盐城湿地类型演化预测分析

doi:10.11821/yj2009060027

地理研究 ›› 2009, Vol. 28 ›› Issue (6): 1713-1721.doi: 10.11821/yj2009060027

盐城湿地类型演化预测分析

张怀清¹, 唐晓旭², 刘锐³, 周金星⁴, 凌成星¹

1. 中国林业科学研究院资源信息研究所,北京 100091;
2. 北京市测绘设计研究院,北京 100038;
3. 北京师范大学地理学与遥感科学学院,北京100875;
4. 中国林业科学研究院林业研究所,北京 100091

收稿日期:2009-02-18 修回日期:2009-06-15 出版日期:2009-11-25 发布日期:2009-11-25
作者简介:张怀清(1973-),男,湖南宁乡人,博士,副研究员。主要从事林业可视化模拟技术与湿地资源监测技术研究。E-mail:zhang@caf.ac.cn
基金资助:
国家"十一五"科技支撑项目资助(2006BAD23B03,2006BAC08B03)

Study on prediction models of wetland types in Yancheng

ZHANG Huai-qing¹, TANG Xiao-xu², LIU Rui³, ZHOU Jin-xing⁴, LING Cheng-xing¹

1. Research Institute of Forestry Resource Information Techniques, Chinese Academy of Forestry (CAF), Beijing 100091, China;
2. Beijing Institute of Surveying and Mapping, Beijing 100038, China;
3. School of Geography, Beijing Normal University, Beijing 100875, China;
4. Research Institute of Forestry, CAF, Beijing 100091, China

Received:2009-02-18 Revised:2009-06-15 Online:2009-11-25 Published:2009-11-25
Supported by:
国家"十一五"科技支撑项目资助(2006BAD23B03,2006BAC08B03)

摘要/Abstract

摘要：

以盐城湿地主要分布的三个县市:射阳、大丰和东台作为研究区,通过1988~2006年每隔6年的4期TM遥感影像,开展盐城湿地类型的动态变化分析,根据遥感影像解译结果,利用基于可拓物元模型的湿地演化元胞自动机(CA)模型和马尔可夫模型从空间和数据上进行湿地类型的变化预测。分析结果表明:(1)将基于可拓物元CA模型模拟预测结果与遥感分类结果进行逐个像元比较,计算得出相似程度达到 70%,因此基于可拓物元CA预测模型引入到湿地类型演化预测中是可行的。(2)基于可拓物元CA模型与马尔科夫模型的数值预测结果具有较高的相似度,表明研究区在2012年养殖场将成为盐城湿地最主要的湿地利用类型,预测结果分别达到了750.06km²和721.96km²,同时,耕地、居民用地、养殖场、米草面积总体呈增长趋势,滩地、芦苇、碱蓬和盐田呈剧烈减少趋势,米草逐渐占据优势物种,大面积的滩涂开发是盐城湿地类型变化最主要的原因。

关键词: 遥感监测, 湿地类型, 预测模型, 盐城

Abstract:

This paper takes three main wetland distributing counties of Dongtai, Dafeng and Sheyang of Yancheng as study areas. With the processing of four-period (every six years from 1988 to 2006) remote sensing (RS) images, a dynamic change analysis of the Yancheng wetland types was illuminated at first. Then, according to the results of the RS images interpretation, the change prediction of the wetland types was analyzed by using cellular automata (CA) model based on extension matter-element model and Markov model. The results are shown as follows: (1) It is a feasible method in wetland types prediction according to the comparability (70%) after the comparison between the results calculated by CA model based on extension matter-element model and the remote sensing classification. (2) The results of CA model based on extension matter-element model is greatly consistent with the results of the results of Markov model, that is, the aquaculture farm is the main wetland type covering areas of 750.06 km² and 740.20 km² in 2006, respectively. Generally, the area of cropland, residential land, aquaculture farm, Spartina patens and seepweed has an increasing tendency, while the area of mudflat, reed and brine pan tends to decrease sharply. Spartina patens will become the dominant species gradually due to its evolution trend. The most important reason for these changes is the current policy of large-scale coastal exploitation.

Key words: remote sensing monitoring, wetland types, prediction model, Yancheng

张怀清, 唐晓旭, 刘锐, 周金星, 凌成星. 盐城湿地类型演化预测分析[J]. 地理研究, 2009, 28(6): 1713-1721.

ZHANG Huai-qing, TANG Xiao-xu, LIU Rui, ZHOU Jin-xing, LING Cheng-xing. Study on prediction models of wetland types in Yancheng[J]. GEOGRAPHICAL RESEARCH, 2009, 28(6): 1713-1721.

参考文献

[1] 杨桂山,施雅风.江苏滨海潮滩湿地对潮位变化的生态响应.地理学报,2002,57(3):325~332.

[2] 杨桂山,施雅风,季子修.江苏淤泥质潮滩对海平面变化的形态响应.地理学报,2002,57(1):76~84.

[3] 胡茂桂,傅晓阳,张树清,等.基于元胞自动机的莫莫格湿地土地覆被预测模拟.资源科学,2007,29(2):142~148.

[4] 陈建平,丁文火,王公文,等.基于GIS和元胞自动机的荒漠化演化预测模型.遥感学报,2004,8(3):254~260.

[5] 黎夏,叶嘉安.基于神经网络的元胞自动机及模拟复杂土地利用系统.地理研究,2005,24(1):19~27.

[6] 周成虎,孙战利,谢一春.地理元胞自动机研究.北京:科学出版社,1999.

[7] Simth,Luijten J C.A systematic method for generating land use patterns using tochastic rules and basic landscape characteristics:Results for a Cololombian hillside Watershod.Agriculture Ecosystems& Environment,1991,95:427~441.

[8] Neubert L, Santen L, Schadschneider A, et al, Single-vehicle data of highway traffic: A statistical analysis.Phys. Rev., 1999, (E60): 6480~6490.

[9] 欧维新,杨桂山,李恒鹏.苏北盐城海岸带景观格局时空变化及驱动力分析.地理科学,2004,24(5):610~615.

[10] Stevensa D,S D,Rothleyb,K.iCity:A GIS-CA modeling tool for urban planning and decision making.Environmental Modeling & Software,2006,2(6):761~773.

[11] Batty M,Xie Y,Sun Z.Modeling urban dynamics through GIS-based cellular automata.Computers,Environment,Urban Systems,1999,23(3):205~223.

[12] Batty M,Xie Y.Modeling inside GIS:Part2:Selecting and calibrating urban models using ARC/INFO.International Journal of Geographical Information Systems,1994,8(3):451~470.

[13] Batty M,Xie Y.Modeling inside GIS:Part1:Model structures,exploratory spatial analysis.International Journal of Geographic Information Systems,1994,8(3): 291~307.

[14] Couclelis,From H.Cellular automata to urban models:New principles for model development and implementation.Environment and Planning B:Planning and Design,1997.24(2):165~174.

[15] 蔡文.物元模型及其应用.北京:北京科技文献出版社,1994.

[16] 蔡文,杨春林,林伟初.可拓工程方法.北京:科学出版社,1997. 戴晓兰,季奎,吕方,等.基于物元模型的城市生态健康评价.云南地理环境研究,2007,19(2):58~63.

[17] 高卫东,张海荣,程金平.基于物元可拓模型的地下水质量评价研究.环境科学与管理,2007,32(6):169~172.

[18] 隋海荣,房栓社,马福雷.建设项目方案评价的模糊物元模型及其应用.基建优化,2006,27(4):54~56.

[19] 鲍超,方创琳.基于物元模型的西北干旱区城市环境质量综合评价——以河西走廊的张掖市为例.干旱区地理,2005,28(5):659~664.

[20] 柳金甫,李学伟.应用随机过程.北京:中国铁道出版社,2000.80~121.

[21] 彭月,魏虹,朱韦,等.广东鼎湖山自然保护区森林景观的动态模拟研究.广西植物,2007,2(72):186~190.

[22] 李祥,王心源,张广胜,等.基于马尔科夫模型的芜湖市景观格局演变研究.资源开发与市场,2006,22(1):20~23.

[23] 杨国清,吴志峰,祝国瑞.广州地区土地利用景观格局变化研究.农业工程学报,2006,22(5):218~221.

[24] 彭月,魏虹 ,朱韦.基于马尔科夫模型的土地景观动态模拟预测研究——以重庆永川市为例.安徽农业科学.2006,34(23):6172~6173.

[25] 郭笃发.利用马尔科夫过程预测黄河三角洲新生湿地土地利用／覆被格局的变化.土壤,2006,38(1):42~47.

[26] 杨国清,吴志峰,祝国瑞.广州地区土地利用景观格局变化研究.农业工程学报,2006,22(5):218~221.

[27] Zhou Z.Landscape changes in a rural area in China.Landscape and Urban Planning, 2000,47(1):33~38.

[28] 王尚武.正确认识预测误差.统计与决策,2002,(12):71~72.

[29] Luijten J C.A systematic method for generating land use Patterns using tochastic rules and basic landscape characteristics:results for a Cololombian hillside Watershod.Agriculture Ecosystems& Environment,2003,95:427~441.

[30] Yong,Batty M,Xie Y,Sun Z.Modeling urban dynamics through GIS-based cellular automata.Computers,Environment,Urban Systems,1990,23(3):205~223.

[31] Tony Prato,Donald Hey.Economic analysis of wetland restoration along the Illinois river.American Water Resources Association,2006,42(1):125~131.

盐城湿地类型演化预测分析

Study on prediction models of wetland types in Yancheng

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