Earth observation has been widely recognised as having considerable potential to aid an improved understanding of tropical forest biodiversity. However, studies that have explored the use of the multispectral response recorded by Earth observation satellites to infer climatically and edaphically determined floristically distinct tropical forest types have on the whole reported disappointing res...

—Hyperspectral imagery from EO-1 Hyperion and AVIRIS were used in conjunction with continuous forest inventory (CFI) data to map detailed forest composition in the state forests of Western Maryland. We developed a hierarchical vegetation classification that conformed to the National Vegetation Classification Standard (NVCS) at the Alliance level and mapped these forest types as a function of hy...

Presettlement forest types were mapped as fuzzy sets from point data representing trees contained in General Land Office survey notes (ca.1850) for Chippewa County, Michigan. The resulting representation agreed with a polygon map of the same forest types at 66 percent of the locations (represented as grid cells) in the county. Boundary vagueness was defined in relation to the slope of a linear ...

This study explores a semi-supervised classification approach using random forest as a base classifier to classify the low-back disorders (LBDs) risk associated with the industrial jobs. Semi-supervised classification approach uses unlabeled data together with the small number of labelled data to create a better classifier. The results obtained by the proposed approach are compared with those o...

Presettlement forest types were mapped as fuzzy sets from point data representing trees contained in General Land O ce survey notes (circa 1850) for Chippewa County, Michigan. The resulting representation agreed with a polygon map of the same forest types at 66% of the locations (represented as grid cells) in the county. Boundary vagueness was de® ned in relation to the slope of a linear funct...

Object-based image analysis (OBIA) is employed to classify forest types, including deciduous, evergreen and mixed forests, in a U.S. National Park unit using very high spatial resolution (VHR) IKONOS satellite imagery. This research investigates the effect of scale on segmentation quality and object-based forest type classification. Average local variance and spatial autocorrelation analyses ar...