Smart Urban Planning and Spatial Data Analytics for Decision-Making

Advanced smart cities and integrated engineering program covering spatial data analytics, urban planning models, GIS dashboards, location intelligence, decision support, with technical workflows, case studies, dashboards, simulations, and applied outputs over approximately 5 training day(s).

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Expert-Led Training

Practical Learning

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5 Days

Language

English / Arabic

Course Summary

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Course Details

Overview

The Smart Urban Planning and Spatial Data Analytics for Decision-Making course is an advanced smart cities, sustainability, and integrated engineering program designed for urban planners, infrastructure engineers, BIM/GIS professionals, smart-city teams, sustainability specialists, digital transformation leaders, consultants, and public-sector project teams.

The program develops practical capability in spatial data analytics, urban planning models, GIS dashboards, location intelligence, decision support, scenario evaluation, while connecting urban strategy, engineering information, spatial data, IoT and operational technologies, sustainability requirements, infrastructure lifecycle management, digital twins, AI-enabled forecasting, and executive decision support.

The course is structured for approximately 5 training day(s) and uses case studies, engineering workflows, digital templates, spatial-data exercises, dashboards, simulations, standards references, scenario analysis, and applied projects. Participants produce practical outputs that support smart-city planning, resilient infrastructure, sustainable urban operations, and measurable performance improvement.

Objectives

Program Objectives

By the end of this course, participants will be able to:

Apply spatial data analytics in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply urban planning models in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply GIS dashboards in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply location intelligence in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply decision support in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply scenario evaluation in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Produce an applied output such as a BIM-GIS integration workflow, digital twin reference architecture, urban dashboard, sustainability action plan, ISO 19650 information plan, smart infrastructure concept, AI forecasting use case, resilience map, or LEED-oriented design checklist according to the course topic.

Target Audience

This program is designed for:

Urban planners, municipal teams, smart-city program managers, infrastructure project managers, and public-sector professionals responsible for city planning and service transformation.
Civil engineers, architects, BIM managers, GIS specialists, surveyors, sustainability specialists, energy and water teams, and infrastructure information managers.
Digital transformation leaders, IoT engineers, SCADA/BMS/ICT/ELV teams, data analysts, AI specialists, control-center teams, and smart operations professionals.
Consultants, real estate developers, facilities and asset managers, academic researchers, and graduates in engineering, urban planning, GIS, sustainability, data science, or related disciplines.

Competencies

Core Competencies

Spatial Data Analytics

Ability to apply spatial data analytics within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Urban Planning Models

Ability to apply urban planning models within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Gis Dashboards

Ability to apply GIS dashboards within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Location Intelligence

Ability to apply location intelligence within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Decision Support

Ability to apply decision support within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Scenario Evaluation

Ability to apply scenario evaluation within Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured smart-city engineering methods, spatial or operational data, relevant standards, implementation templates, dashboards, scenario analysis, and evidence-based recommendations that improve planning quality, infrastructure performance, sustainability outcomes, and executive decision-making.

Learning Journey

Program Outline

Program structure and applied learning approach

Program Design

The program is designed for approximately 5 training day(s) and combines concept review, technical demonstrations, standards references, software-oriented workflows, case studies, templates, dashboards, simulations, and applied outputs related to Smart Urban Planning and Spatial Data Analytics for Decision-Making.

Day 1: Foundations, standards, and strategic context

Core concepts and terminology

Participants review and apply core concepts and terminology in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Saudi smart-city and sustainability context

Participants review and apply saudi smart-city and sustainability context in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Relevant standards, platforms, and governance requirements

Participants review and apply relevant standards, platforms, and governance requirements in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Initial applied workshop and baseline assessment

Participants review and apply initial applied workshop and baseline assessment in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Day 2: Data, models, and integration workflows

Data sources and engineering information models

Participants review and apply data sources and engineering information models in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Interoperability, integration, and quality control

Participants review and apply interoperability, integration, and quality control in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Digital tools, platforms, and workflow documentation

Participants review and apply digital tools, platforms, and workflow documentation in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Applied data or model integration exercise

Participants review and apply applied data or model integration exercise in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Day 3: Analytics, simulation, and decision support

Spatial, operational, or sustainability analytics

Participants review and apply spatial, operational, or sustainability analytics in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Scenario modeling and forecasting methods

Participants review and apply scenario modeling and forecasting methods in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Dashboards, KPIs, and executive reporting

Participants review and apply dashboards, kpis, and executive reporting in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Applied case discussion and decision-support output

Participants review and apply applied case discussion and decision-support output in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Day 4: Implementation, operations, and risk controls

Implementation planning and change management

Participants review and apply implementation planning and change management in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Cybersecurity, privacy, safety, or operational risk considerations

Participants review and apply cybersecurity, privacy, safety, or operational risk considerations in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Service, asset, or infrastructure lifecycle integration

Participants review and apply service, asset, or infrastructure lifecycle integration in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Practical simulation or management review

Participants review and apply practical simulation or management review in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Day 5: Advanced case study and final project

Advanced Saudi and international case studies

Participants review and apply advanced saudi and international case studies in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Business case, ROI, or sustainability impact assessment

Participants review and apply business case, roi, or sustainability impact assessment in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Final team project and presentation

Participants review and apply final team project and presentation in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Closing review and professional action plan

Participants review and apply closing review and professional action plan in the context of Smart Urban Planning and Spatial Data Analytics for Decision-Making, using examples, datasets, engineering documentation, professional templates, and measurable implementation outputs.

Enrollment Summary

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Smart Urban Planning and Spatial Data Analytics for Decision-Making

Certificate Included

Expert-Led Training

Practical Learning

Enrollment Support

days

5 Days

Language

English / Arabic

Overview

Program Objectives

By the end of this course, participants will be able to:

Apply spatial data analytics in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply urban planning models in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply GIS dashboards in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply location intelligence in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply decision support in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Apply scenario evaluation in realistic smart-city, sustainability, urban planning, infrastructure, or integrated engineering scenarios related to Smart Urban Planning and Spatial Data Analytics for Decision-Making, using structured methods, data-driven tools, professional templates, and measurable decision criteria.
Produce an applied output such as a BIM-GIS integration workflow, digital twin reference architecture, urban dashboard, sustainability action plan, ISO 19650 information plan, smart infrastructure concept, AI forecasting use case, resilience map, or LEED-oriented design checklist according to the course topic.

Target Audience

This program is designed for:

Urban planners, municipal teams, smart-city program managers, infrastructure project managers, and public-sector professionals responsible for city planning and service transformation.
Civil engineers, architects, BIM managers, GIS specialists, surveyors, sustainability specialists, energy and water teams, and infrastructure information managers.
Digital transformation leaders, IoT engineers, SCADA/BMS/ICT/ELV teams, data analysts, AI specialists, control-center teams, and smart operations professionals.
Consultants, real estate developers, facilities and asset managers, academic researchers, and graduates in engineering, urban planning, GIS, sustainability, data science, or related disciplines.

Core Competencies