. DOI: 10.1108/13683040210451697
doi: 10.1108/13683040210451697 |
[39] | 王秀丽, 李恒凯, 刘小生. 基于GIS的房地产市场比较法评估模型研究[J]. 中国土地科学, 2011, 25(10):70-76,97. |
[ Wang X L, Li H K, Liu X S. Study on the market sales comparison model in real estate appraisal based on GIS[J]. China Land Science, 2011, 25(10):70-76,97. ] DOI: 10.3969/j.issn.1001-8158.2011.10.012
doi: 10.3969/j.issn.1001-8158.2011.10.012 |
|
[40] |
Cortes C, Vapnik V. Support-vector networks[J]. Machine Learning, 1995, 20(3):273-297. DOI: 10.1007/BF00994018
doi: 10.1007/BF00994018 |
[41] | 刘思峰, 党耀国, 方志耕. 灰色系统理论及其应用[M].5版. 北京: 科学出版社, 2010. |
[ Liu S F, Dang Y G, Fang Z G. Grey systems: theory and application[M]. Beijing: Science Press, 2010. ] | |
[42] | 李鹏山, 吕雅慧, 张超, 等. 基于核密度估计的京津冀地区耕地破碎化分析[J]. 农业机械学报, 2016, 47(5):281-287. |
[ Li P S, Lü Y H, Zhang C, et al. Analysis of cultivated land fragmentation in Beijing-Tianjin-Hebei region based on kernel density estimation[J]. Transactions of the Chinese Society for Agricultural Machinery, 2016, 47(5):281-287. ] DOI: 10.6041/j.issn.1000-1298.2016.05.038
doi: 10.6041/j.issn.1000-1298.2016.05.038 |
|
[43] |
Davies D L, Bouldin D W. A cluster separation measure[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1979, PAMI-1(2):224-227. DOI: 10.1109/TPAMI.1979.4766909
doi: 10.1109/TPAMI.1979.4766909 |
[1] | 袁源, 毛磊, 李洪庆, 赵小风. 基于位置大数据的城市居住用地效率指标构建及评价研究[J]. 地球信息科学学报, 2022, 24(2): 235-248. |
[2] | 陈霆, 徐伟铭, 吴升, 刘洁. 国土空间规划视角下的城镇开发边界划定和空间管控体系构建[J]. 地球信息科学学报, 2022, 24(2): 263-279. |
[3] | 谢花林, 温家明, 陈倩茹, 何亚芬. 地球信息科学技术在国土空间规划中的应用研究进展[J]. 地球信息科学学报, 2022, 24(2): 202-219. |
[4] | 陈伟杰, 赵楠, 张婕姝, 宋炳良. AIS数据在集装箱港口服务效率的应用研究[J]. 地球信息科学学报, 2022, 24(1): 153-164. |
[5] | 黄隆杨, 王静, 李泽慧, 赵晓东, 刘晶晶, 方莹. 基于自然资源大数据的城市多功能景观识别与国土空间规划分区[J]. 地球信息科学学报, 2021, 23(9): 1617-1631. |
[6] | 胡添, 刘涛, 杜萍, 余贝贝, 张萌生. 空间同位模式支持下城市服务业关联发现及特征分析[J]. 地球信息科学学报, 2021, 23(6): 969-978. |
[7] | 李雨欣, 王瑛, 马庆媛, 刘天雪, 司丽丽, 俞海洋. 基于DTW与K-means算法的河北场雨及雨型分区特征研究[J]. 地球信息科学学报, 2021, 23(5): 860-868. |
[8] | 刘稳, 詹庆明, 赵中元, 林苏靖, 肖琨, 李荣. 面向自然资源统一管理的多源土地利用信息一致性分析评价[J]. 地球信息科学学报, 2021, 23(3): 365-376. |
[9] | 谢聪慧, 吴世新, 张晨, 孙文涛, 何海芳, 裴韬, 罗格平. 基于谱系聚类的全球各国新冠疫情时间序列特征分析[J]. 地球信息科学学报, 2021, 23(2): 236-245. |
[10] | 尹凌, 刘康, 张浩, 奚桂锴, 李璇, 李子垠, 薛建章. 耦合人群移动的COVID-19传染病模型研究进展[J]. 地球信息科学学报, 2021, 23(11): 1894-1909. |
[11] | 覃湘栋, 庞治国, 江威, 冯天时, 付俊娥. 土壤水分微波反演方法进展和发展趋势[J]. 地球信息科学学报, 2021, 23(10): 1728-1742. |
[12] | 宋关福, 陈勇, 罗强, 武梦瑶. GIS基础软件技术体系发展及展望[J]. 地球信息科学学报, 2021, 23(1): 2-15. |
[13] | 陈芳淼, 黄慧萍, 贾坤. 时空大数据在城市群建设与管理中的应用研究进展[J]. 地球信息科学学报, 2020, 22(6): 1307-1319. |
[14] | 胡最. 传统聚落景观基因的地理信息特征及其理解[J]. 地球信息科学学报, 2020, 22(5): 1083-1094. |
[15] | 柯新利, 肖邦勇, 郑伟伟, 马艳春, 李红艳. 城镇-农业-生态空间划定的多情景模拟[J]. 地球信息科学学报, 2020, 22(3): 580-591. |
|