AUTOMATING THE PHOTOGRAMMETRIC WORKFLOW IN A NATIONAL MAPPING AGENCY

• Main Authors: D. Holland, C. Gladstone, I. Sargent, J. Horgan, A. Gardiner, M. Freeman
• Format: Article
• Language: English
• Published: Copernicus Publications 2012-07-01
• Series: ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
• Online Access: http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/I-4/83/2012/isprsannals-I-4-83-2012.pdf

The goal of automating the process of identifying changes to topographic features in aerial photography, extracting the geometry of these features and recording the changes in a database, is yet to be fully realised. At Ordnance Survey, Britain's national mapping agency, research into the automation of these processes has been underway for several years, and is now beginning to be implemented in production systems. <br><br> At the start of the processing chain is the identification of change &ndash; new buildings and roads being constructed, old structures demolished, alterations to field and vegetation boundaries and changes to inland water features. Using eCognition object-based image analysis techniques, a system has been developed to detect the changes to features. This uses four-band digital imagery (red, green, blue and near infra-red), together with a digital surface model derived by image matching, to identify all the topographic features of interest to a mapping agency. Once identified, these features are compared with those in the National Geographic Database and any potential changes are highlighted. These changes will be presented to photogrammetrists in the production area, who will rapidly assess whether or not the changes are real. If the change is accepted, they will manually capture the geometry and attributes of the feature concerned. <br><br> The change detection process, although not fully automatic, cuts down the amount of time required to update the database, enabling a more efficient data collection workflow. Initial results, on the detection of changes to buildings only, showed a completeness value (proportion of the real changes that were found) of 92% and a correctness value (proportion of the changes found that were real changes) of 22%, with a time saving of around 50% when compared with the equivalent manual process. The completeness value is similar to those obtained by the manual process. Further work on the process has added vegetation, water and many other rural features to the list of features that can be detected, and the system is currently being evaluated in a production environment. In addition to this work, the research team at Ordnance Survey are working with the remote sensing (data collection) department to develop more efficient methods of DSM and DTM creation; more automated seamline-generation for the creation of orthoimage mosaics; and methods to automatically record simple building heights on buildings in the database. These are all methods that have been proven in a research environment &ndash; the challenge is to implement them within the working environment of the existing data collection process.