Training Course on Cloud-based GIS Platforms - ArcGIS Online, Google Earth Engine

Module 1: Introduction to Cloud GIS and ArcGIS Online

Theoretical Concepts:

Definition and evolution of cloud GIS.

Advantages over traditional GIS: scalability, collaboration, accessibility, and big data handling.

Cloud GIS architecture and service models (SaaS, PaaS, IaaS).

Overview of ArcGIS Online as a SaaS platform.

Platform Exploration:

ArcGIS Online account setup and interface walkthrough.

User roles and permissions in organizational accounts.

Hands-On Practical:

Uploading shapefiles, CSV, and GeoJSON data.

Creating and customizing a web map with basemaps, symbols, and pop-ups.

Exploring ArcGIS Online content libraries and Living Atlas datasets.

Module 2: Spatial Data Management and Sharing in ArcGIS Online

Data Publishing:

Hosting feature layers, tile layers, and map services.

Configuring symbology, labels, and metadata in the cloud.

Understanding data credits and storage considerations.

Collaboration and Sharing:

Setting up groups and workspaces for organizations.

Publishing maps/apps for private, group, or public access.

Linking ArcGIS Pro projects with ArcGIS Online.

Hands-On Practical:

Publish and style a hosted feature layer.

Configure user permissions and invite collaborators.

Create a shared story map combining text, maps, and multimedia.

Module 3: Introduction to Google Earth Engine (GEE)

Foundations of GEE:

Cloud computing for big geospatial data.

GEE data catalog: Landsat, Sentinel, MODIS, climate, terrain, and socio-economic datasets.

JavaScript vs Python APIs in Earth Engine.

Interface and Tools:

Earth Engine Code Editor workspace.

Understanding map layers, console outputs, and script panels.

Importing datasets and defining regions of interest (ROIs).

Hands-On Practical:

Load Landsat or Sentinel imagery, visualize in true/false color composites.

Export maps and data outputs to Google Drive.

Compare land cover across two different years.

Module 4: Cloud-based Geospatial Analysis

ArcGIS Online Analysis Tools:

Buffering, overlays, spatial joins, and summarizing attributes.

Raster analysis in the cloud: elevation, slope, and viewshed tools.

Real-time data feeds and IoT integrations.

Google Earth Engine Analysis:

Raster operations: band math (e.g., NDVI, NDWI, NDBI).

Time-series analysis for vegetation monitoring.

Land cover classification using supervised/unsupervised methods.

Change detection for deforestation, urbanization, or flood monitoring.

Hands-On Practical:

Perform NDVI analysis using Sentinel-2 in GEE.

Create a time-series vegetation health chart.

Use ArcGIS Online to analyze urban green spaces with buffer and overlay tools.

Module 5: Cloud GIS Applications and Visualization

Application Development:

Building interactive dashboards in ArcGIS Online (charts, indicators, live feeds).

Configuring ArcGIS Web AppBuilder for customizable web apps.

Developing data stories with ArcGIS StoryMaps.

Visualization in GEE:

Creating animations and exporting GIFs of land cover change.

Adding charts and visual summaries within GEE scripts.

Integrating Google Maps and external data with Earth Engine outputs.

Capstone Project:

Participants design a mini-project using either ArcGIS Online or GEE:

Example 1: Urban growth monitoring using Sentinel imagery in GEE.

Example 2: Disaster response dashboard using ArcGIS Online real-time data feeds.

Presenting results to the class.