Application of a generalized additive model (GAM) for estimating chlorophyll-a concentration from MODIS data in the Bohai and Yellow Seas,China

In optically complex waters, it is important to evaluate the accuracy of the standard satellite chlorophyll-a (chl-a) concentration algorithms, and to develop accurate algorithms for monitoring the dynamics of chl-a concentration. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite remote-sensing reflectance and concurrent in situ measured chl-a (2010–2013) were used to evaluate the standard OC3M algorithm (ocean chlorophyll-a three-band algorithm for MODIS) and Graver–Siegel–Maritorena model version 1 (GSM01) algorithm for estimating chl-a concentration in the Bohai and Yellow Seas (BYS). The results showed that the chl-a algorithms of OC3M and GSM01 with global default parameters presented poor performance in the BYS (the mean absolute percentage difference (MAPD) and coefficient of determination (R²) of OC3M are 222.27% and 0.25, respectively; the MAPD and R² of GSM01 are 118.08% and 0.07, respectively). A novel statistical algorithm based on the generalized additive model (GAM) was developed, with the aim of improving the satellite-derived chl-a accuracy. The GAM algorithm was established using the in situ measured chl-a concentration as the output variable, and the MODIS above water remote-sensing reflectance (visible bands at 412, 443, 469, 488, 531, 547, 555, 645, 667, and 678 nm) and bathymetry (water depth) as input variables. The MAPD and R² calculated between the GAM and the in situ chl-a concentration are 39.96% and 0.67, respectively. The results suggest that the GAM algorithm can yield a superior performance in deriving chl-a concentrations relative to the standard OC3M and GSM01 algorithms in the BYS.     

Retrieval of remotely sensed sea surface salinity using MODIS data in the Chinese Bohai Sea

Salinity dominates seawater density and directly affects physical and biochemical processes. Having a reliable retrieval model is essential to providing frequent and accurate sea surface salinity (SSS) data for marine research. Remote-sensing techniques provide alternatives for SSS data retrieval with its advantages of wide area surveys and real-time monitoring. In the present study, inverse relationship between SSS and coloured dissolved organic matter (CDOM) concentration in the Chinese Bohai Sea was verified. Thus, four simple band ratios of the original remote-sensing reflectance (R_rs) used to retrieve the CDOM concentration were compared and tested during SSS retrieval. R_rs (531)/R_rs (551) performed best among the four given band ratios. The model employed here can be applied to derive SSS with a root mean square error (RMSE) of 0.26 practical salinity units (psu) (R² = 0.76). A calibration model was verified using a discrete dataset of the measured SSS and was tested further during mapping of SSS in the Chinese Bohai Sea during 2010–2014. The yielded spatial patterns of SSS were satisfactory and an inverse relationship between SSS and the Yellow River discharge was confirmed.     

Remote-sensing estimation of dissolved inorganic nitrogen concentration in the Bohai Sea using band combinations derived from MODIS data

Remote sensing has been widely used for water quality monitoring, but most monitoring studies have only focused on a few water quality variables, such as chlorophyll-a, turbidity, and total suspended solids, which have typically been considered optically active variables. Remote sensing presents a challenge in estimating dissolved inorganic nitrogen (DIN) concentration in water. DIN in inland waters and estuaries had been estimated from remotely sensed observations. However, remote-sensing estimation of DIN in seawater over a large area had not yet been performed. Moreover, the bands used to estimate DIN in water were limited to 4 or 7 anterior bands of Moderate Resolution Imaging Spectroradiometer (MODIS) data at high spatial resolution rather than high spectral resolution. In this study, we attempted to establish a model to estimate DIN concentration in the Bohai Sea using band combinations derived from all the visible/near-infrared (Vis-NIR) bands of MODIS data. The results showed that regional multiple stepwise regression analysis (MLSR) yields a highly significant positive relationship between DIN concentration and certain remotely sensed combination variables. The modelling yielded higher accuracy for DIN concentration estimation in the Bohai Sea compared with previous studies. DIN concentration values showed a clear spatial variability, being high in coastal waters and relatively low further out. These results strongly suggest that the modelling demonstrates advantages for estimating DIN concentration in the Bohai Sea and has major potential for universal application in DIN concentration estimation in other waters.     

Evaluation of standard and regional satellite chlorophyll-a algorithms for moderate-resolution imaging spectroradiometer (MODIS) in the Bohai and Yellow Seas,China: a comparison of chlorophyll-a magnitude and seasonality

Retrieval of satellite remotely sensed chlorophyll-a (chl-a) concentrations in coastal regions such as the Bohai and Yellow Seas (BYS) is challenging due to their complex oceanic and atmospheric optical properties. The standard OC3M (ocean chl-a three-band algorithm for MODIS (moderate-resolution imaging spectroradiometer)) algorithm has been widely used in the BYS, despite well-known uncertainties about its accuracy in terms of absolute magnitude. This was based on the belief that OC3M chl-a is capable of representing reliable relative spatial and temporal patterns of sea surface chl-a concentrations. In this study, the ability of the standard OC3M chl-a algorithm to reproduce accurate seasonality patterns was evaluated, based on comparisons with in situ chl-a measurements in the BYS. The results quantified the overestimation by the standard OC3M algorithm with a median absolute percentage difference of 98.48% and a median relative difference of 1.13 mg m^?3.More importantly, the seasonality from OC3M chl-a was significantly biased relative to the seasonal patterns of in situ chl-a. In addition, a regional GAM (generalized additive model)-based satellite chl-a algorithm was evaluated and compared with OC3M chl-a. The results showed the GAM chl-a improved accuracy in both magnitude and seasonality when compared with in situ chl-a, relative to that from OC3M chl-a.     

我国湖泊湿地面临的问题及其对策研究

在综合分析国内外湖泊湿地保护、治理及管理等研究的基础上,比较系统地讨论了我国湖泊湿地面临的问题:泥沙淤积;湖泊面积萎缩;水位下降;湖泊水质恶化等。提出了一系列湖泊湿地管理对策,如建立湿地自然保护区、开展湿地生态系统健康评价、湿地生态功能区划及可持续管理对策研究等,为湖泊湿地的可持续发展和管理提供理论指导和科学依据。     

基于TRMM 3B42数据的1998-2010年中国暴雨时空特征分析

基于TRMM 3B42数据,构建5个年尺度时间序列参数,借助GIS空间分析和数学方法,揭示和分析1998-2010年暴雨降水的格局与过程特征。研究表明:13年来,年暴雨降水总量与年降水总量均呈缓慢下降的趋势,且空间格局相似,年暴雨降水比例时间波动较显著;暴雨集中分布区年降水以及年暴雨降水的时间波动均比较明显,年暴雨频次的时间波动较小但空间差异显著;暴雨降水空间分布在东西方向的差异性明显强于南北方向;年暴雨降水呈现向东北方向偏移的趋势;5个变量的变化趋势均表现出较强的空间差异性,且大部分像元呈增加(或减少)但统计不显著的趋势。     

Pyrolytic characteristics and kinetic studies of agricultural wastes—Four kinds of grasses

Several grasses are among the agricultural wastes generated annually in a large quantity during farming activities. In this study, thermogravimetric analysis was used to evaluate the fuel properties of a number of grasses, including Aeluropus sinensis, Conyza canadensis, Imperata cylindrica, and Setaria viridis. The pyrolysis behavior was also compared with the other biomasses. The thermal reaction systems fitted well with the distributed activation energy model and the global kinetic model and it is obvious that the values of E and k₀ calculated by the distributed activation energy model were much higher than that of the global kinetic model.     

Comparative study of low-frequency noise in 0.18 μm and 0.35 μm gate-length nMOSFETs with gate area of 1.1 μm2

We analyzed the noise characteristics of 0.18 μm and 0.35 μm nMOSFETs with a gate area of 1.1 μm² in the frequency range of 1 Hz to 100 kHz. Both two- and four-finger devices were investigated and analyzed. The experimental results show that the noise of 0.35 μm gate-length nMOSFET possesses lower 1/f component than the 0.18 μm one, whereas the four-finger devices reveal less 1/f noise than those of with two-finger ones. Furthermore, we used time domain measurement of drain current and also the statistical analysis of wafer level on the random telegraph signals (RTS) tests, and the results showed that RTS noise is higher in devices with a 0.35 μm gate-length, and devices with a smaller gate finger width produce more RTS noise than devices with a larger gate finger width.     

An optical biosensor-based immunoassay for the determination of bovine serum albumin in milk and milk products

An automated biosensor immunoassay, exploiting surface plasmon resonance detection, is described for the quantitation of bovine serum albumin (BSA) in milk products. Antibody selection, assay conditions and potential non-specific binding interferences were defined. Analytical performance includes a working range of 10–1000 ng mL⁻¹, a method detection limit of 0.02 mg g⁻¹ in milk, an instrument intermediate precision relative standard deviation (RSD_iR) of 3.7%, an intermediate precision RSD_iR of 8.9% for whey protein concentrate, and a single flow cell stable for at least 400 cycles. Accuracy was demonstrated by recovery, compliance with a certified reference material and comparison with a high performance liquid chromatographic method. The technique was applied to the estimation of BSA content of bovine milk, colostrum, whey protein fractions and infant formulae. The change in BSA expression during early bovine lactation and across a production season, and the thermal denaturation of BSA were also investigated.