“
“QuestionIncreasing population pressure, socio-economic development and associated natural resource use in savannas are resulting in large-scale land cover changes, which can be mapped using remote

sensing. Is a three-dimensional (3D) woody vegetation structural Geneticin classification applied to LiDAR (Light Detection and Ranging) data better than a 2D analysis to investigate change in fine-scale woody vegetation structure over 2yrs in a protected area (PA) and a communal rangeland (CR)? LocationBushbuckridge Municipality and Sabi Sand Wildtuin, NE South Africa. MethodsAirborne LiDAR data were collected over

3300ha in April 2008 and 2010. Individual Blebbistatin ic50 tree canopies were identified using object-based image analysis and classified into four height classes: 1-3, 3-6, 6-10 and bigger than 10m. Four structural metrics were calculated for 0.25-ha grid cells: canopy cover, number of canopy layers present, cohesion and number of height classes present. The relationship between top-of-canopy cover and sub-canopy cover was investigated using regression. Gains, losses and persistence (GLP) of cover at each height class and the four structural metrics were calculated. GLP of clusters of each structural metric (calculated using LISA – Local Indicators of Spatial Association – statistics) were used to assess the changes in clusters of each metric

over time. ResultsTop-of-canopy GS-1101 mw cover was not a good predictor of sub-canopy cover. The number of canopy layers present and cohesion showed gains and losses with persistence in canopy cover over time, necessitating the use of a 3D classification to detect fine-scale changes, especially in structurally heterogeneous savannas. Trees bigger than 3m in height showed recruitment and gains up to 2.2 times higher in the CR where they are likely to be protected for cultural reasons, but losses of up to 3.2-fold more in the PA, possibly due to treefall caused by elephant and/or fire. ConclusionLand use has affected sub-canopy structure in the adjacent sites, with the low intensity use CR showing higher structural diversity. A 3D classification approach was successful in detecting fine-scale, short-term changes between land uses, and can thus be used as a monitoring tool for savanna woody vegetation structure.