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Multitemporal spectroradiometry-guided object-oriented classification of salt marsh vegetation

机译:盐沼植被多时相光谱法指导的面向对象分类

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This study addresses the use of multitemporal field spectral data, satellite imagery, and LiDAR top of canopy data to classify and map common salt marsh plant communities. Visible to near-infrared (VNIR) reflectance spectra were measured in the field to assess the phenological variability of the dominant species - Spartina patens, Phragmites australis and Typha spp. The field spectra and single date LiDAR canopy height data were used to define an object-oriented classification methodology for the plant communities in multitemporal QuickBird imagery. The classification was validated using an extensive field inventory of marsh species. Overall classification accuracies were 97% for Phragmites, 63% for Typha spp. and 80% for S. patens meadows. Using a fuzzy assessment analysis, these accuracies were 97%, 76%, and 92%, respectively, for the three major species.
机译:这项研究致力于利用多时相野外光谱数据,卫星图像和冠层数据的LiDAR顶部对常见的盐沼植物群落进行分类和绘制地图。在野外测量了可见到近红外(VNIR)反射光谱,以评估优势种-斯巴特那(Spartina patens),芦苇(Phragmites australis)和香蒲(Typha spp)的物候变化。现场光谱和单日LiDAR冠层高度数据用于为多时相QuickBird影像中的植物群落定义面向对象的分类方法。使用大量的沼泽物种实地清单对分类进行了验证。芦苇的总体分类准确度为97%,香蒲属的总体分类准确度为63%。 S. patens草甸为80%。使用模糊评估分析,三个主要物种的这些准确度分别为97%,76%和92%。

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