Abstract
Retrieval of forest biophysical properties using airborne LiDAR is known to differ between leaf-on and leaf-off states of deciduous trees, but much less is understood about the within-season effects of leafing phenology. Here, we compare two LiDAR surveys separated by just six weeks in spring, in order to assess whether LiDAR variables were influenced by canopy changes in Mediterranean mixed-oak woodlands at this time of year. Maximum and, to a slightly lesser extent, mean heights were consistently measured, whether for the evergreen cork oak (Quercus suber) or semi-deciduous Algerian oak (Q. canariensis) woodlands. Estimates of the standard deviation and skewness of height differed more strongly, especially for Algerian oaks which experienced considerable leaf expansion in the time period covered. Our demonstration of which variables are more or less affected by spring-time leafing phenology has important implications for analyses of both canopy and sub-canopy vegetation layers from LiDAR surveys.
Highlights
Airborne laser scanning, or Light Detection and Ranging (LiDAR), is a proven technique for making precise and accurate three-dimensional measurements of forest and other complex vegetation canopies over large spatial extents [1,2,3]
A better representation of ground and understorey layers in leaf-off state of Japanese deciduous forest has been shown [17], and comparable results were obtained for an English mixed deciduous woodland [16] where as much as 57% of last return height measurements were from the ground layer (
April–May comparisons were made on eight LiDAR metrics calculated for segmented trees crowns (Figure 3), and four metrics for 5 m grid cells (Figure 4)
Summary
Light Detection and Ranging (LiDAR), is a proven technique for making precise and accurate three-dimensional measurements of forest and other complex vegetation canopies over large spatial extents [1,2,3]. It is a powerful tool for an increasing range of applications in forestry, ecology and conservation. These include habitat suitability modelling [4,5,6] and the monitoring of carbon stocks, which is an essential requirement of projects for reducing emissions from deforestation and forest degradation (REDD+) [7,8]. A better representation of ground and understorey layers in leaf-off state of Japanese deciduous forest has been shown [17], and comparable results were obtained for an English mixed deciduous woodland [16] where as much as 57% of last return height measurements were from the ground layer (
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