青川县LUCC遥感动态监测及驱动力分析

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刘萌, 杨武年, 邵怀勇, 孙小飞. 青川县LUCC遥感动态监测及驱动力分析[J]. 国土资源遥感, 2014,26(3): 160-165
LIU Meng, YANG Wunian, SHAO Huaiyong, SUN Xiaofei. Remote sensing dynamic monitoring and driving force analysis of land use/cover changes in Qingchuan County[J]. REMOTE SENSING FOR LAND & RESOURCES,2014,26(3): 160-165 复制到剪切板

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《国土资源遥感》编辑部

青川县LUCC遥感动态监测及驱动力分析

刘萌, 杨武年, 邵怀勇, 孙小飞

成都理工大学地学空间信息技术国土资源部重点实验室,成都 610059

杨武年(1954-),男,博士,博士生导师,研究方向为3S技术在国土资源勘查、生态环境监测与评价等方面的应用。Email:ywn@cdut.edu.cn。

第一作者简介: 刘萌(1990- ),女,硕士研究生,研究方向为RS和GIS在生态环境评价方面的应用。Email:xinyin_liumeng@163.com。

收稿日期: 2013-07-26

基金: 国家自然科学基金资助项目(编号: 41071265,41302282,41372340)、高等学校博士学科点专项科研基金课题(编号: 20105122110006)和四川省教育厅重点项目(编号: 13ZA0059)共同资助

摘要

四川广元市青川县是国家生态试点县和退耕还林实施县,查明该区土地利用/覆被现状及其时空动态变化信息,为政府有关部门规划决策提供科学依据具有重要意义。应用RS和GIS技术,基于2000年、2005年和2010年3个时相的陆地卫星TM图像,通过图像处理和信息提取,获得了该区3期土地利用/覆被数据。在此基础上,分析了青川县近10 a土地利用/覆被动态变化过程,查明了引起动态变化的主要驱动力因素,最后,对该区2015年和2020年土地利用/覆被的面积比例进行了预测。研究结果表明: 青川县2000—2005年间,耕地、水域和未利用地面积减少,林地、草地和建设用地面积增加; 2005—2010年间,耕地和草地面积减少,林地、水域、建设用地和未利用地面积增加; 两段时期耕地面积持续减少,但减幅减小,林地面积持续增加,增幅减小,建设用地持续增加且增幅增大,水域和未利用地先减后增,草地先增后减。究其原因,认为政策、经济发展和人口增长及自然灾害等因素是研究区土地利用变化的主要影响因子。经过预测,在相关政策不变且没有自然灾害发生的情况下,2015年林地面积占全县总面积的比例将由2010年的58.57%增长为59.01%,到2020年将继续增长为59.44%,耕地面积比例到2020年将减少至29.13%,建设用地面积比例继续增加至0.22%。

关键词: 遥感; GIS; 土地利用/覆被变化(LUCC); 转移矩阵; 马尔科夫预测

中图分类号:TP79 文献标志码:A 文章编号:1001-070X(2014)03-0160-06 doi: 10.6046/gtzyyg.2014.03.26

Remote sensing dynamic monitoring and driving force analysis of land use/cover changes in Qingchuan County

LIU Meng, YANG Wunian, SHAO Huaiyong, SUN Xiaofei

Key Laboratory of Geo-spatial Information Technology, Ministry of Land and Resources, Chengdu University of Technology, Chengdu 610059, China

Abstract

Qingchuan County of Guangyuan City in Sichuan Province is a national ecological pilot county and implementation country of returning farmland to forest. The understanding of the current situation and spatial-temporal dynamic change of land use/cover is of great significance in providing the scientific basis for relevant government departments. In this paper, with the application of RS and GIS technology, on the basis of TM images in 2000, 2005 and 2010, and through image processing and information extracting, the authors acquired land use/cover maps in different years and established the database. On such a basis, the land use/cover dynamic change process in Qingchuan in the past 10 years was analyzed, and the driving force that caused the change was identified. At last, land use/cover area ratio of the study area in 2015 and 2020 were predicted. According to the results obtained, between 2000 and 2005, the area of arable land, water and unused land decreased, while the area of woodland, grassland and construction land increased; between 2015 and 2020, the area of arable land and grassland decreased, while the area of woodland, water, construction land and unused land increased. During the ten years, the area of arable land continually decreased with the scale reduced, the area of woodland continually increased with the scale reduced, the area of construction land increased continually with the scale increased, the area of water and unused land decreased and then increased, and the area of grassland increased and then decreased. An analyses reveals that policy, economic development, population growth, and natural disasters seem to be the principal impact factors of land use changes in the study area. It is inferred that, under the conditions that relevant policy is unchanged and no natural disasters occur, the proportion of woodland area will increase from 58.57% in 2010 to 59.01% in 2015, and increase to 59.44% in 2020. The proportion of arable area will decrease to 29.13% and the proportion of construction land will continually increase to 0.22% by 2020.

Keyword: remote sensing; GIS; land use/cover change (LUCC); transfer matrix; Markov forecast

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0 引言

伴随着人类社会不断的技术进步, 人们改造和利用自然环境的能力虽在不断提高, 污染环境和破坏生态平衡的问题屡见不鲜, 而这些问题往往首先表现在土地利用上。随着信息技术的快速发展, 利用RS和GIS技术进行土地利用动态监测, 及时准确地了解和掌握土地利用的时空动态变化信息, 对于研究如何实现土地的可持续利用、建立和谐的社会具有重要意义。刘纪远等对2000— 2005年中国土地利用变化的空间格局与驱动力进行了分析^[1]; 李晓文等对长江下游地区1988— 1998年10 a来土地利用类型变化进行了研究^[2]; 朱会义等对环渤海地区1985— 1995年间土地利用的数量变化和空间变化特征进行了研究^[3]; 伍星等对长江上游1970— 2000年土地利用/覆被变化特征及其驱动力进行了分析^[4]。

2008年四川省发生了“ 5· 12” 汶川地震, 与之相距不远的青川县受灾严重, 土地利用类型发生了很大的变化, 但是目前尚未见对青川县近些年土地利用/覆被变化情况的分析研究成果发表。本文主要研究青川县2000— 2010年土地利用/覆被变化情况, 深入了解和掌握青川县土地利用/覆被变化过程, 并对2015年和2020年其土地利用面积比例进行了马尔科夫预测, 以期为青川县生态恢复和重建提供决策依据。

1 研究区概况及数据处理

青川县地处四川盆地北部边缘, 白龙江下游, 川、甘、陕3省结合部, 总面积326 519.20 km²。位于E104° 36'~105° 38', N32° 12'~32° 56'之间, 北接甘肃省文县、武都县和陕西省宁强县, 南邻江油市、剑阁县, 西靠平武县, 东连利州区、朝天区。青川县以中山地形为主, 境内地势西北高而东南低, 最高海拔3 837 m, 最低海拔491 m。研究区属亚热带温润季风气候, 年平均气温13.7℃, 气温从东至西逐渐降低。年均降水量为1 021.7 mm, 降水南多北少。

本研究选取了青川县2000年5月、2005年5月、2010年5月3期TM图像, 青川县1:10万DEM数据等资料。根据青川县土地利用的特点, 参照2007年中国土地资源分类系统的二级分类体系^[5], 将研究区土地利用类型划分为耕地、林地、草地、水域及水利设施用地、城乡建设用地和未利用地6类。建立研究区TM图像的土地利用类型解译标志, 运用ERDAS和ArcGIS软件对TM图像进行拼接、裁剪等预处理, 采取监督分类和人工目视解译相结合的方法及野外验证, 得到青川县2000年5月、2005年5月和2010年5月土地利用/覆被现状图, 并建立了相应数据库。在对各期TM数据的解译过程中, 本着边解译边检验的原则, 采用2.5 m分辨率的SPOT5图像辅助解译, 以保证判读结果的精度要求, 并对2010年解译的6种土地利用类型共选取约60个点进行野外验证。经统计各土地利用类型的解译精度均在90%以上, 取得了较高的工作精度。

2 研究区土地利用变化总体分析

通常用土地利用变化幅度这一土地利用类型的变化率指数来定量研究土地利用类型的总体变化^{[6, 7]}。由于各种用地类型或不同区域相同用地类型的面积基数不同, 变化率指数高的类型只是变化快的类型, 而并不一定是区域变化的主要类型, 对主要类型的判断通常还要考虑变化面积的大小。变化幅度模型计算公式为

K_t= $\begin{matrix} \frac{U_{b} - U_{a}}{U_{a}} \end{matrix}$ × 100% , (1)

式中: K_t为某一研究时段某一种土地利用类型变化类型的变化幅度; U_a和U_b分别为研究初期和末期某一种土地利用类型的面积。

研究区2000年5月、2005年5月及2010年5月各土地利用类型面积、占总面积的比例及其变化幅度如表1所示。

表1 研究区2000年5月、2005年5月及2010年5月土地利用类型面积、比例及变化幅度统计表 Tab.1 Area, percentage and change of land use types in May 2000, 2005 and 2010 of study area

分析表1可知:

1)研究区土地利用类型面积从大到小依次为林地、耕地、草地、水域、未利用地、建设用地。

2)研究区2000年5月— 2005年5月建设用地变化幅度最大, 且总面积增加, 增加幅度达27.58%; 耕地、水域和未利用地面积均减少, 减少幅度依次为1.76%, 0.17%和1.93%; 林地和草地变化幅度相差不大, 增长幅度分别为0.79%和0.82%。

3)研究区2005年5月— 2010年5月未利用地变化幅度最大, 总面积增加且幅度达71.82%; 建设用地变化幅度次之且继续保持增长态势, 增加幅度为41.62%; 水域面积不再减少反而增加, 增加幅度为6.32%; 耕地面积继续减少, 减少幅度为1.52%; 林地面积继续增长, 幅度为0.33%; 草地面积减少, 减少幅度微乎其微。

4)研究区10 a间建设用地和未利用地面积均增长了一半以上, 耕地面积持续减少, 水域面积先减后增, 林地面积持续较缓增长, 草地面积先增后减, 但减少幅度很小。

5)研究区耕地和林地变化面积最大, 但由于总面积大, 所以变化幅度并不大。虽然建设用地和未利用地面积变化较小, 但是由于总面积基数较小, 故其变化幅度较大。

3 研究区土地利用变化过程分析

本文利用转移矩阵来对研究区土地利用变化过程进行分析, 用地类型间的转移分析可全面而又具体地刻画区域土地利用变化的结构特征与各用地类型变化的方向^{[6, 8, 9, 11, 12]}, 即

(2)

式中: S为面积; n为土地利用的类型数; i, j分别代表研究初期与研究末期的土地利用类型。经计算得到研究区2000年5月— 2005年5月及2005年5月— 2010年5月的土地利用转移矩阵, 具体见表2和表3。

表2 研究区2000年5月— 2005年5月土地利用转移矩阵 Tab.2 Land use transition matrix in May 2000— May 2005 of study area(hm²)

从表2可以直观地看出, 研究区2000年5月— 2005年5月面积变化从大到小依次是: 林地、耕地、草地、建设用地、未利用地、水域。林地发生变化的总面积最大且总面积增加, 大部分是由耕地转化而来, 其次是由草地转化而来; 耕地变化的面积次之且总面积减少, 大多减少的耕地转化为林地, 少部分转化为草地, 极少部分转化为建设用地; 草地面积总体增加; 水域面积总体减少; 建设用地面积增加, 均由耕地转变而来; 未利用地面积减少, 减少的部分均转化为草地。

表3 研究区2005年6月— 2010年5月土地利用转移矩阵 Tab.3 Land use transition matrix in June 2005— May 2010 of study area(hm²)

从表3可以直观地看出, 研究区2005年5月— 2010年5月面积变化从大到小依次是: 林地、耕地、草地、水域、未利用地、建设用地。林地发生变化最大且总面积增加, 大多是由耕地其次由草地转化而来; 耕地变化的面积次之且总面积减少, 减少的耕地大多转化为林地, 少部分转化为水域, 极少部分转化为建设用地以及未利用地; 草地面积总体增加; 水域面积总体增加, 由耕地、草地、林地转化而来; 建设用地面积增加, 由耕地、草地及林地转变而来; 未利用地总体面积增加, 由林地、耕地和草地转化而来。

近10 a内, 林地面积持续增加, 耕地面积持续减少, 主要是受退耕还林政策的影响。青川县属国家生态试点县和退耕还林实施县, 该县立足资源优势, 出台了多项政策确保退耕还林政策的实施, 取得了较好的生态、经济和社会效益。在退耕还林政策的影响下, 青川县2000年5月— 2005年5月和2005年5月— 2010年5月期间均有多处耕地转变为林地。近10 a内建设用地面积增加主要是受社会经济因素的影响, 2000年5月— 2005年5月和2005年5月— 2010年5月主要建设用地面积持续增加主要是城镇建设以及新修道路的原因。2005年5月— 2010年5月未利用地面积增加主要是受“ 5· 12” 汶川地震的影响。青川县是重灾区之一, 受地震灾害影响, 滑坡、泥石流等地质灾害频频发生, 对植被造成破坏, 使土地利用类型发生了变化, 未利用地面积明显增加。

经过解译获得的研究区2000年5月、2005年5月、2010年5月土地利用类型分布图见图1。

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	图1 研究区2000年5月、2005年5月、2010年5月土地利用类型分布Fig.1 Distribution of land use types in May 2000、2005 and 2010 of study area

对比图1可以看出, 林地和耕地所占面积比例较大, 县境西北和东北两处没有耕地分布, 但林地分布较广, 中部耕地较多而林地较少, 其余部分耕地和林地交错分布; 草地主要分布在西北和西南, 东部也有分布; 水库位于研究区东北, 河流分布较广; 建设用地主要有4处, 均分布在青竹江、白龙江、乔庄河3条河流附近; 未利用地所占比例很小。

4 研究区土地利用变化趋势预测

马尔可夫过程模型是预测土地利用变换和情景分析的有效方法之一, 近年来国内外许多学者使用马尔科夫模型预测植被覆盖和土地利用变化^{[9, 14, 15]}。马尔可夫预测模型的原理为

P(t)=P(t-1)P_i_,_j=P(0) $\begin{matrix} P_{i, j}^{n} \end{matrix}$ , (3)

式中: P(0)代表研究初始时刻土地利用类型的状态概率向量, 简称初始状态矩阵; P_ij代表土地利用类型i经一步转变为j的转移概率矩阵; P(t)代表将来时刻t时的土地利用类型的状态概率向量; n为初始时刻到t时刻的转移次数。

转移概率矩阵可通过一定时间段内某类土地利用类型的年平均转化率获得, 即

P_i_,_j=C_i_,_j/S_i , (4)

式中: C_i_,_j为研究期内第i类土地利用类型转变为第j

类土地利用类型的面积; S_i为研究初期第i类土地利用类型的总面积。

研究区2000年5月— 2005年5月青川县土地利用转移概率矩阵如表4所示。

表4 研究区2000年5月— 2005年5月土地利用转移概率矩阵 Tab.4 Land use transition probability matrix in May2000— May 2005 of study area(%)

本次研究将土地利用类型分为耕地、林地、草地、水域、建设用地、未利用地6大类, 研究时段内各土地利用类型在这6类之间相互转换。考虑到2008年“ 5· 12” 汶川地震对青川县土地利用类型带来的影响, 采用2000年5月— 2005年5月的土地利用转移概率矩阵来进行预测计算, 以2010年5月青川县各种土地利用类型面积百分比数据确定为研究初始时刻的状态向量, 以5 a为步长, 预测2015年和2020年土地利用类型百分比。即采用表4作为转移概率矩阵P_ij, 得到初始状态向量P(0)如下

P(0)=[30.17 58.57 8.77 2.08 0.17 0.24]=[耕地林地草地水域建设用地未利用地] 。 (5)

经马尔科夫模型预测的结果如表5所示。

表5 研究区2015年和2020年土地利用类型占青川县用地总面积的百分比预测 Tab.5 Forecast of land use types in 2015 and 2020 of study area(%)

5 结论

采用RS和GIS技术, 对四川省青川县2000年5月、2005年5月及2010年5月土地利用/覆被及土地利用/覆被动态变化进行了研究, 并对2015年和2020年研究区土地类型占地百分比进行了预测, 得到以下结论:

1)2000年5月— 2005年5月间, 面积变化从大到小依次是: 林地、耕地、草地、建设用地、未利用地、水域; 2005年5月— 2010年5月间, 面积变化从大到小依次是: 林地、耕地、草地、水域、未利用地、建设用地。

2)2000年5月— 2005年5月和2005年5月— 2010年5月2个时期内, 耕地面积持续减少但减幅减小; 林地面积持续增加而增幅减小; 建设用地持续增加且增幅增大; 水域和未利用地先减后增; 草地先增后减。

3)2000年5月— 2010年5月间, 增加的林地主要由耕地转变而来。

4)青川县的退耕还林的政策, 社会经济发展、人口增长及地震影响是土地利用变化的最主要原因。

The authors have declared that no competing interests exist.

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[2]	李晓文, 方精云, 朴世龙. 近十年来长江下游土地利用变化及其生态环境效应[J]. 地理学报, 2003, 58(5): 659-667. Li X W, Fang J Y, Piao S L. Land use changes and its implication to the ecological consequences in lower Yangtze Region[J]. Acta Geographica Sinica, 2003, 58(5): 659-667. [本文引用:1] [CJCR: 2.937]
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[4]	伍星, 沈珍瑶, 刘瑞民. 长江上游土地利用/覆被变化特征及其驱动力分析[J]. 北京师范大学学报: 自然科学版, 2007, 43(4): 461-465. Wu X, Shen Z Y, Liu R M. An analysis on the land use/cover change characteristics and driving forces in the upper reaches of Yangtze River[J]. Journal of Beijing Normal University: Natural Science, 2007, 43(4): 461-465. [本文引用:1] [CJCR: 0.4356]
[5]	中华人民共和国国家标准. 土地利用现状分类[S]. GB/T 21010-2007, 2007. National Stand ard of the People’s Republic of China. Classification of current land using situation[S]. GB/T 21010-2007, 2007. [本文引用:1]
[6]	朱会义, 李秀彬. 关于区域土地利用变化指数模型方法的讨论[J]. 地理学报, 2003, 58(5): 643-650. Zhu H Y, Li X B. Discussion on the index method of regional land use change[J]. Acta Geographica Sinica, 2003, 58(5): 643-650. [本文引用:2] [CJCR: 2.937]
[7]	臧淑英, 孙学孟, 韩冬冰. 黑龙江省大庆市土地利用/覆被变化及其驱动力分析[J]. 北京林业大学学报, 2005, 27: 63-68. Zang S Y, Sun X M, Han D B. The process of land -use and land -cover changes and analysis of its driving forces in Daqing, northeast China[J]. Journal of Beijing Forestry University, 2005, 27: 63-68. [本文引用:1] [CJCR: 1.242]
[8]	刘湘南, 许红梅. 基于RS, GIS的松嫩沙地土地利用变化研究-以吉林省前郭县为例[J]. 国土资源遥感, 2001, 13(1): 54-59. Liu X N, Xu H M. Study on land use change of Songnen sand y plain based on RS and GIS[J]. Remote Sensing for Land and Resources, 2001, 13(1): 54-59. [本文引用:1]
[9]	夏小梅, 陈阿林, 杨华. 基于遥感与GIS的LUCC及马尔柯夫过程趋势预测——以重庆市南岸区为例[J]. 水土保持研究, 2009, 16(5): 19-24. Xia X M, Chen A L, Yang H. Land use and land cover change and the tendency forecast of markov process based on RS and GIS: A case study in Nan’an District, Chongqing City[J]. Research of Soil and Water Conservation, 2009, 16(5): 19-24. [本文引用:2] [CJCR: 0.66]
[10]	魏显虎, 张增祥, 胡顺光, 等. 北京山区土地利用转移的系统性和随机性[J]. 国土资源遥感, 2010, 22(4): 77-84. Wei X H, Zhang Z X, Hu S G, et al. Rand om and systematic land -use transitions in mountainous area of Beijing[J]. Remote Sensing for Land and Resources, 2010, 22(4): 77-84. [本文引用:1]
[11]	刘瑞, 朱道林. 基于转移矩阵的土地利用变化信息挖掘方法探讨[J]. 资源科学, 2010, 32(8): 1544-1550. Liu R, Zhu D L. Methods for detecting land use changes based on the land use transition matrix[J]. Resources Science, 2010, 32(8): 1544-1550. [本文引用:1] [CJCR: 2.123]
[12]	李振, 黄海军. 胶州湾海岸带土地利用/覆被变化研究[J]. 国土资源遥感, 2010, 22(4): 71-76. Li Z, Huang H J. Land use and land cover change of the coastal zone around Jiaozhou Bay[J]. Remote Sensing for Land and Resources, 2010, 22(4): 71-76. [本文引用:1]
[13]	杨武年, 刘恩勤, 陈宁, 等. 成都市土地利用遥感动态监测及驱动力分析[J]. 西南交通大学学报, 2010, 45(2): 185-190. Yang W N, Liu E Q, Chen N, et al. Remote sensing dynamic moitoring and driving force analysis of land use/cover changes in Chengdu[J]. Journal of Southwest Jiaotong University, 2010, 45(2): 185-190. [本文引用:1] [CJCR: 0.608]
[14]	徐岚, 赵羿. 利用马尔柯夫过程预测东陵区土地利用格局的变化[J]. 应用生态学报, 1993, 4(3): 272-277. Xu L, Zhao Y. Forecast of land use pattern change in Dongling District of Shenyang: An application of Markov process[J]. Chinese Journal of Applied Ecology, 1993, 4(3): 272-277. [本文引用:1] [CJCR: 1.742]
[15]	刘启承, 熊文强, 韩贵锋. 用马尔可夫理论预测三峡库区的土地利用趋势[J]. 重庆大学学报: 自然科学版, 2005, 28(2): 107-110. Liu Q C, Xiong W Q, Han G F. Tendency forecast of three gorge land using by means of Markov[J]. Journal of Chongqing University: Natural Science Edition, 2005, 28(2): 107-110. [本文引用:1] [CJCR: 0.5143]
[16]	方秀琴, 任立良, 李琼芳. 近40年老哈河流域土地利用变化监测与分析[J]. 国土资源遥感, 2012, 24(2): 125-131. Fang X Q, Ren L L, Li Q F. The detection and analysis of land use change in the Laoha river basin during the past four decade[J]. Remote Sensing for Land and Resources, 2012, 24(2): 125-131. [本文引用:1]
[17]	李秀梅, 袁承志, 李月洋. 渤海湾海岸带遥感监测及时空变化[J]. 国土资源遥感, 2013, 25(2): 156-163. Li X M, Yuan C Z, Li Y Y. Remote sensing monitoring and spatial-temporal variation of Bohai bay coastal zone[J]. Remote Sensing for Land and Resources, 2013, 25(2): 156-163. [本文引用:1]
[18]	庞小笑, 封建民, 李晓华, 等. 近40年来五陵原土地利用变化研究[J]. 水土保持研究, 2013, 20(2): 73-79. Pang X X, Feng J M, Li X H, et al. Reaearch of land -use change in Wulingyuan during the last 40 years[J]. Research of Soil and Water Conservation, 2013, 20(2): 73-79. [本文引用:1] [CJCR: 0.66]
[19]	王振波, 方创琳, 王婧. 1991年以来长三角快速城市化地区生态经济系统协调度评价及其空间演化模式[J]. 地理学报, 2011, 66(12): 1657-1668. Wang Z B, Fang C L, Wang J. Evaluation on the coordination of ecological and economic systems and associated spatial evolution patterns in the rapid urbanized Yangtze Delta region since 1991[J]. Acta Geographica Sinica, 2011, 66(12): 1657-1668. [本文引用:1] [CJCR: 2.937]

2009

0.0

2.937

刘纪远, 张增祥, 徐新良, 等. 21世纪初中国土地利用变化的空间格局与驱动力分析[J]. 地理学报, 2009, 64(12): 1411-1420.

Liu J

, Zhang Z

, Xu X

, et al. Spatial patterns and driving forces of land use change in China in the early 21st century[J]. Acta Geographica Sinica, 2009, 64(12): 1411-1420.

Land use and land cover change as the core of coupled human-environment systems has become a potential field of land change science (LCS) in the study of global environment change. Based on remotely sensed data of land use change with the spatial resolution of 1km ×1km on national scale among every five years, this paper designed a new dynamic regionalization according to the comprehensive characteristics of land use including regional differentiation, physical, economic, and macro-policy factors as well. Spatial pattern of land use change and its driving forces were investigated in Chia in the early 21st century. To sum up, land use pattern of this period was characterized by rapid changes in the whole country. Over the agricultural zones,e.g., Huang-Huai-Hai Plains, the southeast coastal area and Sichuan Basin, the built-up and residential areas were considerably expanded to a great proportion in the northwestern oasis agricultural zones and the northeastern zone led to a slight increase of arable land aea in the northern China. Due to the "grain for green" policy, forest area was significantly increased in the middle and western developing region,Where the vegetation coverage was substanially enlarged, likewise. This paper argued the main driving forces as the implementation of the strategy on land use and regional development, such as the "Western Development", "the Revitalization of the Northeast" policy, coupled with rapidly economic development during this period.

1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; 2. Institute of Remote Sensing Applications, CAS, Beijing 100101, China; 3. Chengdu Institute of Mountain Hazards and Environment, CAS, Chengdu 610041, China; 4. Northeast Institute of Geography and Agricultural Ecology, CAS, Changchun 130012, China; 5. Wuhan Institute of Geodesy and Geophysics, CAS, Wuhan 430077, China; 6. Cold and Arid Regions Environmental and Engineering Research Institute, CAS, Lanzhou 730000, China; 7. Nanjing Institute of Soil Science, CAS, Nanjing 210008, China; 8. Xinjiang Institute of Ecology and Geography, CAS, Urumqi 830011, China; 9. Nanjing Institute of Geography and Limnology, CAS, Nanjing 210008, China

在全球环境变化研究中，以土地利用与土地覆盖动态为核心的人类－环境耦合系统研究逐渐成为土地变化科学 (LCS) 研究的新动向。基于覆盖中国21世纪初5年间隔的遥感卫星数据获取的1 km网格土地利用变化空间信息，依据近5年土地利用变化区域分异的显著特征，以及自然地理、经济发展与国家宏观政策因素综合考虑，设计针对21世纪初5年新的中国土地利用动态区划图，揭示土地利用变化的空间格局与驱动因素。总体上，21世纪初5年中国处于土地利用快速变化期，黄淮海平原、东南沿海地区与四川盆地城乡建设用地显著扩张，占用大规模优质农田，导致南方水田面积明显减少；西北绿洲农业发展与东北地区开垦导致北方旱地面积略有增加；受西部开发“生态退耕”政策的影响中西部地区林地面积显著增加，国家退耕还林还草政策成效明显，对区域土地覆盖状况的改善产生积极的影响；这一时段国土开发与区域发展战略的实施，包括“西部大开发”、“东北振兴”等国家重大政策，加之快速的经济发展是该阶段土地利用变化格局形成的主要驱动因素。

... 2005年中国土地利用变化的空间格局与驱动力进行了分析^[1] ...

2003

0.0

2.937

李晓文, 方精云, 朴世龙. 近十年来长江下游土地利用变化及其生态环境效应[J]. 地理学报, 2003, 58(5): 659-667.

Li X

, Fang J

, Piao S

Land use changes and its implication to the ecological consequences in lower Yangtze Region[J]. Acta Geographica Sinica, 2003, 58(5): 659-667.

Based on the multi-temporal remotely sensed data of TM, this research attempted to reveal the spatio-temporal trends in landuse and landcover in Lower Yangtze Region by depicting and analyzing the process and spatial heterogeneity of landuse & landcover changes in the region, especially placing emphasis on the transformation modes and spatial behavior of landuse. In order to achieve the goal, the magnitude and spatial distribution of landuse transformation from the 1988 to the 1998 were analyzed by the transformation matrixes and the spatial layouts of landuse, then changes of landuse degree and associated traits in spatial distribution were targeted by establishing and applying the landuse index. Furthermore, the spatial shifting of landuse transformation intensity was studied by conceiving and using Landuse Transformation Index. As a hot topic, the loss of cultivated land and its driving force were also included in this step, and the top ten significant forms of landuse transformation were analyzed, in particular the trends in spatial transformation according to their Important Value individually.

1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; 2. Department of Urban and Environmental Science, Peking University, Beijing 100871, China

基于TM卫星遥感数据，对长江下游地区1988~1998年10年来土地利用类型的数量和时空变化特征进行了研究。为表征长江下游土地利用及其变化的时空分异特征，以县级行政区为基本空间分析单元，利用土地利用程度变化模型以及土地利用类型变化强度指数分析了长江下游近10年来的土地利用程度及其变化的区域分异特征、各土地利用类型变化强度的区域分异特征；通过计算土地利用变化类型的重要值，分析了区域土地利用变化的空间趋向性。研究中还对农田的数量变化特征、耕地流失强度的区域分异，特别是土地利用变化的区域生态环境效应等问题进行了分析和探讨。

... 1998年10 a来土地利用类型变化进行了研究^[2] ...

2001

0.0

2.937

... 1995年间土地利用的数量变化和空间变化特征进行了研究^[3] ...

2007

0.0

0.4356

... 2000年土地利用/覆被变化特征及其驱动力进行了分析^[4] ...

2007

0.0

... 根据青川县土地利用的特点,参照2007年中国土地资源分类系统的二级分类体系^[5],将研究区土地利用类型划分为耕地、林地、草地、水域及水利设施用地、城乡建设用地和未利用地6类 ...

2003

0.0

2.937

朱会义, 李秀彬. 关于区域土地利用变化指数模型方法的讨论[J]. 地理学报, 2003, 58(5): 643-650.

Zhu H

, Li X

Discussion on the index method of regional land use change[J]. Acta Geographica Sinica, 2003, 58(5): 643-650.

Recently, many sorts of index models have been widely adopted in the analysis of land use change in China. And they do play an important role in summarizing the rule of regional land use changes. However, according to the present research papers, there are some confusions and misuses in their applications, which root in faultiness, abnormity and misunderstanding of the indices or index calculation. By detailed exploration of the indices embedded in research materials, three classifications are identified on the basis of their application purposes: the change of regional land resources (change rate index and level change index), the direction of land use change (transition matrix and flow direction rate) and the spatial pattern of land use change (dynamic degree, relative change rate, adjacency degree, barycenter, frequency degree and importance degree). Then all the indices listed above are discussed under the purposed framework, including their concepts, calculation methods, application fields, misuses, and some application suggestions. This paper also gives a remark in the end that the research of land use change needs new breakthroughs in both theory and methodology. Index method is only a simple kind with limited functions, and much more efforts should be devoted to integrative, predictive methods in the coming days.

Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

近几年来，各类指数模型方法被广泛应用于我国土地利用变化研究中，并在区域土地利用变化规律总结上发挥了重要作用。这些指数方法包括变化率、土地利用程度综合指数、转移矩阵、流向百分比、动态度、相对变化率、邻接度、多度、重要度、景观指数等。但有关文献对这些指数的表述与计算中，还存在一些明显的混乱与误用。文章通过分析国内相关文献中所涉及的各类指数方法，将其按资源变化的分析、变化方向分析、变化的空间形式分析等目的取向加以归类，然后在此类型框架下，详细阐述了各种指数方法的概念、计算方法、意义、存在的问题，并提出应用建议。

... 2 研究区土地利用变化总体分析通常用土地利用变化幅度这一土地利用类型的变化率指数来定量研究土地利用类型的总体变化^[6,7] ...

... 3 研究区土地利用变化过程分析本文利用转移矩阵来对研究区土地利用变化过程进行分析,用地类型间的转移分析可全面而又具体地刻画区域土地利用变化的结构特征与各用地类型变化的方向^{[6,8,9,11,12]},即 ...

2005

0.0

1.242

... 2 研究区土地利用变化总体分析通常用土地利用变化幅度这一土地利用类型的变化率指数来定量研究土地利用类型的总体变化^[6,7] ...

2001

0.0

刘湘南, 许红梅. 基于RS, GIS的松嫩沙地土地利用变化研究-以吉林省前郭县为例[J]. 国土资源遥感, 2001, 13(1): 54-59.

Liu X

, Xu H

Study on land use change of Songnen sand y plain based on RS and GIS[J]. Remote Sensing for Land and Resources, 2001, 13(1): 54-59.

Land use change is a result of complex interaction between natural factor and various human work, and soc-economic factor are the important drive force in short term. The study area is Qianguo county of Jilin province lies in northeast of China. To discuss the progress of land use change and the soc-economic driving mechanism of these changes since 10 years in study area, we analyze TM image of 1987 and 1996, and related statistic data by using spatial analysis, statistic analysis and the method integrated image data with vector data. The result shows that farmland area increased significantly while forest and grassland area decreased, and others changed a little. The main driving forces lead to these changes are agriculture production, breeding production, agriculture population and food production.

1. School of Urban and Environmental Science, Northeast Normal University, Changchun 130024, China; 2. The Institute of Resource Science of Beijing Normal University and The Open Research Lab. of Environment Change and Natural Disasters of the State Education Commission, Beijing 100875, China

土地利用变化是自然与人文因素综合作用的结果。在较短时间尺度上,社会经济因素是土地利用变化的主要驱动力。本文以吉林省前郭尔罗斯县为例,运用1987年和1996年TM影像及相关统计数据,采用空间分析、统计分析和遥感信息与空间化非遥感信息集成等方法,研究了10a来该县土地利用变化过程及其社会经济驱动机制。结果表明,近10a来,耕地面积明显增加,林地、牧草地面积减少,其它土地利用类型面积变化不大,农业产值、牧业产值、农业人口数和粮食产量是该县土地利用变化的主要社会经济驱动力.

2009

0.0

0.66

... 4 研究区土地利用变化趋势预测马尔可夫过程模型是预测土地利用变换和情景分析的有效方法之一,近年来国内外许多学者使用马尔科夫模型预测植被覆盖和土地利用变化^[9,14,15] ...

2010

0.0

魏显虎, 张增祥, 胡顺光, 等. 北京山区土地利用转移的系统性和随机性[J]. 国土资源遥感, 2010, 22(4): 77-84.

Wei X

, Zhang Z

, Hu S

, et al. Rand om and systematic land -use transitions in mountainous area of Beijing[J]. Remote Sensing for Land and Resources, 2010, 22(4): 77-84.

As an important part of Beijing’s suburbs, the mountainous area of Beijing has both the characteristics of metropolitan suburbs and the features of mountains, and so its land use pattern is different from other areas. Based on statistics, the authors separated land-use transformations of the mountainous area of Beijing to random and systematic transitions through an in-depth analysis of land use transition matrix. A land-use transition is random if a land-use category gains from other categories in proportion to the availability of those other losing categories, or if a category loses to other categories in proportion to the size of those other gaining categories. Any large deviation from those proportions is referred to as a systematic transition. From the concurrent incidence of systematic gains and losses, it is concluded that the most dominant signals of change find expression in the following aspects: the conversion of higher coverage grassland and other woodland to cropland, the conversion of cropland and sparse woodland to other woodland, the conversion of sparse woodland to higher coverage grassland, the conversion of cropland and higher coverage grassland to water areas and the conversion of cropland to built-up areas. The transition areas from cropland to other woodland and built-up areas are relatively large and have obvious advantages for systematic transitions. While the areas of transitions from other woodland to cropland and from sparse woodland to higher coverage grassland are relatively small, the transitions are still attributed to dominant signals of change. This method is simple and practical and enables scientists to focus their research on the most important land transitions, which will help in linking patterns to processes and in management of land resources.

1. Remote Sensing Application Institute, Chinese Academy of Sciences, Beijing 100101, China; 2. Graduate School of Chinese Academy of Sciences, Beijing 100039, China

从统计学的角度出发，通过深入分析土地利用转移矩阵，将北京山区土地利用转移过程分为系统转移和随机转移。从同时发生的系统性增加和系统性减少推断出土地利用变化的优势信息有：高覆盖度草地和其他林地转换为耕地；耕地和疏林地转换为其他林地；疏林地转换为高覆盖度草地；耕地和高覆盖度草地转换为水域；耕地转换为建设用地。其中耕地向其他林地和建设用地转移的面积都很大，且系统性转换优势明显；其他林地转换为耕地、疏林地转换为高覆盖度草地虽然不具有数量上的转换优势，但该转换属于很强的系统性转换。该方法能快速挖掘最具系统优势的土地利用转移信息，有助于科研人员将土地利用格局和变化过程联系起来，为土地资源管理提供有用信息。

2010

0.0

2.123

刘瑞, 朱道林. 基于转移矩阵的土地利用变化信息挖掘方法探讨[J]. 资源科学, 2010, 32(8): 1544-1550.

Liu

, Zhu D

Methods for detecting land use changes based on the land use transition matrix[J]. Resources Science, 2010, 32(8): 1544-1550.

Land use change is a key component for global environment change, and also a representation of the impact of human activities on the environment. The cross-tabulation matrix is a fundamental tool in analyses of land use change, but many studies seem to be short of analyzing the matrix in terms of its various components, failing to obtain as much insight as possible concerning the potential processes that determine a general pattern of land use change. This paper aims to use the cross-tabulation matrix to assess the total land use change on the basis of the net change and transfer change. The relative differences between the observed transition and expected transition, which were generated by random transitions, can be used to extract systematic inter-category transitions. An example of changes among five land use categories in Linyi County in Shandong Province illustrated the effectiveness of the suggested method. The amount of total change for cropland was found largest, followed by forest land, unused land, construction land and others. The change in cropland was nearly a pure swap-type of change. In contrast, the unused land indicated no swap change but net change. Changes in others consisted of both swap and net change. The most prominent transition was the conversion from cropland to forest, accounting for 2.63% of the landscape, followed by the conversion from unused land to cropland, and cropland to construction land. If the gains occurred at random categories, it replaced the unused land at a rate eight times of the expected rate. The large conversion from cropland to forest could be attributed to the largest cropland in all categories, since the quantity of the conversion was almost equivalent to what would be expected from a random process. If the processes of loss occurred at random categories and the other land lost, forest tended to replace it at a rate exceeding two times of the expected rate. A relatively large conversion from cropland to forest could be as a result of the smallest area of forest in all land use categories, since the quantity of the conversion was larger than what would be expected from a random process. It was concluded that these methods can facilitate detection of the strongest signals from systematic land use transitions, which would be greatly helpful for analyses and modeling of land use change.

土地利用变化是全球变化中的重要组成部分。本文以土地利用转移矩阵为基础，构建了土地利用净变化量、交换变化量、总变化量的计算方法，并计算了随机状态下各地类间相互转换的理论频数，通过实际转换量与理论转换量进行对比，构建判断土地利用转换规则的方法，从而能够更加清晰地判断土地利用变化的系统过程。应用上述方法对山东省德州市临邑县土地利用变化进行了实证分析，结果显示：临邑县耕地总变化量最大，其次是园林地和未利用地，最后是建设用地和其他土地，其中耕地几乎全部都是交换变化，而未利用地则相反，园林地和其他土地以交换变化为主，建设用地以净变化为主；从新增的角度来说，未利用地转化为其他土地最具有转换优势，其次是未利用地转换为园林地；从流失的去向看，其他土地转换为园林地最具转换优势，其次是耕地转换为园林地。结果表明该方法可以有效获取各土地利用类型动态变化信息，更清晰地辨别土地利用类型间的转换规则，能够为土地利用空间分析和建模提供更有用的信息。

2010

0.0

李振, 黄海军. 胶州湾海岸带土地利用/覆被变化研究[J]. 国土资源遥感, 2010, 22(4): 71-76.

, Huang H

Land use and land cover change of the coastal zone around Jiaozhou Bay[J]. Remote Sensing for Land and Resources, 2010, 22(4): 71-76.

Land use and land cover change constitutes significant problems in the study of global environmental change. In this paper, the authors used the single decision tree method to classify two images of Landsat TM/ETM+ in 1989 and 2000 and obtained land use patterns of the coastal zone around Jiaozhou Bay. In this process, atmospheric correction and geo-knowledge study are recommended. Then through "overlay" analysis, the transfer matrix of land use can be obtained. The characteristics of land use/cover change are mainly demonstrated as follows: land for construction use such as cities and countries increases rapidly at the expense of occupying large amounts of farmland, land for marine culture and saltern expands by taking the place of some farmland and sea area; nevertheless, farmland and inland beach decrease greatly, and land for forest and grass changes very little. In the past ten years or more, human activities such as increasing the amount of waste gas, waste water and industrial residue, dumping a lot of land-sourced nutritive salt and pollutants into the Jiaozhou Bay, have exerted increasingly strong effect on ecological environment, which finds expression in the following aspects: the water of Jiaozhou Bay has deteriorated, the amount of heavy metals in sediments has increased, the population and biodiversity of plankton have decreased and harmful algal blooms have happened frequently.

1.Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China; 2.Graduate University of Chinese Academy of Sciences, Beijing 100049, China

对影像进行大气校正等处理后，引入地学知识构建决策树，运用决策树法对1989年及2000年Landsat TM/ETM影像进行分类，得到这两个时期的土地利用类型图，然后对这两期土地利用类型进行叠加分析，得到土地利用变化矩阵。1989~2000年胶州湾土地利用变化过程表现为：城镇等建成地、养殖及盐田用地、城镇的建设裸地或待建地等迅速扩增，而耕地、内陆滩涂迅速减少，海域减少，林、草地变化不大；耕地主要向城镇等建成地、养殖及盐田用地转化，海域向养殖及盐田用地、城镇建成地转化。十余年间，人类活动对环境的影响增强，城市“三废”增加，陆源营养盐和其他污染物大量排放入海，引起胶州湾海水水质恶化、沉积物重金属含量增加，浮游生物减少，生物多样性降低，赤潮频发。

2010

0.0

0.608

杨武年, 刘恩勤, 陈宁, 等. 成都市土地利用遥感动态监测及驱动力分析[J]. 西南交通大学学报, 2010, 45(2): 185-190.

Yang W

, Liu E

, Chen

, et al. Remote sensing dynamic moitoring and driving force analysis of land use/cover changes in Chengdu[J]. Journal of Southwest Jiaotong University, 2010, 45(2): 185-190.

To explore variation in the structure of land use/ land cover in Chengdu City due to the rapid development of urban construction in the past approximate 30 years, changes of its land use were dynamically monitored with its Landsat MSS and TM satellite remote sensing images in the years 1978 1992, 2000 and 2005, and a land use database for different times was established by the processing of the remote sensing images and the extraction and interpretation of information. With the help of support of GIS (geographic information system) spatial analysis function, the information of land use changes in Chengdu in the recent 28 years was extracted. The characteristics in the structure of its land use changes in the recent 28 years were analyzed quantitatively, and the driving forces of land use changes in Chengdu were discussed from natural and human factors. The research results provides a scientific basis for the relevant departments of the government to improve their acts scientifically and rationally in urban and rural planning, management and decision-making.

1. State Key Laboratory of Geo-hazard Prevention and Geo-environment Protection, Chengdu University of Technology, Chengdu 610059, China; 2. Institute of RS & GIS, Chengdu University of Technology, Chengdu 610059, China; 3. Prospect and Design Institute of Chengdu Military Command Air Force, Chengdu 610041, China

为查明成都市近30 a 来由于城市建设高速发展导致市区土地利用/ 覆被结构的重大变化,应用成都市1978,1992,2000 和2005 年4 个时相的卫星遥感图像,通过图像处理和信息提取,对其土地利用变化进行了动态监测,建立了不同时期土地利用数据库. 利用GIS 强大的空间分析功能,提取了成都市28 a 间4 个时相土地利用的变化信息,对其近28 a 间土地利用方式的变化特征进行了定量分析,并从自然因素和人文因素等方面探讨了土地利用变化的驱动机制. 研究成果为政府有关部门科学、合理地进行城乡规划与管理决策提供了科学依据.

1993

0.0

1.742

徐岚, 赵羿. 利用马尔柯夫过程预测东陵区土地利用格局的变化[J]. 应用生态学报, 1993, 4(3): 272-277.

, Zhao

Forecast of land use pattern change in Dongling District of Shenyang: An application of Markov process[J]. Chinese Journal of Applied Ecology, 1993, 4(3): 272-277.

Based on the data obtained from remote sensing aerial photographes and topographic maps during three different periods, the transition probability of land use pattern in Dongling District of Shenyang is defined, and the tendency of its change is forecasted with application of Markov process. The resuits show that over a long period of time, the arable land area will be decreased gradually and the area occupied by residence, factory and mine will be increased day by day. Finally, the land use pattern will be lied in a stable state, e. g. , non -irrigated farmland occupies by 20. 66%, paddy field by 28.41%, residential area and factory-mine by 37.42%, vegetable field by 6.15% , forest land by 4.36％. At that time, a new land use pattern of urban and rural integration will be formed.

Institute of Applied Ecology, Academia Sinica, Shenyang 110015

根据沈阳市东陵区3个时期遥感航片和地形图获得的土地利用类型数据,成功地确定了土地利用类型的转移概率,并用马氏链模型预测了该区土地利用类型变化趋势.结果表明,当前该区的土地利用格局正处于一种耕地逐渐减少,居民点工矿用地逐渐增加的变化状态,而且这种变化将持续很长时间,最后将达到以旱地20.66％、水田28.41％、居民点工矿用地37.42％、菜地6.15％、林地4.36％等为主要土地利用类型的稳定状态,形成一个城乡结合的新的土地利用格局.

2005

0.0

0.5143

刘启承, 熊文强, 韩贵锋. 用马尔可夫理论预测三峡库区的土地利用趋势[J]. 重庆大学学报: 自然科学版, 2005, 28(2): 107-110.

Liu Q

, Xiong W

, Han G

Tendency forecast of three gorge land using by means of Markov[J]. Journal of Chongqing University: Natural Science Edition, 2005, 28(2): 107-110.

In order to grasp the trend of land-using structure transition, adjust social and economical development strategies, and optimize the land-using structure, the land structure in latest years is forecasted, based on the analysis of land using actually and the first-hand data of the year 1995~2001. The theory of Markov chain is used to construct the transition probability matrix. The character of land structure transition is analyzed. The result shows that the plough reduce rapidly,the land is not fully utilize and the traffic land increase slowly.

为了把握土地利用结构变化的趋势,调整社会经济发展的策略,优化土地利用的结构,实现土地的可持续利用,根据重庆市万州区1995～2001年连续清查的第一手土地利用资料,在分析土地利用现状的基础上,应用马尔可夫理论,对万州区未来几年土地利用过程进行了模拟分析和定量预测.预测结果表明耕地减少速度加快,未利用地开发不充分,交通面积增长缓慢.

2012

0.0

方秀琴, 任立良, 李琼芳. 近40年老哈河流域土地利用变化监测与分析[J]. 国土资源遥感, 2012, 24(2): 125-131.

Fang X

, Ren L

, Li Q

The detection and analysis of land use change in the Laoha river basin during the past four decade[J]. Remote Sensing for Land and Resources, 2012, 24(2): 125-131.

On the basis of the multiple remote sensing images of Landsat MSS, TM and ETM + and other auxiliary data, two classification approaches of decision tree and support vector machine were applied to land use/cover classifications in the semiarid Laoha river basin over the past 40 years since the 1970s. The land use changes and their spatial distribution were analyzed quantitatively and mapped with GIS techniques. The results show that land use/cover maps in 1976, 1989, 1999 and 2007 could be generated based on the implementation of support vector machine classification with satisfying results. The analysis shows that land use has changed very obviously in the study area over the last 40 years. The areas of water body and grassland have decreased while rural and urban areas increased persistently. The cultivated land area has increased substantially. Forest land and fallow land have changed in fluctuation with a decrease on the whole. It’s obvious that the most remarkable change has been the interconversion of lands for agriculture (cultivated land), for forestry (forest land), and for animal husbandry (grassland). Moreover, the spatial distribution of the conversion was greatly different in different periods. An analysis of the intensity of land use changes indicates that the highest annual rate of land use change has been increased gradually and the annual intensity has been spatially heterogeneous. Moreover, the suburbs surrounding Chifeng city always have changed intensively during the past decades, suggesting the persistent urbanization of Chifeng city.

1. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China; 2. State Key Laboratory of Hydrology, Water Resources and Hydraulic Engineering, Hohai University, Nanjing, 210098, China

利用决策树和支持向量机分类方法,基于多期Landsat MSS, TM and ETM + 遥感图像和其他辅助数据,对1970s以来近40年半干旱的老哈河流域土地利用变化(land use and land cover change, LUCC)进行动态监测,并利用GIS方法对LUCC进行了定量分析和空间分布制图。结果显示,利用支持向量机分类方法对该地区1976年、1989年、1999年和2007年土地覆盖类型分类可达到较满意的效果; 近40年老哈河流域土地利用变化显著,水体和草地减少,城乡用地持续扩张,耕地大幅增加,林地和未利用地大幅度波动、总体减少。LUCC主要发生在林地、草地和耕地之间,表明农、林、牧用地之间转换显著,且在各个时期的空间分布差别较大。从变化强度来看,土地利用的年综合变化率最大值渐趋增大,年均土地动态度在空间分布上差异很大,另外在各研究期赤峰市区周边动态度都很大,反映了赤峰市持续性的城市化进程。

2013

0.0

2013

0.0

0.66

2011

0.0

2.937

王振波, 方创琳, 王婧. 1991年以来长三角快速城市化地区生态经济系统协调度评价及其空间演化模式[J]. 地理学报, 2011, 66(12): 1657-1668.

Wang Z

, Fang C

, Wang

Evaluation on the coordination of ecological and economic systems and associated spatial evolution patterns in the rapid urbanized Yangtze Delta region since 1991[J]. Acta Geographica Sinica, 2011, 66(12): 1657-1668.

Based on the Landsat TM remote sensed imageries in the periods of 1991, 2001 and 2008 Yangtze Delta Economic Region, and taking 90 counties in this region as basic units, this paper builds spatial data transformation models, i.e., the ESV and the EEH models. Spatial analysis of massive vector and raster data were done within the environment of ArcGIS 9.3. The ESV index and the EEH index reveal the relationship between economic development and eco-environment system of the Yangtze River Delta and its evolution . Furthermore, the function regionalization and the model modification were developed. The results are shown as follows. (1) Since 1991, the conversion of land-use type has been significant, and the city and town land has converted mainly from the paddy field, dry land, grass land, garden plot and other lands. (2) The ESV model shows that the eco-system tends to be degraded in the 9101 period of time, while in the 0801 period, the degradation trends are less significant. At the same time, it proves that the development pattern of the conversion of water body and paddy field to the city, town and dry land deteriorated the eco-system severely. (3) Since 1991, GDP in the central and southern parts is lower than that in the northern, and GDP growth rate in the central part for the 9101 period is higher than that in the northern, while in the 0108 period, it is higher than those in the central and southern parts. (4) According to EEH index, the paper divides Yangtze Delta Economic Region into 12 zones. The spatial characteristics of the EEH are: ecological conflict zone and ecological coordination zone are located in the center and fringe areas respectively, presenting a "core-fringe" structure in the "low to high" order, and in 9101 period eco-economic relationship tends to be concentrated on initial degradation, while in 0108, it converses to dispersed degradation and coordination. (5) Using the model of spatial data transformation, five types of eco-economic evolution are identified, namely, initial degradation zone, initial coordination zone, continuous degradation zone, reduced coordination zone and increased coordination zone. (6) Finally, the paper summarizes the spatial evolution patterns of the Yangtze Delta Region: the coexistence of the gradient mode and the core-fringe mode. The former consists of three horizontal belts in the northern, central and southern parts as the first grade gradient mode and of three N-S belts along the east, middle and west for the second grade gradient mode. The latter consists of seven groups, which are Suzhou-Wuxi-Changzhou group, Nanjing group, Shaoxing-Ningbo group, northern Jiangsu group, Taizhou group, Hangzhou group and Nantong group. Different modes correspond to different evolution patterns of the eco-economic system, which reflects a spatial differentiation trend of eco-economic relationship at a high level.

Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China

以长江三角洲经济区1991、2001、2008 年的Landsat TM影像解译数据为基础,以长三角90 个县(市、市区) 为基本研究单元,构建空间数据转换模型、ESV模型、EEH模型,借助ArcGIS 9.3 平台对海量的栅格和矢量数据进行空间分析,依据ESV指数和EEH指数揭示长三角经济发展与生态环境系统的相关关系和演变特征,并进行功能分区和模式提炼.研究表明:① 1991 年以来长三角地区土地利用类型大幅转换,城镇面积增长最大,来源主要是水田、旱地、草地、园地和其他用地;② ESV模型研究发现,1991-2001 时段长三角生态系统呈现恶化趋势,2001-2008 时段恶化幅度有所减缓,同时证明水域、水田变为城镇和旱地的开发行为对生态系统的稳定性具有极大的伤害;③ 1991 年来GDP空间格局为中、南部高北部低,其中1991-2001 时段中部增长率明显高于北部,2001-2008 时段中部增长率明显高于南北;④依据EEH指数将长三角分为12 类区域,EEH空间特征为生态冲突区居中心区位,生态协调区居边缘区位,并且按EEH由低到高呈现出明显的核心—边缘空间结构;1991-2001 时段长三角生态—经济关系已经出现了集中型初步恶化趋势,2001-2008 时段则由集中型初步恶化趋势向分散型恶化与协调并存状态;⑤ 通过空间数据转换模型将长三角分为5 种生态经济演变类型分区:初始恶化区、初始协调区、持续恶化区、协调降低区、协调升级区;⑥ 总结出长三角EEH的空间演变模式:梯度模式与核心边缘模式共存,其中一级梯度模式为北中南三大横向梯度带,二级梯度模式为长三角南北两翼的东中西三大纵向梯度带;核心边缘模式概括为7 大组团:即苏锡常沪组团、南京组团、绍甬组团、苏北组团、泰州组团、杭州组团、南通组团.不同的模式对应着不同的生态经济系统演变方式,反映出长三角快速城市化地区内部存在着较大程度的生态经济关系空间分化趋势.