GIS and Remote Sensing for Electric Mobility and Charging Infrastructure Planning Course

Course Introduction

The global shift towards electric mobility is reshaping transportation systems, urban infrastructure, and energy demand planning. Effective adoption requires accurate geospatial data to guide decisions on charging infrastructure, route optimization, and integration with renewable energy systems.

GIS and remote sensing provide powerful tools to analyze mobility patterns, land suitability, grid capacity, and environmental impacts for electric vehicle (EV) infrastructure planning. By leveraging these technologies, planners can design efficient, equitable, and sustainable charging networks.

This course equips participants with advanced knowledge of geospatial technologies tailored for electric mobility transitions. It integrates urban mobility analysis, renewable energy siting, and charging station location modeling with sustainability principles.

Participants will gain hands-on skills in applying GIS and remote sensing for spatial analysis of EV demand, infrastructure accessibility, and urban-rural integration. Special focus will be placed on integrating electric mobility planning with climate goals and low-carbon development strategies.

The program also explores emerging trends such as AI, big data, and IoT-enabled mobility solutions. By addressing interoperability and policy integration, the course bridges the technical and governance dimensions of sustainable e-mobility.

By the end of the course, participants will be able to design, evaluate, and implement geospatial strategies for EV infrastructure that support equitable access, environmental goals, and smart city development.

Who Should Attend

• Urban and regional transport planners
• Government officials in transport and energy ministries
• EV infrastructure project managers
• GIS and remote sensing professionals in mobility planning
• Energy utilities and renewable energy planners
• Smart city development agencies
• Environmental and climate policy advisors
• Automotive industry professionals focusing on EV strategies
• Development organizations supporting clean mobility initiatives
• Researchers and academics in sustainable transport and geospatial sciences

Duration

10 days

Course Objectives

• Equip participants with knowledge of GIS and remote sensing applications for planning sustainable electric mobility transitions.
• Train professionals to analyze spatial patterns of EV adoption, charging demand, and transport flows for data-driven decision-making.
• Build expertise in location-allocation modeling for optimal charging station siting across urban and rural landscapes.
• Provide skills to integrate renewable energy potential mapping with EV charging infrastructure for sustainability.
• Enable participants to assess socio-economic and environmental impacts of EV infrastructure deployment through geospatial analysis.
• Strengthen capacity to incorporate geospatial insights into transport, energy, and climate policy frameworks.
• Develop participant skills in applying AI, IoT, and big data to enhance EV infrastructure planning with GIS and remote sensing.
• Foster the ability to use remote sensing for land suitability, urban heat mitigation, and environmental monitoring in EV contexts.
• Provide practical experience in scenario modeling for future EV growth and infrastructure resilience.
• Train participants to prepare geospatial datasets and dashboards for EV infrastructure monitoring and decision support.
• Enhance knowledge of stakeholder engagement, governance, and policy integration for EV planning with SDGs and climate targets.
• Equip participants with skills to design comprehensive geospatial strategies for equitable and efficient EV infrastructure development.

Comprehensive Course Outline

Module 1: Foundations of GIS and Remote Sensing for Mobility

• Basics of GIS and remote sensing in transport planning
• Data sources for e-mobility applications
• Mapping transport networks and demand flows
• Case studies in geospatial mobility planning

Module 2: Electric Mobility Transitions and Policy Context

• Global trends in EV adoption and infrastructure
• Policy drivers for clean mobility and net-zero targets
• Regulatory frameworks for EV integration
• Role of geospatial data in EV policymaking

Module 3: Spatial Analysis of EV Adoption and Demand

• Mapping EV adoption trends by region
• Analyzing socio-economic drivers of EV use
• Predicting demand hotspots for charging
• Accessibility and equity in EV adoption

Module 4: Charging Infrastructure Planning with GIS

• Location-allocation modeling for charging sites
• Proximity analysis for accessibility optimization
• Grid integration mapping with EV loads
• Multi-criteria decision analysis for siting

Module 5: Renewable Energy Integration in EV Infrastructure

• Mapping solar and wind resources for charging
• GIS for integrating distributed energy with EVs
• Remote sensing for solar rooftop mapping
• Policy strategies for clean energy-powered EVs

Module 6: Environmental and Climate Dimensions

• Carbon reduction impacts of EV adoption
• Land-use suitability for charging infrastructure
• Remote sensing for air quality and emissions
• Climate resilience of EV networks

Module 7: Urban Mobility and Smart Cities

• GIS for urban EV mobility systems
• Smart city initiatives and EV charging planning
• EV integration with public transport systems
• IoT-enabled geospatial mobility solutions

Module 8: Rural and Regional Infrastructure Planning

• Addressing rural EV infrastructure gaps
• GIS for regional charging network expansion
• Equity in rural-urban EV transitions
• Case studies in regional planning

Module 9: Geospatial Big Data and AI in Mobility

• Big data analytics for EV usage patterns
• AI for charging station prediction modeling
• Integrating mobility data streams into GIS
• Digital twins for EV infrastructure

Module 10: Remote Sensing Applications in EV Planning

• Land cover and land use mapping for siting
• Thermal mapping for urban EV infrastructure
• Remote sensing for transport emissions monitoring
• Spatial monitoring of EV charging installations

Module 11: Stakeholder Engagement and Governance

• Multi-stakeholder approaches to EV infrastructure
• Governance models for e-mobility transitions
• Public-private partnerships in EV networks
• Community participation in planning

Module 12: Financing and Economic Planning

• Cost-benefit analysis of charging infrastructure
• Economic incentives for EV adoption
• Financing models for large-scale EV infrastructure
• GIS-based tools for economic evaluation

Module 13: Monitoring and Evaluation with GIS

• Developing indicators for EV infrastructure performance
• GIS dashboards for monitoring adoption and access
• Remote sensing for environmental impact evaluation
• Reporting for policy and SDG tracking

Module 14: Case Studies and Global Best Practices

• National EV infrastructure plans and lessons learned
• Smart city EV integration examples
• Regional cooperation in cross-border EV corridors
• Industry innovations in charging solutions

Module 15: Future Directions in E-Mobility

• Vehicle-to-grid integration and smart grids
• Autonomous EVs and geospatial requirements
• Hydrogen and alternative e-mobility pathways
• Innovation in mobility-as-a-service models

Module 16: Project and Policy Simulation

• Group projects on EV infrastructure planning
• Scenario modeling for EV growth and resilience
• Policy simulation and geospatial decision-making
• Presentation of project outcomes and peer review

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better