Earth Observation & GeoAI Track (2026)

A National Space Academy programme, delivered with Space42

Sponsor

Programme framework

Delivery partner

A programme with a track record

The third edition, delivered with Space42

Two cohorts have already completed the programme, and their graduates were honoured at the UAE Space Agency's Space Research Conference in Abu Dhabi during World Space Week in October 2024. The teaching approach has stayed consistent - practical knowledge in remote sensing, artificial intelligence and space data analysis, through lectures, workshops and hands-on training.

2024 · First cohort

Space Applications

Launched March 2024 and delivered in Abu Dhabi from April to August 2024 - covering space fundamentals, remote sensing, satellite image processing, programming, AI and machine learning, Python, and the GIQ platform.

2025 · Second cohort

Space Applications - Earth Observation

A ten-week programme delivered 13 May – 17 July 2025, open to UAE nationals in the public and private sectors, academic researchers in Earth observation, and graduates in STEM, programming or AI.

2026 · Third edition

Restructured into two sequential courses - a four-week Earth Observation Fundamentals course (Level 1) and a five-week Application Development course (Level 2) - alongside the specialised Hyperspectral Earth Observation course.

Who should apply

Built for professionals moving into space data

The Earth Observation & GeoAI Track is aimed at Emirati professionals from government, civil, non-civil and private sectors, entrepreneurs, researchers and university graduates - best suited to those with a background in engineering or data science. Python is taught from the ground up in the Space Academy courses.

Researchers

Academic and applied researchers working with Earth observation and geospatial data.

Data scientists

Practitioners in AI and machine learning ready to apply their skills to satellite imagery.

Engineers

Engineering professionals building the technical foundations for geospatial work.

University graduates

Recent graduates with backgrounds in STEM, programming or artificial intelligence.

Environmental experts

Specialists applying remote sensing to water, agriculture, climate and natural resources.

Entrepreneurs

Founders and innovators building products and start-ups on Earth observation data.

Curriculum

Week by week, course by course

A consistent professional toolchain runs through all three courses, so skills carry directly from one to the next. Select a course to see what you will learn and how each week is structured.

Fundamentals (L1) Application Development (L2) Hyperspectral

Earth Observation Fundamentals (Level 1)

4 weeks14 Sep – 7 Oct 2026 2 onsite · 2 online

Gives participants the technical grounding to understand satellite data, work with geospatial tools, and apply core GeoAI concepts - through lectures, hands-on labs and guided mini projects. Applications open until 27 Aug 2026.

What you will learn

Foundations of remote sensing, including optical and SAR sensors
Data acquisition, processing and geospatial analytics
Core GIS concepts, satellite image analysis and digital cartography
Python for geospatial analytics - data wrangling, visualisation and basic ML
Practical work with QGIS, the GIQ platform and Google Colab
Object detection and image classification (supervised and unsupervised)
Introductory deep learning - object detection and segmentation

Commitment4 days/week · ~7 hrs/day

TeachingLectures + practical mini-labs

LocationAbu Dhabi · Space42 Smart Solutions Office

Finishes withMini project + elevator pitch; certificate

Week by week

Week 1 · 14–17 Sep - FoundationsOnsite

Introduction to Space Academy and course objectives; fundamentals of remote sensing and GIS; introduction to GIQ and QGIS; optical image processing with GIQ; GeoAI applications; SAR fundamentals.

Week 2 · 21–24 Sep - Data & PythonOnline

Data acquisition with GIQ and an LLM chatbot; prompt engineering for Python data science (Google Colab); SAR and optical image processing techniques; introduction to the mini project; SAR-ship object detection in Python; supervised and unsupervised image classification.

Week 3 · 28 Sep–2 Oct - Machine learningOnline

Machine learning concepts - regression and classification; introduction to deep learning; object detection with YOLO and Faster R-CNN; hands-on deep learning notebooks; segmentation models including U-Net and Mask R-CNN.

Week 4 · 5–7 Oct - Project & evaluationOnsite

Segmentation models in practice; evaluation metrics; data augmentation; mini project presentations; reserved time for overflow, feedback and optional labs.

Geospatial AI Application Development (Level 2)

5 weeks19 Oct – 20 Nov 2026 3 onsite · 2 onlineTeam-based projects

A practical course focused on designing, building, testing and presenting deployable geospatial AI solutions, using high-resolution imagery, GIQ and agent-based application building. Applications open until 25 Sep 2026.

What you will learn

Frame real-world geospatial challenges into practical AI solution concepts
Satellite data acquisition, data labeling, model training, testing, inference and deployment
Build deployable geospatial AI apps in GIQ with the Auto Model Development (AMD) module and agents
Model deployment and accuracy evaluation in GIQ
Multidisciplinary teamwork, iterative development and stakeholder communication
Presenting a working solution to technical and non-technical stakeholders

TeachingAMD, agents and PoC app building

PlatformGIQ + AMD AI platform

Who it's forLevel 1 graduates or equivalent

Finishes withFinal presentation to stakeholders; certificate

Week by week

Week 1 · 19–23 Oct - OrientationOnsite

Orientation - objectives, schedule and logistics; introduction to GIQ; introduction to the application challenges; introduction to Auto Model Development (AMD).

Week 2 · 26–30 Oct - Build beginsOnline

GIQ data acquisition and the GIQ LLM chatbot; application building with agents (hands-on coding workshop).

Week 3 · 2–6 Nov - Train & inferOnline

AMD project work - collecting training data; model training and inference; application building with agents.

Week 4 · 9–13 Nov - AccuracyOnsite

AMD AI project work; AMD AI sandbox and model accuracy; application building with agents.

Week 5 · 16–20 Nov - Deploy & presentOnsite

AMD project work; model deployment in GIQ; application building with agents; presentation rehearsal; final presentation day to stakeholders.

Hyperspectral Earth Observation

4 weeks3 – 25 Nov 2026 Hybrid · onsite + online

A focused, application-oriented journey in hyperspectral Earth observation, geospatial analytics and AI-enabled solution development - connecting scientific understanding with a project-based final output. Applications open until 12 Oct 2026.

What you will be able to do

Understand hyperspectral imaging principles, spectral signatures, sensor concepts and reflectance behaviour
Access, visualise, preprocess and explore hyperspectral datasets with reproducible workflows
Apply dimensionality reduction, spectral similarity, classification and target detection
Use validation methods and accuracy assessment
Apply AI and GeoAI methods to environmental, agricultural, water, mineral and infrastructure use cases

FormatWk 1 & 4 onsite + online · Wk 2–3 online

FocusApplied hyperspectral analytics + GeoAI

LocationAbu Dhabi · Space42 Smart Solutions Office

Finishes withFinal graduation project submission

Week by week

Week 1 · 3–5 Nov - PrinciplesOnsite + online

Course orientation and objectives; introduction to hyperspectral Earth observation; spectral signatures, sensor concepts and hyperspectral use cases; data access, visualisation and exploration; preprocessing concepts.

Week 2 · 9–13 Nov - ProcessingOnline

Hyperspectral image processing workflows; feature extraction and dimensionality reduction; material discrimination and target detection; classification approaches; project scoping and use-case definition.

Week 3 · 16–20 Nov - GeoAI & validationOnline

GeoAI methods for hyperspectral applications; AI-assisted classification and mapping; validation methods and accuracy assessment; applied project development workshop; interim feedback and quality assurance.

Week 4 · 23–25 Nov - Final projectOnsite + online

Advanced hyperspectral analytics and solution refinement; final project implementation and testing; presentation preparation and rehearsal; final graduation project submission; final evaluation and feedback.

Who it's for. Selected Emirati professionals from government, civil, non-civil and private sectors, plus entrepreneurs, researchers, graduates and early-career professionals - especially those with backgrounds in engineering, data science, remote sensing, environmental sciences, space technology or AI-enabled product development. Also open to Space Academy graduates and Arab 813 Space Hackathon incubation teams.

Entry requirements & how to apply

Who can apply, and what to expect

Level 1 · Fundamentals

Apply by 27 Aug 2026

Course runs 14 Sep – 7 Oct 2026

Level 2 · Application Development

Apply by 25 Sep 2026

Course runs 19 Oct – 20 Nov 2026

Hyperspectral Earth Observation

Apply by 12 Oct 2026

Course runs 3 – 25 Nov 2026

Eligibility & commitment

Emirati professionals from government, civil, non-civil and private sectors, entrepreneurs, researchers and university graduates.
Best suited to a background in engineering or data science. Python is taught from the ground up in the Space Academy courses.
The Hyperspectral Earth Observation course suits those with backgrounds in engineering, data science, remote sensing or environmental sciences, and is also open to Space Academy graduates and hackathon incubation teams.
Intensive: four days a week, roughly six to seven hours a day. Arrange time with your employer before applying.
Participants are selected through an application and review process.

Participation & fees

Emirati participantsFully sponsored

Non-Emirati participantsTuition fees apply - confirmed at a later stage

Seat allocationLimited; a small number of seats per cohort is available to non-Emirati participants

SelectionBy application and review

CertificateAwarded on completion; graduation held separately by UAESA

Course dates are confirmed (see above); registration links will be published on the National Space Academy website. Register your interest to be notified the moment they open.

Register your interest

Frequently asked questions

Good to know before you apply

Do I need to take all three courses?

No. Each course can be taken on its own, but they are designed as a progression. The Application Development course (Level 2) assumes the knowledge taught in the Fundamentals course (Level 1).

What is the difference between the first two courses?

The Fundamentals course (Level 1) teaches the principles of remote sensing, GIS and GeoAI. The Application Development course (Level 2) applies them - you work in a team to build, train and deploy a working AI solution in GIQ.

Do I need to know how to code?

For the Space Academy courses, a background in engineering or data science is recommended, but Python is taught from the ground up. The Hyperspectral Earth Observation course is applied and suits participants with some remote-sensing, data-science or programming background.

Are the courses online or in person?

Both. Each course mixes onsite weeks in Abu Dhabi with online weeks - Fundamentals is 2 onsite + 2 online, Application Development 3 onsite + 2 online, and Hyperspectral Earth Observation is hybrid across its four weeks.

Can I attend while working full time?

The courses are intensive - four days a week, six to seven hours a day. Participants should arrange time with their employer before applying.

Who can apply?

Emirati professionals from government, civil, non-civil and private sectors, entrepreneurs, researchers and university graduates. The hyperspectral course is also open to Earth observation specialists and to Arab 813 Space Hackathon incubation teams.

Is there a fee?

Participation is fully sponsored for Emirati participants. A limited number of seats is available to non-Emirati participants, for which tuition fees will be confirmed at a later stage.

Do I receive a certificate?

Yes. Participants receive a certificate on completion, and a graduation ceremony is held separately by the UAE Space Agency.

How does this relate to the Arab 813 Space Hackathon?

Both run under the National Space Academy. The courses build skills; the hackathon applies them competitively. The hyperspectral course is open to graduates of the Space Academy courses and to hackathon incubation teams.

Has this programme run before?

Yes. 2026 is the third edition. The first cohort ran from April to August 2024 and the second from May to July 2025, both delivered with Space42.

When do the courses start, and what are the deadlines?

The 2026 courses run from September to November: Fundamentals 14 Sep – 7 Oct, Application Development 19 Oct – 20 Nov, and Hyperspectral Earth Observation 3 – 25 Nov. Application deadlines are 27 Aug (Fundamentals), 25 Sep (Application Development) and 12 Oct (Hyperspectral). Weekly schedules may be adjusted slightly during delivery.

Building the UAE's capability in Earth observation and applied AI