Introduction

This guide explains how to plan and capture drone images effectively for SkyMap. It covers best practices for selecting capture angles, ensuring sufficient image overlap, flying in a consistent way to support reliable processing results, and preparing Ground Control Point (GCP) targets for improved georeferencing accuracy.

Note: This article covers capture planning and execution. For step-by-step upload instructions, see the Upload Drone Photos for SkyMap.

Before You Fly: Key Concepts to Understand

SkyMap Drone Image Requirements

SkyMap processes standard drone photos into georeferenced aerial datasets such as Orthomosaic, DSM, Point Cloud, and Mesh.

To be eligible for processing, drone images must meet the following requirements:

• Supported formats: .jpg, .jpeg
• Minimum of 6 images required to create an aerial map
• Maximum of 4,000 images per aerial map
• Images must include valid geolocation data (latitude, longitude, and altitude in the GPS EXIF metadata)
• Images must be captured using a consistent strategy and have sufficient overlap; refer to the best practices below for guidance.

Note: Image quality issues cannot be fully corrected during processing, so poor image quality may affect final results.

Nadir vs. Oblique Capture

Drone photos can be captured using two primary acquisition methods: Nadir and Oblique. Each method is suited to different output types and use cases in SkyMap.

Nadir Capture

Nadir capture refers to drone photos captured from directly above, with the camera pointing straight downward toward the ground.

Use nadir capture when your goal is to generate:

• Orthomosaic (Ortho): A georeferenced 2D aerial image corrected for distortion and scale
• Digital Surface Model (DSM): A height map representing terrain and surface elevations

Nadir capture is commonly used for site overviews, progress tracking, and measurements where consistent scale and top-down accuracy are required.

Oblique Capture

Oblique capture refers to drone photos captured at an angled view, with the camera tilted to include vertical surfaces.

Use oblique capture when your goal is to generate:

• Point Cloud: A 3D point-based reconstruction of the site
• Mesh: A 3D textured surface for realistic visualization

Oblique capture is typically used when 3D context is required, such as capturing building façades, vertical structures, or complex site geometry.

Drone Capture Best Practices

The following best practices help ensure consistent image coverage and reliable processing results when capturing drone photos for SkyMap.

Flight Pattern and Image Overlap

Plan your drone capture using a grid-based flight pattern to ensure even site coverage and sufficient image overlap.

• Fly parallel paths across the site
• Maintain consistent spacing between flight lines
• Capture images at regular intervals along each path

• Maintain a consistent flight height throughout the capture

  Note: When multiple flight passes are required, keep the height consistent within each pass and avoid frequent or unplanned height changes.

This capture pattern helps achieve the overlap required for reliable processing.

Recommended minimum overlap

• Front overlap: 75% or higher
• Side overlap: 60% or higher

Note: For flat areas with homogeneous visual content (such as agricultural fields or concrete surfaces), increase front and side overlap to at least 80% to ensure reliable image alignment.

Insufficient overlap is one of the most common causes of processing failure or inaccurate results.

Considerations for Oblique Capture

When using oblique capture, maintaining consistency is especially important to ensure reliable 3D reconstruction.

When capturing buildings or vertical structures:

• Use intentional, structured flight passes rather than free or random movement
• If multiple passes are required, make angle or distance changes between passes, not continuously
• Keep the camera angle and flight height consistent within each pass
• Ensure sufficient overlap along façades and vertical surfaces

This approach helps ensure vertical surfaces are captured clearly and can be reconstructed reliably in 3D outputs.

Image Sharpness and Lighting

Maintain stable flight and lighting conditions to capture clear, usable images.

• Fly at a steady speed to reduce motion blur
• Capture images in consistent lighting conditions across the site
• Avoid capture during low-light conditions or when strong glare is present

Camera Settings

• Use default camera settings unless image quality issues occur
• If needed, adjust settings to reduce blur or noise and avoid heavy image enhancement

GCP Target Best Practices

If you plan to use Ground Control Points (GCPs) to improve georeferencing accuracy, follow these best practices when placing GCP targets on site and capturing drone images over them.

Note: GCPs are optional. GPS-based georeferencing is used by default. GCPs are recommended for civil and survey workflows that require higher positional accuracy.

GCP Target Requirements

• Target pattern: Black and white, square or diagonal pattern with high contrast.
• Minimum target size: 50 cm (20 inches). Targets must be large enough to be clearly visible in drone images.
• Minimum number of GCPs: 3 targets. More GCPs generally improve accuracy and allow better error distribution.

GCP Placement Guidelines

• Distribute GCPs evenly across the site to provide balanced spatial coverage.
• Place GCPs on flat, stable surfaces where they will remain undisturbed during the flight.
• Ensure each GCP is visible in multiple drone images from different positions to support reliable triangulation.
• Measure each GCP’s 3D coordinates (X, Y, Z) using RTK GNSS, Total Station, or equivalent survey equipment.

Drone Image Requirements for GCP Detection

When capturing drone images over GCP targets:

• Image quality: Sharp and high contrast. Avoid blurry or overexposed images.
• Camera angle: Nadir or slight oblique (less than 30°). Steep oblique angles reduce detection reliability.
• Image overlap: Good overlap (greater than 75%) over GCP target areas.

Auto GCP Detection Scope

SkyMap uses Auto GCP Detection to automatically identify GCP targets in drone images during processing.

• The detection algorithm searches within a 5×5 m range of the uploaded GCP coordinates.
• If detection fails for a GCP, that GCP is not applied during processing.
• Manual tie points are not supported.

Note: For details on uploading GCP coordinates and reviewing detection results, refer to the Upload Drone Photos for SkyMap and SkyMap Editor articles.

Common Capture Mistakes to Avoid

Below are some common issues to watch for during drone capture:

• Mixing nadir and oblique images unintentionally
• Flying too fast, resulting in motion blur
• Capturing images with insufficient overlap
• Changing flight height frequently or unintentionally during capture
• Capturing images with GPS location data disabled
• Using GCP targets that are too small, low contrast, or partially obscured