Sentinel data use for Land Cover and Forest Fires monitoring
This two-day hands-on training course is organized by Research and User Support for Sentinel Core products (RUS) and the NOVA Information Management School.
The event is organized in cooperation with Direção-Geral do Território.
The main goal of this training session is to create theoretical and practical competences on the use of Sentinel data for Land Cover Land Use (LCLU) monitoring (i.e. mapping and change detection) and for forest fires related applications (e.g. fire risk and burned area mapping).
This training course is the outcome of the Copernicus Training and Information session which took place in Lisbon on 7 June 2017, where the requirements for hands-on sessions were defined and participants' interest collected.
Preliminary Programme
The course includes lectures on the theory of satellite image processing and classification as well as hands-on exercises.
DAY 1 (Thursday 8 February 2018) - LCLU theory and mapping
Morning:
Theoretical background, principles and methods for land cover mapping. Topics will include:
The need for LCLU monitoring
Sentinel 2 satellite data
Understanding satellite images and pre-processing
Satellite image classification
Post-classification and accuracy assessment
Overview of change detection methods
Afternoon:
Practical exercises on the topics presented during the theory session using Copernicus Sentinel data and the RUS Virtual Machines.
DAY 2 (Friday 9 February 2018) - Forest Fires applications
Morning:
Theoretical background, principles and methods for monitoring forest fires from space. Topics will include, amongst others:
Sensitivity and specificity of the fire signals
Multitemporal compositing for burned area mapping
Mapping the 2017 area burned in Portugal with Sentinel-2 data
Global pyrogeography research
Afternoon:
Practical exercises on the topics presented during the theory session using Copernicus Sentinel data and the RUS Virtual Machines.
This training course is addressed to participants with a few years' experience (2-5) in Earth Observation and an understanding of automatic image processing. Participants will be selected to attend on the basis of the questionnaire filled in at application. Confirmation e-mails to selected attendees will be sent in early January 2018.
