EuroSDR Projects - Host Ireland

Implementation
The project should be implemented by the formation of a working group (WG), with a proposed lifetime
of one and a half to two years from its constitution. It is proposed that the Chair/Co-Chair of the
WG are respectively: Helmut Mayer, UniBW München and Emmanuel Baltsavias, ETH Zürich. The
WG will recruit members among researchers active in the field, data producers and users, as well as
commercial vendors. A list of potential interested groups has already being compiled. These groups
will be informed of the aims and plans of the WG and will be asked for input to refine the aims and
finalize activities. Concrete plans and activities include:
1. Establishment of a web-page with full and up-to-date information. The WG aims could be officially
announced and presented (kick-off) at a planned workshop "Incremental Updating" before Intergeo,
14-15 October 2002, Frankfurt.
2. Distribution of a questionnaire to data producers and users mainly including NMCAs and firms
producing digital road maps, especially for car navigation.
3. Distribution of a questionnaire to researchers in the field, including groups outside Europe.
4. Preparation of a report summarizing the outcome of points 2 and 3 and giving an overview and
classification of existing methods and the state-of-the-art in the field, including an extensive literature
review, for which much material has been already collected. Road modeling aspects as well as data
structures, e.g., hierarchical, object-oriented, play a significant role for successful extraction and will
be treated accordingly. Attribute information, although currently mainly neglected, may be of
importance for generation of a rich and useful road database. Attributes could include width, number
of lanes, road class, (coarse) surface material, road markings, etc. Attention will also be paid to related
tasks such as automatic generalization and data mining. Knowledge about automated generalization
may lead to a refined search space when starting from given generalized map data, while data mining
or machine learning can discover and formulate properties hidden in existing road databases, which
can be favorably exploited in the update and refinement. The results of this point will be preferably
presented within a larger, already planned event such as the Joint ISPRS Conference
"Photogrammetric Image Analysis", 17-19 September 2003, Munich.
5. Preparation and distribution of test data sets, including extensive documentation. At this stage,
evaluation procedures for the results and quantitative quality measures should be elaborated and
finalized before point 6 below.
The test and related data will be designed in a way that it will allow the participation of groups using
various methods and data: single/stereo/multiple images, black and white (B/W)/color/CIR imagery,
DSMs/DTMs stemming from photogrammetry or ALS, 2D/3D extraction, semi-/fully automated
methods, etc. However, the test will clearly focus towards (3D) approaches that aim at operational
procedures and the extraction of a large part of the road network and not just a few (isolated) road
sides/edges. The input and output data requirements will basically comply with the needs of European
NMCAs. For example, aerial color stereo film imagery of scale 1:15,000-1:30,000 will mainly be
used together with existing DTMs and vector GIS/map data. To reduce the amount of data and
simplify their processing and analysis, as well as for better focus, uncommon data, such as CIR, may
be made available at a limited extent. The data will focus on low to medium difficulty cases, i.e., flat
to hilly terrain, rural and suburban areas. A limited amount of urban data may be made available to
demonstrate the limitations of some recent approaches. Accurate reference data, possibly with some
attributes, like width, will be provided for the major part of the data set. If data from the new digital
photogrammetric cameras is available sufficiently early, it will be integrated. For the provision of test
and reference data, the support of NMCAs is a must. Such data already exist in Switzerland and
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