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Classification of Australian Waterbodies across a Wide Range of Optical Water Types
Remote Sensing ( IF 4.2 ) Pub Date : 2020-09-16 , DOI: 10.3390/rs12183018
Elizabeth J. Botha , Janet M. Anstee , Stephen Sagar , Eric Lehmann , Thais A. G. Medeiros

Baseline determination and operational continental scale monitoring of water quality are required for reporting on marine and inland water progress to Sustainable Development Goals (SDG). This study aims to improve our knowledge of the optical complexity of Australian waters. A workflow was developed to cluster the modelled spectral response of a range of in situ bio-optical observations collected in Australian coastal and continental waters into distinct optical water types (OWTs). Following clustering and merging, most of the modelled spectra and modelled specific inherent optical properties (SIOP) sets were clustered in 11 OWTs, ranging from clear blue coastal waters to very turbid inland lakes. The resulting OWTs were used to classify Sentinel-2 MSI surface reflectance observations extracted over relatively permanent water bodies in three drainage regions in Eastern Australia. The satellite data classification demonstrated clear limnological and seasonal differences in water types within and between the drainage divisions congruent with general limnological, topographical, and climatological factors. Locations of unclassified observations can be used to inform where in situ bio-optical data acquisition may be targeted to capture a more comprehensive characterization of all Australian waters. This can contribute to global initiatives like the SDGs and increases the diversity of natural water in global databases.

中文翻译:

多种光学水类型对澳大利亚水体的分类

为了向可持续发展目标(SDG)报告海洋和内陆水的进展,需要对水质进行基线确定和大陆范围的可操作监测。这项研究旨在提高我们对澳大利亚水域光学复杂性的认识。开发了一个工作流以将在澳大利亚沿海和大陆水域中收集的一系列原位生物光学观测结果的建模光谱响应聚类为不同的光学水类型(OWT)。在聚类和合并之后,大多数建模光谱和建模特定固有光学特性(SIOP)集聚在11个OWT中,从透明的蓝色沿海水域到非常浑浊的内陆湖泊。所得的OWT用于对Sentinel-2 MSI表面反射率观测进行分类,该观测值是从澳大利亚东部三个排水区域的相对永久性水体中提取的。卫星数据分类显示,与一般的河床,地形和气候因素相一致的排水分区内和排水区之间的水质在季节和季节上存在明显差异。未分类观测的位置可用于告知原位生物光学数据采集的目标,以捕获澳大利亚所有水域的更全面特征。这可以促进诸如SDGs之类的全球计划,并增加全球数据库中天然水的多样性。卫星数据分类显示,与一般的河床,地形和气候因素相一致的排水分区内和排水区之间的水质在季节和季节上存在明显差异。未分类观测的位置可用于告知原位生物光学数据采集的目标,以捕获澳大利亚所有水域的更全面特征。这可以促进诸如SDGs之类的全球计划,并增加全球数据库中天然水的多样性。卫星数据分类显示,与一般的河床,地形和气候因素相一致的排水分区内和排水区之间的水质在季节和季节上存在明显差异。未分类观测的位置可用于告知原位生物光学数据采集的目标,以捕获澳大利亚所有水域的更全面特征。这可以促进诸如SDGs之类的全球计划,并增加全球数据库中天然水的多样性。未分类观测的位置可用于告知原位生物光学数据采集的目标,以捕获澳大利亚所有水域的更全面特征。这可以促进诸如SDGs之类的全球计划,并增加全球数据库中天然水的多样性。未分类观测的位置可用于告知原位生物光学数据采集的目标,以捕获澳大利亚所有水域的更全面特征。这可以促进诸如SDGs之类的全球计划,并增加全球数据库中天然水的多样性。
更新日期:2020-09-16
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