Please use this identifier to cite or link to this item: http://cicy.repositorioinstitucional.mx/jspui/handle/1003/1535
Effects of sample plot size and GPS location errors on aboveground biomass estimates from LiDAR in tropical dry forests
JOSE LUIS HERNANDEZ STEFANONI
GABRIELA REYES PALOMEQUE
MIGUEL ANGEL CASTILLO SANTIAGO
STEPHANIE PATRICIA GEORGE CHACON
ASTRID HELENA HUECHACONA RUIZ
Fernando de Jesús Tun Dzul
DINOSCA DULMARY RONDON RIVERA
JUAN MANUEL DUPUY RADA
Acceso Abierto
Atribución-NoComercial-SinDerivadas
10.3390/rs10101586
AIRBORNE LASER SCANNER
FOREST BIOMASS
PLOT SIZE
CO-REGISTRATION ERROR
MONTE CARLO SIMULATION
Accurate estimates of above ground biomass (AGB) are needed for monitoring carbon in tropical forests. LiDAR data can provide precise AGB estimations because it can capture the horizontal and vertical structure of vegetation. However, the accuracy of AGB estimations from LiDAR is affected by a co-registration error between LiDAR data and field plots resulting in spatial discrepancies between LiDAR and field plot data. Here, we evaluated the impacts of plot location error and plot size on the accuracy of AGB estimations predicted from LiDAR data in two types of tropical dry forests in Yucatán, México. We sampled woody plants of three size classes in 29 nested plots (80 m2, 400 m2 and 1000 m2) in a semi-deciduous forest (Kiuic) and 28 plots in a semi-evergreen forest (FCP) and estimated AGB using local allometric equations. We calculated several LiDAR metrics from airborne data and used a Monte Carlo simulation approach to assess the influence of plot location errors (2 to 10 m) and plot size on ABG estimations from LiDAR using regression analysis. Our results showed that the precision of AGB estimations improved as plot size increased from 80 m2 to 1000 m2 (R2 = 0.33 to 0.75 and 0.23 to 0.67 for Kiuic and FCP respectively). We also found that increasing GPS location errors resulted in higher AGB estimation errors, especially in the smallest sample plots. In contrast, the largest plots showed consistently lower estimation errors that varied little with plot location error. We conclude that larger plots are less affected by co-registration error and vegetation conditions, highlighting the importance of selecting an appropriate plot size for field forest inventories used for estimating biomass.
2018
Artículo
Remote Sensing, 10(10), 1586, 2018.
Inglés
Hernández-Stefanoni, J., Reyes-Palomeque, G., Castillo-Santiago, M., George-Chacón, S., Huechacona-Ruiz, A., Tun-Dzul, F., ... & Dupuy, J. (2018). Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests. Remote Sensing, 10(10), 1586.
BIOLOGÍA Y QUÍMICA
Versión publicada
publishedVersion - Versión publicada
Appears in Collections:Artículos de Investigación Arbitrados

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