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CREATING A SPECTRAL LIBRARY OF COASTAL RESOURCES IN THE PHILIPPINES

机译:在菲律宾建立海岸资源谱库

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Mapping of coastal resources using the remote sensing approach provides information to support the wide-scale monitoring, protection and conservation of these vulnerable resources. Spectral library of coastal resources is an important reference data for its remote sensing applications including high characterization of various features. This paper described the field protocols in collecting spectral signatures of coastal resources (corals, seagrass, seaweeds, mangroves) throughout the Philippines. Field data collection was carried out in various sites of the country. Spectral measurements were conducted using a 10-meter optical fiber probe cable attached to a portable visible-near infrared spectrometer unit which covers approximately 345 - 1036 nanometer wavelength range. Twenty-five in-situ spectral measurements for each sample were calculated and filtered using the Savitzky-Golay algorithm. This method fits a least square polynomial curve in smoothing the spectral graph. Metadata sheet was prepared to indicate the characteristics of the features, the equipment used, the sampling location, the acquisition settings, and the environmental conditions at the time of measurement A standardized methodology of spectral measurements was developed and sample spectra of various coastal resources in the Philippines were also acquired. The creation of spectral library could be used as an aid in creating a detailed and accurate resource maps for the better ecological assessment and has the potential to compare data acquired at different times and locations.
机译:使用遥感方法绘制沿海资源图可提供信息,以支持对这些脆弱资源的大规模监测,保护和养护。沿海资源光谱库是其遥感应用(包括各种特征的高特征化)的重要参考数据。本文描述了在整个菲律宾收集沿海资源(珊瑚,海草,海藻,红树林)的光谱特征的现场协议。在该国的各个地点进行了实地数据收集。使用连接到便携式可见近红外光谱仪单元的10米光纤探头电缆进行光谱测量,该单元覆盖大约345-1036纳米波长范围。使用Savitzky-Golay算法计算并过滤了每个样品的25个原位光谱测量值。该方法在平滑光谱图时拟合最小二乘多项式曲线。准备了元数据表,以指示测量时的特征,所用设备,采样位置,采集设置和环境条件的特​​征。开发了光谱测量的标准化方法,并在其中测量了各种沿海资源的光谱。菲律宾也被收购。光谱库的创建可以用来帮助创建详细而准确的资源图,以进行更好的生态评估,并有可能比较在不同时间和位置获取的数据。

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