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Mountain vegetation mapping in Dovre area, Norway, using Landsat TM data and GIS

机译:使用Landsat TM数据和GIS在挪威多夫尔地区的山地植被图

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摘要

Vegetation mapping by use of satellite data are often divided into two main operations, the pre- and post-classification processes. Experience from producing vegetation maps based on spectral-only classifications, has shown that misclassifications occurs. The aim of the post-classification process is to improve the pre-classified product by use of ancillary data. The mountain areas of Norway are characterized by complex topography. Vegetation maps are though difficult to produce for these areas. In this study two Landsat 5/TM image from 1986 and 1998, covering parts of the Dovre mountain massif in Norway, are classified using unsupervised classification methods. The spectrally classified product is thereafter corrected using several ancillary data layers. Based on the ancillary data the delineation of forest vegetation and the heather vegetation above the woodland limit is more precisely defined. Bogs and mires are easily differentiated from snow-bed communities. The grass- and herb-rich communities in the mountain areas are spectrally much similar to agricultural areas in the lowland; even the floristical composition and content are totally different. By use of digital elevation models the alpine meadows and cultivated land in the lowland are separated into different classes by the use of an altitude threshold. The cost of, and types of corrections we can do in the post-classification process, largely depends on what additional information is available and the quality of this information.
机译:利用卫星数据进行的植被测绘通常分为两个主要操作,即分类前和分类后的过程。根据仅光谱分类生成植被图的经验表明,存在分类错误的情况。后分类过程的目的是通过使用辅助数据来改进预分类产品。挪威的山区地势复杂。尽管在这些地区很难制作植被图。在这项研究中,使用无监督分类方法对1986年和1998年的两幅Landsat 5 / TM影像进行了分类,覆盖了挪威多夫勒山区的部分地区。此后,使用几个辅助数据层对光谱分类的产品进行校正。根据辅助数据,可以更精确地定义森林植被和林地以上的希瑟植被的轮廓。沼泽和泥潭很容易与雪床社区区分开。山区的草和草药丰富的社区在光谱上与低地的农业区非常相似;即使是植物的成分和含量也完全不同。通过使用数字高程模型,通过使用高度阈值将高地草甸和低地的耕地分为不同的类别。我们在后分类过程中可以进行的成本和校正类型在很大程度上取决于可提供哪些其他信息以及此信息的质量。

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