Insights into mapping tropical primary wet forests in the Amazon Basin from satellite-based time series metrics of canopy stability - Brendan Mackey; Sonia Hugh; Tatiana Shestakova; Brendan M. Rogers; Ludmila Rattis (Discover Conservation)
Abstract Deforestation and forest degradation are of continued and growing concern for biodiversity loss, carbon emissions, and a host of ecosystem services for local and global communities. Current remote sensing-based products of forest condition offer valuable information, but typically require extensive training data and represent snapshots in time. Here we provide complementary analyses that address some of these limitations by quantifying forest stability, a key component of ecosystem integrity, of wet tropical forests in the Amazon Basin over a 20-year period using an unsupervised classification method and identify areas of primary and secondary forest. Canopy stability was explored using a time series of remotely sensed MODIS data for the period 2003–2019 at a 500 m pixel resolution. We built on previous work to develop a pixel-based Canopy Stability Index based on the slope and coefficient of variation in fPAR (the fraction of photosynthetically active radiation intercepted by sunlit vegetation canopy) and SIWSI (the shortwave infrared water stress index), which collectively provide information on biophysical processes, canopy structure, and water stress. We examined temporal trends in canopy responses to environmental factors, natural disturbances and land use impacts and compared our results with the MapBiomas forest condition product. Analyses were focused on the Brazilian Amazon but extended to the entire Amazon Basin. The findings revealed a high level of agreement between the Canopy Stability Index and forest categories classified by MapBiomas. However, notable mismatches exist, particularly in ecoregions which contain non-forest ecosystems (e.g., Guianan Highlands Moist Forests, Gurupa varzea, and Pantepui forests and shrublands). Disturbances such as fires are correlated with high levels of canopy instability. The time series analysis revealed prior land use impacts and the occurrence of otherwise unrecognized degraded forest. High resolution modelled data on forest structure can be usefully complemented in tropical wet forests by the kinds of time series analyses presented here, which can assist in tracking changes in forest condition and responses to disturbances.