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Regional measurements and spatial/temporal analysis of CDOM in 10,000 + optically variable Minnesota lakes using Landsat 8 imagery

机译:使用Landsat 8图像的10,000 +光学变量明尼苏达湖中CDOM的区域测量和空间/时间分析

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Information on colored dissolved organic matter (CDOM) is essential for understanding and managing lakes but is often not available, especially in lake-rich regions where concentrations are often highly variable in time and space. We developed remote sensing methods that can use both Landsat and Sentinel satellite imagery to provide census-level CDOM measurements across the state of Minnesota, USA, a lake-rich landscape with highly varied lake, watershed, and climatic conditions. We evaluated the error of satellite derived CDOM resulting from two atmospheric correction methods with in situ data, and found that both provided substantial improvements over previous methods. We applied CDOM models to 2015 and 2016 Landsat 8 OLI imagery to create 2015 and 2016 Minnesota statewide CDOM maps (reported as absorption coefficients at 440 nm, a_440) and used those maps to conduct a geospatial analysis at the ecoregion level. Large differences in a_440 among ecoregions were related to predominant land cover/use; lakes in ecoregions with large areas of wetland and forest had significantly higher CDOM levels than lakes in agricultural ecoregions. We compared regional lake CDOM levels between two years with strongly contrasting precipitation (close-to-normal precipitation year in 2015 and much wetter conditions with large storm events in 2016). CDOM levels of lakes in agricultural ecoregions tended to decrease between 2015 and 2016, probably because of dilution by rainfall, and 7% of lakes in these areas decreased in α_440 by ≥3 m~(-1). In two ecoregions with high forest and wetlands cover, α_(440) increased by >3 m~(-1) in 28 and 31% of the lakes, probably due to enhanced transport of CDOM from forested wetlands. With appropriate model tuning and validation, the approach we describe could be extended to other regions, providing a method for frequent and comprehensive measurements of CDOM, a dynamic and important variable in surface waters.
机译:有关彩色溶解有机物(CDOM)的信息对于了解和管理湖泊来说是必不可少的,但通常不可用,特别是在富湖的地区,其中浓度在时间和空间中往往是高度变化的。我们开发了遥感方法,可以使用Landsat和Sentinel卫星图像,以在美国明尼苏达州的州,富裕的景观中提供人口普查级CDom测量,具有高度多变的湖泊,流域和气候条件。我们评估了由两个大气校正方法具有原位数据产生的卫星衍生CDom的误差,发现两者都提供了对先前方法的大量改进。我们将CDOM模型应用于2015和2016 Landsat 8 Oli Imagery,以创建2015年和2016年Minnesota StateWide CDom Maps(报告为440 nm,a_440的吸收系数),并使用这些地图在EcoreGion水平进行地理空间分析。 eCoregions中A_440的大差异与主要陆地覆盖/使用有关;在大面积湿地和森林的河流中的湖泊具有明显高于农业生态湖泊的CDOM水平。我们比较了两年间的区域湖CDOM水平与2015年近常对比的沉淀(2015年近常沉淀年份,2016年患有大型风暴事件的潮湿条件)。 2015年和2016年,农业生态湖泊水平趋于减少,可能是因为由于降雨量稀释,而7%的这些区域的湖泊≥3m〜(-1)减少。在具有高森林和湿地覆盖的两种eCoregions中,α_(440)在28和31%的湖泊中增加> 3 m〜(-1),可能是由于森林湿地的CDOM运输增强。通过适当的模型调谐和验证,我们描述的方法可以扩展到其他地区,提供了一种用于CDOM的频繁和综合测量的方法,表面水域中的动态和重要变量。

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