Abstract
Mapping aboveground carbon density in tropical forests can support CO2 emission monitoring and provide benefits for national resource management. Although LiDAR technology has been shown to be useful for assessing carbon density patterns, the accuracy and generality of calibrations of LiDAR-based aboveground carbon density (ACD) predictions with those obtained from field inventory techniques should be intensified in order to advance tropical forest carbon mapping. Here we present results from the application of a general ACD estimation model applied with small-footprint LiDAR data and field-based estimates of a 50-ha forest plot in Ecuador’s Yasuní National Park. Subplots used for calibration and validation of the general LiDAR equation were selected based on analysis of topographic position and spatial distribution of aboveground carbon stocks. The results showed that stratification of plot locations based on topography can improve the calibration and application of ACD estimation using airborne LiDAR (R2 = 0.94, RMSE = 5.81 Mg·C·ha−1, BIAS = 0.59). These results strongly suggest that a general LiDAR-based approach can be used for mapping aboveground carbon stocks in western lowland Amazonian forests.
Highlights
Tropical forests are important carbon and biodiversity reserves, and characterizing the spatial distribution of their aboveground carbon density (ACD; units of Mg of carbon per hectare orMg Cha1 ) is a prerequisite for understanding the spatial and temporal dynamics of the terrestrial carbon cycle
In the present study, when selecting the subplots for fitting and validating the model, we considered the present study, when selecting the subplots for fitting and validating the model, we considered the spatial distribution of ACD and topographic position in the 50-ha spatial distribution of ACD and topographic position in the 50-ha plot
The model was multiplied by a correction factor (CF) to account for the back-transformation of the regression
Summary
Tropical forests are important carbon and biodiversity reserves, and characterizing the spatial distribution of their aboveground carbon density (ACD; units of Mg of carbon per hectare orMg Cha1 ) is a prerequisite for understanding the spatial and temporal dynamics of the terrestrial carbon cycle. Tropical forests are important carbon and biodiversity reserves, and characterizing the spatial distribution of their aboveground carbon density Accurate estimations of ACD and any changes in carbon stocks due to human activities are required in order to reduce emissions from deforestation and forest degradation (REDD+), and so contribute to the efforts being made to mitigate climate change [1]. Tropical forests hold large stores of carbon, yet uncertainty remains regarding their precise contribution to the global carbon cycle and how it is distributed in space and time [2,3]. Modern forest ecology and management applications require accurate maps so that their dynamics, biodiversity and carbon content can be tracked through time, especially in ecologically fragile and/or inaccessible regions, as is the case of many tropical forests.
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