Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors
Currently, climate change requires the quantification of carbon stored in forest biomass. Synthetic aperture radar (SAR) data offers a significant advantage over other remote detection measurement methods in providing structural and biomass-related information about ecosystems. This study aimed to d...
| Autores principales: | , , , |
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| Formato: | Artículo |
| Lenguaje: | English |
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MDPI AG
2023-07-01
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| Colección: | Remote Sensing |
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| Acceso en línea: | https://www.mdpi.com/2072-4292/15/13/3430 |
| _version_ | 1827734531944218624 |
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| author | Edward A. Velasco Pereira María A. Varo Martínez Francisco J. Ruiz Gómez Rafael M. Navarro-Cerrillo |
| author_facet | Edward A. Velasco Pereira María A. Varo Martínez Francisco J. Ruiz Gómez Rafael M. Navarro-Cerrillo |
| author_sort | Edward A. Velasco Pereira |
| collection | DOAJ |
| description | Currently, climate change requires the quantification of carbon stored in forest biomass. Synthetic aperture radar (SAR) data offers a significant advantage over other remote detection measurement methods in providing structural and biomass-related information about ecosystems. This study aimed to develop non-parametric Random Forest regression models to assess the changes in the aboveground forest biomass (AGB), basal area (G), and tree density (N) of Mediterranean pine forests by integrating ALOS-PALSAR, Sentinel 1, and Landsat 8 data. Variables selected from the Random Forest models were related to NDVI and optical textural variables. For 2015, the biomass models with the highest performance integrated ALS-ALOS2-Sentinel 1-Landsat 8 data (R<sup>2</sup> = 0.59) by following the model using ALS data (R<sup>2</sup> = 0.56), and ALOS2-Sentinel 1-Landsat 8 (R<sup>2</sup> = 0.50). The validation set showed that R<sup>2</sup> values vary from 0.55 (ALOS2-Sentinel 1-Landsat 8) to 0.60 (ALS-ALOS2-Sentinel 1-Landsat 8 model) with RMSE below 20 Mg ha<sup>−1</sup>. It is noteworthy that the individual Sentinel 1 (R<sup>2</sup> = 0.49). and Landsat 8 (R<sup>2</sup> = 0.47) models yielded equivalent results. For 2020, the AGB model ALOS2-Sentinel 1-Landsat 8 had a performance of R<sup>2</sup> = 0.55 (validation R<sup>2</sup> = 0.70) and a RMSE of 9.93 Mg ha<sup>−1</sup>. For the 2015 forest structural variables, Random Forest models, including ALOS PAL-SAR 2-Sentinel 1 Landsat 8 explained between 30% and 55% of the total variance, and for the 2020 models, they explained between 25% and 55%. Maps of the forests’ structural variables were generated for 2015 and 2020 to assess the changes during this period using the ALOS PALSAR 2-Sentinel 1-Landsat 8 model. Aboveground biomass (AGB), diameter at breast height (dbh), and dominant height (Ho) maps were consistent throughout the entire study area. However, the Random Forest models underestimated higher biomass levels (>100 Mg ha<sup>−1</sup>) and overestimated moderate biomass levels (30–45 Mg ha<sup>−1</sup>). The AGB change map showed values ranging from gains of 43.3 Mg ha<sup>−1</sup> to losses of −68.8 Mg ha<sup>−1</sup> during the study period. The integration of open-access satellite optical and SAR data can significantly enhance AGB estimates to achieve consistent and long-term monitoring of forest carbon dynamics. |
| first_indexed | 2024-03-11T01:29:57Z |
| format | Article |
| id | doaj.art-03610ac976a4471e83574988965e7978 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-11T01:29:57Z |
| publishDate | 2023-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-03610ac976a4471e83574988965e79782023-11-18T17:26:12ZengMDPI AGRemote Sensing2072-42922023-07-011513343010.3390/rs15133430Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 SensorsEdward A. Velasco Pereira0María A. Varo Martínez1Francisco J. Ruiz Gómez2Rafael M. Navarro-Cerrillo3Silviculture Laboratory, Dendrochronology, and Climate Change, DendrodatLab-ERSAF, Department of Forestry Engineering, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, SpainSilviculture Laboratory, Dendrochronology, and Climate Change, DendrodatLab-ERSAF, Department of Forestry Engineering, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, SpainSilviculture Laboratory, Dendrochronology, and Climate Change, DendrodatLab-ERSAF, Department of Forestry Engineering, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, SpainSilviculture Laboratory, Dendrochronology, and Climate Change, DendrodatLab-ERSAF, Department of Forestry Engineering, University of Cordoba, Campus de Rabanales, Crta. IV, km. 396, E-14071 Córdoba, SpainCurrently, climate change requires the quantification of carbon stored in forest biomass. Synthetic aperture radar (SAR) data offers a significant advantage over other remote detection measurement methods in providing structural and biomass-related information about ecosystems. This study aimed to develop non-parametric Random Forest regression models to assess the changes in the aboveground forest biomass (AGB), basal area (G), and tree density (N) of Mediterranean pine forests by integrating ALOS-PALSAR, Sentinel 1, and Landsat 8 data. Variables selected from the Random Forest models were related to NDVI and optical textural variables. For 2015, the biomass models with the highest performance integrated ALS-ALOS2-Sentinel 1-Landsat 8 data (R<sup>2</sup> = 0.59) by following the model using ALS data (R<sup>2</sup> = 0.56), and ALOS2-Sentinel 1-Landsat 8 (R<sup>2</sup> = 0.50). The validation set showed that R<sup>2</sup> values vary from 0.55 (ALOS2-Sentinel 1-Landsat 8) to 0.60 (ALS-ALOS2-Sentinel 1-Landsat 8 model) with RMSE below 20 Mg ha<sup>−1</sup>. It is noteworthy that the individual Sentinel 1 (R<sup>2</sup> = 0.49). and Landsat 8 (R<sup>2</sup> = 0.47) models yielded equivalent results. For 2020, the AGB model ALOS2-Sentinel 1-Landsat 8 had a performance of R<sup>2</sup> = 0.55 (validation R<sup>2</sup> = 0.70) and a RMSE of 9.93 Mg ha<sup>−1</sup>. For the 2015 forest structural variables, Random Forest models, including ALOS PAL-SAR 2-Sentinel 1 Landsat 8 explained between 30% and 55% of the total variance, and for the 2020 models, they explained between 25% and 55%. Maps of the forests’ structural variables were generated for 2015 and 2020 to assess the changes during this period using the ALOS PALSAR 2-Sentinel 1-Landsat 8 model. Aboveground biomass (AGB), diameter at breast height (dbh), and dominant height (Ho) maps were consistent throughout the entire study area. However, the Random Forest models underestimated higher biomass levels (>100 Mg ha<sup>−1</sup>) and overestimated moderate biomass levels (30–45 Mg ha<sup>−1</sup>). The AGB change map showed values ranging from gains of 43.3 Mg ha<sup>−1</sup> to losses of −68.8 Mg ha<sup>−1</sup> during the study period. The integration of open-access satellite optical and SAR data can significantly enhance AGB estimates to achieve consistent and long-term monitoring of forest carbon dynamics.https://www.mdpi.com/2072-4292/15/13/3430biomassALOSSENTINEL 1LANDSAT 8polarizationbackscatter |
| spellingShingle | Edward A. Velasco Pereira María A. Varo Martínez Francisco J. Ruiz Gómez Rafael M. Navarro-Cerrillo Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors Remote Sensing biomass ALOS SENTINEL 1 LANDSAT 8 polarization backscatter |
| title | Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors |
| title_full | Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors |
| title_fullStr | Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors |
| title_full_unstemmed | Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors |
| title_short | Temporal Changes in Mediterranean Pine Forest Biomass Using Synergy Models of ALOS PALSAR-Sentinel 1-Landsat 8 Sensors |
| title_sort | temporal changes in mediterranean pine forest biomass using synergy models of alos palsar sentinel 1 landsat 8 sensors |
| topic | biomass ALOS SENTINEL 1 LANDSAT 8 polarization backscatter |
| url | https://www.mdpi.com/2072-4292/15/13/3430 |
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