DRONE EMOTIONS RESEARCH · TECHNICAL TOOL 001

Photogrammetry Project Readiness Checklist for Agisoft Metashape

A structured planning resource for reviewing datasets, accuracy requirements, coordinate systems, computing resources, licensing, processing strategy and expected deliverables before committing time and infrastructure to an Agisoft Metashape project.

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01
TECHNICAL TOOL

8 REVIEW AREAS

Planning · Data · Accuracy
Hardware · Workflow · Delivery

DEVELOPED BY DRONE EMOTIONS

Last reviewed: September 2026

TRANSPARENT CONTENT CLASSIFICATION

This is an original professional planning resource developed by Drone Emotions Srl. It is not a customer case study, a performance benchmark or official Agisoft LLC documentation. It is designed to help identify project questions and risks that must be validated against the actual dataset, software version, hardware environment and required deliverables.

WHY READINESS MATTERS

Reduce avoidable uncertainty before processing begins

Many photogrammetry problems become visible only after significant processing time has already been spent. Incomplete coverage, inconsistent reference data, an unsuitable coordinate system, insufficient storage or undefined deliverables can lead to unnecessary reprocessing and unreliable outputs.

A readiness review does not replace technical validation. It creates a documented starting point from which the dataset, resources, workflow and acceptance criteria can be assessed in a controlled sequence.

✓ Define the decision the project must support

✓ Identify missing or inconsistent data before processing

✓ Match computing resources to the actual workload

✓ Establish quality-control and delivery requirements

INTENDED USERS

A planning framework for professional projects

Surveying and mapping teams
Planning referenced aerial and terrestrial projects.

Engineering and infrastructure organizations
Defining measurable outputs and repeatable documentation.

Universities and research laboratories
Preparing shared workflows, hardware and licensing environments.

Photogrammetry professionals
Reviewing unfamiliar, large or technically demanding datasets.

HOW TO USE THE TOOL

Four steps before committing to the full workflow

Use the checklist during project intake, before a quotation, before acquisition or before starting expensive processing stages.

01

Define

Clarify the project objective, required outputs, accuracy expectations and acceptance criteria.

02

Inspect

Review image quality, metadata, coverage, reference data and coordinate-system information.

03

Plan

Match hardware, storage, licensing and workflow stages to the actual dataset and deliverables.

04

Validate

Run representative tests and approve defined quality gates before generating final products.

PROJECT READINESS CHECKLIST

Eight areas to review before full processing

Expand each area and record the information that is known, unknown or still requires verification. An unanswered critical question should become a documented project action.

01 — Project objective and required deliverables

Start with the purpose of the project, not with the processing settings.

  • What operational, scientific, engineering or documentation decision must the project support?
  • Which outputs are required: referenced point cloud, mesh, textured model, orthomosaic, DSM, DTM, contours, measurements or reports?
  • What ground resolution, model detail or measurement capability is actually required?
  • Is absolute accuracy required, or is relative geometry sufficient?
  • Which output coordinate system, units, file formats and delivery platforms are required?
  • What area, object, time period or change must be documented?
  • Who will review and accept the final deliverables?
  • Which acceptance criteria will determine whether the project is complete?

Readiness evidence: a written project brief listing deliverables, required accuracy, coordinate system, resolution, formats and acceptance criteria.

Verify whether the source imagery can support the expected result.

  • How many images are included and what is their resolution and file format?
  • Which cameras, lenses, focal lengths or sensors were used?
  • Are the images nadir, oblique, terrestrial or a combination of capture geometries?
  • Is forward and side overlap sufficient and reasonably consistent?
  • Are there missing flight lines, gaps, occlusions or poorly observed surfaces?
  • Are focus, shutter speed, exposure and motion blur acceptable across the dataset?
  • Are timestamps, GNSS coordinates, orientation data and camera metadata intact?
  • Does the dataset combine several flights, dates, altitudes, cameras or environmental conditions?
  • Are duplicate, corrupted or irrelevant images present?
  • Do data ownership and usage permissions allow processing and publication?

Readiness evidence: an image-quality audit and a documented inventory of sensors, flights, metadata, coverage and known limitations.

Separate information used to control the project from information used to validate it.

  • Are camera coordinates autonomous GNSS, RTK, PPK or derived from another system?
  • Are position accuracies known and assigned realistically?
  • Are Ground Control Points available and were they surveyed with an appropriate method?
  • Are control points clearly identifiable in the images?
  • Are checkpoints reserved for independent validation rather than used in the adjustment?
  • Are control points and checkpoints distributed across the full site and elevation range?
  • Are marker coordinates, units, point identifiers and accuracy values consistent?
  • Is there an external survey specification or tolerance that must be satisfied?
  • Will the final report distinguish reprojection error, control residuals and checkpoint error?

Readiness evidence: a reference-data plan identifying camera accuracy, control points, independent checkpoints and acceptance tolerances.

Coordinate-system problems can produce plausible-looking but unusable results.

  • What is the source horizontal coordinate reference system?
  • What is the required project and delivery coordinate reference system?
  • Is the relevant EPSG code known and appropriate for the project area?
  • Are heights ellipsoidal, orthometric or referenced to a local datum?
  • Is a geoid model or vertical transformation required?
  • Are all coordinates expressed in compatible units and axis order?
  • Do camera coordinates, GCPs, checkpoints and expected outputs use compatible reference definitions?
  • Has a known point been checked after transformation?
  • Will the CRS, transformation and height convention be documented in the final delivery?

Readiness evidence: a documented source, project and output CRS, including vertical datum, units and required transformation resources.

Plan for input data, working files, intermediate products and final deliverables.

  • What is the total image count, resolution and source-data size?
  • How much system RAM and GPU memory is available?
  • Which CPU and GPU will perform the workload and are drivers current?
  • Is fast local SSD or NVMe storage available for active processing?
  • How much free working space is available beyond the source dataset?
  • Will network-attached storage introduce a throughput or reliability limitation?
  • Where will backups, project versions and exported products be stored?
  • Can a representative subset be processed before committing the full dataset?
  • Is a single workstation sufficient, or should network processing be evaluated?
  • Who is responsible for monitoring storage, failed tasks and recovery?

Readiness evidence: a documented hardware and storage plan supported by a representative test where project scale or output demand is uncertain.

Confirm that the selected environment supports the required functions and number of users.

  • Which Agisoft Metashape functions are required by the expected workflow?
  • Does the project require Professional-specific georeferencing, measurement or geospatial outputs?
  • Which operating system and Metashape version will be used?
  • Is a Node-Locked or, where applicable, Floating configuration more appropriate?
  • How many simultaneous users or processing clients are required?
  • Will the software operate on a workstation, server, secure network or offline environment?
  • Does the organization need centralized license availability or transfer between workstations?
  • Is network processing planned, and have client, node and shared-storage roles been defined?
  • Have activation, firewall, update and support requirements been reviewed?
  • Has the deployment been tested before the production schedule begins?

Readiness evidence: a licensing and deployment plan aligned with the required functions, users, devices, network and security constraints.

Approve each critical stage before starting the next expensive operation.

  • How will images, calibration groups, flights and sensors be organized?
  • Which alignment strategy will be tested first and why?
  • Will a representative area be used to evaluate settings and resource demand?
  • How will weak connections, unaligned cameras and poor tie-point distribution be identified?
  • When will camera calibration and reference accuracy be reviewed?
  • What conditions must be satisfied before generating depth maps, point clouds, DEMs, orthomosaics or models?
  • Will the project be processed as one coherent block or divided into chunks?
  • How will classification, masking, cleaning and manual edits be documented?
  • Which intermediate products must be retained for recovery or audit?
  • Who approves each quality gate?

Readiness evidence: a staged workflow with explicit review points after data import, alignment, reference optimization and each final-product stage.

A professional result should remain understandable after the project has been delivered.

  • Which outputs, file formats, resolutions, units and coordinate systems will be delivered?
  • Will the processing report and accuracy information accompany the results?
  • Will control and checkpoint statistics be presented separately?
  • Are naming conventions and version numbers defined?
  • Which source images, project files, intermediate data and exports must be archived?
  • Are software version, processing settings and manual interventions documented?
  • How will large files be transferred securely to the recipient?
  • Are confidentiality, retention and deletion requirements defined?
  • Can another qualified operator understand how the outputs were produced?
  • Who provides final technical approval?

Readiness evidence: a delivery and archive specification that preserves the context, quality information and reproducibility of the project.

READINESS DECISION

Proceed, review or resolve first

The checklist is not a numerical certification. It supports a documented professional decision about whether the project is sufficiently defined to move forward.

PROCEED

Critical inputs are defined

Objectives, deliverables, CRS, validation strategy, hardware, storage and quality gates are documented. Representative testing can begin.

REVIEW

Some assumptions remain open

A limited test, technical clarification or additional project information is required before committing to full processing.

RESOLVE FIRST

A critical dependency is missing

Coverage, image quality, coordinate reference, validation data, storage or expected deliverables are insufficiently defined.

PROJECT INTAKE · DATASET

Information to record

Application
Surveying, inspection, heritage, research, mining, construction or other.

Image dataset
Count, megapixels, file format, total size, capture dates and sensors.

Capture geometry
Aerial nadir, oblique, terrestrial, close range or mixed.

Reference data
Camera coordinates, RTK/PPK, GCPs, checkpoints and their accuracy.

Known limitations
Missing coverage, blur, occlusion, inconsistent conditions or metadata.

PROJECT INTAKE · REQUIREMENTS

Decisions to document

Expected deliverables
Point cloud, mesh, orthomosaic, DEM, DTM, measurements, report or other.

Accuracy and resolution
Required GSD, absolute accuracy, relative precision and acceptance tolerance.

Coordinate system
Horizontal CRS, vertical datum, geoid, units and transformation requirements.

Computing environment
CPU, GPU, RAM, SSD, network storage, operating system and deployment.

Delivery and deadline
Formats, recipient, transfer method, review process and required completion date.

Need an expert review of your project?

Send the dataset profile and project requirements to Drone Emotions. Do not attach confidential or large source datasets until an appropriate transfer method has been agreed.

Request a Readiness Review

LIMITATIONS AND RESPONSIBLE USE

A checklist supports judgment; it does not replace validation

Photogrammetry performance and accuracy depend on acquisition geometry, image quality, scene characteristics, reference data, software version, processing parameters, hardware and the intended output. Completing this checklist does not guarantee a particular result, processing time or accuracy level.

Where contractual, surveying, safety, regulatory or scientific requirements apply, the project should be reviewed by appropriately qualified professionals and validated against independent evidence.

✓ No customer project is represented

✓ No measured performance is claimed

✓ Project-specific testing remains necessary

✓ Method and limitations are disclosed

Agisoft and Metashape are trademarks of their respective owner. This independent resource is developed by Drone Emotions Srl, an Agisoft Authorized Reseller and Training Center, and is not official Agisoft LLC documentation.

CONTINUE EXPLORING

From project planning to workflow decisions

TECHNICAL SCENARIOS

Explore Workflow Decisions

Review transparent illustrative scenarios covering multi-sensor documentation, large datasets and university deployment.

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PROFESSIONAL LEARNING

Build Practical Skills

Develop workflow capability through instructor-led workshops, structured online learning and personal consultation.

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EXPERT SUPPORT

Discuss Your Requirements

Receive guidance on licensing, deployment, hardware planning and professional Agisoft Metashape workflows.

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QUESTIONS

About this technical tool

The checklist is intended to improve project conversations and expose uncertainty before expensive processing begins.

No. This is an independent technical planning resource developed by Drone Emotions Srl. Official product documentation, specifications and licensing terms should always be confirmed through Agisoft LLC and current authorized information.

Yes. It can help identify missing metadata, reference limitations, coordinate-system questions, resource constraints and delivery requirements before the existing dataset is processed or reprocessed.

No. Image count alone is not sufficient to predict resource demand. Image resolution, scene complexity, processing stages, selected parameters and outputs all influence CPU, GPU, RAM, storage and processing time. A representative test is recommended for demanding projects.

No. Accuracy must be evaluated using appropriate acquisition, reference data, camera modelling, independent checkpoints, quality-control procedures and professional interpretation of the results.

Yes. Drone Emotions can review the project objective, dataset profile, expected deliverables, licensing and computing environment. Contact the team by email before sending confidential or large source datasets.

DRONE EMOTIONS RESEARCH

Turn project uncertainty into documented decisions

Describe your dataset, expected deliverables and current workflow. Drone Emotions can help identify the technical, licensing and infrastructure questions that should be resolved before full processing.

Email the Technical Team

Drone Emotions Srl
Agisoft Authorized Reseller & Training Center