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Full-Text Articles in Physical Sciences and Mathematics
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.
Regional Scale Dryland Vegetation Classification With An Integrated Lidar-Hyperspectral Approach, Hamid Dashti, Andrew Poley, Nancy Glenn, Nayani Ilangakoon, Lucas Spaete, Dar Roberts, Et. Al.
Michigan Tech Publications
The sparse canopy cover and large contribution of bright background soil, along with the heterogeneous vegetation types in close proximity, are common challenges for mapping dryland vegetation with remote sensing. Consequently, the results of a single classification algorithm or one type of sensor to characterize dryland vegetation typically show low accuracy and lack robustness. In our study, we improved classification accuracy in a semi-arid ecosystem based on the use of vegetation optical (hyperspectral) and structural (lidar) information combined with the environmental characteristics of the landscape. To accomplish this goal, we used both spectral angle mapper (SAM) and multiple endmember spectral …
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Discovery Of Topological Constraints On Spatial Object Classes Using A Refined Topological Model, Ivan Majic, Elham Naghizade, Stephan Winter, Martin Tomko
Journal of Spatial Information Science
In a typical data collection process, a surveyed spatial object is annotated upon creation, and is classified based on its attributes. This annotation can also be guided by textual definitions of objects. However, interpretations of such definitions may differ among people, and thus result in subjective and inconsistent classification of objects. This problem becomes even more pronounced if the cultural and linguistic differences are considered. As a solution, this paper investigates the role of topology as the defining characteristic of a class of spatial objects. We propose a data mining approach based on frequent itemset mining to learn patterns in …