Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest
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 betwe...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/11/3/199 |
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| author | Dimitris Stratoulias Narissara Nuthammachot Tanita Suepa Khamphe Phoungthong |
| author_facet | Dimitris Stratoulias Narissara Nuthammachot Tanita Suepa Khamphe Phoungthong |
| author_sort | Dimitris Stratoulias |
| collection | DOAJ |
| description | 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 R<sup>2</sup> = 0.70 (R<sup>2</sup> = 0.78 when considering only monodominant plots). An application of eight traditional vegetation indices provided, at best, R<sup>2</sup> = 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. |
| first_indexed | 2024-03-09T19:43:59Z |
| format | Article |
| id | doaj.art-09524a05d2544d458092ca0e60dc11bb |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-09T19:43:59Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-09524a05d2544d458092ca0e60dc11bb2023-11-24T01:28:44ZengMDPI AGISPRS International Journal of Geo-Information2220-99642022-03-0111319910.3390/ijgi11030199Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical ForestDimitris Stratoulias0Narissara Nuthammachot1Tanita Suepa2Khamphe Phoungthong3Environmental Assessment and Technology for Hazardous Waste Management Research Center, Faculty of Environmental Management, Prince of Songkla University, Songkhla 90112, ThailandFaculty of Environmental Management, Prince of Songkla University, Songkhla 90112, ThailandGeo-Informatics and Space Technology Development Agency (GISTDA), Chonburi 20230, ThailandEnvironmental Assessment and Technology for Hazardous Waste Management Research Center, Faculty of Environmental Management, Prince of Songkla University, Songkhla 90112, ThailandEarth 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 R<sup>2</sup> = 0.70 (R<sup>2</sup> = 0.78 when considering only monodominant plots). An application of eight traditional vegetation indices provided, at best, R<sup>2</sup> = 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.https://www.mdpi.com/2220-9964/11/3/199remote sensingdata fusiontropical forestcomplete band combinationsvegetation indices |
| spellingShingle | Dimitris Stratoulias Narissara Nuthammachot Tanita Suepa Khamphe Phoungthong Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest ISPRS International Journal of Geo-Information remote sensing data fusion tropical forest complete band combinations vegetation indices |
| title | Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest |
| title_full | Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest |
| title_fullStr | Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest |
| title_full_unstemmed | Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest |
| title_short | Assessing the Spectral Information of Sentinel-1 and Sentinel-2 Satellites for Above-Ground Biomass Retrieval of a Tropical Forest |
| title_sort | assessing the spectral information of sentinel 1 and sentinel 2 satellites for above ground biomass retrieval of a tropical forest |
| topic | remote sensing data fusion tropical forest complete band combinations vegetation indices |
| url | https://www.mdpi.com/2220-9964/11/3/199 |
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