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首页> 外文期刊>Geocarto international >Combined object-based classification and manual interpretation-synergies for a quantitative assessment of parcels and biotopes
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Combined object-based classification and manual interpretation-synergies for a quantitative assessment of parcels and biotopes

机译:结合基于对象的分类和手动解释协同作用,对包裹和生物群落进行定量评估

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摘要

Recent technical advances in remote sensing data capture and spatial resolution lead to a widening gap between increasing data availability on the one hand and insufficient methodology for semi-automated image data processing and interpretation on the other hand. At the interface of GIS and remote sensing, object-based image analysis methodologies are one possible approach to close this gap. With this, methods from either side are integrated to use both the capabilities of information extraction from image data and the power to perform spatial analysis on derived polygon data. However, dealing with image objects from various sources and in different scales implies combining data with inconsistent boundaries. A landscape interpretation support tool (LIST) is introduced which seeks to investigate and quantify spatial relationships among image objects stemming from different sources by using the concept of spatial coincidence. Moreover, considering different categories of object fate, LIST enables a change categorization for each polygon of a time series of classifications. The application of LIST is illustrated by two case-studies, using Landsat TM and ETM as well as CIR aerial photographs: the first showing how the tool is used to perform object quantification and change analysis; the latter demonstrating how superior aggregation capabilities of the human brain can be combined with the fine spatial segmentation and classification. Possible fields of application are identified and limitations of the approach are discussed.
机译:遥感数据捕获和空间分辨率方面的最新技术进步一方面导致数据可用性不断提高,另一方面对半自动图像数据进行处理和解释的方法不足,导致差距不断扩大。在GIS和遥感的接口上,基于对象的图像分析方法是缩小这一差距的一种可能方法。通过这种方式,可以集成来自任一侧的方法,以使用从图像数据中提取信息的功能和对派生的多边形数据执行空间分析的功能。但是,处理来自不同来源和不同比例的图像对象意味着要结合边界不一致的数据。引入了景观解释支持工具(LIST),该工具旨在通过使用空间重合的概念来调查和量化源自不同来源的图像对象之间的空间关系。此外,考虑到对象命运的不同类别,LIST可以对分类时间序列的每个多边形进行更改分类。 LIST的应用通过两个案例研究进行了说明,分别使用Landsat TM和ETM以及CIR航空照片:第一个显示了该工具如何用于执行对象定量和变化分析;后者展示了如何将人类大脑的卓越聚集功能与精细的空间分割和分类结合在一起。确定了可能的应用领域,并讨论了该方法的局限性。

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