Comparison of MODIS-based models for retrieving suspended particulate matter concentrations in Poyang Lake, China
Comparison of MODIS-based models for retrieving suspended particulate matter concentrations in Poyang Lake, China
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基于MODIS的鄱阳湖悬浮颗粒物浓度反演模型比较
DOI：
10.1016/j.jag.2013.03.001
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发表时间：
2013-10
影响因子：
7.5
通讯作者：
Liu, Yaolin
中科院分区：
文献类型：
--
作者：
He, Junjun;Duan, Hongtao;Fei, Teng;Liu, Yaolin
悬浮颗粒物（SPM）是描述水质的关键参数，建立悬浮颗粒物浓度的反演模型是获取悬浮颗粒物时空信息的基础，是进一步认识、管理和保护水生生态系统的基础。本研究旨在比较基于中分辨率成像光谱辐射计（MODIS）的cspm反演模型，以寻找改善鄱阳湖cspm估算的最佳模型。利用2007年9月27日的cspm观测数据及其同步的MODIS Terra图像，利用最小二乘技术对反演模型进行校正。利用2012年8月31日的cspm观测数据和2012年8月30日的MODIS Terra影像对校正后的模型进行验证，比较cspm实测值与估计值的相关系数(r)、估计值的均方根误差（RMSE）和相对均方根误差（RRMSE）以及模型偏差评价结果，确定MODIS影像估算鄱阳湖cspm的最优模型。模型校正表明，去除两个样本后，蓝、绿、红波段的指数模型、红外波段的线性模型、红波段的三次模型和红-红外波段的指数模型分别解释了CSPM变化的92%、88%、90%、89%、90%和76%；而模型验证表明，在剔除2个样本后，蓝、绿波段的指数模型的cspm估计值存在偏差，单红、红外波段模型的cspm实测值与估计值之间的一致性不是很高（r=<0.8），其中红-红外波段的指数模型在所有校准模型中效果最好（r=0.87， RMSE=22.1mg/l， RRMSE=52.8%）。我们认为，红-红外波段指数模型获得了稳定的cspm估计，是本研究cspm估计的最佳模型，需要获得更多的独立数据集来进一步验证我们的发现，以改进鄱阳湖cspm的估计。
Suspended particulate matter (SPM) is a key parameter describing water quality, and developing the retrieval model of SPM concentration (CSPM) is fundamental for obtaining the spatiotemporal information of CSPMand further for understanding, managing and protecting aquatic ecosystems. This study aimed to compare moderate resolution imaging spectroradiometer (MODIS)-based CSPMretrieval models in order to find the optimal model for improving the CSPMestimation in Poyang Lake. The CSPMmeasurements on 27 September 2007 and their coincident MODIS Terra image were used to calibrate retrieval models with the least-squares technique. The CSPMmeasurements on 31 August 2012 and the MODIS Terra image on 30 August 2012 were applied to validate the calibrated models, and the correlation coefficient (r) between the measured and estimated CSPMvalues, the root mean square error (RMSE) and relative root mean square error (RRMSE) of estimation as well as the model bias evaluation result were compared to determine the optimal model for estimating the CSPMvalues of Poyang Lake from MODIS images. Model calibration showed that, after two samples were removed, the exponential models of blue, green and red band, the linear model of infrared band, the cubic model of red band as well as the exponential model of red minus infrared band explained about 92%, 88%, 90%, 89%, 90% and 76% of the variation of CSPM, respectively; while model validation indicated that, after removing two samples, the exponential models of blue and green band got biased CSPMestimations, the agreement between the measured and estimated CSPMvalues was not very high (r=<0.8) for the models with single red and infrared band, and the exponential model of red minus infrared band got the best result among all calibrated models (r=0.87, RMSE=22.1mg/l, RRMSE=52.8%). We concluded that the exponential model of red minus infrared band obtained stable CSPMestimation and was the optimal model for CSPMestimation in this study, and more independent datasets should be obtained to further validate our finding for improving the CSPMestimation in Poyang Lake.
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影响因子：
1.9
作者：
Kotchenova, Svetlana Y.;Vermote, Eric F.
通讯作者：
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影响因子：
13.5
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作者：
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