RENalyzer: A tool to facilitate the spatial accuracy assessment of digital cartography

Managing spatial data in paper maps is quite different from managing digital spatial information. Sometimes manual vectorization of scanned maps is the only way to produce digital cartography, especially when the only source of spatial information is a paper map. Digital scanning and manual vectorization are two processes well known for adding error to data and accuracy is a particularly important issue for users of spatial information. The National Ecological Reserve (REN) established in the Portuguese national law protects areas with a diversified bio-physical structure and specific ecological characteristics. This information is often required to manage several human activities, such as mineral extraction, real estate, industry, tourism, etc. REN maps were originally produced in paper and were vectorized to produce digital cartography. The objective of this study is to measure the spatial accuracy and to assure the conformity with the original cartography. The accuracy of the REN digital cartography was assessed through a stratified sampling scheme, as described in Peixoto et al. (2006). The preparation of the digitized maps for the needs and the appliance of the sampling method as well as the data quality control were combined in the RENalyzer application. The application calculates areas of all polygons respective to their attribute classes using object oriented computation methods. As described in the sampling method, all class combinations (overlaying polygons) are considered. These areas and the global area are the base of the global sample size and the sample size per class and class combination. Considering these guidelines the application creates random points in randomly chosen polygons. The data quality control is done by facilitating the map reviewing process. After adding the scanned map and automatically setting map properties, the application zooms to each point and allows a fast and accurate quality control. Errors in digitizing are computed and classified in spatial and thematic errors. The attributes distance to original class and error description are added to the table.