摘要
利用遥感、地理信息系统和神经网络的方法，对沿海城市广州市番禺的湿地生态环境质量进行研究，其结果表明：广州番禺建筑用地面积从1979年的2．43％增长到1990年的10．03％，2000年的29．94％，2006年的37．82％；水田的面积从1979年的42．92％增长到1990年的49．19％减少到2000年的22．70％，2006年的17．97％，由水田为模地变成了建筑用地为模地。利用信息熵的方法得到各种湿地类型的生态效应值：1979年各种湿类型的生态效应值都小于2．2，属于生态环境质量相对良好区，从1990年到2000年的湿地生态环境质量发生了分异，其生态效应值在2．2—3之间是相对较好区，在3—3．8之间是相对一般区，大于3．8是相对较差区；在2006年，模地由水田变为建筑用地后，湿地生态效应值都小于2．2。利用BP神经网络的方法预测2011年和2016年的各种湿地类型的生态效应值，只有近海岸湿地类型的生态效应值在3—3．8之间，其余的都小于2．2。
Evaluation of eco-environment quality based on remote sensing （RS）, geographical information system （GIS） and neural network were carried out on Panyu district of Guangzhou. The results show that the background of ecological environment has changed radically ： from 1979 to 2006, the proportion of building area were increased from 2. 43% to 29. 94% in 2004 and it reached 37. 82% in 2006; the proportion of paddy field area were increased from 42. 92% to 49. 19% in 1990, but it decreased to 22. 70% in 2000 and it reached 17.97% in 2006; so the background in Panyu changed from paddy field area in 1979 to building area in 2006. The qualities of the local wetland ecological environment were declining from 1979 to 2000. The ecological environment qualities were good and the ecological effects is less than 2. 2 in 1997. During 1990 to 2000, there are some changes in the ecological environment qualities. The ecological environment qualities of some of the wetland were good and the ecological effect was 2. 2 - 3, but the ecological effect in bad environment was over 3.8. After changing from wetland background to building background in 2006, the relative quality of this area got better and the ecological effect was less than 2. 2. According to the prediction values of the ecological effect classification of wetland from 2011 to 2016, the qualities of coastal wetland in Panyu will be attributed to the normal level, the ecological effects will be 3.2.
出处
《中山大学学报（自然科学版）》
CAS
CSCD
北大核心
2008年第5期104-109,共6页
Acta Scientiarum Naturalium Universitatis Sunyatseni
基金
广州市科技计划项目资助(2005Z3-D0551)
关键词
遥感
生态环境质量
景观指数
神经网络
广州番禺区
remote sensing
eco-environmental quality
landscape index
neural network
Panyu and Nansha districts of Guangzhou
