ArcGIS Production Mapping
National mapping organizations must effectively maintain authoritative data and efficiently produce foundational information products, including maps, data, services, and apps. This requires constantly updating the base data to keep up with the pace of change. The demand by users for a wider variety of information products generated from that data is also increasing. These challenges can be met by leveraging GIS to automate workflows and reduce duplication of work.
Automate data and map production workflows by putting scripting geoprocessing tasks into repeatable workflows. This harnesses the hundreds of tasks GIS operators and cartographers do with Python scripts using ArcGIS geoprocessing tools. It frees staff to work on other geospatial information products your customers need. It also captures the knowledge base that would otherwise be lost when staff leave.
Maintain data once and leverage GIS to derive many information products at different resolutions. Realize significant savings by eliminating redundant data capture for various scales of data. That data can be automatically transformed and used for a variety of data and map information products. For the cost of collecting the data once, you can reap the benefits of reusing it many times.
Realize significant efficiencies by generating digital and hard-copy maps from the same database. Separate production lines and workers can be streamlined into one to create and maintain many different data and map products at various resolutions. Modernizing and automating workflows with ArcGIS increases productivity and maximizes your bottom line.
Map data quality and consistency are ensured with ArcGIS tools configured to reflect your business rules. Automated quality control is integrated into your production processes. Quality assurance tools ensure the integrity of your branded information products.
GEOSPATIAL DATA PRODUCTION
Dutch Kadaster, was the first mapping authority in the world to fully automate the production of multiscale maps and data.