How to Build Data-Driven Maps for Better Decision Making

Flood management teams use rainfall, river, and elevation data to assess risks and improve planning. However, analyzing rainfall records, river networks, elevation data, and flood-prone locations through spreadsheets alone can be challenging. Moreover, MAPOG simplifies this process by enabling users to build data-driven maps that combine multiple datasets into a single visual platform. Also, This helps decision-makers identify flood-risk areas, prioritize mitigation efforts, plan emergency responses, and make informed decisions based on real-world data.

Key Concept: Data-Driven Maps

Data-driven maps integrate geographic locations with datasets such as rainfall intensity, river proximity, historical flood events, elevation, population density, and infrastructure information. However, By visualizing these datasets on a map, users can identify flood-prone zones, vulnerable communities, safe locations, and patterns that support better planning and risk management.

Methodology: Data-Driven Mapping

Accordingly, Create interactive flood-risk maps by combining environmental and geographic datasets to visualize hazards, analyze vulnerable areas, support emergency planning, and improve decision-making.

1. Choosing Your Map Type

Launch MAPOG, navigate to Create and Publish Maps, and then select Open Workplace.

navigate to Create and Publish Maps  by Data-Driven Maps

Besides, Start by opening MAPOG and clicking + Create New Map.

Start by opening MAPOG by Data-Driven Maps

Similarly, Choose a Blank Map to visualize flood data, identify risk zones, and support planning decisions.

Choose a Blank Map by Data-Driven Maps

Enter a clear title and a brief description, then click Create to save your map.

clear title and a brief description by Data-Driven Maps

Likewise, A Blank Map lets you visualize flood data, analyze risk areas, and generate insights for better planning.

Blank Map lets you visualize flood databy Data-Driven Maps
2. Upload and Add Layers

In Process Data, select GIS Data Library and add the following layers.

GIS Data Library by Data-Driven Maps

In addition, River Layer: Visualize river networks to identify areas that may be affected by river overflow and flooding. Meanwhile, Navigate to Country → State → Nature → River, select the River layer, and click Add on Map.

Visualize river networks by Data-Driven Maps

Subsequently, Keep only the line layer and remove the unnecessary layers 

Keep only the line layer by Data-Driven Maps

Therefore, Residential Building Layer: Navigate to Country → State → Housing → Residential Building, select the layer, and click Add on Map to display residential areas that may be vulnerable to flood events and require mitigation planning.

Residential Building Layer by Data-Driven Maps

Thus, Keep only the polygon layer and remove all unnecessary layers.

Keep only the polygon layer by Data-Driven Maps
3. Create Buffer Zone for Flood-Prone River Areas

Consequently, Go to Process Data and select the Buffer Analysis Tool.Choose the River Layer as the input layer.Set the buffer distance to 1 km.

Buffer Analysis Too

Save the output and rename the layer as Buffer 1 Km.

Save the output and rename the layer

Additionally, Go to Process Data and select Merge Polygon. Furthermore, Choose the River Flood Buffer layer as the input. Select Merge by Attribute.Choose Waterway as the attribute.Set the attribute value to River.Save the output as a new layer.

Merge Polygon

Rename the new layer as River Flood Layer.

River Flood Layer
4. Filter Residential Areas Within the Flood Buffer

Go to Process Data and select the Advanced Filter Tool. Choose Land Use: Residential as the target layer. Select Filter by Applying Layer Operations.

Advanced Filter Tool

Choose the River Flood Layer as the source layer. Set the operation to Within. Click Submit to extract residential areas located within the flood buffer.

operation to Within

Publish the layer and save and rename the layer.

Publish the layer

Style the output layer to highlight residential areas that may be at risk of flooding.

Style the output layer
5. Identify Safe Residential Zones

Go to Process Data and select the Advanced Filter Tool. Choose Land Use: Residential as the target layer. Select Filter by Applying Layer Operations.

Advanced Filter Tool

Choose the River Flood Layer as the source layer.Set the operation to Outside. Click Submit to extract residential areas located outside the flood buffer.

 Outside

Publish the layer and save and rename the layer.

Publish the layer

Style the output layer using a different color scheme and label it as Safe Zones to clearly distinguish lower-risk residential areas from flood-prone locations.

Style the output layer

Now customize your project branding from Map Settings. Click Replace to upload a company logo or project image, make the required adjustments.

Map Settings

And save it as the branding element. 

save it as the branding element
8. Publish and Share Your Map

Once setup is complete, use Preview & Share  to publish your map and generate a shareable or embeddable link, letting users explore properties by all or selected attributes.

Preview & Share 

Provide map access by adding users, assigning roles, and enabling shared tools like geometry filters, search, and map controls. Use +Add Users to invite members, assign view/edit permissions, and enable public map features like search, filters, sorting, and shared tools.

Provide map access by adding users

Industry Use Cases and Benefits

Visualize flood-risk and safe residential areas on interactive maps to support disaster preparedness, urban planning, emergency response, risk assessment, and community protection, helping organizations make data-driven decisions and improve flood management strategies.

Data-Driven Maps

Conclusion

In conclusion, MAPOG simplifies flood risk mapping by combining river and residential datasets with spatial analysis tools. This enables users to identify vulnerable communities, locate safe zones, and generate actionable insights for better planning, risk mitigation, and disaster preparedness without requiring advanced GIS expertise.

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