National Forest Monitoring

SEPAL online course draws global audience to advance capacities for forest and land monitoring

Thousands of professionals will learn about using high-resolution satellite imagery through SEPAL
02/03/2023

The National Forest Monitoring (NFM) team is proud to announce that in just two weeks, the online facilitated course, Forest and Land Monitoring for Climate Action – SEPAL is at maximum capacity (with 2,372 participants registered)[1].The high demand for participation reflects the growing interest in forest and land monitoring using freely available high-resolution satellite imagery (through the NICFI satellite data program), particularly in countries with tropical forests that are most affected by climate change. The countries with the highest number of registered participants are Peru, Ecuador, Spain, Nigeria, Kenya, Colombia, Indonesia, Benin, Democratic Republic of the Congo, India, and Uganda. Registered participants will be attending from more than 150 countries from around the world with all regions well represented– making it truly a global initiative.

Running from 24 March to 7 May 2023, the course aims to support knowledge and skills development for applying high-resolution satellite imagery for forest and land monitoring. It has drawn participants from universities and research centres (39 percent), governments (23 percent), the private sector (10 percent), and non-governmental organizations and civil society (10 percent). With 34 percent of the participants being women, the course is also making strides in promoting gender equality.

Forest and Land Monitoring for Climate Action – SEPAL allows participants to tailor the course to their specific needs. Depending on a participant’s chosen learning path, they will learn about the foundations of a National Forest Monitoring Systems, how SEPAL can support forest and land monitoring for climate action, perform sample-based area estimation for high-integrity measurement reporting and verification, perform soil moisture mapping for peatlands monitoring, as well as how to generate information and maps to support ecosystem restoration through tools such as se.plan.

The course will be delivered in three languages simultaneously, giving nearly half of the participants (47 percent) the opportunity to follow the course in French and Spanish; the remaining participants (53 percent) will follow in English.

This SEPAL course is not just about learning new skills; it's also about creating a community of professionals who are passionate about forest and land monitoring for climate action. Throughout the course duration (two to six weeks depending on the chosen learning path), participants will have occasions to connect, share ideas, and seek opportunities for networking and collaboration. The outcomes of the course will be presented during the Global Forest Observation Initiative (GFOI) Plenary from 9 May to 11 May 2023, taking place in Rome and online.

For those who were unable to register, a self-paced version of the course will be available later this year through the FAO elearning Academy.  If you're interested in taking the self-paced course or learning more about the SEPAL project, follow the discussion on our social media channels (#LearningSEPAL, @OpenForis in TwitterLinkedIn and Facebook), visit our website or contact us via email ([email protected]).

This article was originally published on the SEPAL website: https://www.fao.org/in-action/sepal/news-and-events/news/detail/sepal-online-course-draws-global-audience-to-advance-capacities-for-forest-and-land-monitoring/en

1] System for Earth Observation, Data Access, Processing and Analysis for Land Monitoring (SEPAL) – sepal.io – is a free, open-source, online platform that enables autonomous processing of geospatial data for customized forest and land monitoring by anyone, anywhere. Part of the Open Foris suite of tools, the platform empowers users to process satellite data, create maps, and detect land cover and land-use change. It also offers other functions critical for generating data for effective land management – without the need of coding skills.