首页> 外文会议>International Conference on Geoinformatics;Geoinformatics 2012 >Aquatic plant functional type spectral characteristics analysis and comparison using multi-temporal and multi-source remote sensing over the Poyang Lake wetland,China
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Aquatic plant functional type spectral characteristics analysis and comparison using multi-temporal and multi-source remote sensing over the Poyang Lake wetland,China

机译:temp阳湖湿地水生植物功能型光谱特征的多时空多源遥感分析与比较

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In systems with strong seasonal difference in vegetation structure and appearance, multi-temporal imagery can be particularly useful for community-and species-level discrimination. And, since the availability of past data for one source of time series images may be limited, so we need to develop multi-temporal and multi-source method for wetland ecosystem monitoring. To perform this type of analysis, the image spectral characteristics comparison between different aquatic macrophytes and different sensors should be studied firstly. We used TM images, Beijing-1 images and HJ-1 images for this analysis and based on the determination of aquatic plant functional types (PFTs). The objectives of this study were: ⑴ single-sensor single-date aquatic PFT analysis; ⑵ multi-source single-date diagnostic spectral characteristics analysis and comparison for different aquatic PFTs; ⑶ multi-source multitemporal diagnostic spectral characteristics analysis for different aquatic PFTs. From this analysis we found that: ⑴ For the single-date TM data, the diagnostic spectral band and indexes are Band 2, 4, 5, NDVI, and MNDWI; the best temporal for discriminating different Nonpersistent Emergent Wetland PFTs are in low water level periods, and water infilling and subsiding periods for seasonal submerged and floating aquatic macrophyte. Multispectral Decision Tree classification method lead the more good results for most of PFTs; ⑵ the same type of aquatic PFTs have similar and comparable reflectance characteristics between multi-sensor optical data which could satisfy the time series analysis by compensating more available past images; ⑶ phenological curves and relative canopy moisture curves extracted from time series remote sensing images provide important information for distinguish different PFTs.
机译:在植被结构和外观具有强烈的季节性差异的系统中,多时相影像对于社区和物种一级的判别尤其有用。并且,由于过去对于一个时间序列图像源的数据可用性可能受到限制,因此我们需要开发用于湿地生态系统监测的多时间和多源方法。要进行此类分析,首先应研究不同水生植物和不同传感器之间的图像光谱特征比较。我们使用TM图像,Beijing-1图像和HJ-1图像进行此分析,并基于水生植物功能类型(PFT)的确定。本研究的目标是:⑴单传感器单日期水生PFT分析; for针对不同水生PFT的多源单日诊断光谱特性分析和比较; ⑶针对不同水生PFT的多源多时相诊断光谱特征分析。通过此分析,我们发现:⑴对于单日TM数据,诊断光谱带和索引为2、4、5,NDVI和MNDWI波段;区分不同的非持久性紧急湿地PFT的最佳时间是在低水位时期,以及季节性淹没和漂浮水生植物的充水和沉降期。多光谱决策树分类方法为大多数PFT带来了更好的结果。 ⑵相同类型的水生PFT在多传感器光学数据之间具有相似和可比的反射特性,通过补偿更多可用的过去图像可以满足时间序列分析; ⑶从时间序列遥感影像中提取的物候曲线和相对冠层湿度曲线为区分不同的PFT提供了重要的信息。

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