posted on 2018-09-03, 11:12authored byJames Edward Maxwell Wheeler
This thesis presents improved forest extent monitoring using L-band Synthetic Aperture Radar (SAR) data freely provided by the Japanese Aerospace Exploration Agency (JAXA) over the Congo Basin, which contains the second largest area of rainforest in the world. Forest loss in the region, estimated to be up to 0.63 billion Mg in the period 1990-2005, is predominantly driven by bush fuel collection, at a characteristically small scale. Single medium resolution SAR scene (75 km x 75 km), wide area (550 km x 550 km) and full Central African (2000 km x 3300 km) forest extent classifications are generated, and inform best practice for operational annual forest cover production from L-band SAR data. Improvements in one or more of overall accuracy, consistency, scope and replicability are observed compared with existing wide area forest cover and forest/non-forest products in Central Africa, using robust statistical methods to quantify errors in reported class areas. Seasonally inundated forest, a regional obstacle to previous SAR forest cover classifications, is identified by the range of co-polarised SAR data and tested using a novel metric incorporating a normalised cumulative rainfall value aggregated by sub-basin catchment area and SAR polarimetric analysis, which is itself compared with coarse resolution Soil Moisture and Vegetation Water Content Metrics from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). A quantitative analysis of multiple SAR resolutions supports the continued and future use of 30 m and higher resolution L-band SAR data to map forest cover in the region.