In this paper, an algorithm for estimating shallow-water depth from hyperspectral data is proposed. This methodology is based on the different responses of shallow-water reflectance on depth and substrate type. Two parameters-similarity coefficient and Pearson correlation coefficient-are introduced to describe the different types of responses, and a linear logarithm ratio model is established. Using Hyperion data over the coastal regions of O'Ahu Island and Saint Thomas Island, the retrieved bathymetry is compared with the airborne LIDAR data. The validation results show that the proposed method has good performance, and the root mean square error is less than 1.5 m over shallow water (shallower than 20 m).

Bathymetry Retrieval From Hyperspectral Remote Sensing Data in Optical-Shallow Water

Minerals mapping of the lunar surface with Clementine UVVIS/NIR data based on spectra unmixing method and Hapke model

Automated lithological mapping using airborne hyperspectral thermal infrared data: A case study from Anchorage Island, Antarctica

In this study we evaluate a methodology for disaggregating land surface energy fluxes estimated with the Two-Source Energy Balance (TSEB)-based Dual-Temperature Difference (DTD) model which uses day and night polar orbiting satellite observations of land surface temperature (LST) as a remotely sensed input. The DTD model is run with MODIS input data at a spatial resolution of around 1 km while the disaggregation uses Landsat observations to produce fluxes at a nominal spatial resolution of 30 m. The higher-resolution modelled fluxes can be directly compared against eddy covariance (EC)-based flux tower measurements to ensure more accurate model validation and also provide a better visualization of the fluxes' spatial patterns in heterogeneous areas allowing for development of, for example, more efficient irrigation practices. The disaggregation technique is evaluated in an area covered by the Danish Hydrological Observatory (HOBE), in the west of the Jutland peninsula, and the modelled fluxes are compared against measurements from two flux towers: the first one in a heterogeneous agricultural landscape and the second one in a homogeneous conifer plantation. The results indicate that the coarse-resolution DTD fluxes disaggregated at Landsat scale have greatly improved accuracy as compared to high-resolution fluxes derived directly with Landsat data without the disaggregation. At the agricultural site the disaggregated fluxes display small bias and very high correlation ( r a 0.95) with EC-based measurements, while at the plantation site the results are encouraging but still with significant errors. In addition, we introduce a~modification to the DTD model by replacing the "parallel" configuration of the resistances to sensible heat exchange by the "series" configuration. The latter takes into account the in-canopy air temperature and substantially improves the accuracy of the DTD model.

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Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

The Advanced Topographic Laser Altimeter System (ATLAS) on ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) uses a 532 nm band photon-counting LiDAR (Light Detection and Ranging), which has ce...

An active-passive fusion strategy and accuracy evaluation for shallow water bathymetry based on ICESat-2 ATLAS laser point cloud and satellite remote sensing imagery

The solar radiance obtained by a sensor is modified by atmosphere interaction, affected by its path through the
atmospheric absorption and scattered in the combined Sun-surface-aircraft. In this paper, we described a method using
RTM to simulate atmospheric spectral for deriving surface reflectance from Hyperspectral data (Hyperion). Preliminary
application of the technique to Hyperion data indicates that the retrieval results are reasonable, and available techniques
including retrieval of water vapor amount with MODTRAN look-up- table.

Atmospheric correction of hyperspectral data using MODTRAN model

Quantitatively retrieving mineral abundances from hyperspectral data is one of promising and challenging geological
application fields of hyperspectral data, and the most basic obstacles are mixture characteristic of mineral spectra and
deconvolution method of mixture spectra. A series of mineral mixture schemes were designed, and several kinds of
mineral were used for investigating the two obstacles. In the experiment, average single scattering albedo was calculated
from reflectance spectra on the basis of Hapke radiative transfer model. The error of mineral abundances derived from
reflectance spectra and single scattering albedo is 20.05% and 5.03% respectively, which shows that mixture spectra of
all kinds of mineral belongs to nonlinear mixing, and Hapke model is a good method of resolving this problem. Finally,
deconvolution of continuum-removed single scattering albedo spectra other than single scattering albedo spectra is
considered to be the possible method that could be applied to imaging spectrometer data (e.g. AVIRIS and Hyperion data)
to retrieve mineral abundances successfully, because intensity of spectra is influenced by terrain considerably rather than
shape of spectra feature is influenced by terrain slightly.

Bokun Yan

Papers

Atmospheric correction of hyperspectral data using MODTRAN model

Experiment study on quantitative retrieval of mineral abundances from reflectance spectra