Hi everyone, We will start adding tags this week. A list of usernames that will be performing the tasks is here:
https://github.com/osmlab/sf_building_height_import/issues/23 Tasks will be tracked at a new project on the main openstreetmap.us Tasking Manager: http://tasks.openstreetmap.us/project/71 Other questions and comments can be put in our GitHub repo or Gitter channel. We're also arranging for a community mapping event in San Francisco. Brandon On Fri, Nov 18, 2016 at 4:25 PM, Brandon Liu <b...@bdon.org> wrote: > Hi Christoph, > > For data accuracy: > > Yes, our goal is to automate the tagging for flat-roofed and > unobstructed buildings. Sloped or uneven roofs and trees can be > identified in the JOSM hillshade tileset [0]. Mappers will then refer > to the raw LIDAR or street level imagery to determine the correct > height. > > We want to prepare for mappers a complete set of tools and imagery to > create an accurate dataset. We believe the result will be up to the > standards of height data elsewhere in OSM. It should also be better > than a mapper on foot could estimate without special equipment. > > For the community: > > I don't believe that this import will discourage community mapping. I > used the Overpass API and found only 424 edit actions since 2012 > adding a height tag to a building in San Francisco. Details are on > GitHub here [1]. > > Two users are responsible for 65% of these building height edits. > There are only 10 users total who have added a building height tag to > more than 2 buildings. I have messaged all these users, inviting > comments on the wiki. These results suggest to me that heights are not > a current focus of mapping in the affected area. > > I do think that getting started with building heights will encourage > further mapping. A complete 3D dataset like in New York City is a > great showcase for OSM data and attracts new users. Getting to a > similar level of detail in San Francisco is a compelling goal for the > local community. We've had offers to help from local meetup groups and > companies that are excited about the project. > > Brandon > > [0] > https://wiki.openstreetmap.org/wiki/San_Francisco_Building_Height_Import#Failure_Modes > [1] https://github.com/osmlab/sf_building_height_import/issues/21 > > On Thu, Nov 17, 2016 at 9:41 AM, Christoph Hormann <chris_horm...@gmx.de> > wrote: >> >> First of all thanks for doing a more elaborate preparation than back in >> May. The whole process is now much clearer. >> >> To verify my understanding: the height values you assign are the median >> height values of the city footprint data set when there is a matching >> footprint within the area percentage cutoff chosen. >> >> This median height value is the median height in the 0.5m gridded data >> set within the city dataset footprint that has been calculated as the >> difference between a gridded first reflector data set and a gridded >> ground level data set, both derived from the raw LIDAR data. >> >> I am sure this often leads to fairly reasonable results, in particular >> with flat top buildings and flat ground with no significant structures >> except the buildings but it does not appear to be a really good >> approach in principle. >> >> Sources of error here are not only the systematic error with non-flat >> roofs, the footprint mismatch and obstructions of the roof. Likewise >> important are the inaccuracies introduced by the grid sampling step and >> ambiguities in the ground level definition like plants, cars and >> non-building structures. >> >> These technical things aside i am not sure it is a good idea to enter >> this kind of data in OSM. This likely won't encourage community >> mapping and it will be of little gain for data users. Producing a >> separate point data set with the height values that can be easily >> matched with the OSM geometries would IMO be better. You could then >> also replace the fixed geometry matching cutoff with a reliability >> attribute and data users could decide how strict they want to be in >> that regard. >> >> -- >> Christoph Hormann >> http://www.imagico.de/ >> >> _______________________________________________ >> Imports mailing list >> Imports@openstreetmap.org >> https://lists.openstreetmap.org/listinfo/imports _______________________________________________ Imports mailing list Imports@openstreetmap.org https://lists.openstreetmap.org/listinfo/imports