Description: In this study, we developed an approach, Continuous Change Detection and Classification - Spectral Mixture Analysis (CCDC-SMA), that combines time series analysis and spectral mixture analysis for monitoring abrupt and gradual forest degradation in temperate regions. We used this approach to monitor forest degradation and deforestation from 1987 to 2019 in the country of Georgia. CCDC-SMA runs on Google Earth Engine without the need to download data and can be easily adjusted and applied to other regions. 

Publications: Chen, S., Woodcock, C.E., Bullock, E.L., Arévalo, P., Torchinava, P., Peng, S. and Olofsson, P., 2021. Monitoring temperate forest degradation on Google Earth Engine using Landsat time series analysis. Remote Sensing of Environment, 265, p.112648. [apps  codes products]

Cortner, O., Chen, S., Olofsson, P., Gollnow, F., Torchinava, P., & Garrett, R. D. (2024). Exploring natural and social drivers of forest degradation in post-Soviet Georgia. Global Environmental Change, 84, 102775.

Funded by: NASA Land-Cover and Land-Use Change Program - Comprehensive analysis of thirty years of land change in Georgia: patterns, carbon dynamics and drivers.