Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2
Sunlight is the primary source of energy in forest ecosystems and subcanopy light regimes largely determine the establishment, growth and dispersal of plants and thus forest floor plant communities. Subcanopy light regimes are highly variable in both space and time, which makes monitoring them chall...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-12-01
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| Series: | Science of Remote Sensing |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666017223000329 |
| _version_ | 1797401701218516992 |
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| author | Felix Glasmann Cornelius Senf Rupert Seidl Peter Annighöfer |
| author_facet | Felix Glasmann Cornelius Senf Rupert Seidl Peter Annighöfer |
| author_sort | Felix Glasmann |
| collection | DOAJ |
| description | Sunlight is the primary source of energy in forest ecosystems and subcanopy light regimes largely determine the establishment, growth and dispersal of plants and thus forest floor plant communities. Subcanopy light regimes are highly variable in both space and time, which makes monitoring them challenging. In this study, we assess the potential of Sentinel-1 and Sentinel-2 time series for predicting subcanopy light regimes in temperate mountain forests. We trained different random forest regression models predicting field-measured total site factor (TSF, proportion of potential direct and diffuse solar radiation reaching the forest floor, here defined as the transition zone between belowground and aboveground biomass) from a set of metrics derived from Sentinel-1 and Sentinel-2 time series. Model performance was benchmarked against a model based on structural metrics derived from Airborne Laser Scanning (ALS) data, serving as an empirical gold-standard in modelling subcanopy light regimes. We found that Sentinel-1 and Sentinel-2 time series performed nearly as good as the model based on high-resolution ALS data (R2/RMSE of 0.80/0.11 for Sentinel-1/2 compared to R2/RMSE of 0.90/0.08 for ALS). We furthermore tested the generalizability of the trained models to two new sites not used for training for which field data was available for validation. Prediction accuracy for the ALS model decreased substantially for the two independent test sites due to variable ALS data quality and acquisition date (ΔR2/ΔRMSE of 0.29/0.05 and 0.11/0.03 for both independent test sites). The prediction accuracy of the Sentinel-1/2 model, however, remained more stable (ΔR2/ΔRMSE of 0.13/0.02 and 0.13/0.04). We therefore conclude that a combination of Sentinel-1 and Sentinel-2 time series has the potential to map subcanopy light conditions spatially and temporally independent of the availability of high-resolution ALS data. This has important implications for the operational monitoring of forest ecosystems across large scales, which is often limited by the challenges related to acquiring airborne datasets. |
| first_indexed | 2024-03-09T02:13:53Z |
| format | Article |
| id | doaj.art-92768e54a1f148d785061a5768a22e7c |
| institution | Directory Open Access Journal |
| issn | 2666-0172 |
| language | English |
| last_indexed | 2024-03-09T02:13:53Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Science of Remote Sensing |
| spelling | doaj.art-92768e54a1f148d785061a5768a22e7c2023-12-07T05:30:20ZengElsevierScience of Remote Sensing2666-01722023-12-018100107Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2Felix Glasmann0Cornelius Senf1Rupert Seidl2Peter Annighöfer3Technical University of Munich, School of Life Sciences, Forest and Agroforest Systems, Hans-Carl-v.-Carlowitz-Platz 2, 85354, Freising, Germany; Corresponding author.Technical University of Munich, School of Life Sciences, Ecosystem Dynamics and Forest Management Group, Hans-Carl-v.-Carlowitz-Platz 2, 85354, Freising, GermanyTechnical University of Munich, School of Life Sciences, Ecosystem Dynamics and Forest Management Group, Hans-Carl-v.-Carlowitz-Platz 2, 85354, Freising, Germany; Berchtesgaden National Park, Doktorberg 6, 83471, Berchtesgaden, GermanyTechnical University of Munich, School of Life Sciences, Forest and Agroforest Systems, Hans-Carl-v.-Carlowitz-Platz 2, 85354, Freising, GermanySunlight is the primary source of energy in forest ecosystems and subcanopy light regimes largely determine the establishment, growth and dispersal of plants and thus forest floor plant communities. Subcanopy light regimes are highly variable in both space and time, which makes monitoring them challenging. In this study, we assess the potential of Sentinel-1 and Sentinel-2 time series for predicting subcanopy light regimes in temperate mountain forests. We trained different random forest regression models predicting field-measured total site factor (TSF, proportion of potential direct and diffuse solar radiation reaching the forest floor, here defined as the transition zone between belowground and aboveground biomass) from a set of metrics derived from Sentinel-1 and Sentinel-2 time series. Model performance was benchmarked against a model based on structural metrics derived from Airborne Laser Scanning (ALS) data, serving as an empirical gold-standard in modelling subcanopy light regimes. We found that Sentinel-1 and Sentinel-2 time series performed nearly as good as the model based on high-resolution ALS data (R2/RMSE of 0.80/0.11 for Sentinel-1/2 compared to R2/RMSE of 0.90/0.08 for ALS). We furthermore tested the generalizability of the trained models to two new sites not used for training for which field data was available for validation. Prediction accuracy for the ALS model decreased substantially for the two independent test sites due to variable ALS data quality and acquisition date (ΔR2/ΔRMSE of 0.29/0.05 and 0.11/0.03 for both independent test sites). The prediction accuracy of the Sentinel-1/2 model, however, remained more stable (ΔR2/ΔRMSE of 0.13/0.02 and 0.13/0.04). We therefore conclude that a combination of Sentinel-1 and Sentinel-2 time series has the potential to map subcanopy light conditions spatially and temporally independent of the availability of high-resolution ALS data. This has important implications for the operational monitoring of forest ecosystems across large scales, which is often limited by the challenges related to acquiring airborne datasets.http://www.sciencedirect.com/science/article/pii/S2666017223000329Airborne Laser ScanningSentinel-1Sentinel-2Light regimeForest structure |
| spellingShingle | Felix Glasmann Cornelius Senf Rupert Seidl Peter Annighöfer Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 Science of Remote Sensing Airborne Laser Scanning Sentinel-1 Sentinel-2 Light regime Forest structure |
| title | Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 |
| title_full | Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 |
| title_fullStr | Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 |
| title_full_unstemmed | Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 |
| title_short | Mapping subcanopy light regimes in temperate mountain forests from Airborne Laser Scanning, Sentinel-1 and Sentinel-2 |
| title_sort | mapping subcanopy light regimes in temperate mountain forests from airborne laser scanning sentinel 1 and sentinel 2 |
| topic | Airborne Laser Scanning Sentinel-1 Sentinel-2 Light regime Forest structure |
| url | http://www.sciencedirect.com/science/article/pii/S2666017223000329 |
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