---

作 者 ：韩贵锋,徐建华*

期 刊 ：生态学报 2009年 29卷 4期 页码：1793~1803

关键词：城市植被；植被变化轨迹；城市化；Logistic回归；上海市；

Keywords:urban vegetation, vegetation change trajectory, urbanization, logistic regression, Shanghai City,

摘 要 ：通过TM影像解译，获取上海市1989、1997和2003年共3个时期的植被分布，构造植被变化轨迹，分析轨迹的空间格局；选择距离、人口和景观等3类共12个影响因子，使用Logistic回归进行成因分析。研究结果表明：①14年来，上海市的植被面积呈现持续下降趋势，浦东新区植被减少最多；3个时期均为植被的轨迹占总面积的一半以上，其次是3个时期均为非植被的轨迹占总面积的1/5。早期植被转化为非植被的轨迹主要在城区周围，而近期的转化的轨迹发生在距城区较远的地区；植被与非植被的交替变化轨迹，说明了植被并不是一味地被破坏，而是出现了可逆的变化过程。②Logistic回归分析发现，各因子对植被变化轨迹的影响强度大小依次是，离道路的距离＞离行政中心的距离＞离植被-非植被边界的距离＞离商业中心的距离＝1990年人口密度＞离河流的距离＞离高速公路的距离＞土地利用多样性＞2003年与1990年人口密度差＝离上海市中心的距离。③回归模型的精度是满意的，其中二分类Logistic模型精度高于多分类Logistic模型。总体上，离道路的距离对植被变化影响最明显；变化轨迹表明在部分地区植被出现了植被-非植被反复变化的过程；植被分布不但具有空间依赖性，还具有较强的时间依赖性。

Abstract:Vegetation cover maps of three different years (e.g. 1989, 1997 and 2003) were derived from the Landsat TM images for the city of Shanghai. Eight types of cover change trajectories were then identified from the maps, and their spatial patterns were analyzed from the perspective of landscape ecology. The Logistic regression was used to model the relationship between the vegetation change trajectories and 12 spatial, demographic, and landscape factors. The analytic results led to three most important conclusions. (1) Within the concerned time period, the total vegetated area in Shanghai followed a continual downward trend, particularly in the Pudong new district. Trajectories of remaining vegetated in all three years comprised more than 50% of the total city area, and trajectories of non-vegetated throughout the entire period made up about 20%. Transformation from vegetation to non-vegetation in the first phase (1989 to 1997) took place largely in the surrounding area of the urban districts, whereas the same process in the second phase (1997 to 2003) often occurred farther away from the urbanized area. The fact that some trajectories exhibited an alternation between vegetation and non-vegetation suggested the existence of a process of vegetation restoration instead of permanent destruction or removal of vegetation over time. (2) The results from the Logistic regression model indicated that the distance from roads had the strongest influence on vegetation change trajectories. The rest of the factors can be ranked in descending order by the level of influence as follows: distance from district centers, distance from the patch border between vegetation and non-vegetation (1997), distance from edge between vegetation patch and non-vegetation (1989), distance from business center, population density (1990), distance from river, distance from expressway, land use diversity within 100 meters, population density difference between 2003 and 1990 and distance from the center point of Shanghai. (3) The Logistic regression models produced a satisfactory accuracy; however, the binary logistic model performed better than the multinomial logistic model being used for this study. Overall speaking, the factor of distance from roads seemed to have a strong influence on vegetation changes. The alternating vegetation change trajectories in this study demonstrated a rather complicated changing pattern in parts of Shanghai′s vegetation cover from 1989 to 2003, implying the existence of spatial dependence and temporal dependence in the changing process.

---