Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing
The estimation of forest biomass by remote sensing is constrained by different uncertainties. An important source of uncertainty is the border effect, as tree crowns are not constrained by plot borders. Lidar remote sensing systems record the canopy height within a certain area, while the ground-tru...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/8/1592 |
| _version_ | 1797537027665690624 |
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| author | Nikolai Knapp Andreas Huth Rico Fischer |
| author_facet | Nikolai Knapp Andreas Huth Rico Fischer |
| author_sort | Nikolai Knapp |
| collection | DOAJ |
| description | The estimation of forest biomass by remote sensing is constrained by different uncertainties. An important source of uncertainty is the border effect, as tree crowns are not constrained by plot borders. Lidar remote sensing systems record the canopy height within a certain area, while the ground-truth is commonly the aboveground biomass of inventory trees geolocated at their stem positions. Hence, tree crowns reaching out of or into the observed area are contributing to the uncertainty in canopy-height–based biomass estimation. In this study, forest inventory data and simulations of a tropical rainforest’s canopy were used to quantify the amount of incoming and outgoing canopy volume and surface at different plot sizes (10, 20, 50, and 100 m). This was performed with a bottom-up approach entirely based on forest inventory data and allometric relationships, from which idealized lidar canopy heights were simulated by representing the forest canopy as a 3D voxel space. In this voxel space, the position of each voxel is known, and it is also known to which tree each voxel belongs and where the stem of this tree is located. This knowledge was used to analyze the role of incoming and outgoing crowns. The contribution of the border effects to the biomass estimation uncertainty was quantified for the case of small-footprint lidar (a simulated canopy height model, CHM) and large-footprint lidar (simulated waveforms with footprint sizes of 23 and 65 m, corresponding to the GEDI and ICESat GLAS sensors). A strong effect of spatial scale was found: e.g., for 20-m plots, on average, 16% of the CHM surface belonged to trees located outside of the plots, while for 100-m plots this incoming CHM fraction was only 3%. The border effects accounted for 40% of the biomass estimation uncertainty at the 20-m scale, but had no contribution at the 100-m scale. For GEDI- and GLAS-based biomass estimates, the contributions of border effects were 23% and 6%, respectively. This study presents a novel approach for disentangling the sources of uncertainty in the remote sensing of forest structures using virtual canopy modeling. |
| first_indexed | 2024-03-10T12:09:16Z |
| format | Article |
| id | doaj.art-08993fdfafba48448a920c489dd429d1 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T12:09:16Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-08993fdfafba48448a920c489dd429d12023-11-21T16:18:32ZengMDPI AGRemote Sensing2072-42922021-04-01138159210.3390/rs13081592Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote SensingNikolai Knapp0Andreas Huth1Rico Fischer2Department of Ecological Modelling, Helmholtz Centre for Environmental Research—UFZ, 04318 Leipzig, GermanyDepartment of Ecological Modelling, Helmholtz Centre for Environmental Research—UFZ, 04318 Leipzig, GermanyDepartment of Ecological Modelling, Helmholtz Centre for Environmental Research—UFZ, 04318 Leipzig, GermanyThe estimation of forest biomass by remote sensing is constrained by different uncertainties. An important source of uncertainty is the border effect, as tree crowns are not constrained by plot borders. Lidar remote sensing systems record the canopy height within a certain area, while the ground-truth is commonly the aboveground biomass of inventory trees geolocated at their stem positions. Hence, tree crowns reaching out of or into the observed area are contributing to the uncertainty in canopy-height–based biomass estimation. In this study, forest inventory data and simulations of a tropical rainforest’s canopy were used to quantify the amount of incoming and outgoing canopy volume and surface at different plot sizes (10, 20, 50, and 100 m). This was performed with a bottom-up approach entirely based on forest inventory data and allometric relationships, from which idealized lidar canopy heights were simulated by representing the forest canopy as a 3D voxel space. In this voxel space, the position of each voxel is known, and it is also known to which tree each voxel belongs and where the stem of this tree is located. This knowledge was used to analyze the role of incoming and outgoing crowns. The contribution of the border effects to the biomass estimation uncertainty was quantified for the case of small-footprint lidar (a simulated canopy height model, CHM) and large-footprint lidar (simulated waveforms with footprint sizes of 23 and 65 m, corresponding to the GEDI and ICESat GLAS sensors). A strong effect of spatial scale was found: e.g., for 20-m plots, on average, 16% of the CHM surface belonged to trees located outside of the plots, while for 100-m plots this incoming CHM fraction was only 3%. The border effects accounted for 40% of the biomass estimation uncertainty at the 20-m scale, but had no contribution at the 100-m scale. For GEDI- and GLAS-based biomass estimates, the contributions of border effects were 23% and 6%, respectively. This study presents a novel approach for disentangling the sources of uncertainty in the remote sensing of forest structures using virtual canopy modeling.https://www.mdpi.com/2072-4292/13/8/1592tropical forestsaboveground biomassplot borderstree crownsuncertaintylidar simulations |
| spellingShingle | Nikolai Knapp Andreas Huth Rico Fischer Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing Remote Sensing tropical forests aboveground biomass plot borders tree crowns uncertainty lidar simulations |
| title | Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing |
| title_full | Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing |
| title_fullStr | Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing |
| title_full_unstemmed | Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing |
| title_short | Tree Crowns Cause Border Effects in Area-Based Biomass Estimations from Remote Sensing |
| title_sort | tree crowns cause border effects in area based biomass estimations from remote sensing |
| topic | tropical forests aboveground biomass plot borders tree crowns uncertainty lidar simulations |
| url | https://www.mdpi.com/2072-4292/13/8/1592 |
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