What’s New on Kili — Key Enhancements for Geospatial Projects

Geospatial teams on Kili just received a wave of updates that make labeling richer, clearer, and more efficient than ever. These improvements deepen context inside the labeling interface, streamline visual interpretation, and strengthen organizational visibility — all essential for working with complex geospatial datasets.

Below is a walkthrough of what’s new, starting with the most impactful updates for your workflows.

🌍 External Geospatial Layer Integration — A New Level of Context

The most transformative update: you can now connect external map layers directly from project settings and make them instantly available to annotators inside the labeling interface.

This includes layers powered by WMS and WMTS,  — a major step forward for teams who rely on rich contextual information.

Why it matters:

You can now enrich your geospatial projects with authoritative layers such as:

• topographic or terrain maps,
• hydrology, vegetation, or environmental datasets,
• infrastructure or cadastral maps,
• custom layers from internal GIS platforms.

Annotators can toggle these layers on or off and reorder them on the fly. This flexibility enhances spatial understanding and reduces annotation noise or uncertainty — especially in projects like land-use classification, environmental monitoring, or infrastructure mapping.

🧭 Image Borders for Geospatial Assets — Clearer Spatial Footprints

To help you better understand exactly what portion of the map corresponds to your imagery, Kili now lets you overlay image borders directly onto the basemap.

What this unlocks:

• A clear visual delineation of where an image starts and ends.
• Better interpretation when working with overlapping scenes or mosaics.
• Fewer mistakes due to annotators accidentally venturing outside image boundaries.

This simple visual cue helps anchor your labeling work in reality and makes complex datasets much easier to navigate.

🗂️ Layer Reordering — A More Flexible Labeling Workspace

Another upgrade that boosts clarity and control: you can now drag and drop layers within the labeling interface to reorder them however you like.

Whether you're working with basemaps, contextual overlays, or newly integrated external layers, this feature allows you to:

• bring the most relevant layer to the foreground,
• hide or push back visual distractions,
• fine-tune your view depending on the task at hand.

This introduces a fully customizable geospatial visualization environment — tailored by each user for each annotation.

🌐 What This Means for Your Geospatial Workflows

The latest updates reshape the geospatial annotation experience on Kili by bringing richer context, sharper visual clarity, and greater control directly into the labeling interface. Together, they create a faster, more intuitive, and more reliable workflow for anyone working with satellite, aerial, drone, or orthomosaic imagery.

More context → More accurate annotations

With external layers now available inside the labeling UI — and fully reorderable — annotators can finally interact with geospatial imagery in a deeply contextualized environment.

• Need elevation or slope context for environmental classification? Add it.
• Working on road or infrastructure mapping? Bring in cadastral or transportation layers.
• Conducting vegetation or land-use analysis? Integrate NDVI or land-cover tiles.

This variety of external information empowers annotators to make more confident decisions, reduces uncertainty in complex scenes, and leads to consistently higher-quality labels without requiring separate GIS tools.

Sharper visual boundaries → Fewer errors and cleaner datasets

Displaying image borders directly on top of the basemap ensures that annotators instantly know where the image begins and ends — a crucial improvement when working with overlapping scenes, mosaics, or basemap-integrated imagery.

• It prevents label drift outside the intended footprint.
• It helps reviewers identify inconsistencies quickly.
• It eliminates the guesswork that often occurs when satellite imagery blends seamlessly into background tiles.

This clarity doesn’t just make labeling easier — it improves dataset integrity and makes downstream model training more reliable.

A more controlled, user-centric workspace

The combination of layer reordering and external layer integration transforms the labeling interface into a customizable geospatial environment. Each annotator can configure their workspace to match the task at hand, whether that means pushing a distracting layer behind the imagery, bringing a roads overlay to the top, or toggling reference layers on and off as they work.

This flexibility supports a wide range of project types — from flood mapping to agricultural monitoring to urban planning — without forcing a one-size-fits-all visualization.

🚀 Try Kili with a Free Evaluation

Ready to experience these new geospatial capabilities for yourself?

Start your free evaluation period and explore how Kili can elevate your geospatial imagery annotation workflows — from richer contextual layers to precision-driven labeling tools.

👉 Get started today: Test Kili