Vegetation survey in the former brown coal mining area of eastern Germany by integrating remote sensing and ground‐based methods
Vegetation survey in the former brown coal mining area of eastern Germany by integrating remote sensing and ground‐based methods
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DOI：
10.2307/1478953
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发表时间：
1998-12
影响因子：
2.8
通讯作者：
B. Felinks;Monika Pilarski;G. Wiegleb
中科院分区：
文献类型：
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作者：
B. Felinks;Monika Pilarski;G. Wiegleb
在德国东部的前褐煤矿区，现在被规划为自然保护区，植被空间分布分析被认为是景观规划的重要工具。因此，通过卫星图像（Landsat-TM）、机载图像（CASI）和地面方法，特别是栖息地测绘和植被采样，进行了全面的植被调查。就分辨率尺度而言，四种方法的分类结果在一定程度上具有可比性。结果的差异可以归因于以下事实：低分辨率方法会产生离散的多边形阵列，而高分辨率方法则描绘具有底层连续变化梯度的马赛克结构。如果知道遥感分类的生物学意义，从单一植被格局到景观尺度的转变将是可能的。卫星图像和机载图像均不限于测绘目的，还可以用于植被分类本身。
In the former brown coal mining area of eastern Germany, now scheduled as a nature conservation area, an analysis of the spatial distribution of vegetation was consid- ered as an important tool in landscape planning. Therefore a comprehensive vegetation survey by means of satellite imagery (Landsat-TM), airborne imagery (CASI), and ground-based methods, notably habitat mapping and vegetation sampling was carried out. With respect to the scales of resolution the classifi- cation results of the four methods are, to a certain degree, comparable. Differences in the outcome can be ascribed to the fact that methods of low resolution result in a discrete array of polygons whereas methods of high resolution depict a mosaic structure with an underlying, continuously changing gradient. Provided that the biological meaning of the remote sensing classification is known, a shift from single vegetation patterns to the landscape scale will be possible. Neither satellite nor air- borne imagery is restricted to the purpose of mapping but may also serve for vegetation classification itself.