[Interpretation of spatial distribution pattern for dissolved inorganic nitrogen concentration in coastal estuary using hyperspectral data].
Choosing dissolved inorganic nitrogen (DIN) as one of the representative nutritional salt monitoring indexes, a hyperspectral remotely sensed inversion model was built and applied to quantitatively retrieve water quality parameters with its spatial distribution patterns in coastal estuary with high suspended sediment concentration (SSC). It was found that when SSC was larger than 0.1 kg/m3, DIN concentration had a notable inverse correlation with SSC and the correlation coefficient R2 reached 0.617. Based on this conclusion, firstly the in-situ observed water surface remote sensing reflectance was resampled according to the spectral response characters of Hyperion sensor. And then, statistical correlation analysis between reflectance and DIN concentration was carried out. The results showed that band reflectance of R804 and R630 representing the second and first reflectance peak of water spectrum curve were sensitive to the variation of DIN concentration. And then, a pseudo remotely sensed sand parameter index R804 x R630/(R804 - R630) was calculated for the construction of the nonlinear DIN quantitative reversion model. Correlation coefficient R2 between observed and simulated DIN concentrations for 29 calibrating samples and 10 validating samples were 0.746 and 0.67, while their mean absolute errors reached 109.07 and 147.58 microg/L, respectively. The model was then applied on Hyperion hyperspectral image to get the spatial distribution character of DIN concentration in Sheyanghe river estuary and the DIN concentration was between 52 to 513 microg/L. Results indicated that in coastal estuary which was dominated by suspended sediments, the diffusive trends of DIN concentration reversed by remote sensing techniques had an intimate relationship with motions of tidal current and transportation attributes of SSC. As the hydrodynamic conditions were unclear, hyperspectral remote sensing technique was an effective technical way for dynamic survey of DIN concentration.
Zhang
Dong
D
School of Geographic Science, Nanjing Normal University, Nanjing 210046, China. zhangdong@njnu.edu.cn
Xu
Yong
Y
Zhang
Ying
Y
Li
Huan
H
D004784:Environmental Monitoring / Q000379:methods; D009584:Nitrogen / Q000032:analysis*; D017711:Nonlinear Dynamics; D009792:Oceans and Seas; D058998:Remote Sensing Technology; D012995:Solubility; D013057:Spectrum Analysis / Q000379:methods*; D014874:Water Pollutants, Chemical / Q000032:analysis*
D014874:Water Pollutants, Chemical; D009584:Nitrogen