#geomapping

Teams working in the field often manage location-heavy datasets for inspections, routing, and daily operations. Exporting the entire dataset each time slows everything down. Filtered map data export eliminates this friction by allowing you to download only the points currently visible on your screen. This delivers cleaner files, cuts down wasted effort, and speeds up every analytical step.

Key Concept

Filtered map export captures only the data that matches the filters you apply. Whether you sort by category, service area, timeline, or operational status, the map instantly hides unrelated points and exports only what’s relevant. This reduces file size, removes unnecessary rows, and improves the precision of every dataset you generate.

Methodology

Open your project and load the dataset or insert points through the Custom Locations Library. Once your map displays all locations, apply the required filters such as region, type, date, or workflow stage. The map updates automatically to show only filtered points.

When the view is ready, choose Download or Export Layer to generate a CSV, XLSX, GeoJSON, or other supported file containing only the filtered data. These focused outputs can be used immediately for dashboards, compliance checks, planning sessions, or performance reviews without any manual clean-up.

Use Case: Fleet & Delivery Management

Logistics teams tracking delivery hubs, driver routes, and service zones often need to review only a specific subset of locations like pending deliveries, high-priority zones, or active drivers. Rather than exporting the entire network and filtering manually, filtered downloads let them extract just the required segments instantly. This speeds up operational reviews, supports faster route decisions, and improves day-to-day coordination across teams.

Extended Applications

This export method supports sectors such as utilities, public safety, real estate, healthcare, research, and telecom. Teams can skip unnecessary downloads and rely on precise, filter-based files that enhance audits, planning, and reporting. Whether dealing with incidents, surveys, network assets, or project checkpoints, filtered exports keep datasets clean and meaningful.

Conclusion

Key Concept

The idea behind a reusable location library is simple: store important GIS points once and reuse them endlessly. Every saved point complete with its name, category, address, and custom attributes remains consistent across all future projects, improving both speed and accuracy.

Methodology

Create a new Custom Layer Map in and give it a clear title and description. Next, head to Process Customer Locations and select Add from the Customer Location Library. Pick the locations you want or grab the full list and add them straight to your map in a single action. Use the Style Editor to categorize and color-code your points for clarity, choosing labels like Service, Retail, or Wholesale. Wrap up by sharing your finalized map using the platform’s Share and Preview tools.

Use Case: Hospital Network Coordination

For healthcare networks managing hospitals, clinics, labs, and emergency centers, repeated mapping is common. Instead of manually entering each facility for planning, routing, or crisis coordination, teams simply pull these points from the reusable library. This supports quicker decision-making, consistent datasets, and faster preparation for emergency or patient-flow planning.

Extended Applications

Any organization dealing with recurring location data transportation fleets, financial branches, telecom partners, campus facilities, government assets, or service networks benefits from this streamlined approach. It strengthens planning, reduces errors, and ensures every team works with the same reliable data.

Conclusion

Digital Naksha is an online platform that allows its users to create, access, and interact with different kinds of maps. Our products include web GIS, web mapping applications, and SaaS-based mapping products. 

For more details, visit - http://www.digitalnaksha.com/ 

I know right?

One of them, I think it was incestshipper, said that the distance between countries was easy to surmount in Europe and they could be together in hours. This strikes me as an amazingly stupid argument.