Correlating Airborne Hyperspectral Images with Geological Field Data at Red Lake Ontario

2002 ◽  
Author(s):  
P Assouad ◽  
V Singhroy

2002 ◽  
Vol 353 (1-4) ◽  
pp. 115-149 ◽  
Author(s):  
Khaled Ouassaa ◽  
David A. Forsyth




1937 ◽  
Vol 32 (2) ◽  
pp. 131-153
Author(s):  
William Bardwell Mather
Keyword(s):  


2010 ◽  
Vol 37 (12) ◽  
pp. 1631-1640
Author(s):  
A. Jalili ◽  
S. S. Li

The exchange flow through the Burlington Ship Canal connecting Hamilton Harbour with Lake Ontario is investigated, using a two-layer internal hydraulics model. The summer exchange features an upper layer of polluted Harbour Water flowing from the harbour into the lake, whereas a lower layer of fresh Lake Ontario Water flowing from the lake into the harbour. We predict this exchange, taking into account the effects of both friction and barotropic forcing of multiple frequencies. Predictions of density interface and volume flux compare well with experimental and field data. The interface varies non-linearly with distance along the canal, with and without barotropic forcing. Our results indicate that the exchange flow is highly frictional. The barotropic forcing comprises oscillation modes of different frequency; these individual forcing modes cause the interface and layer velocities to fluctuate significantly in time, but their influence on the time average flows through the canal is minimal.



2017 ◽  
Vol 53 (1) ◽  
pp. 127-141 ◽  
Author(s):  
Shaun Gallagher ◽  
Alfredo Camacho ◽  
Mostafa Fayek ◽  
Mark Epp ◽  
Terry L. Spell ◽  
...  
Keyword(s):  
Red Lake ◽  
East Bay ◽  


Author(s):  
Vidya Manian ◽  
Alejandro Sotomayor ◽  
Ollantay Medina

Hyperspectral images are an important tool to assess ecosystem biodiversity both on terrestrial and benthic habitats. To obtain more precise analysis of biodiversity indicators that agree with indicators obtained using field data, analysis of spectral diversity calculated from images have to be validated with field based diversity estimates. The plant species richness is one of the most important indicators of biodiversity. This indicator can be measured in hyperspectral images considering the Spectral Variation Hypothesis (SVH) which states that the spectral heterogeneity is related to spatial heterogeneity and thus to species richness. The goal of this research is to capture spectral heterogeneity from hyperspectral images for a terrestrial neo tropical forest site using Vector Quantization (VQ) method and then use the result for prediction of plant species richness. The results are compared with that of Hierarchical Agglomerative Clustering (HAC). The validation of the process index is done calculating the Pearson correlation coefficient between the Shannon entropy from actual field data and the Shannon entropy computed in the images. Terrestrial dry forest and marine coastal hyperspectral images with different resolutions have been used for spectral diversity feature validation.



1941 ◽  
Vol 49 (6) ◽  
pp. 641-656
Author(s):  
W. K. Gummer


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