Woody Cover Mapping in the Kruger National Park using Sentinel-1 time series and LiDAR data (Q6684849)

This data repository presents a workflowto derive woody cover information for the Kruger National Park, South Africa,from freely available Sentinel-1C-Band time seriesand LiDAR data (modified from Smit et al. 2016) using machinelearning (MLR and Rangerin R). The methodology is described in following publication: Urban, M., K. Heckel, C. Berger, P. Schratz, I.P.J. Smit, T. Strydom,J. Baade C. Schmullius (2020):Woody Cover Mapping in the Savanna Ecosystem of the Kruger National Park Using Sentinel-1 C-Band Time Series Data. Koedoe. In order to derive woody cover percentage information, download all files into one folder and runthe R-Filesconsecutively from 01_ to 04_. Follow the instruction within each of the R-Files, which are written as comments in the programming code. The data repository consist of the following files: R-Files: 1. Script 1: 01_MLR_tune_spatial_final 2.Script 2: 02_MLR_cross_validation_spatial_final 3.Script 3: 03_MLR_RANGER_train_final 4.Script 4: 04_MLR_prediction_woody_cover_final Training dataset - ENVI FILE (layerstack of Sentinel-1 VH and VV backscatter between 2016 and 2017 and the woody cover reference derived from the LiDAR data): 1.S1_A_VH_VV_16_17_lidar Data for prediction - ENVI FILES (3 example regions in theKruger National Park): 1.S1_A_VH_VV_16_17_subset_example_Letaba_Rest_Camp 2.S1_A_VH_VV_16_17_subset_example_Lower_Sabie 3.S1_A_VH_VV_16_17_subset_example_Pafuri Final woody cover maps of theKruger National Park: 1.xx_woody_cover_map_final.rar (contains final maps in 10m, 30m, 50m and 100m spatial resolutionas .tif and a QGIS project) References: Smit, I.P.J., Asner, G.P., Govender, N., Vaughn, N.R. Wilgen, B.W. van, 2016, An examination of the potential efficacy of high-intensity fires for reversing woody encroachment in savannas, Journal of Applied Ecology, 53(5), 16231633.