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首页> 外文期刊>Geoscience and Remote Sensing, IEEE Transactions on >Cross-Sensor Continuity of Satellite-Derived Water Clarity in the Gulf of Mexico: Insights Into Temporal Aliasing and Implications for Long-Term Water Clarity Assessment
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Cross-Sensor Continuity of Satellite-Derived Water Clarity in the Gulf of Mexico: Insights Into Temporal Aliasing and Implications for Long-Term Water Clarity Assessment

机译:墨西哥湾卫星水净度的跨传感器连续性:对时间混叠的见解和长期水净度评估的意义

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Addressing critical earth science questions often requires time scales beyond the life of any single satellite sensor. Overlap between satellite-based datasets allows for the quantification of continuity (and discrepancies) between sensors. Toward that end, collocated matchups between Sea-viewing Wide Field-of-View Sensor (SeaWiFS), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imager Radiometer Suite (VIIRS) water clarity data from the Gulf of Mexico were analyzed at simultaneous, daily, and monthly time scales. Simultaneous data indicated strong agreement between sensors, with unbiased percent difference (UPD) generally less than 10% for both SeaWiFS/MODIS and VIIRS/MODIS matchups, with no apparent temporal trends. Spatially, UPD was highest near frontal boundaries and at high sensor zenith angles, while bias showed nearshore/offshore trends. UPD and bias statistics did not diminish for daily matchups; however, large degradation was seen for comparisons of monthly means between sensors, particularly SeaWiFS/MODIS matchups. Data coverage represented an important factor contributing to uncertainties in monthly mean data, as higher UPD was observed when fewer valid satellite measurements were recorded. Requiring a minimum of 15 samples per pixel per month minimizes the uncertainties in monthly mean products, with UPD between satellites roughly equivalent to that for simultaneous matchups. Overall, these findings demonstrate high consistency between three satellite instruments for most locations, while several “hot spots” of inconsistency are also revealed, which should be avoided in time-series studies. The findings also highlight the need to quantify uncertainties in often-used satellite products (particularly monthly mean composites) as well as the need to have a sufficient number of observations to assure the fidelity of monthly means.
机译:解决关键的地球科学问题通常需要超出任何单个卫星传感器寿命的时间范围。基于卫星的数据集之间的重叠可以量化传感器之间的连续性(和差异)。为此,同时分析了来自墨西哥湾的海景宽视场传感器(SeaWiFS),中分辨率成像光谱仪(MODIS)和可见红外成像辐射仪套件(VIIRS)水清晰度数据之间的并置配对。 ,每日和每月的时间范围。同时的数据表明传感器之间的一致性很强,SeaWiFS / MODIS和VIIRS / MODIS配对的无偏差百分比差异(UPD)通常小于10%,没有明显的时间趋势。在空间上,UPD在前边界附近和高传感器天顶角处最高,而偏差则显示近岸/近海趋势。 UPD和偏差统计数据不会因每日比赛而减少;但是,对于传感器之间每月平均值的比较,尤其是SeaWiFS / MODIS配对的比较,看到了很大的下降。数据覆盖率是造成月平均数据不确定性的重要因素,因为当记录的有效卫星测量值较少时,UPD会升高。每月每个像素至少需要15个样本,这将使月平均乘积的不确定性最小化,卫星之间的UPD大约等于同时进行对等的情况。总体而言,这些发现表明,大多数位置的三颗卫星仪器之间具有高度一致性,同时还揭示了几个不一致的“热点”,应在时序研究中避免使用。研究结果还强调,有必要量化常用卫星产品(尤其是月度均值组合)中的不确定性,并且需要进行足够数量的观察以确保月度均值的逼真度。

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