High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica)
Tropical forests play a key role in global carbon cycle. Reducing Emissions from Deforestation and forest Degradation (REDD+) program requires reliable mechanisms for Monitoring, Reporting and Verification (MRV). In this regard, new methods must be developed using updated technologies to assess carb...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Italian Society of Silviculture and Forest Ecology (SISEF)
2017-02-01
|
| Series: | iForest - Biogeosciences and Forestry |
| Subjects: | |
| Online Access: | https://iforest.sisef.org/contents/?id=ifor1744-009 |
| _version_ | 1830485632717160448 |
|---|---|
| author | Fernández-Landa A Navarro JA Condés S Algeet-Abarquero N Marchamalo M |
| author_facet | Fernández-Landa A Navarro JA Condés S Algeet-Abarquero N Marchamalo M |
| author_sort | Fernández-Landa A |
| collection | DOAJ |
| description | Tropical forests play a key role in global carbon cycle. Reducing Emissions from Deforestation and forest Degradation (REDD+) program requires reliable mechanisms for Monitoring, Reporting and Verification (MRV). In this regard, new methods must be developed using updated technologies to assess carbon stocks. The combination of LiDAR technology and in situ forest networks allows the estimation of biomass with high resolution in low data environments, such as tropical countries. However, the evaluation of current LiDAR methods of biomass inventory, and the development of new methodologies to reduce uncertainty and increase accuracy, is still needed. Our aim is to evaluate new methodologies of spatially explicit LiDAR biomass inventories based on local and general plot-aggregate allometry. For this purpose, 25 field plots were inventoried, covering the structural and ecological variability of Poás Volcano National Park (Costa Rica). Important differences were detected in the estimation of aboveground biomass (92.74 t ha-1 considering the mean value of plot sample) depending on the chosen tree allometry. We validated the general aboveground biomass plot-aggregate allometry proposed by Asner & Mascaro (2014) in our study area, and we fitted two specific models for Poás forests. Both locals and general models depend on LiDAR top-of-canopy height (TCH), basal area (BA) and wood density. Small deviations in the wood density plot sample (0.60 ± 0.05) indicated that a single wood density constant value could be used throughout the study area. A BA-TCH origin forced linear model was fitted to estimate basal area, as suggested by the general methodology. Poás forest has a larger biomass density for the same THC compared to the rest of the forests previously studied, and shows that the BA-TCH relationship might have different trends in each life zone. Our results confirm that the general plot-aggregate methodology can be easily and reliably applied as aboveground biomass in a new area could be estimated by only measuring BA in field plots to obtain a local BA-TCH regression. For both local and general methods, the estimation of BA is critical. Therefore, the definition of precise basal area field measurement procedures is decisive to achieve reliable results in future studies. |
| first_indexed | 2024-12-21T18:29:09Z |
| format | Article |
| id | doaj.art-0fa4eac117774260bf813c6d8b448da9 |
| institution | Directory Open Access Journal |
| issn | 1971-7458 1971-7458 |
| language | English |
| last_indexed | 2024-12-21T18:29:09Z |
| publishDate | 2017-02-01 |
| publisher | Italian Society of Silviculture and Forest Ecology (SISEF) |
| record_format | Article |
| series | iForest - Biogeosciences and Forestry |
| spelling | doaj.art-0fa4eac117774260bf813c6d8b448da92022-12-21T18:54:19ZengItalian Society of Silviculture and Forest Ecology (SISEF)iForest - Biogeosciences and Forestry1971-74581971-74582017-02-0110125926610.3832/ifor1744-0091744High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica)Fernández-Landa A0Navarro JA1Condés S2Algeet-Abarquero N3Marchamalo M4Agresta Soc. Coop, C/ Duque de Fernán Núñez 2, Madrid 28012 (Spain)Agresta Soc. Coop, C/ Duque de Fernán Núñez 2, Madrid 28012 (Spain)Dept. Natural Systems and Resources, Technical University of Madrid. School of Forestry, Ciudad Universitaria, Madrid 28040 (Spain)Agresta Soc. Coop, C/ Duque de Fernán Núñez 2, Madrid 28012 (Spain)Dept. of Land Morphology and Engineering, Technical University of Madrid, Ciudad Universitaria, Madrid 28040 (Spain)Tropical forests play a key role in global carbon cycle. Reducing Emissions from Deforestation and forest Degradation (REDD+) program requires reliable mechanisms for Monitoring, Reporting and Verification (MRV). In this regard, new methods must be developed using updated technologies to assess carbon stocks. The combination of LiDAR technology and in situ forest networks allows the estimation of biomass with high resolution in low data environments, such as tropical countries. However, the evaluation of current LiDAR methods of biomass inventory, and the development of new methodologies to reduce uncertainty and increase accuracy, is still needed. Our aim is to evaluate new methodologies of spatially explicit LiDAR biomass inventories based on local and general plot-aggregate allometry. For this purpose, 25 field plots were inventoried, covering the structural and ecological variability of Poás Volcano National Park (Costa Rica). Important differences were detected in the estimation of aboveground biomass (92.74 t ha-1 considering the mean value of plot sample) depending on the chosen tree allometry. We validated the general aboveground biomass plot-aggregate allometry proposed by Asner & Mascaro (2014) in our study area, and we fitted two specific models for Poás forests. Both locals and general models depend on LiDAR top-of-canopy height (TCH), basal area (BA) and wood density. Small deviations in the wood density plot sample (0.60 ± 0.05) indicated that a single wood density constant value could be used throughout the study area. A BA-TCH origin forced linear model was fitted to estimate basal area, as suggested by the general methodology. Poás forest has a larger biomass density for the same THC compared to the rest of the forests previously studied, and shows that the BA-TCH relationship might have different trends in each life zone. Our results confirm that the general plot-aggregate methodology can be easily and reliably applied as aboveground biomass in a new area could be estimated by only measuring BA in field plots to obtain a local BA-TCH regression. For both local and general methods, the estimation of BA is critical. Therefore, the definition of precise basal area field measurement procedures is decisive to achieve reliable results in future studies.https://iforest.sisef.org/contents/?id=ifor1744-009CarbonRemote SensingREDDLiDARPlot-level AllometryBiomassBasal Area |
| spellingShingle | Fernández-Landa A Navarro JA Condés S Algeet-Abarquero N Marchamalo M High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) iForest - Biogeosciences and Forestry Carbon Remote Sensing REDD LiDAR Plot-level Allometry Biomass Basal Area |
| title | High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) |
| title_full | High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) |
| title_fullStr | High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) |
| title_full_unstemmed | High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) |
| title_short | High resolution biomass mapping in tropical forests with LiDAR-derived Digital Models: Poás Volcano National Park (Costa Rica) |
| title_sort | high resolution biomass mapping in tropical forests with lidar derived digital models poas volcano national park costa rica |
| topic | Carbon Remote Sensing REDD LiDAR Plot-level Allometry Biomass Basal Area |
| url | https://iforest.sisef.org/contents/?id=ifor1744-009 |
| work_keys_str_mv | AT fernandezlandaa highresolutionbiomassmappingintropicalforestswithlidarderiveddigitalmodelspoasvolcanonationalparkcostarica AT navarroja highresolutionbiomassmappingintropicalforestswithlidarderiveddigitalmodelspoasvolcanonationalparkcostarica AT condess highresolutionbiomassmappingintropicalforestswithlidarderiveddigitalmodelspoasvolcanonationalparkcostarica AT algeetabarqueron highresolutionbiomassmappingintropicalforestswithlidarderiveddigitalmodelspoasvolcanonationalparkcostarica AT marchamalom highresolutionbiomassmappingintropicalforestswithlidarderiveddigitalmodelspoasvolcanonationalparkcostarica |