| Autor: |
Vahid Akbari, Svein Solberg, Stefano Puliti |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 5049-5063 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2151-1535 |
| DOI: |
10.1109/JSTARS.2021.3073101 |
| Popis: |
There is a need for mapping of forest areas with young stands under regeneration in Norway, as a basis for conducting tending, or precommercial thinning (PCT), whenever necessary. The main objective of this article is to show the potential of multitemporal Sentinel-1 (S-1) and Sentinel-2 (S-2) data for characterization and detection of forest stands under regeneration. We identify the most powerful radar and optical features for discrimination of forest stands under regeneration versus other forest stands. A number of optical and radar features derived from multitemporal S-1 and S-2 data were used for the class separability and cross-correlation analysis. The analysis was performed on forest resource maps consisting of the forest development classes and age in two study sites from south-eastern Norway. Important features were used to train the classical random forest (RF) classification algorithm. A comparative study of performance of the algorithm was used in three cases: I) using only S-1 features, II) using only S-2 optical bands, and III) using combination of S-1 and S-2 features. RF classification results pointed to increased class discrimination when using S-1 and S-2 data in relation to S-1 or S-2 data only. The study shows that forest stands under regeneration in the height interval for PCT can be detected with a detection rate of 91% and F-1 score of 73.2% in case III as most accurate, while tree density and broadleaf fraction could be estimated with coefficient of determination ($\text {R}^2$) of about 0.70 and 0.80, respectively. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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