The Moisture Content Prediction Model of Surface Sediment in Intertidal Flat by Hyperspectral Remote Sensing

  • 1. School of Geographic Science, Nanjing Normal University, Nanjing 210046, China;
    2. College of Harbour, Coastal and Offshore Engineering, Hohai University, Nanjing 210098, China

Received date: 2012-07-19

  Revised date: 2013-03-18

  Online published: 2013-08-08


Owing to the tidal fluctuation, interstitial water content in intertidal flat changes frequently and spatially. It gives important influence to the reflectance of surface spectrum in this area. Precisely prediction of tidal flat moisture content can make the extraction of surface feature information by remote sensing easier and more accurate. Based on detailed analysis of the characteristics of 449 sediment spectral curves with different moisture contents, three kinds of water content index namely difference water index (DWI), ratio water index (RWI) and normalized differential water index (NDWI) were proposed. And then they were used for the construction of water content reversion models and applied for the accurate prediction of moisture content in tidal flat for different sediment types. Results showed that: (1) Moisture content for sediment samples had a good segment linear correlation with its reflectance in short-wave infrared band area. The corresponding moisture contents for segmentation points were 42% and 62% respectively; (2) Reflectance of characteristic bands with central wavelengths at 1165nm, 1336nm, 1568nm and 1780nm has very good responses to the changes of water contents for different sediment types. DWI, RWI and NDWI calculated by the combinations of reflectance at characteristic bands had a significant linear correlation with moisture contents of different soil types; (3) Among the three moisture content reversion indexes, DWI had a better prediction accuracy than RWI and NDWI and a good adaptability for water contents distributed in wide ranges. In comparison, RWI and NDWI were more suitable for a moderate moisture content level. Much smaller or much larger of the water content level would lead to a relatively larger deviation for its prediction; and (4) Using the model constructed by DWI1336,17801336, λ1780), water contents were reserved and correlation coefficients between the predicted and observed ones were 0.891, 0.915, 0.920 and 0.905 for four different sediment types names silt, sandy silt, silty sand and sand while their root mean square errors were 9.87%, 3.56%, 4.24% and 2.98% respectively. So DWI is suitable for the prediction of spatial and temporal variation of the moisture contents in tidal flat areas.

Cite this article

ZHANG Dong, LI Huan, ZHENG Xiao-Dan . The Moisture Content Prediction Model of Surface Sediment in Intertidal Flat by Hyperspectral Remote Sensing[J]. Journal of Geo-information Science, 2013 , 15(4) : 581 -589 . DOI: 10.3724/SP.J.1047.2013.00581


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