Name
Title | ||
|---|---|---|
An Assessment Of Image Features And Random Forest For Land Cover Mapping Over Large Areas Using High Resolution Satellite Image Time Series |
Abstract | ||
|---|---|---|
New high resolution Satellite Image Time Series (SITS) are becoming crucial to land cover mapping over large areas. Their high temporal resolution will allow to better depict scene dynamics. However, it will also increase the amount of data to process. The classification of these data involves therefore new challenges such as: (1) selecting the best feature set to use as input data, (2) dealing with data variability coming from landscape diversity, and (3) establishing the robustness of existing classifiers over large areas. This work aims at addressing these questions through three different studies. Experimental results are obtained by using SPOT-4 and Landsat-8 SITS. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IGARSS.2016.7729863 | 2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) |
Keywords | Field | DocType |
Land cover mapping, Satellite Image Time Series, High resolution, Classification, Random Forest | Time series,Computer science,Feature (computer vision),Satellite Image Time Series,Remote sensing,Robustness (computer science),Random forest,Land cover,Temporal resolution,Image resolution | Conference |
ISSN | Citations | PageRank |
2153-6996 | 0 | 0.34 |
References | Authors | |
3 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Charlotte Pelletier | 1 | 66 | 5.97 |
| Silvia Valero | 2 | 171 | 13.81 |
| Jordi Inglada | 3 | 426 | 43.13 |
| Gérard Dedieu | 4 | 149 | 30.83 |
| Nicolas Champion | 5 | 0 | 0.34 |