Name
Abstract | ||
|---|---|---|
A novel multiannual land-cover-classification scheme for classifying hypertemporal image data is suggested, which is based on a supervised decision fusion (DF) approach. This DF approach comprises two steps: First, separate support vector machines (SVMs) are trained for normalized difference vegetation index (NDVI) time-series and mean annual temperature values of three consecutive years. In the s... |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/LGRS.2009.2021960 | IEEE Geoscience and Remote Sensing Letters |
Keywords | Field | DocType |
Vegetation mapping,Support vector machines,Support vector machine classification,Radiometry,Spatial resolution,Associate members,Image resolution,MODIS,Remote sensing,Ocean temperature | Data mining,Data set,Support vector machine,Remote sensing,Robustness (computer science),Advanced very-high-resolution radiometer,Posterior probability,Normalized Difference Vegetation Index,Majority rule,Contextual image classification,Mathematics | Journal |
Volume | Issue | ISSN |
6 | 3 | 1545-598X |
Citations | PageRank | References |
5 | 0.73 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| T. Udelhoven | 1 | 13 | 1.45 |
| S. van der Linden | 2 | 5 | 0.73 |
| B. Waske | 3 | 131 | 8.94 |
| M. Stellmes | 4 | 22 | 4.10 |
| L. Hoffmann | 5 | 31 | 5.23 |