Biodiversity is widely acknowledged to provide multiple benefits including environmental services such as water regulation or provision of direct socio-economic benefits and potentially climate change mitigation via increased ecosystem productivity resulting in higher carbon storage.
Although none of the Remote Sensing sensors have been specifically designed to monitor biodiversity, existing data sources can inform on some components of an ecosystem (e.g.: forest structure, phenological cycles, vegetation response to climate events, regrowth dynamics). Such potential of Remote Sensing has not fully been explored yet, particularly over tropical areas. The project aims at exploring the potential for Remote Sensing techniques to inform on the status of ecosystems over tropical areas of Latin America. The approach will take advantage of the availability of multiple data sources to develop composite indices partly reflecting the state of forest ecosystems in Latin America. Temporal dynamics and forest resilience from climate change and anthropogenic disturbances will also be investigated by analysing the whole cycle of forest dynamics, including detection of forest disturbances, characterization of post disturbance paths and quantification of recovery potential. The project will deliver methodological frameworks and products; developing methods to extract biodiversity proxies from multiple Remote Sensing data sources and characterize forest dynamics from optical image time-series. The work will be carried out at multiple scales, from local case studies to continental scale for some biodiversity indices produced. The work involves harmonizing existing databases of in-situ forest inventory data, as well as development and testing of methods and algorithms.