MF-RADAR · Multi-frequency RADAR imaging for the analysis of tropical forest structure in the Amazon

Multi-frequency RADAR imaging for the analysis of tropical forest structure in the Amazon

The tropical rainforests of the Amazon basin are one of the world’s areas that are richest in biodiversity. They cover the largest terrestrial tropical biome in the world, store significant amounts of carbon and stabilise the regional and global climate. Deforestation, forest degradation and climate change impacts are posing a threat to the future of this unique region. This project helped in the capability for vegetation monitoring of the tropics. It represented an advance in the state-of-the-art because it developed innovative mapping and monitoring methods for estimating vegetation structural parameters based on the synergy between different data sources and methods. These new approaches are important in the context of carbon markets and REDD+ (Reducing emissions from deforestation and forest degradation). The importance of the project to society is that it has improved the monitoring of tropical areas to mitigate deforestation and forest degradation, and estimated the biomass and carbon stock with more accuracy, thus providing quantitative evidence needed for a better understanding of the Amazon region. The main research goal of this project was to develop a methodology to derive information on forest structure and floristics based on the polarimetric and interferometric variables from TanDEM-X (X band), PALSAR/ALOS (L band) and Sentinel 1 (C band) integrated with geomorphometric data derived from the Shuttle Radar Topography Mission, SRTM (C band), to benefit the monitoring of plant communities in the Amazon, estimate biomass and carbon stocks. The specific research objectives were: 1. To determine which variables/attributes (geomorphometric and SAR variables) are related to the floristic composition and structure of forest plant communities; 2. To develop a methodology to derive information on forest floristic structure from the integration of multi-frequency (2 to 8 GHz) SAR data and geomorphometry; 3. To develop and validate a predictive model for forest structure, especially the above ground biomass and floristics based on the integration of different data sources; 4. To quantify the relationship between biomass and the rate of carbon stocks in tropical areas. The fellow developed a multi-frequency SAR method for mapping forest structure and biomass in the Amazon. Open access publications describe the progress made for each objective. From the secondment, courses, conferences and meetings, the fellow learned new skills and improved her existing skills in radar remote sensing. She also increased her professional network and has secured another research position at the University of Leicester on a project called Forest 2020 (https://ecometrica.com/forests2020). Forests 2020 is a major investment by the UK Space Agency as part of the International Partnerships Programme (IPP) to help protect and restore up to 300 million hectares of tropical forests by improving forest monitoring in six partner countries through advanced uses of satellite data.

Data: CORDIS, © European Union