- What is the spatial and temporal coverage of the map archive content and does it vary across different cartographic scales? The user will need to know the potential extent, temporally and spatially, of the extracted data to understand benefit and value of the intended information extraction effort and for comparing different map archives.
- How accurate is the georeference of maps contained in the archive? Does the accuracy vary in the spatio-temporal domain? This constitutes a pressing question if ancillary geospatial data is used for the information extraction and certain degrees of spatial alignment with map features are required. For example, if it is possible to a priori identify map sheets likely to suffer from a high degree of positional inaccuracy, the user can exclude those map sheets from template or training data collection and, thus, reduce the amount of noise in the collected training data.
- How much variability is there in the map content, regarding color, hue, contrast, and in the cartographic styles used to represent the symbol of interest? This is a central question affecting the choice and design of a suitable recognition model. More powerful models or even different models for certain types of maps may be required if the representation of map content of interest varies heavily across the map archive. Furthermore, knowledge of variations in map content and similarity between individual map sheets is useful to optimize the design of training data sampling and to ensure the collection of representative and balanced training samples.
2. Background and Related Research
2.1. Map Processing
2.2. Recent Developments in Map-Based Information Extraction
2.3. Image Information Mining
4.1. Metadata Analysis
4.1.1. Spatio-Temporal Coverage Analysis
4.1.2. Assessing Positional Accuracy
4.2. Content-Based Image Analysis
4.2.1. Low-Level Image Descriptors
4.2.2. Dimensionality Reduction
4.2.3. Multi-Level Content Analysis
5.1. Metadata Analysis
5.1.1. Metadata-Based Spatial-Temporal Coverage Analysis
5.1.2. Metadata-Based Spatial-Temporal Analysis of Positional Accuracy
5.2. Content-Based Analysis
5.2.1. Content-Based Analysis at the Map Level
5.2.2. Content-Based Analysis at Within-Map Patch Level
5.2.3. Content-Based Analysis at the Cross-Map Patch Level
6. Conclusions and Outlook
- Spatio-temporal coverage analysis:
- Estimation of the spatio-temporal coverage of the extracted data; and
- Guidance for the design of the training data collection, to ensure the collection of balanced and representative training data across the spatio-temporal domain.
- Spatio-temporal analysis of spatial accuracy:
- Estimating the spatial accuracy of the extracted data; and
- Excluding map sheets of potential low spatial accuracy to ensure high degrees of spatial alignment of map and ancillary data used for training data collection and, thus, to reduce noise in the collected training data
- Content-based image analysis:
- Assessing the variations in map content as a fundamental step in order to choose adequate information extraction methods capable of handling data of the given variability and to create representative training data accounting for such variations.
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