CCDC-SMA

CCDC-SMA combines time series and spectral mixture analyses of Landsat imagery to monitor abrupt and gradual forest degradation.

Google Earth Engine Scripts:

CCDC-related papers (theory + applications)

Zhu, Z. & Woodcock, C.E. (2014). Continuous change detection and classification of land cover using all available Landsat data. Remote Sensing of Environment, 144, 152-171.

Arévalo, P., Bullock, E.L., Woodcock, C.E. & Olofsson, P. (2020). A Suite of Tools for Continuous Land Change Monitoring in Google Earth Engine. Frontiers in Climate, 2:576740.

Chen, S., Woodcock, C.E., Bullock, E.L., Arévalo, P., Torchinava, P., Peng, S. & Olofsson, P. (2021). Monitoring temperate forest degradation on Google Earth Engine using Landsat time series analysis. Remote Sensing of Environment, 265, 112648.

Chen, S., Olofsson, P., Sapangthong, T., &  Woodcock, C.E. (2023). Monitoring shifting cultivation in Laos with Landsat time series. Remote Sensing of Environment, 288, 113507.

Arévalo, P., Woodcock, C.E. & Olofsson, P. (2020). Continuous monitoring of land change activities and post-disturbance dynamics from Landsat time series: A test methodology for REDD+ reporting. Remote Sensing of Environment, 238, 111051.

Tang, X., Hutyra, L. R., Arévalo, P., Baccini, A., Woodcock, C.E. & Olofsson, P. (2020). Spatiotemporal tracking of carbon emissions and uptake using time series analysis of Landsat data: A spatially explicit carbon bookkeeping model. Science of The Total Environment. 720, 137409. 

Zhang, Y., Woodcock, C.E., Chen, S., Wang, J.A., Sulla-Menashe, D., Zuo, Z., Olofsson, P., Wang, Y. & Friedl, M.A. (2022). Mapping causal agents of disturbance in boreal and arctic ecosystems of North America using time series of Landsat data. Remote Sensing of Environment, 272,112935.

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