RT info:eu-repo/semantics/article
T1 Combining hand-held and drone-based lidar for forest carbon monitoring: insights from a Mediterranean mixed forest in central Portugal
A1 Tupinambá Simões, Frederico
A1 Pascual, Adrián
A1 Guerra Hernández, Juan
A1 Ordoñez Alonso, Ángel Cristobal
A1 Barreiro, Susana
A1 Bravo Oviedo, Felipe
K1 Precision forestry
K1 Forest monitoring
K1 Mobile laser scanning
K1 Forest inventory
K1 31 Ciencias Agrarias
AB The adoption of novel methods in forest management planning requires the incorporation of precise forest and tree data toimprove scheduling and meet multi-objective criteria principles. This study evaluates advanced methods for mapping treestructural attributes to create detailed baselines for forest carbon biomass, a key indicator in environmental policies. Wespecifically investigate the combined use of mobile sensors (hand-held laser scanning, HLS) and airborne (unmanned laserscanning, ULS), to estimate biomass and carbon stocks in a Mediterranean mixed forest. The novelty of our study lies in thesynergistic application of HLS and ULS technologies and the evaluation of different ULS flight altitudes (50, 70, 90, 110 m)and scanning modes to optimize data accuracy and coverage. The main questions addressed are: (1) How do different flightaltitudes and scanning modes of ULS affect the accuracy of biomass and carbon stock estimations? (2) What is the impact ofmerging HLS and ULS data on the precision of tree structural attribute measurements? (3) Can the combined use of HLS andULS overcome the limitations of individual systems, particularly in complex forest structures? Our case study is conductedin a 1-ha plot in a complex, terraced forest region in Central Portugal, chosen for its high species diversity and structuralcomplexity, which present significant challenges for remote sensing technologies. This site represents a typical Mediter-ranean mixed forest, allowing us to test methods in conditions that are both typical and challenging for forest monitoring.The distribution of HLS estimates was aligned with reference DBH measurement, though systematically lower (~ 2–3 cmbias). The impact of these measurement errors on total biomass estimation was around 13%. In contrast, major discrepancieswere observed in tree height estimations when comparing HLS, ULS, fused ULS-HLS point clouds, with field referencedata. ULS operated effectively at heights up to 110 m, increasing coverage without compromising result quality. However,merging point cloud datasets did not significantly improve the accuracy of tree height estimates due to the complexity andhigh species mingling of the forest stand. We recommend caution in using field measurements for validating tree heightestimates with laser sensors under these conditions.
PB Springer
SN 1612-4669
YR 2025
FD 2025
LK https://uvadoc.uva.es/handle/10324/75936
UL https://uvadoc.uva.es/handle/10324/75936
LA eng
NO European Journal of Forest Research, 2025.
NO Producción Científica
DS UVaDOC
RD 16-jun-2025