Geospatial Intelligence Challenges
The rapidly increasing amount and variety of data coming from satellites and other sources in the Space and Security domain is raising new issues such as the management and exploitation of extremely large and complex datasets.
In these challenges, BETTER will explore the added value provided by Big Data methods in developing products and applications tackling the following main topics:
Currently, the EU Satellite Centre (SatCen) supports the decision making and actions of the European Union in the field of Common Foreign and Security Policy (CFSP), in particular, Common Security and Defence Policy (CSDP), including European Union crisis management missions and operations, by providing products and services resulting from the exploitation of relevant space assets and collateral data, including satellite imagery and aerial imagery, and related services.
The purpose of this challenge is to investigate the possibility of producing accurate water and vegetation indexes (e.g. NDWI and NDVI) using time series of Sentinel-2 data.
The purpose of this challenge is to provide a stack of Multi-Temporal Coherence from Sentinel-1 StripMap images acquired over the same area, in order to visualize changes over man-made and natural structures.
The purpose of this challenge is to collect Sentinel-2 atmospherically corrected images (Level 2A), to obtain analysis-ready data to be used for further applications (e.g. the detection of illicit crops based on spectral signatures).
SAR sensors are a valuable tool to detect changes over man-made and natural structures: especially in equatorial regions, where clouds are present throughout the whole year thus limiting the use of optical sensors, SAR sensors could be used as complementary sources of information.
Sentinel-2 data are used to identify minerals from illegal mining activities (e.g. hydrothermal alteration associated with gold prospect locations). Illegal mining detection is also important to understand other illicit related activities (e.g. pollutants discharge).
Sentinel-2 data are processed for the extraction of vegetation and bare soil indexes, in order to assess (with higher accuracy respect to the standard vegetation analysis) vegetated areas and to monitor potential deforestation activities
The goal of this challenge is to test the use of Sentinel-1 coherence products to detect wildfires and their evolution.
This challenge aims to identify fire patterns and expansion through Sentinel-2 images, in order to support authorities for an appropriate response.
The goal of this challenge is to detect burned areas based on the joint use of Sentinel-2 and Sentinel-1 images.
As a result of addressing the identified BETTER Geospatial Intelligence challenges, change detection algorithms have been applied to a real use case scenario. The promoter of challenges in this thematic area, SatCen, is using the deployed pipelines to explore how to improve its operational capabilities and apply the new solutions for a localized objective.
The chosen geographical area, in Madre de Dios, Peru (shown below), is marked by deforestation problems resulting from illegal mining activities and the conversion of forest cover to agricultural areas. The area was monitored during the period April – October 2019 and different pipelines were used to understand the trend of deforestation: SAR change detection, mineral indexes, and vegetation cover mask.
Geographical area where BETTER pipelines were used to improve existing operations tackling illegal deforestation
The results of the BETTER pipelines show that deforestation due to mineral extraction looks to decrease during the study period in the main area (where the government put in place some controlling measures), but it seems to increase in surrounding areas. Moreover, the area shows frequently cut of the forest due to the conversion to agricultural fields. In the future, the pipelines developed within BETTER will be integrated into the SatCen GEO-DAMP platform.