当前位置: X-MOL 学术Remote Sens. Environ. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Quantifying decadal stability of lake reflectance and chlorophyll-a from medium-resolution ocean color sensors
Remote Sensing of Environment ( IF 13.5 ) Pub Date : 2024-03-23 , DOI: 10.1016/j.rse.2024.114120
Xiaohan Liu , Mark Warren , Nick Selmes , Stefan G.H. Simis

Multi-decadal time-series of Lake Water-Leaving Reflectance (LWLR), part of the Lakes Essential Climate Variable, have typically been interrupted for the 2012–2016 period due to lack of an ocean color sensor with capabilities equivalent to MERIS (2002−2012) and OLCI (2016 - present). Here we assess, for the first time, the suitability of MODIS/Aqua to estimate LWLR and the derived concentration of chlorophyll- (Chl) at the global scale across optically complex water types, in an effort to fill these information gaps for climate studies. We first compare the normalized water-leaving reflectance () derived from two atmospheric correction algorithms (POLYMER and L2gen) against in situ observations. POLYMER shows superior performance, considering the agreement with in situ measurements and the number of valid outputs. An extensive assessment of nine Chl algorithms is then performed on POLYMER-corrected from MODIS observations. The algorithms are tested both in original parameterizations and following calibration against in situ measurements of Chl. We find that the performance of algorithms parameterized per Optical Water Type (OWT) allows considerable improvement of the global Chl retrieval capability. Using 3 years of overlapping observations between MODIS/Aqua and MERIS (2009–2011) and OLCI (2017–2019), respectively, MODIS-derived reflectance and Chl products showed a reasonable degree of long-term stability in 48 inland water bodies. These water bodies, therefore, mark the candidates to study long-term environmental change.

中文翻译:

通过中等分辨率海洋颜色传感器量化湖泊反射率和叶绿素-a 的十年稳定性

作为湖泊基本气候变量的一部分,湖泊离水反射率 (LWLR) 的数十年时间序列通常在 2012-2016 年期间被中断,因为缺乏具有与 MERIS 功能相当的海洋颜色传感器(2002− 2012 年)和 OLCI(2016 年至今)。在这里,我们首次评估 MODIS/Aqua 在全球范围内估计光学复杂水类型的 LWLR 和衍生的叶绿素 (Chl) 浓度的适用性,以努力填补气候研究的这些信息空白。我们首先将两种大气校正算法(POLYMER 和 L2gen)得出的归一化水离开反射率 () 与现场观测进行比较。考虑到与现场测量和有效输出数量的一致性,POLYMER 显示出卓越的性能。然后对 MODIS 观测结果进行 POLYMER 校正,对九种 Chl 算法进行广泛评估。该算法在原始参数化和随后针对叶绿素原位测量的校准中进行了测试。我们发现,按光学水类型 (OWT) 参数化的算法性能可以显着提高全局 Chl 检索能力。分别利用 MODIS/Aqua 和 MERIS (2009-2011) 和 OLCI (2017-2019) 之间 3 年的重叠观测,MODIS 衍生的反射率和 Chl 产品在 48 个内陆水体中显示出合理程度的长期稳定性。因此,这些水体标志着研究长期环境变化的候选水体。
更新日期:2024-03-23
down
wechat
bug