 |
| Titel |
Estimation of soil types by non linear analysis of remote sensing data |
| VerfasserIn |
C. Hahn, R. Gloaguen |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1023-5809
|
| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 15, no. 1 ; Nr. 15, no. 1 (2008-02-15), S.115-126 |
| Datensatznummer |
250012559
|
| Publikation (Nr.) |
 copernicus.org/npg-15-115-2008.pdf |
|
|
|
|
|
| Zusammenfassung |
| The knowledge of soil type and soil texture
is crucial for environmental monitoring purpose
and risk assessment. Unfortunately, their mapping using
classical techniques is time consuming and costly. We present here
a way to estimate soil types based on limited field observations and
remote sensing data. Due to the fact that the relation between the soil
types and the considered attributes that were extracted from remote sensing
data is expected to be non-linear, we apply Support Vector Machines (SVM) for
soil type classification. Special attention is drawn to different training site
distributions and the kind of input variables. We show that SVM based on carefully
selected input variables proved to be an appropriate method for soil type estimation. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|