Geospatial Data & Mapping

Understand the place before the plan.

Geospatial data and mapping for location-based planning. Explore PetaNusa, permanent object identities, evidence, and the context behind every map.

Where we can help

Understand an area

Bring location data and relevant layers together to understand the area you are planning for.

Organise location records

Keep coordinates, attributes, sources, and supporting evidence connected to each mapped object.

Prepare data for decisions

Define the question first, then check whether the available data is complete, current, and suitable for that purpose.

Scope of service

Buildings, roads, administrative areas, and utility assets have different roles in a plan. We work from the question you want to answer and the data available for the area.

Location and coverage context

Organise layers to understand the relationship between premises, routes, boundaries, and infrastructure. Data coverage and freshness are reviewed for the requested area.

Object identity and evidence

PetaNusa’s published concept uses permanent PNID identifiers, supporting evidence, confidence scoring, and version history to describe an object’s provenance.

Data prepared for the workflow

Agree on geometry, attributes, coordinate reference systems, and delivery formats. Separate public reference layers from private infrastructure information.

Location data with a traceable context.

PetaNusa’s direction connects a mapped object to its identity, supporting evidence, and review history. The platform is in its MVP phase; coverage and feature availability are confirmed for each project.

Explore PetaNusa (new tab)

Object identity

PNID

Supporting evidence

Source & context

Review history

Changes & validation

PetaNusa data concept · MVP

How we work

We agree on the scope before starting, then review the work with you at each stage.

  1. Define the area and question

    Share the area of interest, the planning objective, and the layers you need to make a decision.

  2. Review the starting data

    Check sources, dates, coordinate systems, completeness, and whether new survey evidence is needed.

  3. Structure and map

    Prepare geometry and attributes, identify inconsistencies, and organise the data into usable layers.

  4. Deliver with context

    Document sources, limitations, metadata, and agreed formats so the dataset remains understandable beyond the map itself.

What you receive

Choose a complete engagement or the stages you need. Deliverables are confirmed in the proposal.

A structured map

Layers and attributes arranged around your planning question, with a clear area of interest.

Traceable data context

Source, survey or update dates where available, coordinate reference system, evidence references, and known gaps.

An agreed delivery format

Define export and integration needs at scoping. PetaNusa’s MVP roadmap lists GeoJSON/KML export and a basic API; availability is confirmed for your use case.

Related products

MVP today. Planned roadmap features are confirmed separately before inclusion in a project.

Questions & answers

Does PetaNusa already cover every area in Indonesia?

The platform’s national ambition does not imply complete coverage today. Dataset completeness, freshness, and suitability must be checked for the specific area and project.

Is private fiber infrastructure exposed publicly?

PetaNusa’s published policy describes the Fiber/ISP layer as private by default and excluded from its public Open API. Project-specific access and sharing must be agreed separately.

Are enterprise integrations and offline surveys available now?

The public roadmap places offline surveys, enterprise API, organization workspaces, and QGIS/AutoCAD plugins in planned phases. We confirm availability before including them in a project scope.

Let’s discuss your project.

Tell us what you have in mind. We’ll help define the scope and the next step.

Discuss your mapping needs
What to share with us
  • Area of interest and the question the map or dataset needs to answer.
  • Available datasets, source dates, required layers, and known gaps.
  • Required coordinates, attributes, export formats, and data access restrictions.