Tree species composition is one of the criteria required for assessing forest reclamation in the province of Alberta in Canada. This information is also very important for forest management and conservation purposes. In this paper the performances of RapidEye data alone and in combination with the Light Detection And Ranging data is assessed for mapping tree species in a boreal forest area in Alberta. Both the random forest and support vector machine classification techniques were evaluated. A significant improvement in the classification outputs was observed when using both data types. Random forest outperformed the support vector machine classifier. Overall, the difference in acquisition time between the RapidEye and Light Detection And Ranging data did not seem to affect significantly the classification results. Using random forest, six input variables were identified as the most important for the classification process including digital elevation model, terrain slope, canopy height, the red-edge normalized difference vegetation index, and the red-edge and near-infrared bands.
This paper investigates the abundance mapping of rangeland plant communities using hyperspectral remote sensing data.
Spectral Mixture Analysis (SMA) was used to estimate the cover fraction of five rangeland components: green grass,
yellow grass, litter, shrubs and soil. Two types of endmembers were assessed using canopy reflectance modeling and
tested over real data. The first type is the leaf endmember based on the laboratory reflectance measurements of different
samples of leaves. The second is the canopy endmember based on reflectance simulation using the canopy radiative
transfer model SAIL. These two endmember types were first assessed in SMA using a number of homogenous canopy
simulations with different Leaf Area Index (LAI). Subsequently, the leaf and the canopy endmembers were evaluated
using ground spectra, and cover fractions were compared to actual data. Finally, both endmember types were applied in
SMA to CHRIS/PROBA data to estimate the rangeland component cover fractions. Performances of leaf and canopy
endmembers were evaluated based on the field knowledge of the area of interest. Results showed overall that the cover
fraction estimates using the canopy endmembers tend to better agree with actual data.