| Autor: |
Unmesh Khati, Gulab Singh |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Frontiers in Forests and Global Change, Vol 5 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2624-893X |
| DOI: |
10.3389/ffgc.2022.918408 |
| Popis: |
Synthetic aperture radar (SAR) backscatter based above-ground biomass (AGB) estimates are limited by the saturation of the backscatter-AGB curve. This work explores the potential of combining backscatter with polarimetric SAR interferometry (PolInSAR) estimated forest stand height for improved AGB estimation. The models combining L-band backscatter and TanDEM-X height are compared with established backscatter based models. The models are also temporally cross-validated, i.e., trained on one acquisition date and validated for other dates. It is observed that with the input of height, the combined models perform significantly better than backscatter based models, with an improvement in root mean square error (RMSE) between 19% and 46%. The model utilizing HV-polarized backscatter and TanDEM-X PolInSAR height provide the best case AGB inversion with an R2 = 0.78 and an RMSE of 27.1 Mg/ha or 22% of mean AGB. The results demonstrate the potential of the synergistic combination of L-band PolSAR (backscatter) and X-band PolInSAR (height) products for AGB mapping over a tropical forest range in India. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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