Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools
The Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a sur...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/15/2970 |
| _version_ | 1797525185907130368 |
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| author | Borja Rodríguez-Lozano Emilio Rodríguez-Caballero Lisa Maggioli Yolanda Cantón |
| author_facet | Borja Rodríguez-Lozano Emilio Rodríguez-Caballero Lisa Maggioli Yolanda Cantón |
| author_sort | Borja Rodríguez-Lozano |
| collection | DOAJ |
| description | The Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a surrogate of many ecosystem functions and services and one of the main terrestrial carbon pools. Thus, accurate methodologies for AGB estimation are needed. This has been traditionally done by performing direct field measurements. However, field-based methods, such as biomass harvesting, are destructive, expensive, and time consuming and only provide punctual information, not being appropriate for large scale applications. Here, we propose a new non-destructive methodology for monitoring the spatiotemporal dynamics of AGB and green biomass (GB) of <i>M. tenacissima</i> L. plants by combining structural information obtained from terrestrial laser scanner (TLS) point clouds and spectral information. Our results demonstrate that the three volume measurement methods derived from the TLS point clouds tested (3D convex hull, voxel, and raster surface models) improved the results obtained by traditional field-based measurements. (Adjust-R<sup>2</sup> = 0.86–0.84 and RMSE = 927.3–960.2 g for AGB in OLS regressions and Adjust-R<sup>2</sup> = 0.93 and RMSE = 376.6–385.1 g for AGB in gradient boosting regression). Among the approaches, the voxel model at 5 cm of spatial resolution provided the best results; however, differences with the 3D convex hull and raster surface-based models were very small. We also found that by combining TLS AGB estimations with spectral information, green and dry biomass fraction can be accurately measured (Adjust-R<sup>2</sup> = 0.65–0.56 and RMSE = 149.96–166.87 g in OLS regressions and Adjust-R<sup>2</sup> = 0.96–0.97 and RMSE = 46.1–49.8 g in gradient boosting regression), which is critical in heterogeneous Mediterranean ecosystems in which AGB largely varies in response to climatic fluctuations. Thus, our results represent important progress for the measurement of <i>M. tenacissima</i> L. biomass and dynamics, providing a promising tool for calibration and validation of further studies aimed at developing new methodologies for AGB estimation at ecosystem regional scales. |
| first_indexed | 2024-03-10T09:09:12Z |
| format | Article |
| id | doaj.art-76ba4a6624074fdc8821ca53ef4c8277 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T09:09:12Z |
| publishDate | 2021-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-76ba4a6624074fdc8821ca53ef4c82772023-11-22T06:06:55ZengMDPI AGRemote Sensing2072-42922021-07-011315297010.3390/rs13152970Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing ToolsBorja Rodríguez-Lozano0Emilio Rodríguez-Caballero1Lisa Maggioli2Yolanda Cantón3Agronomy Department, University of Almería, 04120 Almería, SpainAgronomy Department, University of Almería, 04120 Almería, SpainAgronomy Department, University of Almería, 04120 Almería, SpainAgronomy Department, University of Almería, 04120 Almería, SpainThe Mediterranean region is experiencing a stronger warming effect than other regions, which has generated a cascade of negative impacts on productivity, biodiversity, and stability of the ecosystem. To monitor ecosystem status and dynamics, aboveground biomass (AGB) is a good indicator, being a surrogate of many ecosystem functions and services and one of the main terrestrial carbon pools. Thus, accurate methodologies for AGB estimation are needed. This has been traditionally done by performing direct field measurements. However, field-based methods, such as biomass harvesting, are destructive, expensive, and time consuming and only provide punctual information, not being appropriate for large scale applications. Here, we propose a new non-destructive methodology for monitoring the spatiotemporal dynamics of AGB and green biomass (GB) of <i>M. tenacissima</i> L. plants by combining structural information obtained from terrestrial laser scanner (TLS) point clouds and spectral information. Our results demonstrate that the three volume measurement methods derived from the TLS point clouds tested (3D convex hull, voxel, and raster surface models) improved the results obtained by traditional field-based measurements. (Adjust-R<sup>2</sup> = 0.86–0.84 and RMSE = 927.3–960.2 g for AGB in OLS regressions and Adjust-R<sup>2</sup> = 0.93 and RMSE = 376.6–385.1 g for AGB in gradient boosting regression). Among the approaches, the voxel model at 5 cm of spatial resolution provided the best results; however, differences with the 3D convex hull and raster surface-based models were very small. We also found that by combining TLS AGB estimations with spectral information, green and dry biomass fraction can be accurately measured (Adjust-R<sup>2</sup> = 0.65–0.56 and RMSE = 149.96–166.87 g in OLS regressions and Adjust-R<sup>2</sup> = 0.96–0.97 and RMSE = 46.1–49.8 g in gradient boosting regression), which is critical in heterogeneous Mediterranean ecosystems in which AGB largely varies in response to climatic fluctuations. Thus, our results represent important progress for the measurement of <i>M. tenacissima</i> L. biomass and dynamics, providing a promising tool for calibration and validation of further studies aimed at developing new methodologies for AGB estimation at ecosystem regional scales.https://www.mdpi.com/2072-4292/13/15/2970TLSremote sensingabove ground biomassdrylandgrasstussock |
| spellingShingle | Borja Rodríguez-Lozano Emilio Rodríguez-Caballero Lisa Maggioli Yolanda Cantón Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools Remote Sensing TLS remote sensing above ground biomass dryland grass tussock |
| title | Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools |
| title_full | Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools |
| title_fullStr | Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools |
| title_full_unstemmed | Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools |
| title_short | Non-Destructive Biomass Estimation in Mediterranean Alpha Steppes: Improving Traditional Methods for Measuring Dry and Green Fractions by Combining Proximal Remote Sensing Tools |
| title_sort | non destructive biomass estimation in mediterranean alpha steppes improving traditional methods for measuring dry and green fractions by combining proximal remote sensing tools |
| topic | TLS remote sensing above ground biomass dryland grass tussock |
| url | https://www.mdpi.com/2072-4292/13/15/2970 |
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