| Autor: |
Sourabh Pargal, Rakesh Fararoda, Gopalakrishnan Rajashekar, Natesan Balachandran, Maxime Réjou-Méchain, Nicolas Barbier, Chandra Shekhar Jha, Raphaël Pélissier, Vinay Kumar Dadhwal, Pierre Couteron |
| Jazyk: |
angličtina |
| Rok vydání: |
2017 |
| Předmět: |
|
| Zdroj: |
Remote Sensing, Vol 9, Iss 3, p 228 (2017) |
| Druh dokumentu: |
article |
| ISSN: |
2072-4292 |
| DOI: |
10.3390/rs9030228 |
| Popis: |
Large scale assessment of aboveground biomass (AGB) in tropical forests is often limited by the saturation of remote sensing signals at high AGB values. Fourier Transform Textural Ordination (FOTO) performs well in quantifying canopy texture from very high-resolution (VHR) imagery, from which stand structure parameters can be retrieved with no saturation effect for AGB values up to 650 Mg·ha−1. The method is robust when tested on wet evergreen forests but is more demanding when applied across different forest types characterized by varying structures and allometries. The present study focuses on a gradient of forest types ranging from dry deciduous to wet evergreen forests in the Western Ghats (WG) of India, where we applied FOTO to Cartosat-1a images with 2.5 m resolution. Based on 21 1-ha ground control forest plots, we calibrated independent texture–AGB models for the dry and wet zone forests in the area, as delineated from the distribution of NDVI values computed from LISS-4 multispectral images. This stratification largely improved the relationship between texture-derived and field-derived AGB estimates, which exhibited a R2 of 0.82 for a mean rRMSE of ca. 17%. By inverting the texture–AGB models, we finally mapped AGB predictions at 1.6-ha resolution over a heterogeneous landscape of ca. 1500 km2 in the WG, with a mean relative per-pixel propagated error |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
