Name
Abstract | ||
|---|---|---|
In this paper, we study the land use distribution of the city of Munich, Germany. We describe the city as a set of Urban Structural Types (UST) related to the type of spatial patterns occurring within regions composed of 200m side cells. To do so, we resort to a set of multimodal descriptors extracted from remote sensing data, a 3D city model and open access vector information. Based on these descriptors, we train a SVM classifier and apply two structured prediction models to enforce spatial relationships (Markov and Conditional Random fields). |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/JURSE.2015.7120489 | Urban Remote Sensing Event |
Keywords | Field | DocType |
remote sensing,support vector machines,solid modeling,markov processes | Conditional random field,Data mining,Markov process,Computer science,Markov chain,Support vector machine,Structured prediction,Solid modeling,Artificial intelligence,Spatial ecology,Machine learning,Land use | Conference |
Citations | PageRank | References |
2 | 0.45 | 14 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| arnaud poncet montanges | 1 | 2 | 0.45 |
| Gabriele Moser | 2 | 919 | 76.92 |
| hannes taubenbock | 3 | 2 | 0.45 |
| michael wurm | 4 | 2 | 0.45 |
| Devis Tuia | 5 | 1715 | 101.88 |