基于开发利用与产出视角的区域土地利用隐性形态综合研究——以黄淮海地区为例

doi:10.11821/dlyj201701005

摘要/Abstract

摘要：

从土地开发利用与产出视角出发,以黄淮海地区为研究区,开展区域土地利用隐性形态的综合研究。首先,从土地开发利用强度、土地经济发展水平和土地污染排放水平三个维度构建了区域土地利用隐性形态的三维表征模型。其次,引入基于遗传算法的K-means聚类方法（KGA）对研究区不同单元的综合土地利用隐性形态进行了类型划分,发现不同类型单元的综合土地利用隐性形态特征与其所处的区域发展水平紧密相关。第三,引入空间距离和空间自相关检验,提出了一种综合空间与非空间属性信息的空间聚类方法（SKGA）,用于研究区综合土地利用隐性形态的分区研究。结果表明：基于SKGA的分区方案既能保留各研究单元非空间属性的分异性,又能兼顾不同单元间的空间邻接性和空间关联性。研究结果可为差别化的土地管理决策提供参考。

关键词: 土地利用转型, 土地利用隐性形态, 遗传算法, 空间自相关, 空间聚类, 黄淮海地区

Abstract:

Land use transition refers to the changes in land use morphology including dominant morphology and recessive morphology of a certain region over a certain period of time. If we take different land use morphologies as the points, then different land use transition processes might be the line connecting different points driven by regional socio-economic change and innovation. So, in-depth research on land use morphology may make great contribution to a better understanding of regional land use transition. This paper paid more attention to the recessive land use morphology, a multi-dimensional conception with multiple spatial and non-spatial properties. Taking the Huang-Huai-Hai region as a case study, this paper studies regional land use recessive morphology in a comprehensive way from the view point of exploitation and output. Firstly, a three-dimensional representative model for land use recessive morphology was built. This model consists of the attributes of land use intensity, land use economic condition and land use emission condition. It was subsequently used in recessive land use morphology analysis of the study area. Secondly, a K-means clustering method based on the Genetic Algorithm (KGA) was introduced into the classification for the units with different comprehensive land use recessive morphologies. This showed that the comprehensive land use recessive morphology types of the unit have close relationship to its economic development level. For example, Beijing may have the highest regional land use intensity, highest land use economic level, but lowest land use emission level for its advanced economic development level, while Zhumadian with the lowest regional land use intensity, land use economic level and land use emission level for its underdeveloped economy. Thirdly, by introducing the spatial distance and spatial autocorrelation into the KGA method, this paper proposed a new spatial clustering method combining spatial and non-spatial properties (spatial K-means clustering method based on the Genetic Algorithm, SKGA). As shown that this method performed well in the zoning analysis of comprehensive land use recessive morphologies, for it can maintain the heterogeneity in non-spatial properties, as well as take full account of spatial contiguity and spatial correlation. Finally, differentiated management measures were proposed based on the features of different comprehensive land use recessive morphology zones to support land use policy decision-making.

Key words: land use transition, land use recessive morphology, the genetic algorithm, spatial autocorrelation, spatial clustering, Huang-Huai-Hai Region

曲艺, 龙花楼. 基于开发利用与产出视角的区域土地利用隐性形态综合研究——以黄淮海地区为例[J]. 地理研究, 2017, 36(1): 61-73.

Yi QU, Hualou LONG. The integrated research on regional land use recessive morphology from the perspectives of exploitation and output:The case of the Huang-Huai-Hai Region[J]. GEOGRAPHICAL RESEARCH, 2017, 36(1): 61-73.

图/表 9

图1

图2

表1

图3

图4

图5

表2

图6

表3

参考文献 40

[1]	Long Hualou.Land use policy in China: Introduction. Land Use Policy, 2014, 40: 1-5. doi: 10.1016/j.landusepol.2014.03.006
[2]	刘纪远, 匡文慧, 张增祥, 等. 20世纪80年代末以来中国土地利用变化的基本特征与空间格局. 地理学报, 2014, 69(1): 3-14. doi: 10.11821/dlxb201401001
	[Liu Jiyuan, Kuang Wenhui, Zhang Zengxiang, et al.Spatio-temporal characteristics, patterns and causes of land use changes in China since the late 1980s. Acta Geographica Sinica, 2014, 69(1): 3-14.] doi: 10.11821/dlxb201401001
[3]	宋小青, 吴志峰, 欧阳竹. 耕地转型的研究路径探讨. 地理研究, 2014, 33(3): 403-413. doi: 10.11821/dlyj201403001
	[Song Xiaoqing, Wu Zhifeng, Ouyang Zhu.Route of cultivated land transition research. Geographical Research, 2014, 33(3): 403-413.] doi: 10.11821/dlyj201403001
[4]	李志江, 马晓冬, 孙姗姗. 苏北乡村转型与土地利用转型的耦合分析: 以沛县为例. 江苏师范大学学报: 自然科学版, 2015, 33(1): 36-39. doi: 10.3969/j.issn.2095-4298.2015.01.004
	[Li Zhijiang, Ma Xiaodong, Sun Shanshan.Coupling analysis of rural transformation and land use change in Northern Jiangsu: a case study of Peixian County. Journal of Jiangsu Normal University: Natural Science Edition, 2015, 33(1): 36-39.] doi: 10.3969/j.issn.2095-4298.2015.01.004
[5]	吕晓, 黄贤金, 张全景. 城乡建设用地转型研究综述. 城市规划, 2015, 39(4): 105-112. doi: 10.11819/cpr20150417a
	[Lv Xiao, Huang Xianjin, Zhang Quanjing.A literature review on urban-rural construction land transition. City Planning Review, 2015, 39(4): 105-112.] doi: 10.11819/cpr20150417a
[6]	王建康, 谷国锋. .

[7]	夏方舟, 严金明, 徐一丹. 基于随机边界分析的土地要素对中国经济技术效率影响研究. 中国土地科学, 2014, 28(7): 4-10. doi: 10.3969/j.issn.1001-8158.2014.07.001
	[Xia Fangzhou, Yan Jinming, Xu Yidan.Study on the effects of land elements on technical efficiency of economic growth in China based upon Stochastic Frontier Analysis. China Land Science, 2014, 28(7): 4-10.] doi: 10.3969/j.issn.1001-8158.2014.07.001
[8]	Nichols D A.Land and economic growth. The American Economic Review, 1970, 60(3): 332-340. doi: 10.1016/0016-3287(69)90009-3
[9]	刘永强, 廖柳文, 龙花楼, 等. 土地利用转型的生态系统服务价值效应分析: 以湖南省为例. 地理研究, 2015, 34(4): 691-700. doi: 10.11821/dlyj201504008
	[Liu Yongqiang, Liao Liuwen, Long Hualou, et al.Effects of land use transition on ecosystem services value: A case study of Hunan province. Geographical Research, 2015, 34(4): 691-700.] doi: 10.11821/dlyj201504008
[10]	Liu Yongqiang, Long Hualou, Li Tingting, et al.Land use transitions and their effects on water environment in Huang-Huai-Hai Plain, China. Land Use Policy, 2015, 47: 293-301. doi: 10.1016/j.landusepol.2015.04.023
[11]	Long Hualou, Liu Yongqiang, Hou Xuegang, et al.Effects of land use transitions due to rapid urbanization on ecosystem services: Implications for urban planning in the new developing area of China. Habitat International, 2014, 44: 536-544. doi: 10.1016/j.habitatint.2014.10.011
[12]	杨依天, 郑度, 张雪芹, 等. 1980-2010年和田绿洲土地利用变化空间耦合及其环境效应. 地理学报, 2013, 68(6): 813-824.
	[Yang Yitian, Zheng Du, Zhang Xueqin, et al.The spatial coupling of land use changes and its environmental effects on Hotan oasis during 1980-2010. Acta Geographica Sinica, 2013, 68(6): 813-824.]
[13]	傅伯杰, 陈利顶, 马克明. 黄土丘陵区小流域土地利用变化对生态环境的影响: 以延安市羊圈沟流域为例. 地理学报, 1999, 54(3): 51-56. doi: 10.3321/j.issn:0375-5444.1999.03.006
	[Fu Bojie, Chen Liding, Ma Keming.The effect of land use change on the regional environment in the Yangjuangou catchment in the Loess Plateau of China. Acta Geographica Sinica, 1999, 54(3): 51-56.] doi: 10.3321/j.issn:0375-5444.1999.03.006
[14]	龙花楼, 李秀彬. 区域土地利用转型分析: 以长江沿线样带为例. 自然资源学报, 2002, 17(2): 144-149. doi: 10.3321/j.issn:1000-3037.2002.02.003
	[Long Hualou, Li Xiubin.Analysis on regional land use transition: A case study in transect of the Yangtze River. Journal of Natrual Resources, 2002, 17(2): 144-149.] doi: 10.3321/j.issn:1000-3037.2002.02.003
[15]	Grainger Alan.National land use morphology: Patterns and possibilities. Geography, 1995, 80(3): 235-245. doi: 10.2307/215297
[16]	龙花楼. 论土地利用转型与乡村转型发展. 地理科学进展, 2012, 31(2): 131-138. doi: 10.11821/xb201204012
	[Long Hualou.Land use transition and rural transformation development. Progress in Geography, 2012, 31(2): 131-138.] doi: 10.11821/xb201204012
[17]	龙花楼. 论土地利用转型与土地资源管理. 地理研究, 2015, 34(9): 1607-1618. doi: 10.11821/d1yj201509001
	[Long Hualou.Land use transition and land management. Geographical Research, 2015, 34(9): 1607-1618.] doi: 10.11821/d1yj201509001
[18]	龙花楼. 土地利用转型: 土地利用/覆被变化综合研究的新途径. 地理与地理信息科学, 2003, 19(1): 87-90. doi: 10.3969/j.issn.1672-0504.2003.01.022
	[Long Hualou.Land use transition: A new integrated approach of land use/cover change study. Geography and Geo-Information Science, 2003, 19(1): 87-90.] doi: 10.3969/j.issn.1672-0504.2003.01.022
[19]	张景华, 封志明, 姜鲁光. 土地利用/土地覆被分类系统研究进展. 资源科学, 2011, 33(6): 1195-1203.
	[Zhang Jinghua, Feng Zhiming, Jiang Luguang.Progress on studies of land use/ land cover classification system. Resources Science, 2011, 33(6): 1195-1203.]
[20]	郑新奇, 邓红蒂, 姚慧, 等.中国设区市土地集约利用类型区划分研究. 中国人口⋅资源与环境, 2010, 20(2): 6-11. doi: 10.3969/j.issn.1002-2104.2010.02.002
	doi: 10.3969/j.issn.1002-2104.2010.02.002
[21]	赵荣钦, 黄贤金, 钟太洋, 等. 聚类分析在江苏沿海地区土地利用分区中的应用. 农业工程学报, 2010, 26(6): 310-314. doi: 10.3969/j.issn.1002-6819.2010.06.054
	[Zhao Rongqin, Huang Xianjin, Zhong Taiyang, et al.Application of clustering analysis to land use zoning of coastal region in Jiangsu Province. Transactions of the CSAE, 2010, 26(6): 310-314.] doi: 10.3969/j.issn.1002-6819.2010.06.054
[22]	李小军, 方斌. 基于突变理论的经济发达地区市域城镇化质量分区研究: 以江苏省13市为例. 经济地理, 2014, 34(3): 65-71.
	[Li Xiaojun, Fang Bin.Urbanization quality zoning research of economically developed city based on Catastrophe Theory: A case of 13 perfecture-level cities of Jiangsu province. Economic Geography, 2014, 34(3): 65-71.]
[23]	曹卫东, 曹玉红. 生态、经济协同发展的滨湖区空间管制分区研究: 以巢湖东段为例. 长江流域资源与环境, 2012, 21(4): 426-432.
	[Cao Weidong, Cao Yuhong.Research on spatial management regionalization about lakes under ecological-economic synergy. Resources and Environment in the Yangtze Basin, 2012, 21(4): 426-432.]
[24]	欧维新, 连鹏, 逄谦. 基于水污染总量控制的土地利用管控分区: 以无锡市为例. 自然资源学报, 2014, 29(1): 1-12. doi: 10.11849/zrzyxb.2014.01.001
	[Ou Weixin, Lian Peng, Fang Qian.Land use regulation zoning for controlling the total amount of water pollutants: A case study of Wuxi city. Journal of Natural Resources, 2014, 29(1): 1-12.] doi: 10.11849/zrzyxb.2014.01.001
[25]	蒙莉娜, 郑新奇, 赵璐, 等. 基于生态位适宜度模型的土地利用功能分区. 农业工程学报, 2011, 27(3): 282-287.
	[Meng Lina, Zheng Xinqi, Zhao Lu, et al.Land-use functional regionalization based on niche-fitness model. Transactions of the CSAE, 2011, 27(3): 282-287.]
[26]	赵海霞, 崔建鑫, 董雅文, 等. 基于生态—经济协调发展的乡镇空间功能分区. 长江流域资源与环境, 2016, 25(3): 375-386. doi: 10.11870/cjlyzyyhj201603003
	[Zhao Haixia, Cui Jianxin, Dong Yawen, et al.Spatial function zoning at township scale based on ecological and economic coordinated development. Resources and Environment in the Yangtze Basin, 2016, 25(3): 375-386.] doi: 10.11870/cjlyzyyhj201603003
[27]	Likas A, Vlassis N, Verbeek J J.The global k-means clustering algorithm. Pattern Recognition. 2003, 36(2): 451-461.
[28]	Carslaw D C, Beevers S D.Characterising and understanding emission sources using bivariate polar plots and K-means clustering. Environmental Modelling & Software, 2013, 40: 325-329. doi: 10.1016/j.envsoft.2012.09.005
[29]	Maulik Ujjwal, Bandyopadhyay Sanghamitra.Genetic algorithm-based clustering technique. Pattern Recognition, 2000, 33(9): 1455-1465. doi: 10.1016/S0031-3203(99)00137-5
[30]	Krishna K, Murty M N.Genetic K-means algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1999, 29(3): 433-439.
[31]	Mitchell M.An Introduction to Genetic Algorithms. Cambridge, MA: MIT Press, 1998.
[32]	靳诚, 陆玉麒. 基于县域单元的江苏省经济空间格局演化. 地理学报, 2009, 64(6): 713-724. doi: 10.3321/j.issn:0375-5444.2009.06.008
	[Jin Cheng, Lu Yuqi.Evolvement of spatial pattern of economy in Jiangsu province at county level. Acta Geographica Sinica, 2009, 64(6): 713-724.] doi: 10.3321/j.issn:0375-5444.2009.06.008
[33]	骆剑承, 周成虎, 梁怡, 等. 多尺度空间单元区域划分方法. 地理学报, 2002, 57(2): 167-173.
	[Luo Jiancheng, Zhou Chenghu, Liang Yi, et al.Scale-space theory based regionalization for spatial cells. Acta Geographica Sinica, 2002, 57(2): 167-173.]
[34]	Jiao Limin, Liu Yaolin, Zou Bin.Self-organizing dual clustering considering spatial analysis and hybrid distance measures. Science China Earth Sciences, 2011, 54(8): 1268-1278. doi: 10.1007/s11430-011-4222-1
[35]	林锦耀, 黎夏. 基于空间自相关的东莞市主体功能区划分. 地理研究, 2014, 33(2): 349-357. doi: 10.11821/dlyj201402013
	[Lin Jinyao, Li Xia.MFOZ planning of Dongguan based on spatial autocorrelation by using genetic algorithms. Geographical Research, 2014, 33(2): 349-357.] doi: 10.11821/dlyj201402013
[36]	Anselin L, Sridharan S, Gholston S.Using exploratory spatial data analysis to leverage social indicator databases: The discovery of interesting patterns. Social Indicators Research, 2007, 82(2): 287-309. doi: 10.1007/s11205-006-9034-x
[37]	Moran P A.Notes on continuous stochastic phenomena. Biometrika, 1950, 37(1/2): 17-23.
[38]	樊杰. 中国主体功能区划方案. 地理学报, 2015, 70(2): 186-201. doi: 10.11821/dlxb201502002
	[Fan Jie.Draft of major function oriented zoning of China. Acta Geographica Sinica, 2015, 70(2): 186-201.] doi: 10.11821/dlxb201502002
[39]	周峤. 雾霾天气的成因. 中国人口⋅资源与环境,2015, 25(5): 211-212.

[40]	Yu Lingda, Wang Guangfu, Zhang Renjian, et al.Characterization and source apportionment of PM2.5 in an urban environment in Beijing. Aerosol and Air Quality Research, 2013, 13(2): 574-583. doi: 10.4209/aaqr.2012.07.0192

指标类型	指标名称	单位	计算方法	数据来源
土地经济发展水平	地均产值	（万元/ km²）	地区生产总值/土地总面积	《中国城市统计年鉴》
	城镇居民人均可支配收入	（万元/人）	从年鉴直接获取	《中国统计年鉴》《河北省统计年鉴》《山东省统计年鉴》《江苏省统计年鉴》《安徽省统计年鉴》《河南省统计年鉴》
	第三产业占比	（%）	从年鉴直接获取	《中国城市统计年鉴》
土地污染排放水平	地均废水排放	（t/ km²）	工业废水排放量/土地总面积	《中国城市统计年鉴》
	地均二氧化硫排放	（t/ km²）	工业二氧化硫排放量/土地总面积	《中国城市统计年鉴》
	地均烟（粉）尘排放	（t/ km²）	工业烟（粉）尘排放量/ 土地总面积	《中国城市统计年鉴》
土地开发利用强度	建成区面积占比	（%）	建成区面积/土地总面积	《中国城市建设统计年鉴》

类型	土地经济发展水平	土地污染排放水平	土地开发利用强度
类型一	极高	极低	极高
类型二	高	低	高
类型三	低	极高	高
类型四	低	中等	低
类型五	低	中等	中等
类型六	低	低	低
类型七	极低	极低	极低

类型	指标	单位	统计指标	京津冀区	鲁东南区	冀中南区	中原区	淮北区
土地经济发展水平	地均国内生产总值	（万元/km²）	最大值	12058.54	7096.79	3068.94	8329.17	3171.01
			最小值	1498.02	1941.02	1212.73	1969.74	944.70
			均值	7473.39	3976.24	2154.63	3348.42	1689.42
	城镇居民人均可支配收入	（万元/人）	最大值	4.03	3.56	2.84	2.66	2.31
			最小值	2.40	2.30	1.78	1.95	1.80
			均值	3.08	2.94	2.31	2.20	2.12
	第三产业占比	（%）	最大值	76.85	55.30	41.44	41.67	41.75
			最小值	32.27	26.91	31.54	18.46	25.13
			均值	51.05	40.20	35.66	28.45	32.36
土地污染排放水平	地均工业废水排放	（t/ km²）	最大值	15685.16	29029.67	17511.99	26696.14	41354.49
			最小值	5780.27	4735.57	6350.96	5905.51	2454.02
			均值	9629.17	13060.09	10171.44	14091.28	9117.77
	地均工业二氧化硫排放	（t/ km²）	最大值	20.58	34.66	11.45	18.54	23.52
			最小值	3.17	5.71	0.19	5.63	1.44
			均值	12.62	11.67	5.88	11.62	5.73
	地均工业烟（粉）尘排放	（t/ km²）	最大值	34.83	34.06	7.89	17.73	8.79
			最小值	1.66	0.68	1.58	1.67	0.75
			均值	12.94	5.60	3.53	6.73	3.14
土地开发利用强度	建成区面积占比	（%）	最大值	7.96	5.34	1.37	5.14	4.10
			最小值	1.24	1.06	0.46	0.92	0.46
			均值	4.30	2.59	0.85	2.10	1.32