Landmap was a service that provided UK geospatial data for academic use until its Joint Information Systems Committee (JISC) funding ceased in July 2014. Landmap hosted a large amount of data, including satellite imagery, digital elevation models (LiDAR, satellite and photgrammetric) and building heights and classifications. It was a sad day when Landmap was ‘switched off’, not least because it meant our GIS students had to put in a great deal more effort to find data for their projects!
The good news is that the Landmap data is now hosted at the Centre for Environmental Data Archival (CEDA) and is gradually becoming available once more for educational use. Those who used the previous incarnation of Landmap will have become familiar (or not) with the Kaia user interface. This has now gone, and all data is stored in a hierarchical file system organised into geographic regions. This is fairly coarse, with the highest spatial resolution typically being city.
So far, I have found that there is no unambiguous spatial reference in the naming scheme for files in some collections. This makes it difficult to find the data you want, for example, if there are 100 image files in the ‘London’ folder. I am currently documenting these cases to ensure I am the only one that has to spend time on it!
At the recent International Conference on GeoComputation at UT Dallas, I ran a workshop on Support Vector Machines for Spatial and Temporal Analysis. The participation was boosted to around 30 by the cancellation of one of the other workshops, and I thank those who expected to be discussing Emerging Trends in Data-Intensive, High Performance, and Scalable Geocomputation for their patience and effort!
This was the first workshop run by SpaceTimeLab, and was supported by the Crime, Policing and Citizenship Project (http://www.ucl.ac.uk/cpc/) and ISPRS Working Group II/5: GeoComputation and GeoSimulation (http://www2.isprs.org/commissions/comm2/wg5.html). The workshop was very enjoyable and I was incredibly impressed by the technical ability and enthusiasm of the participants.
At the end of the workshop I circulated a Google poll to get feedback and ideas for future workshops. Thank you to all who completed it. From the responses, it seems that Neural Networks are something that people are still very interested in learning more about. Random Forests also appear to be a hot topic. We are currently doing some work at SpaceTimeLab on Random Forests so I hope to make this a subject for a future workshop.
I will publish some of workshop materials on this site in the near future.
Were you at the workshop? If so feel free to add any more suggestions in the comments below. What should be the topic of SpaceTimeLab’s next workshop?