Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar
Bamboo, a fast-growing vegetation with high carbon sequestration efficiency, is widely distributed across Asia, Central and South America, and Africa. However, mapping aboveground carbon (AGC) density (kgC m−2) in bamboo can be challenging due to the changing composition of old and new culms or the...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-09-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1569843223003114 |
| _version_ | 1797677652872527872 |
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| author | Hsiao-Lung Pan Chu-Mei Huang Cho-ying Huang |
| author_facet | Hsiao-Lung Pan Chu-Mei Huang Cho-ying Huang |
| author_sort | Hsiao-Lung Pan |
| collection | DOAJ |
| description | Bamboo, a fast-growing vegetation with high carbon sequestration efficiency, is widely distributed across Asia, Central and South America, and Africa. However, mapping aboveground carbon (AGC) density (kgC m−2) in bamboo can be challenging due to the changing composition of old and new culms or the phenology of the canopy. In this study, we conducted a UAV-lidar survey on 120 ha of subalpine dwarf bamboo (Yushania niitakayamensis) vegetation in Central Taiwan. We destructively collected dwarf bamboo plants from seventy-four 1 × 1 m plots and derived 64 spatially corresponding lidar height and density distribution metrics to model dwarf bamboo AGC density. We applied five regression models (stepwise linear regression, principal component regression, partial least squares regression, elastic net, and multivariate adaptive regression splines [MARS]) to model dwarf bamboo AGC density. MARS outperformed other models by referring to model residuals. The metrics zmax (maximum of lidar return height distribution), zq95 (95th percentile), and zq65 (65th percentile) were salient variables (p < 0.001), especially zq65, suggesting that the conventional model specification of height percentiles of the canopy top might overlook that near the canopy bottom or might be due to insufficient point density. Finally, we used MARS to map the dwarf bamboo AGC density of the study area. We found that AGC spatial variation in dwarf bamboo may be related to topographic characteristics and/or microclimate. This study proposes a regression model to integrate UAV-lidar metrics for precise subalpine dwarf bamboo carbon density mapping, aiding regional spatial carbon-cycle monitoring. |
| first_indexed | 2024-03-11T22:48:23Z |
| format | Article |
| id | doaj.art-025850e5f34e45e583ddc9d63bed57dc |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-03-11T22:48:23Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-025850e5f34e45e583ddc9d63bed57dc2023-09-22T04:38:21ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322023-09-01123103487Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidarHsiao-Lung Pan0Chu-Mei Huang1Cho-ying Huang2Department of Geography, National Taiwan University, Taipei 10617, Taiwan; Technical Service Division, Taiwan Forestry Research Institute, Taipei 10066, TaiwanSilviculture Division, Taiwan Forestry Research Institute, Taipei 10066, TaiwanDepartment of Geography, National Taiwan University, Taipei 10617, Taiwan; Research Center for Future Earth, National Taiwan University, Taipei 10617, Taiwan; Corresponding author at: 1 Sec. 4, Roosevelt Rd., Taipei 10617, Taiwan.Bamboo, a fast-growing vegetation with high carbon sequestration efficiency, is widely distributed across Asia, Central and South America, and Africa. However, mapping aboveground carbon (AGC) density (kgC m−2) in bamboo can be challenging due to the changing composition of old and new culms or the phenology of the canopy. In this study, we conducted a UAV-lidar survey on 120 ha of subalpine dwarf bamboo (Yushania niitakayamensis) vegetation in Central Taiwan. We destructively collected dwarf bamboo plants from seventy-four 1 × 1 m plots and derived 64 spatially corresponding lidar height and density distribution metrics to model dwarf bamboo AGC density. We applied five regression models (stepwise linear regression, principal component regression, partial least squares regression, elastic net, and multivariate adaptive regression splines [MARS]) to model dwarf bamboo AGC density. MARS outperformed other models by referring to model residuals. The metrics zmax (maximum of lidar return height distribution), zq95 (95th percentile), and zq65 (65th percentile) were salient variables (p < 0.001), especially zq65, suggesting that the conventional model specification of height percentiles of the canopy top might overlook that near the canopy bottom or might be due to insufficient point density. Finally, we used MARS to map the dwarf bamboo AGC density of the study area. We found that AGC spatial variation in dwarf bamboo may be related to topographic characteristics and/or microclimate. This study proposes a regression model to integrate UAV-lidar metrics for precise subalpine dwarf bamboo carbon density mapping, aiding regional spatial carbon-cycle monitoring.http://www.sciencedirect.com/science/article/pii/S1569843223003114Aboveground biomassBiomass-carbon conversionCanopy lidar metricsmultivariate adaptive regression splines (MARS)Topography |
| spellingShingle | Hsiao-Lung Pan Chu-Mei Huang Cho-ying Huang Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar International Journal of Applied Earth Observations and Geoinformation Aboveground biomass Biomass-carbon conversion Canopy lidar metrics multivariate adaptive regression splines (MARS) Topography |
| title | Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar |
| title_full | Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar |
| title_fullStr | Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar |
| title_full_unstemmed | Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar |
| title_short | Mapping aboveground carbon density of subtropical subalpine dwarf bamboo (Yushania niitakayamensis) vegetation using UAV-lidar |
| title_sort | mapping aboveground carbon density of subtropical subalpine dwarf bamboo yushania niitakayamensis vegetation using uav lidar |
| topic | Aboveground biomass Biomass-carbon conversion Canopy lidar metrics multivariate adaptive regression splines (MARS) Topography |
| url | http://www.sciencedirect.com/science/article/pii/S1569843223003114 |
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