ESA Open Invitation to Tender AO9860
Open Date: 12/09/2019
Closing Date: 30/10/2019 13:00:00

Status: ISSUED
Reference Nr.: 19.155.04
Prog. Ref.: EO-Science for Socie
Budget Ref.: E/E105-E5 – EO-Science for Socie
Special Prov.: AT+BE+CZ+DK+EE+FI+FR+DE+GR+HU+IE+IT+LU+NL+NO+PL+PT+RO+ES+SE+CH+GB+CA+SI
Tender Type: C
Price Range: 200-500 KEURO
Products: Satellites & Probes / Other
Technology Domains: Others
Establishment: ESRIN
Directorate: Directorate of EO Programmes
Department: Science, Applications & Climate Dep.
Division: Data Applications Division
Contract Officer: Tamas, Dora
Industrial Policy Measure: N/A – Not apply
Last Update Date: 12/09/2019
Update Reason: Tender issue

Forests help offset a quarter of anthropogenic emissions of fossil-fuel, and hold 80% of the Earths above ground terrestrial carbon, being essential for climate change adaptation and mitigation. Biomass changes are one of the main contributing factors to the global carbon cycle. There are three main processes generating these changes that result in terrestrial carbon sources or sinks: changes in land use and management, natural disturbances and recovery, and physiological or metabolic changes.This activity aims to exploit and validate Sentinel-1A and -1B SAR observations for forest change monitoring, in a data intensive framework to generate innovative products and scientific results contributing to a better characterization and understanding of the Earth System. The use of auxiliary data coming from other sensors is welcomed (e.g. Sentinel-3, TerraSAR-X, ALOS-2 PALSAR-2, RADARSAT-2, etc.), as well as in-situ measurements (e.g. plot data), and non-ESA scientific datasets (e.g. GEDI). One of the aims is to reduce the temporal and spatial bias of existing estimators, and to enhance the consistency of and interpretability of measurements. The procurement will focus on harnessing the power of the new EO capabilities, putting in context heterogeneous data sources with variable temporal and spatial sampling (including verification and in situ validation data), and aiming at advancing the understanding of forest related changes occurring in the Amazonas and what implications they have at local and regional scale. The resulting datasets, algorithms, and software tools are aimed at supporting upcoming land monitoring missions. Therefore, a main objective is to develop and validate innovativemethods and techniques for automatic exploitation of the temporal and spatial dimensions of heterogeneous time series data to detectand interpret forest related changes in relation with their type of manifestation, physical processes and determining factors (e.g.anthropic stress, climate change). The methods and tools shall be designed in such a way that they can accommodate new data types.A key element of this activity will include the exploitation, verification and validation of the products through ground-truth and in-situ data.