![]() For example, the road lines are elongated linear objects and the characters are small connected-objects. The automatic technique eliminates user intervention by exploiting common map properties of how road lines and text labels are drawn in raster maps. This approach includes automatic and supervised techniques to process raster maps for separating individual layers of geographic features from the maps and recognizing geographic features in the separated layers (i.e., detecting road intersections, generating and vectorizing road geometry, and recognizing text labels). In contrast, this thesis investigates a general approach that does not rely on any prior knowledge and requires minimal user effort to process heterogeneous raster maps. Previous work on map processing is typically limited to a specific type of map and often relies on intensive manual work. This is because of the varying image quality of raster maps (e.g., scanned maps with poor image quality and computer-generated maps with good image quality), the overlapping geographic features in maps, and the typical lack of metadata (e.g., map geocoordinates, map source, and original vector data). However, harvesting geographic features locked in heterogeneous raster maps to obtain the geospatial information is challenging. Raster maps offer a great deal of geospatial information and are easily accessible compared to other geospatial data. This article presents an overview of existing map processing techniques, with the goal of bringing together the past and current research efforts in this interdisciplinary field, to characterize the advances that have been made, and to identify future research directions and opportunities. However, map processing literature is spread across a broad range of disciplines in which maps are included as a special type of image. The typical result from map processing is geographic information that can be used in spatial and spatiotemporal analyses in a Geographic Information System environment, which benefits numerous research fields in the spatial, social, environmental, and health sciences. ![]() Since the early 1980s, researchers from a variety of disciplines, including computer science and geography, have been working on computational methods for the extraction and recognition of geographic features from archived images of maps (digital map processing). In order to preserve these unique documents, increasing numbers of digital map archives have been established, driven by advances in software and hardware technologies. In addition, maps-especially historical maps-are often the only information source about the earth as surveyed using geodetic techniques. Maps depict natural and human-induced changes on earth at a fine resolution for large areas and over long periods of time. The methods conducted are simple and robust and could be applied to other regions where historical charts with sufficient quality exist. The outcome of this research shows that the historical BA charts are an unconventional but extremely rich source of baseline coastal habitat data from the 19th century. Potential sources of uncertainty should be considered when working with the historic BA charts such as the surveyor's method for defining floating kelp features, the artistic ability of the cartographer when transcribing the information from the surveys to the BA charts, and the regional seasonality of kelp cover. Recently mapped kelp forests in similar areas reaffirmed the results of the produced baseline map. An accuracy assessment of the digitized kelp features concluded that 99% of the kelp features occurred in expected areas within a depth of less than 40 m, and only about 1% of the features occurred entirely outside of this depth. A total of 137 BA charts were scanned at 200 DPI, georeferenced, and kelp features were manually digitized following a rigorous method considering the scale and quality of the data. In this study, British Admiralty (BA) charts created between 18 covering the British Columbia coast and portions of the adjacent Washington and Alaska coast were used to create a digital historical baseline map of kelp presence. Spatial data such as aerial photos and satellite imagery are key for deriving kelp distribution however, they have only become available at an adequate quality within the 20th and 21st centuries. The quantification of kelp forest distribution across space and time is critical to support decision-makers responsible for habitat management and conservation.
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