高级检索+

基于Markov-FLUS-MCR模型的晋中市"三生"空间优化

李红润, 刘慧芳, 王瑾, 郭永龙

李红润, 刘慧芳, 王瑾, 郭永龙. 基于Markov-FLUS-MCR模型的晋中市"三生"空间优化[J]. 农业工程学报, 2022, 38(10): 267-276. DOI: 10.11975/j.issn.1002-6819.2022.10.032
引用本文: 李红润, 刘慧芳, 王瑾, 郭永龙. 基于Markov-FLUS-MCR模型的晋中市"三生"空间优化[J]. 农业工程学报, 2022, 38(10): 267-276. DOI: 10.11975/j.issn.1002-6819.2022.10.032
Li Hongrun, Liu Huifang, Wang Jin, Guo Yonglong. Optimization of production-living-ecological space based on Markov-FLUS-MCR model in Jinzhong, Shanxi of China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(10): 267-276. DOI: 10.11975/j.issn.1002-6819.2022.10.032
Citation: Li Hongrun, Liu Huifang, Wang Jin, Guo Yonglong. Optimization of production-living-ecological space based on Markov-FLUS-MCR model in Jinzhong, Shanxi of China[J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(10): 267-276. DOI: 10.11975/j.issn.1002-6819.2022.10.032

基于Markov-FLUS-MCR模型的晋中市"三生"空间优化

基金项目: 山西省软科学一般项目(2018041069-3)

Optimization of production-living-ecological space based on Markov-FLUS-MCR model in Jinzhong, Shanxi of China

  • 摘要: 三生空间优化是落实各级国土空间规划和引导土地合理开发保护的重要基础。该研究利用Markov-FLUS模型模拟预测2025年晋中市"三生"空间,选取最小累计阻力(Minimum Cumulative Resistance,MCR)模型评价国土空间开发适宜性,在空间上叠加分析模拟预测结果与开发适宜性评价结果,对晋中市进行"三生"空间优化。结果表明:1)从模拟预测结果来看,Markov-FLUS模型模拟2018年晋中市"三生"空间变化,与实际数据对比精度达到97.17%,模型具有适用性。2025年晋中市生产与生活空间均呈增长态势,其中生产空间涨幅较大,增长面积达813.53 km2,生态空间面积减少892.65 km2。2)从开发适宜性来看,MCR模型将晋中市国土空间分为5种类型:生态保护区、生态优化区、限制开发区、优化开发区和适宜开发区。生态优化区面积最大为4 994 km2,占整个研究区的30.59%,适宜开发区面积最小为1 546 km2。3)"三生"空间优化后,晋中市划分为生产空间、生态空间、生活空间、生产-生活空间、生产-生态空间、生活-生态空间和生产-生活-生态空间7种类型,表现出"整体集聚,局部零散"的空间分布特征,其中生态空间面积占比最大,为41.20%。研究结果有助于促进"三生"空间优化理论与方法的深入研究,也可为晋中市国土空间合理开发保护提供参考。
    Abstract: Abstract: An accurate and rapid optimization of "production-living-ecological" space has been one of the most important steps to implement territorial spatial planning at all levels, particularly for the better rational development and protection of land. Taking the Jinzhong City, Shanxi Province of China as the research object, the status quo of "production-living-ecological" space was first identified to establish the Markov-FLUS model. The number and distribution of "production-living-ecological" space were also predicted for the study area in 2025. Then, seven resistance factors were selected to evaluate the suitability of land development using the MCR model, in order to determine the threshold and zoning. Among them, the towns and residential areas were taken as the source of construction expansion, and the most important area for ecological protection was the ecological source. At last, the prediction and evaluation of development suitability were spatially superimposed to optimize the "production-living-ecological" space, according to the compound partitions. Subsequently, specific control measures were proposed for each partition. The research showed that: 1) The accuracy of the Markov-FLUS model was 97.17%, compared with the actual data. Thus, the model was very feasible to simulate the spatial changes of "production-living-ecological" in the study area in 2018. There was also an increasing trend for the production and living space in the study area in 2025. Specifically, the production space increased significantly, with an increase of 813.53 km2, whereas, the ecological space decreased by 892.65 km2. 2) The land space was divided into five types of zones: ecological protection, ecological optimization, restricted development, optimized development, and suitable development, from the perspective of development suitability using the MCR model. The ecological optimization zone presented the largest area of 4 994 km2, accounting for 30.59% of the total. Meanwhile, the suitable development zone behaved the smallest area of 1 546 km2. 3) Seven types of space after optimization were then divided: production, ecological, living, production-living, production-ecological, living-ecological, and production-living-ecological space. The spatial distribution was characterized by "the overall agglomeration, the local scattered", of which the ecological space area was the largest proportion, accounting for 41.20%. As such, a recommendation was proposed for the management and control strategies, according to the different space uses. Consequently, the Markov-FLUS-MCR coupling model can balance the Markov-FLUS and MCR models at the same time, indicating the demand quantity and the spatial changes of "production-living-ecological" space with high precision. Land spatial suitability can also be evaluated using an ecological process. The ecological security was integrated during optimization to fully consider the evolution process of the quantity scale and spatial distribution of the "production-living-ecological" space over time. The finding can greatly contribute to promoting the "production-living-ecological" space optimization, particularly for the scientific guidance to the rational development and protection of land space in Jinzhong City, Shanxi Province, China.
  • [1] 江东,林刚,付晶莹. "三生空间"统筹的科学基础与优化途径探析[J]. 自然资源学报,2021,36(5):1085-1101.Jiang Dong, Lin Gang, Fu Jingying. Discussion on scientific foundation and approach for the overall optimization of "production-living-ecological" space[J]. Journal of Natural Resources, 2021, 36(5): 1085-1101. (in Chinese with English abstract)
    [2] 凌子燕,李延顺,蒋卫国,等. 山江海交错带城市群国土三生空间动态变化特征:以广西北部湾城市群为例[J]. 经济地理,2022,42(2):18-24.Ling Ziyan, Li Yanshun, Jiang Weiguo, et al. Dynamic change characteristics of "production-living-ecological spaces" of urban agglomeration interlaced with mountains, rivers and sea: A case study of the Beibu Gulf Urban Agglomeration in Guangxi[J]. Economic Geography, 2022, 52(2): 18-24. (in Chinese with English abstract)
    [3] 冀正欣,刘超,许月卿,等. 基于土地利用功能测度的"三生"空间识别与优化调控[J]. 农业工程学报,2020,36(18):222-231.Ji Zhengxin, Liu Chao, Xu Yueqing, et al. Identification and optimal regulation of the production-living-ecological space based on quantitative land use functions[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2020, 36(18): 222-231. (in Chinese with English abstract)
    [4] 黄金川,林浩曦,漆潇潇. 面向国土空间优化的三生空间研究进展[J]. 地理科学进展,2017,36(3):378-391.Huang Jinchuan, Lin Haoxi, Qi Xiaoxiao. A literature review on optimization of spatial development pattern based on ecological-production-living space[J]. Progress in Geography, 2017, 36(3): 378-391. (in Chinese with English abstract)
    [5] 于贵思,赵明华. 基于文献计量的国内"三生空间"研究现状综述[J]. 广州大学学报(自然科学版),2018,17(3):76-82.Yu Guisi, Zhao Minghua. Research status summary of domestic "three-life space" research based on bibliometrics[J]. Journal of Guangzhou University(Natural Science Edition), 2018, 17(3): 76-82. (in Chinese with English abstract)
    [6] 邹利林,王建英,胡学东. 中国县级"三生用地"分类体系的理论构建与实证分析[J]. 中国土地科学,2018,32(4):59-66.Zou Lilin, Wang Jianying, Hu Xuedong. An classification systems of "production-living-ecological" land on the county level: Theory building and empirical research[J]. China Land Science, 2018, 32(4): 59-66. (in Chinese with English abstract)
    [7] 王芳莉. 基于FLUS模型的陇南市土地利用变化与模拟[D].兰州: 西北师范大学,2020.Wang Fangli. Change and Simulation of Land Use in Longnan City Based on FLUS Model[D]. Lanzhou: Northwest Normal University, 2020. (in Chinese with English abstract)
    [8] 黄安,许月卿,卢龙辉,等. "生产-生活-生态"空间识别与优化研究进展[J]. 地理科学进展,2020,39(3):503-518.Huang An, Xu Yueqing, Lu Longhui, et al. Research progress of the identification and optimization of "production- living-ecological" spaces[J]. Progress in Geography, 2020, 39(3): 503-518. (in Chinese with English abstract)
    [9] Campbell D J, Gichohi H, Mwangi A, et al. Land use conflict in Kajiado District, Kenya[J]. Land Use Policy, 2000, 17: 337-348.
    [10] 朱润苗,陈松林. 基于"三生"功能的福建省国土空间特征及优化研究[J]. 水土保持通报,2021,41(4):323-330.Zhu Runmiao, Chen Songlin. Characteristics and optimization of territorial space in Fujian Province based on production-living-ecological functions[J]. Bulletin of Soil and Water Conservation, 2021, 41(4): 323-330.
    [11] 金贵. 国土空间综合功能分区研究[D].武汉:中国地质大学,2014.Jin Gui. Study on Comprehensive Function Regionalization of National Spatial Territory[D]. Wuhan: China University of Geosciences, 2014. (in Chinese with English abstract)
    [12] 郑洋,郝润梅,吴晓光,等. 基于MCR模型的村庄"三生空间"格局优化研究[J]. 水土保持研究,2021,28(5):362-367.Zheng Yang, Hao Runmei, Wu Xiaoguang, et al. Research on the spatial pattern optimization of production- living-ecological spaces in village based on MCR Model[J]. Research of Soil and Water Conservation, 2021, 28(5): 362-367. (in Chinese with English abstract)
    [13] 王昆. 基于适宜性评价的生产-生活-生态(三生)空间划定研究[D]. 杭州:浙江大学,2018.Wang Kun. Study on Delimitation of the Ecological- Production-Living Space Based on Suitability Evaluation: A Case Study of Henan Province[D]. Hangzhou: Zhejiang University, 2018. (in Chinese with English abstract)
    [14] 李媛洁,叶长盛,黄小兰. 基于CLUE-S模型的南昌市"三生"空间时空演变及情景模拟研究[J]. 水土保持研究,2021,28(5):325-332.Li Yunajie, Ye Changsheng, Huang Xiaolan, et al. Temporal-spatial evolution and scenario simulation of production-living- ecological space in Nanchang based on CLUE-S Model[J]. Research of Soil and Water Conservation, 2021, 28(5): 325-332. (in Chinese with English abstract)
    [15] 林伊琳,赵俊三,张萌,等. 滇中城市群国土空间格局识别与时空演化特征分析[J]. 农业机械学报,2019,50(8):176-191.Lin Yilin, Zhao Junsan, Zhang Meng, et al. Identification of territory space pattern and spatio-temporal evolution analysis of urban agglomeration in Central Yunnan[J]. Transactions of the Chinese Society for Agricultural Machinery, 2019, 50(8): 176-191. (in Chinese with English abstract)
    [16] 李国珍. 基于FLUS模型的深圳市土地利用变化与模拟研究[D].武汉:武汉大学,2018.Li Guozhen. Land Use Change and Simulation in Shenzhen Based on FLUS Model[D]. Wuhan: Wuhan University, 2018. (in Chinese with English abstract)
    [17] 林沛锋,郑荣宝,洪晓,等. 基于FLUS模型的土地利用空间布局多情景模拟研究:以广州市花都区为例[J]. 国土与自然资源研究,2019(2):7-13.Lin Peifeng, Zheng Rongbao, Hong Xiao, et al. Simulation of land use spatial layout based on FLUS model: A case study of Huadu district, Guangzhou[J]. Territory & Natural Resources Study, 2019(2): 7-13. (in Chinese with English abstract)
    [18] 曹帅,金晓斌,杨绪红,等. 耦合MOP与GeoSOS-FLUS模型的县级土地利用结构与布局复合优化[J]. 自然资源学报,2019,34(6):1171-1185.Cao Shuai, Jin Xiaobin, Yang Xuhong, et al. Coupled MOP and GeoSOS-FLUS models research on optimization of land use structure and layout in Jintan district[J]. Journal of Natural Resources, 2019, 34(6): 1171-1185. (in Chinese with English abstract)
    [19] 陈兵飞. 基于FLUS模型的万州区土地利用变化模拟及土地利用结构优化研究[D]. 重庆:西南大学,2020.Chen Bingfei. Study on Land Use Change Simulation and Land Use Structure Optimization in Wanzhou District Based on FLUS Model[D]. Chongqing: Southwest University, 2020. (in Chinese with English abstract)
    [20] 王旭,马伯文,李丹,等. 基于FLUS模型的湖北省生态空间多情景模拟预测[J]. 自然资源学报,2020,35(1):230-242.Wang Xu, Ma Bowen, Li Dan, et al. Multi-scenario simulation and prediction of ecological space in Hubei province based on FLUS model[J]. Journal of Natural Resources, 2020, 35(1): 230-242. (in Chinese with English abstract)
    [21] 王雪然,潘佩佩,王晓旭,等. 基于GeoSOS-FLUS模型的河北省土地利用景观格局模拟[J]. 江苏农业学报,2021,37(3):667-675.Wang Xueran, Pan Peipei, Wang Xiaoxu, et al. Simulation of landscape pattern for land use in Hebei province based on GeoSOS-FLUS model[J]. Jiangsu Journal of Agricultural Sciences, 2021, 37(3): 667-675. (in Chinese with English abstract)
    [22] 张颖,徐辉. 基于MCR模型的农村居民点布局适宜性分区及优化模式研究:以南京市六合区金牛湖街道为例[J]. 长江流域资源与环境,2014,23(11):1485-1492.Zhang Ying, Xu Hui. Research on suitability subareas of rural residential distribution based on MCR modle and optimization model: a case study of Jinnue street in Nanjing, Luhe district[J]. Resources and Environment in the Yangtze Basin, 2014, 23(11): 1485-1492. (in Chinese with English abstract)
    [23] 李全宝. 基于MCR与Markov-CA模型的城镇增长边界划定研究:以江苏省新沂市为例[J]. 中国国土资源经济,2019,32(1):83-88.Li Quanbao. Study on the delimitation of urban growth boundary based on MCR and Markov-CA model: A case study of Xinyi City in Jiangsu Province[J]. Natural Resource Economics of China, 2019, 32(1): 83-88. (in Chinese with English abstract)
    [24] 汤鹏,王浩. 基于MCR模型的现代城市绿地海绵体适宜性分析[J]. 南京林业大学学报(自然科学版),2019,43(3):116-122.Tang Peng, Wang Hao. Analysis on the suitability of green sponge space in modern city based on MCR model[J]. Journal of Nanjing Forestry University(Natural Sciences Edition), 2019, 43(3): 116-122. (in Chinese with English abstract)
    [25] 林伊琳,赵俊三,陈国平,等. 基于MCR-FLUS-Markov模型的区域国土空间格局优化[J]. 农业机械学报,2021,52(4):159-170,207.Lin Yilin, Zhao Junsan, Chen Guoping, et al. Optimization of regional territory space pattern based on MCR-FLUS-Markov model[J]. Transactions of the Chinese Society for Agricultural Machinery, 2021, 52(4): 159-170, 207. (in Chinese with English abstract)
    [26] 刘孝富,舒俭民,张林波. 最小累积阻力模型在城市土地生态适宜性评价中的应用:以厦门为例[J]. 生态学报,2010,30(2):421-428.Liu Xiaofu, Su Jianmin, Zhang Linbo. Research on applying minimal cumulative resistance model in urban land ecologicalsuitability assessment: As an example of Xiamen City[J]. Acta Ecologica Sinica, 2010, 30(2): 421-428. (in Chinese with English abstract)
    [27] 张永蕾,栾乔林,熊昌盛,等. 基于多源空间数据的"三生"空间异质性评价与分区划定[J]. 农业工程学报,2021,37(10):214-223.Zhang Yonglei, Luan Qiaolin, Xiong Changsehng, et al. Spatial heterogeneity evaluation and zoning of production-living-ecological space based on multi-source spatial data[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(10): 214-223. (in Chinese with English abstract)
    [28] 刘慧芳,毕如田,王瑾,等. 山西省县域城镇低效用地空间格局分异与影响因素研究[J]. 农业机械学报,2022,53(5):169-180,208.Liu Huifang, Bi Rutian, Wang Jin, et al. Spatial pattern differentiation and influential factors of urban under-used land in county territories in Shanxi Province[J]. Transactions of the Chinese Society for Agricultural Machinery, 2022, 53(5): 169-180, 208. (in Chinese with English abstract)
  • 期刊类型引用(18)

    1. 韩会庆,简元菊,王涛. 贵州传统村落三生空间变化及影响因素研究. 农业与技术. 2025(01): 168-172 . 百度学术
    2. 邓泽澜,刘慧芳,王瑾,郭永龙. 晋中市国土空间利用效率测算与布局优化. 湖北农业科学. 2025(01): 7-15 . 百度学术
    3. 刘佳楠,姬广兴,高红凯,陈伟强,张亚丽,黄珺嫦,郭宇龙,陈轶楠. 基于PLUS模型的河南省“三生空间”多情景模拟及生态环境效应分析. 环境科学. 2025(02): 990-1001 . 百度学术
    4. 杨建强,简元菊,鲁媛媛. 基于ANN-CA模型的喀斯特山区农村三生空间优化. 农业与技术. 2025(04): 103-107 . 百度学术
    5. 李盈盈,刘师旖,计培琨,王东驰,李益敏. 基于“三类空间”的云南省泸水市国土空间优化研究. 山东国土资源. 2025(03): 60-70 . 百度学术
    6. 何青松,张雪韵. 长江中游城市群三生功能权衡尺度效应及影响因素. 农业工程学报. 2025(06): 278-287 . 本站查看
    7. 王凯,周亚杰,穆望舒,王文静,李长风,徐辉,贾鹏飞,秦维. 基于“精准适配”的多情景、多规则都市圈三生空间优化探索——以北京首都都市圈为例. 国际城市规划. 2025(02): 1-9 . 百度学术
    8. 胡后峰,郭永龙,王瑾,刘慧芳. 园地定级中复杂地貌区位作用分的优化算法研究——基于最小费用路径模型. 农业资源与环境学报. 2025(03): 611-622 . 百度学术
    9. 万鼎,王志远,谭勇,李灿斌,陈超,贺寒辉. 基于开发保护综合效益的洞庭湖生态经济区“三生空间”格局优化. 应用生态学报. 2024(01): 255-267 . 百度学术
    10. 尹代皓,赵忠. 延安市“三生”空间格局模拟与优化研究. 西北林学院学报. 2024(02): 133-140 . 百度学术
    11. 马永健,谢红彬,邓红芮,蔡思琪,刘强. 融入功能分区的土地利用变化多情景模拟——以福建南平市建阳区为例. 山地学报. 2024(02): 225-237 . 百度学术
    12. 王乐,熊昌盛,田宇,周斌雄. 中国“三生”空间功能异质性评价、时空演变及分区调控. 农业工程学报. 2024(10): 265-275 . 本站查看
    13. 马浩洋,周敏. 基于CiteSpace的我国土地利用优化问题研究进展综述. 农村经济与科技. 2024(17): 26-29 . 百度学术
    14. 段亚明,付景保,周翼. 南水北调中线工程水源区“三生”空间演化特征与生态效应. 中国人口·资源与环境. 2024(11): 138-150 . 百度学术
    15. 李聪慧,马彩虹,滑雨琪,杨航,刘园园. 黄河上游荒漠绿洲生态系统服务对三生用地变化的响应——以银川市为例. 资源科学. 2023(01): 190-203 . 百度学术
    16. 王浩阳,牛文浩,宋曼,张蚌蚌,靳亚亚. 基于LUCC及其ESV响应的陕西省生态网络构建与空间优化. 资源科学. 2023(07): 1380-1395 . 百度学术
    17. 薛万来,朱莎莎,朱梦洵,刘晔,李垒,苏梓锐,李文忠. 基于FLUS-InVEST模型的永定河流域碳储量功能变化分析. 水利水电技术(中英文). 2023(09): 13-25 . 百度学术
    18. 杨蔡少洁,杨冬冬. 国土空间规划背景下中国生态空间规划研究进展. 风景园林. 2023(S2): 13-17 . 百度学术

    其他类型引用(18)

计量
  • 文章访问数:  152
  • HTML全文浏览量:  0
  • PDF下载量:  157
  • 被引次数: 36
出版历程
  • 收稿日期:  2022-04-01
  • 修回日期:  2022-05-14
  • 发布日期:  2022-05-30

目录

    /

    返回文章
    返回