Ruijin Ma, Ph.D.
Mark P. Kumler, Ph.D.
Monitoring tropical deforestation poses a juxtaposition of urgency and difficulty. Because of nearly constant cloud cover in the tropics, heavily studied and widely implemented methods using multispectral satellite imagery to do large-scale land monitoring are not possible. Being an active sensing system that can penetrate through clouds, Synthetic Aperture Radar (SAR) solves this issue, making it one of the best opportunities for tropical forest change in the tropics. In Mamoní Valley, Panama, Multivariate Alteration Detection (MAD) analysis was used with SAR Ground Range Detected imagery from the European Space Agency’s (ESA) Sentinel 1 satellite to test its viability for detecting forest changes. Multispectral Unmanned Aerial Vehicle (UAV) imagery was used and tested for its viability to provide validation of the change detection analysis. Results of the methodology showed correlation between the SAR MAD results and various land cover types observed in the UAV imagery, though distinct multitemporal changes resulting from the analyses did not appear to correlate with changes shown in the UAV imagery. A comparison with Principal Component Analysis showed similar results, leading to the conclusion that the MAD method implemented was sound, but GRD SAR data may not be most suitable for this method. The results of the analyses can be used to focus future UAV mapping sites which may further develop the accuracy and implementation of SAR for tropical change detection.
Bohman, A. (2019). Testing Multivariate Alteration Detection for Tropical Deforestation using Synthetic Aperture Radar (SAR) and Drone Imagery in Mamomi Valley, Panama (Master's thesis, University of Redlands). Retrieved from https://inspire.redlands.edu/gis_gradproj/280
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