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Estimation of Total Suspended Sediment and Chlorophyll-A Concentration from Landsat 8-Oli: The Effect of Atmospher and Retrieval Algorithm

机译:Landsat 8-Oli的总悬浮泥沙和叶绿素-A浓度的估算:大气和检索算法的影响

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Total Suspended Sediment (TSS) and Chlorophyll-a (Chl-a) are globally knows as a key parameters for regular seawater monitoring. Considering the high temporal and spatial variation of water constituent, remote sensing technique is an efficient and accurate method for extracting water physical parameter. A high accurate estimated data derived from remote sensing depends on an accurate atmospheric correction algorithm and physical parameter retrieval algorithms. In this research, we evaluated the accuracy of atmospheric corrected product of NASA as well as develop algorithms for estimating TSS and Chl-a concentration over Poteran and Gili Iyang island water using Landsat-8 OLI data. The data used in this study was collected from Poteran’s waters (9 stations) on April 22, 2015 and Gili Iyang’s waters (six stations) on October 15, 2015. Low correlation between in situ and Landsat Rrs(λ) (R2= 0.106) indicated that atmospheric correction algorithm performed by NASA has a limitation. The TSS concentration retrieval algorithm produced acceptable accuracy both over Poteran’s Waters (RE of 4.60% and R2 of 0.628) and over Gili Iyang’s waters (RE of 14.82% and R2 of 0.345). Although the R2 lower than 0.5, the relative error was more accurate than the minimum requirement of 30%. Whereas, The Chl-a concentration retrieval algorithm produced acceptable result over Poteran (RE of 13.87% and R2 of 0.416) and failed over Gili Iyang’s waters (RE of 99.140 and R2 of 0.090). The low correlation between TSS or Chl-a measured and estimated TSS or Chl-a concentration were caused not only by performance of the developed TSS and Chl-a estimation retrieval algorithm but also the effect and accuracy of atmospheric corrected reflectance of Landsat product.
机译:总悬浮泥沙(TSS)和叶绿素a(Chl-a)是常规海水监测的关键参数,在全球范围内广为人知。考虑到水成分的时空变化较大,遥感技术是一种提取水物理参数的有效,准确的方法。从遥感获得的高精度估计数据取决于精确的大气校正算法和物理参数检索算法。在这项研究中,我们评估了NASA大气校正产品的准确性,并开发了使用Landsat-8 OLI数据估算Poteran和Gili Iyang岛水上TSS和Chl-a浓度的算法。本研究中使用的数据是2015年4月22日从Poteran水域(9个站点)和Gili Iyang水域(6个站点)收集的。原位与Landsat Rrs(λ)之间的相关性较低(R2 = 0.106)指出NASA执行的大气校正算法有局限性。 TSS浓度检索算法在Poteran水域(RE为4.60%,R2为0.628)和Gili Iyang水域(RE为14.82%,R2为0.345)上产生了可接受的精度。尽管R2低于0.5,但相对误差比30%的最低要求更为准确。而Chl-a浓度检索算法在Poteran上产生了可接受的结果(RE为13.87%,R2为0.416),而在Gili Iyang的水域中失败(RE为99.140,R2为0.090)。测得的TSS或Chl-a与估计的TSS或Chl-a浓度之间的低相关性,不仅是由于开发的TSS和Chl-a估计检索算法的性能,还因为Landsat产品的大气校正反射率的影响和准确性。

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