ArcGIS Portal
a. ArcGIS Portal
ArcGIS Portal has a rich set of tools for creating maps and analyzing spatial data. Using data from the Notification System, users can perform mapping and analytical tasks in web browsers using ArcGIS Portal or its sister software, ArcGIS Online. Users can also download data to the desktop and perform mapping and analysis using ArcGIS Pro.
Click on this link to access ArcGIS Portal. Log in with your ArcGIS Portal account.
b. ArcGIS Tutorials – Getting Started
Below are links to training material for MOHW personnel to get started using notification system data to perform geospatial analysis.
1. Disease Mapping
- Display notification cases as points on a map
- Thematic Mapping – create maps to show variations in disease rates by parishes and communities.
- Introduction to ArcGIS Online (video series)
2. Cluster Analysis
- Use the Kernel Density tool to create heat maps and identify high-density areas of disease incidents.
- Create Next Generation Heat Maps.
- Use cluster analysis tools to identify statistically significant clusters of disease incidents.
- Cluster Analysis: Finding Patterns Using Statistics and Machine Learning.
3. Temporal Analysis
- Create animations to visualize the spread of disease over time and space.
- Create charts and graphs from GIS data (bar charts, line charts, etc.) using ArcGIS tools.
4. Proximity Analysis
- Use the Buffer tool to create zones around disease incidents, identify locations in close proximity, and analyze the impact on surrounding areas.
5. Statistical Analysis
- Calculate basic spatial statistics (mean center, orientation of points, box plots, etc.).
- Identify spatial patterns and clusters using statistical measures.
- Spatial Analysis using ArcGIS Online.
6. Perform Spatial Queries
- Use attribute queries to filter and identify specific disease incidents based on their attributes.
- Location-based queries: find incidents within a specified area.
7. Risk Assessment
- Risk mapping: assess and map areas with a higher risk of disease transmission based on various factors.
- Vulnerability analysis: analyze vulnerability factors in relation to disease occurrences.
8. Predictive Modeling
- Use regression analysis to understand spatial relationships between disease incidents and various factors.
- Apply machine learning models for predictive modeling and pattern detection.
9. Collaboration and Reporting
- Create story maps to communicate and share disease surveillance data.
- Build interactive dashboards for real-time monitoring and reporting.