• 资源利用与管理 •

### 基于BP-CA的海滨湿地利用空间格局优化模拟研究——以大丰海滨湿地为例

1. 1. 南京农业大学土地管理学院, 南京210095;
2. 农村土地资源利用与整治国家地方联合工程研究中心, 南京210095
• 收稿日期:2013-04-11 修回日期:2013-08-20 出版日期:2014-05-20 发布日期:2014-05-20
• 作者简介:欧维新（1974-），男，湖南益阳人，副教授，硕士生导师，中国自然资源学会会员（S300001377M），主要从事湿地资源利用效应与管理研究。E-mail：owx@njau.edu.cn
• 基金资助:
中央高校基本科研业务费自主创新重点研究项目“区域土地利用的生态保护空间网络研究”（KYZ201166）。

### Spatial Pattern Optimization Simulation of Coastal Wetland Use Based on BP Neural Network and Cellular Automata—A Case of Dafeng Coastal Wetland

OU Wei-xin1,2, XIAO Jin-cheng1, LI Wen-hao1

1. 1. College of Land Management, Nanjing Agricultural University, Nanjing 210095, China;
2. National & Local Joint Engineering Research Center for Rural Land Resources Use and Consolidation, Nanjing 210095, China
• Received:2013-04-11 Revised:2013-08-20 Online:2014-05-20 Published:2014-05-20
• About author:10.11849/zrzyxb.2014.05.002

Abstract: In this paper, using BP neural network model and cellular automata (CA) model, 23 spatial variables including natural, economic and social aspects which drive the beach reclamation of coastal vegetation are selected and the spatial pattern simulation model of wetland is established by using MATLAB R2010b software. With remote sensing image of Landsat TM/ ETM+ in Dafeng, Yancheng coastal wetland in three periods of 1988, 2002 and 2009, and the population and economic data of the respective year and based on the simulation thought of optimizing pattern, firstly, we use the wetland function niche model to diagnose historical excessively exploiting areas. Then we train the conversion rules of CA model belonging to the rational development rule. Finally, we simulate the space optimization pattern of Dafeng coastal wetland in 2016. To improve operational efficiency and accuracy of the model, we use two new methods in this study. One method is based on the cover quantity structure in the target year, which limits the proportion of training samples randomly, so as to improve 10000 samples of the effective information amount. The second is through comparing with simulating accuracy under different hiding layer nodes of BP neural network,"23-13-8" and "23-17-8" are determined as the optimal BP structures in two experiments. These two improvements enhance the efficiency of simulation, and the overall accuracy is higher than 93.6%. This research shows that, during these years, the succession among the cover types of Dafeng coastal wetland tends to be frequent, and the speed of reclamational year of natural wetland is obviously faster. At the same time, the development focus is constantly moving eastward, which shows the characteristics of "rolling development" to the sea. Finally, it is recommended to slacken the disorderly development in the surrounding core areas of Jiangsu Yancheng National Nature Reserve and Dafeng Milu National Nature Reserve, and to promote the orderly reclamation of tidal flats near Dafeng Port.

• F301.24