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山东沿海地区土地利用和景观格局变化
Land use and landscape pattern changes in coastal areas of Shandong province,China

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吴莉 1   侯西勇 1 *   徐新良 2   邸向红 1  
文摘 为分析和预测山东省沿海区域土地利用和景观格局变化, 该文将景观格局指数作为评价土地利用变化模拟模型的基本指标;基于RS和GIS技术分析2000-2010年土地利用和景观格局的变化特征, 并尝试CA-Markov模型预测土地利用变化, 发现其在景观格局预测方面的不足, 因而探索和提出Spatial-Markov模型, 该模型不仅适合于土地利用变化模拟, 也适合于景观格局过程分析。具体包括:1)基于2000、2005和2010年的Landsat影像进行土地利用分类, 分析10a间土地利用和景观格局的变化特征, 表明:耕地面积不断减少, 城镇和农村居民点用地不断扩张而占用大量耕地, 草地等又不断开垦为耕地;区域景观格局破碎化趋势显著, 人为干扰加剧, 各种景观类型的分布向均匀化发展;2)基于Logistic-CA-Markov模型, 以11个变量、2000和2005年土地利用分类图为基础, 模拟的2010年土地利用图与观测值相比较, 虽然得到的Kappa系数较高(0.8530), 但难以支持对景观格局特征的预测和分析;3)提出Spatial-Markov模型, 基于2000和2005年土地利用分类图模拟2010年土地利用, 模拟结果的Kappa系数高达0.8872, 且景观格局指数也与观测值非常接近, 因此, 选择该模型预测2015和2020年的土地利用和景观格局;4)预测结果表明, 2010-2020年间耕地面积将继续减少, 城镇、农村居民点将继续保持快速增长的态势;景观尺度除了分形维数, 其他指数保持2000-2010年间的变化趋势, 而在类型尺度, 除水域和未利用地外, 各种景观类型多个景观指数将总体保持原有的变化趋势。该研究可为山东沿海区域土地利用规划提供参考, 并为土地利用预测研究提供了一种新的方法。
其他语种文摘 In this paper, the Spatial-Markov model, which was based on the theory of Markov process and spatial analysis techniques, was proposed to simulate land use change and landscape dynamics. By the Spatial-Markov model, the study area could be divided into numerous lattices and land use change in each lattices was simulated separately by the Markov process model. The outputs of the model include a set of ratio scale images and a nominal scale image. The whole process of the model was fulfilled by compiling programs with AML in ArcGIS 9.3. The coastal area of Shandong province was selected as the case study area. Land use maps were extracted based on Landsat TM/ETM+ images captured in 2000, 2005, and 2010 respectively. Firstly, characteristics of land use change and landscape dynamics were analyzed. It showed that, from 2000 to 2010, urban area and rural settlement expanded dramatically by massively occupying farmland, which, in turn, drove grassland reclaimed to farmland. At the landscape level, the landscape fragmentation increased, and both the diversity and evenness of the landscape increased. Secondly, using land use maps in 2000 and 2005, the Spatial-Markov model was developed to simulate the land use map in 2010 at a spatial scale of 500m. At the same time, the CA-Markov model was selected for model comparison, in specific, eleven driving factors were selected and the Logistic regression method was used to create the transitional maps for CA. Both Kappa coefficient and landscape indices were introduced to evaluate and compare the two models. It showed that the Spatial-Markov model not only achieved much higher Kappa coefficient, but also much better landscape indices than the CA-Markov model. Therefore, the Spatial-Markov model was applied to predict land use change and landscape dynamics in the next decade. Moreover, the prediction result shows that, from 2010 to 2020, areas of urban area and rural settlement will go on increasing, while areas of farmland will continue to decline. At the landscape level, all the landscape indices will follow their historical trend except for fractal dimension. As to the landscape indices at the class level, all landscape types will follow the same trend as before except for water and unused land.
来源 农业工程学报 ,2013,29(5):207-216,293 【核心库】
DOI 10.3969/j.issn.1002-6819.2013.05.028
关键词 土地利用 ; 景观格局 ; 模型 ; 山东沿海区域
地址

1. 中国科学院烟台海岸带研究所, 烟台, 264003  

2. 中国科学院地理科学与资源研究所, 北京, 100101

语种 中文
文献类型 研究性论文
ISSN 1002-6819
学科 农业基础科学
基金 中国科学院知识创新工程重要方向项目 ;  中国科学院战略性先导科技专项 ;  国家自然科学基金项目
文献收藏号 CSCD:4788913

参考文献 共 33 共2页

1.  Turner H B L. Land-use and land-cover change science/research plan. IGBP Report No.35 and HDP Report No.7,1995 被引 1    
2.  吴宏安. 西安地区城镇扩展及其生态环境效应研究. 自然资源学报,2006,21(2):311-318 被引 14    
3.  周红妹. 城市扩展与热岛空间分布变化关系研究——以上海为例. 生态环境,2008,17(1):163-168 被引 22    
4.  Claessens L. Modelling interactions and feedback mechanisms between land use change and landscape processes. Agriculture, Ecosystems and Environment,2009,129(1/2/3):157-170 被引 18    
5.  Veldkamp A. CLUE-CR: an intergrated multi-scale model to simulate land use change scenarios in Costa Rica. Ecological Modelling,1996,91(1/2/3):231-248 被引 48    
6.  Luo Geping. Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang, China. Ecological Complexity,2010,7(2):198-207 被引 20    
7.  Zheng Xinqi. A coupled model for simulating spatio-temporal dynamics of land-use change: A case study in Changqing, Jinan, China. Landscape and Urban Planning,2012,106(1):51-61 被引 10    
8.  李亦秋. 丹江口库区土地利用及其生态系统服务价值情景模拟. 农业工程学报,2011,27(5):329-335 被引 11    
9.  周锐. CLUE-S模型对村镇土地利用变化的模拟与精度评价. 长江流域资源与环境,2012,21(2):174-180 被引 13    
10.  Jantz C A. Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model. Computers, Environment and Urban Systems,2010,34(1):1-16 被引 17    
11.  刘勇. 基于SLEUTH模型的杭州市城市扩展研究. 自然资源学报,2008,23(5):797-807 被引 29    
12.  Pijanowski B C. Using neural networks and GIS to forecast land use changes: a Land Transformation Model. Computers, Environment and Urban Systems,2002,26(6):553-575 被引 47    
13.  Tayyebi A. An urban growth boundary model using neural networks, GIS and radial parameterization: An application to Tehran, Iran. Landscape and Urban Planning,2010,100(1/2):35-44 被引 30    
14.  Al-Ahmadi K. Calibration of a fuzzy cellular automata model of urban dynamics in Saudi Arabia. Ecological Complexity,2009,6(2):80-101 被引 8    
15.  Guan D J. Modeling urban land use change by the integration of cellular automaton and Markov model. Ecological Modelling,2011,222(20/21/22):3761-3772 被引 30    
16.  何丹. 基于Logistic-CA-Markov的土地利用景观格局变化———以京津冀都市圈为例. 地理科学,2011,31(8):903-910 被引 57    
17.  郑青华. 基于CA_Markov模型的伊犁河三角洲景观格局预测. 应用生态学报,2010,21(4):873-882 被引 27    
18.  孙丹峰. 基于动态统计规则和景观格局特征的土地利用覆被空间模拟预测. 农业工程学报,2005,21(3):121-125 被引 11    
19.  崔晓伟. 三峡库区开县蓄水前后景观格局变化特征. 农业工程学报,2012,28(4):227-234 被引 12    
20.  冯异星. 近50a土地利用变化对干旱区典型流域景观格局的影响----以新疆玛纳斯河流域为例. 生态学报,2010,30(16):4295-4305 被引 73    
引证文献 51

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