Regression-bases synergy of optical, shorwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments
van der Wal, D.; Herman, P.M.J. (2007). Regression-bases synergy of optical, shorwave infrared and microwave remote sensing for monitoring the grain-size of intertidal sediments. Remote Sens. Environ. 111(1): 89-106. http://dx.doi.org/10.1016/j.rse.2007.03.019
In: Remote Sensing of Environment. Elsevier: New York,. ISSN 0034-4257; e-ISSN 1879-0704, meer
|  |
| Trefwoorden |
Dimensions > Size > Particle size
Mapping
Multisensor data fusion
Sediments > Clastics > Mud
Marien/Kust; Brak water |
| Author keywords |
SAR; VNIR; SWIR; Mud; Particle size; Multi-sensor data fusion; Mapping |
| Auteurs | | Top |
- van der Wal, D., meer
- Herman, P.M.J.
|
|
|
| Abstract |
A method is developed for monitoring the sediment grain-size of intertidal flats in the Westerschelde (southwest Netherlands), using information from both space-borne microwave (SAR) and optical/shortwave infrared remote sensing. Estimates of the backscattering coefficient were extracted from time-series of C-band ERS SAR imagery. Surface reflectance in the visible, near-infrared (VNIR) and shortwave infrared (SWIR) part of the electromagnetic spectrum, as well as spectral indices, were derived from matching multi-temporal Landsat TM imagery. In addition, surface reflectances were derived from a set of airborne multispectral (VNIR) CASI images, and hyperspectral (VNIR) measurements using a field spectroradiometer. The data were related to matching field measurements of surface characteristics, including sediment properties. Regression-based algorithms were developed to map the spatio-temporal distribution of mud content using (a) the C-band SAR backscattering coefficient, (b) surface reflectance in the green and SWIR, and (c) a combination of these, with corroborative field measurements. Mud content of the sediment has been successfully mapped by all three algorithms, but a combination of information from microwave and VNIR/SWIR provided best results. The algorithms were generally consistent in time, making them suitable for generating time-series and for monitoring. However, they should be validated and calibrated in order to be applicable to other intertidal areas. |
|
