Remote Sensing for Sustainable Development Goals (SDGs) Training Course

Introduction

The United Nations' 2030 Agenda for Sustainable Development, with its 17 Sustainable Development Goals (SDGs), represents a universal call to action to end poverty, protect the planet, and ensure prosperity for all. Achieving and monitoring progress towards these ambitious and interconnected goals requires robust, timely, and spatially explicit data across diverse social, economic, and environmental dimensions. Traditional statistical methods and ground-based surveys, while vital, often face limitations in terms of cost, coverage, frequency, and accessibility, particularly in remote or data-poor regions. Remote Sensing (RS) has emerged as an indispensable technology for monitoring a significant number of SDG indicators, offering a powerful, cost-effective, and scalable solution for data collection and analysis. Satellite and airborne sensors provide continuous, objective observations of Earth's surface and atmosphere, enabling tracking of land cover change, urbanization, forest dynamics, water quality, agricultural productivity, climate patterns, and much more. This wealth of geospatial data provides invaluable evidence for decision-making, policy formulation, and reporting on SDG progress at local, national, and global scales. Without the specialized skills to leverage this vast reservoir of remote sensing data, governments, international organizations, NGOs, and researchers face significant challenges in accurately assessing their contributions and identifying areas requiring targeted interventions to meet the 2030 targets. Many professionals involved in sustainable development recognize the potential of Earth observation data but lack the practical expertise to translate raw imagery into actionable insights for SDG monitoring and reporting.

Conversely, mastering Remote Sensing for Sustainable Development Goals empowers professionals to unlock the full potential of Earth observation data, providing crucial evidence to measure progress, identify vulnerabilities, and inform strategic interventions aimed at achieving the SDGs. This specialized skill set is crucial for transforming raw satellite data into powerful, spatially explicit indicators that support evidence-based decision-making for a more sustainable and equitable future. Our intensive 5-day "Remote Sensing for Sustainable Development Goals" training course is meticulously designed to equip policymakers, statisticians, environmental managers, development practitioners, GIS professionals, and researchers with the essential theoretical knowledge and practical, hands-on skills required to confidently apply remote sensing techniques for comprehensive SDG monitoring and reporting.

Duration

5 Days

Target Audience

The "Remote Sensing for Sustainable Development Goals" training course is ideal for a broad range of professionals and researchers involved in sustainable development, environmental management, policy-making, and data reporting. This includes:

  • National Statistical Office (NSO) staff: For integrating geospatial data into official SDG reporting.
  • Government officials: Involved in policy development, planning, and monitoring for sustainable development.
  • Environmental Managers and Scientists: Working on land degradation, biodiversity, and water quality.
  • Development Practitioners and NGO staff: Implementing and monitoring development projects.
  • Urban Planners: Focused on sustainable cities and communities.
  • Agriculturalists and Food Security Experts: For crop monitoring and drought assessment.
  • Climate Change Analysts: Tracking climate impacts and mitigation efforts.
  • GIS Professionals and Data Scientists: Seeking to apply their skills to global development challenges.
  • Researchers and Academics: In sustainable development, geography, and Earth sciences.
  • International Organization staff: Involved in global SDG monitoring initiatives.

Course Objectives

Upon successful completion of the "Remote Sensing for Sustainable Development Goals" training course, participants will be able to:

  • Understand the fundamental role and contributions of remote sensing to monitoring various SDG indicators.
  • Identify and access key remote sensing data sources relevant to specific SDGs (e.g., Landsat, Sentinel, MODIS).
  • Perform essential pre-processing steps for remote sensing data to derive SDG-relevant information.
  • Apply various remote sensing techniques for mapping and quantifying indicators related to environmental, social, and economic SDGs.
  • Integrate remote sensing products with other geospatial and statistical data for comprehensive SDG analysis.
  • Interpret remote sensing results to inform policy decisions and report on SDG progress.
  • Utilize cloud-based geospatial platforms for scalable SDG monitoring.
  • Develop a conceptual framework for leveraging remote sensing in their specific SDG monitoring context.

 Course Modules

Module 1: Introduction to SDGs and the Power of Remote Sensing

  • Overview of the 2030 Agenda for Sustainable Development and the 17 SDGs.
  • Challenges in SDG monitoring and reporting using traditional methods.
  • The unique advantages of remote sensing for large-scale, frequent, and objective data collection.
  • Connecting remote sensing capabilities to specific SDG targets and indicators.
  • Introduction to key Earth Observation programs and data initiatives supporting SDGs (e.g., Copernicus, Digital Earth Africa).

Module 2: Remote Sensing for SDG 1 (No Poverty) and SDG 2 (Zero Hunger)

  • Mapping human settlements and infrastructure for poverty alleviation (SDG 1).
  • Satellite-derived indicators for economic activity and accessibility in remote areas.
  • Crop type mapping and area estimation for food security (SDG 2).
  • Monitoring crop health, yield prediction, and drought conditions using vegetation indices.
  • Assessing agricultural land degradation and land productivity for sustainable agriculture.

Module 3: Remote Sensing for SDG 6 (Clean Water & Sanitation) and SDG 7 (Affordable & Clean Energy)

  • Water body mapping and monitoring for water availability (SDG 6).
  • Assessing water quality parameters (turbidity, chlorophyll-a) in lakes and reservoirs.
  • Mapping access to water infrastructure (conceptual).
  • Identifying suitable sites for renewable energy infrastructure (solar farms, wind farms).
  • Monitoring energy consumption patterns using nighttime lights imagery (conceptual).

Module 4: Remote Sensing for SDG 11 (Sustainable Cities & Communities) and SDG 13 (Climate Action)

  • Urban extent mapping, growth monitoring, and impervious surface analysis (SDG 11).
  • Assessing access to green public spaces and urban heat islands.
  • Mapping informal settlements and monitoring their development.
  • Monitoring land cover change and deforestation for climate action (SDG 13).
  • Tracking glacier melt, sea ice extent, and sea level rise as climate change indicators.

Module 5: Remote Sensing for SDG 14 (Life Below Water) and SDG 15 (Life On Land)

  • Coastal zone mapping and monitoring: coral reefs, mangroves, seagrass beds (SDG 14).
  • Detecting marine pollution (e.g., oil spills, algal blooms).
  • Forest cover change detection, deforestation, and forest degradation monitoring (SDG 15).
  • Land degradation neutrality (LDN) monitoring and assessment.
  • Mapping protected areas and assessing their effectiveness.

Module 6: Cross-Cutting SDGs and Thematic Applications

  • Remote sensing for disaster risk reduction (SDG 1, 11, 13): Flood mapping, damage assessment.
  • Mapping infrastructure development (SDG 9: Industry, Innovation, Infrastructure).
  • Measuring inequalities through spatial data (SDG 10: Reduced Inequalities).
  • Monitoring land degradation and desertification for various SDGs.
  • Identifying environmental pressures and their socio-economic impacts.

Module 7: Data Integration, Analysis, and Reporting for SDGs

  • Integrating remote sensing data with statistical data, census data, and field observations.
  • Utilizing GIS for spatial analysis of SDG indicators.
  • Developing custom indicators and dashboards for SDG progress visualization.
  • Challenges and best practices in data validation and uncertainty assessment for SDG reporting.
  • Case studies of national and global SDG reporting initiatives leveraging remote sensing.

Module 8: Cloud Platforms, AI/ML, and Future Trends in SDG Monitoring

  • Leveraging cloud-based geospatial platforms (e.g., Google Earth Engine, Digital Earth Africa) for scalable SDG monitoring.
  • Introduction to AI and Machine Learning for automated SDG indicator extraction (e.g., building detection, land cover classification).
  • Crowdsourcing and citizen science for ground truthing and validating remote sensing data.
  • Emerging satellite missions and technologies relevant to SDG monitoring.
  • Strategies for capacity building and fostering collaboration in using geospatial data for SDGs.

CERTIFICATION

  • Upon successful completion of this training, participants will be issued with Macskills Training and Development Institute Certificate

TRAINING VENUE

  • Training will be held at Macskills Training Centre. We also tailor make the training upon request at different locations across the world.

AIRPORT PICK UP AND ACCOMMODATION

  • Airport pick up and accommodation is arranged upon request

TERMS OF PAYMENT

Payment should be made to Macskills Development Institute bank account before the start of the training and receipts sent to info@macskillsdevelopment.com

 

Remote Sensing For Sustainable Development Goals (sdgs) Training Course in Gambia
Dates Fees Location Action
25/08/2025 - 29/08/2025 $1,500 Nairobi
01/09/2025 - 05/09/2025 $1,750 Mombasa
15/09/2025 - 19/09/2025 $1,500 Nairobi
06/10/2025 - 10/10/2025 $1,750 Mombasa
20/10/2025 - 24/10/2025 $1,500 Nairobi
04/11/2025 - 07/11/2025 $1,750 Mombasa
24/11/2025 - 28/11/2025 $1,500 Nairobi
01/12/2025 - 05/12/2025 $1,750 Mombasa
08/12/2025 - 12/12/2025 $1,500 Nairobi
05/01/2026 - 09/01/2026 $1,750 Mombasa
26/01/2026 - 30/01/2026 $1,500 Nairobi
02/02/2026 - 06/02/2026 $1,750 Mombasa
23/02/2026 - 27/02/2026 $1,500 Nairobi
02/03/2026 - 06/03/2026 $1,750 Mombasa
23/03/2026 - 27/03/2026 $1,500 Nairobi
06/04/2026 - 10/04/2026 $1,750 Mombasa
20/04/2026 - 24/04/2026 $1,500 Nairobi
04/05/2026 - 08/05/2026 $1,750 Mombasa