ExPAND, Expanding Primary Attributes for National Decision Making




Low, Brian

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Canada is committed to report on the current state and condition of its forests in support of national commitments such as Montreal Process, Convention on Biodiversity, Kyoto Climate Accord and others. National reporting requires data to be extracted, collated and analyzed from multi-resolution, multi-scale data sets held by the Federal, 10 Provincial, and 3 Territorial jurisdictions. New methods and techniques for the integration, storage and analysis of data held by independent custodians over a distributed infrastructure are reviewed and applied for this project. Problems occur when required data are located in a distributed infrastructure. Accessing, analyzing, and reporting on this data has been time consuming, complicated and expensive. The object of this study was to investigate how spatial operations can be efficiently undertaken in a distributed environment without copying the data to a centralized location for analysis. A study of tessellations, re-sampling approaches, geospatial Web services. and spatial data handling was conducted to create and develop an approach that will allow for the analysis of distributed data sets. The resultant system, Expanding Primary Attributes for National Decision making (ExPAND) allows for the distributed analysis and synthesis of independently collected and stored data held on a distributed network of data warehouses. ExPAND was developed and designed to perform over a formalized international standards based infrastructure. These standards and specifications are created and maintained by the Open Geospatial Consortium (OGC). Any infrastructure that adheres to OGC's Web Mapping Service specifications can benefit from ExPAND. This thesis draws on a subset of Canada's National Forest Inventory (NFI) over an OGC based architecture as a test and demonstration of ExPAND.



geospatial, spatial, inventory, mapping