基于Sentinel-2和Google Earth Engine的Sierpe河叶绿素a模拟

Gabriela Chaves Brenes, Laura Hernandez Alpizar, I. A. Perez
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引用次数: 0

摘要

利用卫星数据对叶绿素-a进行建模,可以在与其浓度相关的反射率光谱波段之间找到一个最佳拟合函数。Google Earth Engine (GEE)是一个为处理多光谱卫星数据库而设计的平台,用于对地面现象进行临时观测。该工具被用来模拟位于哥斯达黎加tsamriraba Sierpe国家湿地(HNTS)内的Sierpe河的叶绿素-a浓度。为了进行调整,我们使用了一个线性相关函数,其中自变量是Sentinel-2 2A级图像的红色边缘被蓝色光谱带分割。适用于热带条件的适当过滤器。用实验室数据对建模结果进行了验证,生成了43幅河流图像,与一年中不同季节的含量变化趋势和报道的水生植物在受精后生长增加的数据完全吻合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chlorophyll-a Modeling in the Sierpe River with Sentinel-2 and Google Earth Engine
Modeling of chlorophyll-a with satellite data can be achieved by finding a best fit function between spectral bands of reflectance related to its concentration. Google Earth Engine (GEE) is a platform designed for the processing of multispectral satellite databases used for the temporary observation of terrestrial phenomena. This tool was selected to model the chlorophyll-a concentration of the Sierpe River, which is located within the Térraba Sierpe National Wetland (HNTS), Costa Rica. For the adjustment, a linear correlation function where the independent variable is the division of the red edge by the blue spectral band from Sentinel-2 level 2A images, was used. Appropriate filters for tropical conditions were applied. The modeling results were validated with laboratory data and 43 images of the river were generated showing a complete correspondence with the trend of the contents in the different seasons of the year, and the reported data of growth of aquatic plants that increase after fertilization.
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