Estimation of forest development stage and crown closure using different classification methods and satellite images: A case study from Turkey
| Autor: | Sinan Bulut, Alkan Günlü, Sedat Keleş |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | Journal of Forest Science, Vol 65, Iss 1, Pp 18-26 (2019) |
| Druh dokumentu: | article |
| ISSN: | 1212-4834 1805-935X |
| DOI: | 10.17221/127/2018-JFS |
| Popis: | The objective of this study is to estimate stand development stages (SDS) and stand crown closures (SCC) of forest using different classification methods (maximum likelihood, support vector machine: linear, polynomial, radial and sigmoid kernel functions and artificial neural network) based on satellite imagery of different resolution (Landsat 7 ETM+ and IKONOS). The results showed that SDS and SCC were estimated with Landsat 7 ETM+ image using the artificial neural network with a 0.83 and 0.78 kappa statistic value, and 92.57 and 89.77% overall accuracy assessments, respectively. On the other hand, SDS and SCC were predicted with IKONOS image using support vector machine (polynomial) method with a 0.94 and 0.88 kappa statistic value, and 95.95 and 91.17% overall accuracy assessments, respectively. Our results demonstrated that IKONOS satellite image and support vector machine (polynomial) method produced a better estimation of SDS and SCC as compared to Landsat 7 ETM+ and other supervised classification methods used in this study. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|