东江流域景观格局演变分析及变化预测
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摘要
以东江流域土地利用解译结果为基础,采用转移矩阵、移动窗口法和景观格局指数对1990—2016年对东江流域的景观格局时空变化进行分析,并结合地形因子、交通通达度因子和限制转化因子采用FLUS(Future Land Use Simulation)模型对流域未来景观格局进行预测。结果表明:(1)自1990年以来,研究区的7种土地利用类型皆发生了变化,其中建设用地由于林地和耕地的大量转入增加最明显。(2)1990—2016年,流域景观破碎化呈现以河道为中心向东西两侧减小的趋势,景观多样性呈现流域上游小,下游大的趋势,且高值区在经济较发达的城镇地区。园地的景观破碎程度最高、林地的优势度减弱,城镇建设用地的集聚度增加。(3)2016—2042年,流域各用地类型变化率不大,景观破碎化和多样性程度虽有增加但增长速度相对放缓。
Land use/cover change is one of the most direct manifestations of interaction between human activity and the natural environment, which reflects the close connection between the land use patterns and different times, locations, and human activities. In order to quantify land use/cover change, changes in the landscape pattern are the most intuitionistic demonstration. In addition, land use prediction is also one of the hotspots in this field. Frequently used models of land use prediction include the conversion of land use and its effects(CLUE) model and cellular automation. However, most models only train and estimate the transition probability of land use types, while barely expressing the competition and reciprocity of those because they ignore the connections among land use types. The future land use simulation(FLUS) model is derived and evolved from the Geographical Simulation and Optimization System. It is based on cellular automation and a self-adapting inertia and competition mechanism. The FLUS model has solved complicated issues in the transition rule of cellular automation, determined the parameters, and produced a simulation of land use under the influence of human activity and natural conditions. At present, it has been applied in many cities and regions successfully. The Dongjiang River Basin, standing on the border of Guangdong, Hong Kong, and Macau, is one of three tributaries of the Zhujiang River. It enjoys abundant natural and human resources and embraces multiple landscape patterns. In recent years, the increasing local population and the comprehensive development of social economy has resulted in a rapid explosion of land use for urban construction. The extensive exploitation of primitive landscape and intervention of artificial activity on landscape is increasing. This thesis analyzes the characteristics of land use and landscape patterns in the Dongjiang River Basin in recent decades. In addition, we use the FLUS model and socioeconomic data to predict future land use patterns in this basin, to provide the scientific basis for the harmonious development of the regional economy and ecological environment. The result shows that(1) since 1990, seven types of land use in the Dongjiang River Basin have changed significantly. Among them, the increase in construction land use was the highest because of the large amount of forest and farm land being converted.(2) In recent decades, the degree of landscape fragmentation has increased while landscape space connectivity has weakened, and the variation range is relatively large in the years 2000—2009. On the whole, the degree of landscape fragmentation degree in orchards was the highest, the dominance of forest land has been subdued, and the concentration of urban construction land has increased.(3) From 2016 to 2042, the rate of change in land use in Dongjiang River Basin is relatively small. Although the degree of landscape fragmentation and diversity is still increasing, the rate of increase has slowed down.
Land use/cover change is one of the most direct manifestations of interaction between human activity and the natural environment, which reflects the close connection between the land use patterns and different times, locations, and human activities. In order to quantify land use/cover change, changes in the landscape pattern are the most intuitionistic demonstration. In addition, land use prediction is also one of the hotspots in this field. Frequently used models of land use prediction include the conversion of land use and its effects(CLUE) model and cellular automation. However, most models only train and estimate the transition probability of land use types, while barely expressing the competition and reciprocity of those because they ignore the connections among land use types. The future land use simulation(FLUS) model is derived and evolved from the Geographical Simulation and Optimization System. It is based on cellular automation and a self-adapting inertia and competition mechanism. The FLUS model has solved complicated issues in the transition rule of cellular automation, determined the parameters, and produced a simulation of land use under the influence of human activity and natural conditions. At present, it has been applied in many cities and regions successfully. The Dongjiang River Basin, standing on the border of Guangdong, Hong Kong, and Macau, is one of three tributaries of the Zhujiang River. It enjoys abundant natural and human resources and embraces multiple landscape patterns. In recent years, the increasing local population and the comprehensive development of social economy has resulted in a rapid explosion of land use for urban construction. The extensive exploitation of primitive landscape and intervention of artificial activity on landscape is increasing. This thesis analyzes the characteristics of land use and landscape patterns in the Dongjiang River Basin in recent decades. In addition, we use the FLUS model and socioeconomic data to predict future land use patterns in this basin, to provide the scientific basis for the harmonious development of the regional economy and ecological environment. The result shows that(1) since 1990, seven types of land use in the Dongjiang River Basin have changed significantly. Among them, the increase in construction land use was the highest because of the large amount of forest and farm land being converted.(2) In recent decades, the degree of landscape fragmentation has increased while landscape space connectivity has weakened, and the variation range is relatively large in the years 2000—2009. On the whole, the degree of landscape fragmentation degree in orchards was the highest, the dominance of forest land has been subdued, and the concentration of urban construction land has increased.(3) From 2016 to 2042, the rate of change in land use in Dongjiang River Basin is relatively small. Although the degree of landscape fragmentation and diversity is still increasing, the rate of increase has slowed down.
引文
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[3] 彭建,党威雄,刘焱序,宗敏丽,胡晓旭.景观生态风险评价研究进展与展望.地理学报,2015,70(4):664- 677.
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[5] 董玉红,刘世梁,安南南,尹艺洁,王军,邱扬.基于景观指数和空间自相关的吉林大安市景观格局动态研究.自然资源学报,2015,30(11):1860- 1871.
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[8] 潘影,刘云慧,王静,宇振荣.基于CLUE-S模型的密云县面源污染控制景观安全格局分析.生态学报,2011,31(2):529- 537.
[9] 詹云军,朱捷缘,严岩.基于元胞自动机的城市空间动态模拟.生态学报,2017,37(14):4864- 4872.
[10] 刘世梁,安南南,尹艺洁,成方妍,董世魁.广西滨海区域景观格局分析及土地利用变化预测.生态学报,2017,37(18):5915- 5923.
[11] Li X,Chen G Z,Liu X P,Liang X,Wang S J,Chen Y M,Pei F S,Xu X C.A new global land-use and land-cover change product at a 1-km resolution for 2010 to 2100 based on human-environment interactions.Annals of the American Association of Geographers,2017,107(5):1040- 1059.
[12] 刘小平,黎夏,艾彬,陶海燕,伍少坤,刘涛.基于多智能体的土地利用模拟与规划模型.地理学报,2006,61(10):1101- 1112.
[13] 朱寿红,舒帮荣,马晓冬,梁迅,姚青.基于“反规划”理念及FLUS模型的城镇用地增长边界划定研究——以徐州市贾汪区为例.地理与地理信息科学,2017,33(5):80- 86.
[14] 陈逸敏,黎夏,刘小平,李少英.基于耦合地理模拟优化系统GeoSOS的农田保护区预警.地理学报,2010,65(9):1137- 1145.
[15] 吕乐婷,彭秋志,廖剑宇,江源,康慕谊.近50年东江流域降雨径流变化趋势研究.资源科学,2013,35(3):514- 520.
[16] Janssen L L F,van der Wel F J M.Accuracy assessment of satellite derived land cover data:a review.Photogrammetric Engineering and Remote Sensing,1994,60(4):419- 426.
[17] 赵英时.遥感应用分析原理与方法(第二版).北京:科学出版社,2013.
[18] 白根川,夏建国,王昌全,陈文宽,杨娟.基于地类空间转化趋势模型的眉山市东坡区土地利用转化分析.资源科学,2009,31(10):1793- 1799.
[19] 张宏锋,袁素芬.东江流域森林水源涵养功能空间格局评价.生态学报,2016,36(24):8120- 8127.
[20] 王兆印,程东升,段学花,李行伟.东江河流生态评价及其修复方略.水利学报,2007,38(10):1228- 1235.
[21] 任斐鹏,江源,熊兴,董满宇,王博.东江流域近20年土地利用变化的时空差异特征分析.资源科学,2011,33(1):143- 152.
[22] 李栋科,丁圣彦,梁国付,赵清贺,汤茜,孔令华.基于移动窗口法的豫西山地丘陵地区景观异质性分析.生态学报,2014,34(12):3414- 3424.
[23] 张玲玲,赵永华,殷莎,房舒,刘晓静,蒲苗苗.基于移动窗口法的岷江干旱河谷景观格局梯度分析.生态学报,2014,34(12):3276- 3284.
[24] 傅伯杰.景观生态学原理及应用(第二版).北京:科学出版社,2011.
[25] Liu X P,Liang X,Li X,Xu X C,Ou J P,Chen Y M,Li S Y,Wang S J,Pei F S.A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects.Landscape and Urban Planning,2017,168:94- 116.
[26] 黎夏,李丹,刘小平.地理模拟优化系统(GeoSOS)及其在地理国情分析中的应用.测绘学报,2017,46(10):1598- 1608.
[27] 龚健,陈耀霖,张志.基于多分类Logistic回归模型的区域土地利用变化及驱动因素研究.湖北农业科学,2016,55(17):4545- 4550.
[28] 舒帮荣,李永乐,曲艺,梅艳,雍新琴.不同经济发展阶段城镇用地扩张特征及其动力——以太仓市为例.经济地理,2013,33(7):155- 162.
[29] 卞子浩,马小雪,龚来存,赵静,曾春芬,王腊春.不同非空间模拟方法下CLUE-S模型土地利用预测——以秦淮河流域为例.地理科学,2017,37(2):252- 258.
[2] 刘纪远,匡文慧,张增祥,徐新良,秦元伟,宁佳,周万村,张树文,李仁东.20世纪80年代以来中国土地利用变化的基本特征与空间格局.地理学报:英文版,2014,24(2):195- 210.
[3] 彭建,党威雄,刘焱序,宗敏丽,胡晓旭.景观生态风险评价研究进展与展望.地理学报,2015,70(4):664- 677.
[4] 陈利顶,李秀珍,傅伯杰,肖笃宁,赵文武.中国景观生态学发展历程与未来研究重点.生态学报,2014,34(12):3129- 3141.
[5] 董玉红,刘世梁,安南南,尹艺洁,王军,邱扬.基于景观指数和空间自相关的吉林大安市景观格局动态研究.自然资源学报,2015,30(11):1860- 1871.
[6] Whittaker R H.Vegetation of the Siskiyou Mountains,Oregon and California.Ecological Monographs,1960,30(4):407- 407.
[7] Jiang W G,Deng Y,Tang Z H,Lei X,Chen Z.Modelling the potential impacts of urban ecosystem changes on carbon storage under different scenarios by linking the CLUE-S and the InVEST models.Ecological Modelling,2017,345:30- 40.
[8] 潘影,刘云慧,王静,宇振荣.基于CLUE-S模型的密云县面源污染控制景观安全格局分析.生态学报,2011,31(2):529- 537.
[9] 詹云军,朱捷缘,严岩.基于元胞自动机的城市空间动态模拟.生态学报,2017,37(14):4864- 4872.
[10] 刘世梁,安南南,尹艺洁,成方妍,董世魁.广西滨海区域景观格局分析及土地利用变化预测.生态学报,2017,37(18):5915- 5923.
[11] Li X,Chen G Z,Liu X P,Liang X,Wang S J,Chen Y M,Pei F S,Xu X C.A new global land-use and land-cover change product at a 1-km resolution for 2010 to 2100 based on human-environment interactions.Annals of the American Association of Geographers,2017,107(5):1040- 1059.
[12] 刘小平,黎夏,艾彬,陶海燕,伍少坤,刘涛.基于多智能体的土地利用模拟与规划模型.地理学报,2006,61(10):1101- 1112.
[13] 朱寿红,舒帮荣,马晓冬,梁迅,姚青.基于“反规划”理念及FLUS模型的城镇用地增长边界划定研究——以徐州市贾汪区为例.地理与地理信息科学,2017,33(5):80- 86.
[14] 陈逸敏,黎夏,刘小平,李少英.基于耦合地理模拟优化系统GeoSOS的农田保护区预警.地理学报,2010,65(9):1137- 1145.
[15] 吕乐婷,彭秋志,廖剑宇,江源,康慕谊.近50年东江流域降雨径流变化趋势研究.资源科学,2013,35(3):514- 520.
[16] Janssen L L F,van der Wel F J M.Accuracy assessment of satellite derived land cover data:a review.Photogrammetric Engineering and Remote Sensing,1994,60(4):419- 426.
[17] 赵英时.遥感应用分析原理与方法(第二版).北京:科学出版社,2013.
[18] 白根川,夏建国,王昌全,陈文宽,杨娟.基于地类空间转化趋势模型的眉山市东坡区土地利用转化分析.资源科学,2009,31(10):1793- 1799.
[19] 张宏锋,袁素芬.东江流域森林水源涵养功能空间格局评价.生态学报,2016,36(24):8120- 8127.
[20] 王兆印,程东升,段学花,李行伟.东江河流生态评价及其修复方略.水利学报,2007,38(10):1228- 1235.
[21] 任斐鹏,江源,熊兴,董满宇,王博.东江流域近20年土地利用变化的时空差异特征分析.资源科学,2011,33(1):143- 152.
[22] 李栋科,丁圣彦,梁国付,赵清贺,汤茜,孔令华.基于移动窗口法的豫西山地丘陵地区景观异质性分析.生态学报,2014,34(12):3414- 3424.
[23] 张玲玲,赵永华,殷莎,房舒,刘晓静,蒲苗苗.基于移动窗口法的岷江干旱河谷景观格局梯度分析.生态学报,2014,34(12):3276- 3284.
[24] 傅伯杰.景观生态学原理及应用(第二版).北京:科学出版社,2011.
[25] Liu X P,Liang X,Li X,Xu X C,Ou J P,Chen Y M,Li S Y,Wang S J,Pei F S.A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects.Landscape and Urban Planning,2017,168:94- 116.
[26] 黎夏,李丹,刘小平.地理模拟优化系统(GeoSOS)及其在地理国情分析中的应用.测绘学报,2017,46(10):1598- 1608.
[27] 龚健,陈耀霖,张志.基于多分类Logistic回归模型的区域土地利用变化及驱动因素研究.湖北农业科学,2016,55(17):4545- 4550.
[28] 舒帮荣,李永乐,曲艺,梅艳,雍新琴.不同经济发展阶段城镇用地扩张特征及其动力——以太仓市为例.经济地理,2013,33(7):155- 162.
[29] 卞子浩,马小雪,龚来存,赵静,曾春芬,王腊春.不同非空间模拟方法下CLUE-S模型土地利用预测——以秦淮河流域为例.地理科学,2017,37(2):252- 258.
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