Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest
Bibliographic Data
| ID | 22033618 |
|---|---|
| Authors | Dimitris Stratoulias (0000-0002-3133-9432, Prince of Songkla University), Narissara Nuthammachot (0000-0001-7975-2018, Prince of Songkla University), Tanita Suepa (National Science and Technology Development Agency), Khamphe Phoungthong (0000-0003-4218-1439, Prince of Songkla University, corresponding author) |
| Year | 2022 |
| Volume | 11 |
| Issue | 3 |
| Pages | 199 |
| Publication date | 2022-03-16 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi11030199 |
| OpenAlex | W4220753913 |
| Language | EN |
| References cited | 86 |
Earth Observation (EO) spectral indices have been an important tool for quantifying and monitoring forest biomass. Nevertheless, the selection of the bands and their combination is often realized based on preceding studies or generic assumptions. The current study investigates the relationship between satellite spectral information and the Above Ground Biomass (AGB) of a major private forest on the island of Java, Indonesia. Biomass-related traits from a total of 1517 trees were sampled in situ and their AGB were estimated from species-specific allometric models. In parallel, the exhaustive band combinations of the Ratio Spectral Index (RSI) were derived from near-concurrently acquired Sentinel-1 and Sentinel-2 images. By applying scenarios based on the entire dataset, the prevalence and monodominance of acacia, mahogany, and teak tree species were investigated. The best-performing index for the entire dataset yielded R2 = 0.70 (R2 = 0.78 when considering only monodominant plots). An application of eight traditional vegetation indices provided, at best, R2 = 0.65 for EVI, which is considerably lower compared to the RSI best combination. We suggest that an investigation of the complete band combinations as a proxy of retrieving biophysical parameters may provide more accurate results than the blind application of popular spectral indices and that this would take advantage of the amplified information obtained from modern satellite systems
Biology · Earth observation · Geography · Leaf area index · Physics · Remote sensing · Satellite · Spectral bands · Statistics · Environmental Science · Land Use and Ecosystem Services · Mathematics · Remote Sensing and LiDAR Applications · Remote Sensing in Agriculture · Ecology
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| Highly cited | No |
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