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Construction InfrastructureTop 10 Best Drone Topography Software of 2026
Compare drone topography software options for mapping workflows, including OpenDroneMap and other tools, with tradeoffs for survey and GIS teams.
How we ranked these tools
An editor sets the topic, the inclusion criteria, and the evaluation framework before research starts.
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Framework: Features 40% · Ease 30% · Value 30%
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3DF Zephyr is the best overall pick for photogrammetry teams that need controlled, repeatable surface deliverables because its camera calibration and reconstruction quality controls keep dense clouds and meshes consistent across datasets, while SimActive Correlator3D fits mapping teams processing lots of flights since its region and tiling reconstruction settings help maintain stable matching quality on large, mixed-overlap projects.
Editor’s top 3 picks
Three quick recommendations before you dive into the full comparison below — each one leads on a different dimension.
3DF Zephyr
Camera calibration and reconstruction quality controls that keep dense cloud and mesh results consistent across datasets.
Best for: Fits when photogrammetry teams need controlled reconstruction and repeatable surface deliverables before GIS processing.
SimActive Correlator3D
Editor pickRegion and tiling based dense reconstruction settings that keep matching quality stable on large, mixed-overlap datasets.
Best for: Fits when mapping teams need controlled dense matching and consistent georeferenced point clouds across many flights.
OpenDroneMap
Editor pickStage-driven processing workflow that exposes intermediate artifacts for inspection and deterministic reruns across AOIs.
Best for: Fits when teams need repeatable drone topography processing with controllable stages and exportable geospatial outputs for GIS workflows.
Comparison Table
3DF Zephyr
SMBPhotogrammetry software that converts drone photos into dense point clouds, meshes, orthophotos, and terrain products for survey and mapping work.
Camera calibration and reconstruction quality controls that keep dense cloud and mesh results consistent across datasets.
3DF Zephyr from 3dflow.net is a photogrammetry processing suite that turns drone imagery into dense clouds, meshes, and orthomosaics within the same workflow. The core strength is production-grade controls for camera calibration, tie point behavior, and reconstruction quality so results stay consistent across large datasets.
Zephyr also supports measurement outputs such as surface models and derived products like contour lines, which helps standardize downstream mapping deliverables. For teams that need repeatable exports for GIS, it provides format options for orthos, meshes, and point cloud outputs that fit common photogrammetry pipelines.
- +Strong camera calibration and reconstruction controls for consistent mapping outputs
- +Single pipeline from images to dense cloud, mesh, and orthomosaic products
- +Measurement-oriented outputs for surface products used in mapping deliverables
- +Export options fit GIS handoff workflows for point clouds and surfaces
- –Less oriented to end-to-end drone mission planning than mapping-first tools
- –Workflow tuning demands expertise to avoid unstable reconstructions
- –Automation and API access for external orchestration are limited compared with platform tools
- –Large datasets can require more workstation resources for dense reconstruction
Best for: Fits when photogrammetry teams need controlled reconstruction and repeatable surface deliverables before GIS processing.
SimActive Correlator3D
enterprisePhotogrammetry software for high-volume aerial processing, DSM and DTM generation, and topographic mapping.
Region and tiling based dense reconstruction settings that keep matching quality stable on large, mixed-overlap datasets.
Correlator3D fits teams that need repeatable dense cloud generation with tight control over matching settings and region-based processing. It supports coordinate reference system and georeferencing steps that help keep results consistent between missions with the same control strategy. For large sites, it can segment imagery and produce dense outputs per block, which reduces manual rework when coverage is uneven.
The tradeoff is that quality depends heavily on input image geometry and matching parameters, which adds setup time for new cameras or new flight patterns. Correlator3D is most effective when the workflow already includes defined ground control points and consistent acquisition planning for reliable tie-point density.
A second tradeoff is limited “end-to-end” deliverable generation compared with integrated drone mapping suites, because Correlator3D primarily anchors the dense matching step and expects downstream tools for DEM differencing, contour generation, and vector outputs.
- +Dense image matching controls that translate into consistent point clouds
- +Block-based processing supports large sites with uneven image overlap
- +Georeferencing workflows align dense outputs to a shared coordinate reference system
- +Repeatable project setups reduce variation between missions
- –Matching parameter tuning takes time for each new camera and capture pattern
- –Downstream DEM and contour workflows require additional tools
- –Dense output sizes can increase compute needs during dense reconstruction
- –Less suited for fully automated mapping from raw drone data
Survey and photogrammetry teams
Dense cloud generation for georeferenced surfaces
Higher usable coverage for surfaces
Enterprise mapping operations
Repeat processing across recurring sites
Lower variation between deliverables
Show 2 more scenarios
Infrastructure asset teams
Change workflows using point cloud baselines
More reliable surface comparisons
Dense outputs provide consistent inputs for downstream DEM differencing and contour updates.
GIS specialists
Input preparation for mesh and classification
Faster time from imagery to GIS layers
Dense cloud outputs support meshing and point cloud classification in downstream toolchains.
Best for: Fits when mapping teams need controlled dense matching and consistent georeferenced point clouds across many flights.
OpenDroneMap
open-sourceOpen source toolkit for processing drone images into maps, point clouds, digital elevation models, and 3D models.
Stage-driven processing workflow that exposes intermediate artifacts for inspection and deterministic reruns across AOIs.
OpenDroneMap turns photogrammetry or related aerial imagery inputs into georeferenced products like orthomosaics and elevation surfaces, with a command-line pipeline geared for repeatable processing. It emphasizes a transparent, file-based workflow built on a sequence of reconstruction stages, so teams can rerun jobs with consistent settings across projects.
Integration is centered on its automation surface, because outputs are stored as standard geospatial files and intermediate artifacts remain available for inspection. Governance and extensibility depend mostly on how teams wrap the pipeline with their own orchestration and data handling rather than a built-in admin console.
- +Pipeline is stage-based so intermediate outputs can be inspected and reused
- +Geospatial outputs are stored as standard files for downstream GIS ingestion
- +Command-line automation supports batch processing across many AOIs
- +Extensible processing can be wrapped into mission-ready workflows
- –Operational setup demands comfort with command-line execution and environment management
- –No built-in project collaboration UI for reviews, approvals, or RBAC
- –Large jobs can require significant compute planning to avoid pipeline stalls
- –Higher-quality results depend on capture quality and control point strategy
Best for: Fits when teams need repeatable drone topography processing with controllable stages and exportable geospatial outputs for GIS workflows.
RealityCapture
professional desktopPhotogrammetry software for fast 3D reconstruction, terrain models, orthophotos, and georeferenced outputs.
Control point adjustment workflow is tightly integrated into the reconstruction stage before dense output.
RealityCapture is a photogrammetry desktop tool that emphasizes fast dense reconstruction from aerial imagery and supports high-throughput projects with large image sets. It generates dense point clouds and mesh reconstructions that can feed downstream orthomosaic stitching and terrain products for drone topography deliverables.
- +Fast dense cloud reconstruction on large aerial image sets
- +Strong control point adjustment and coordinate reference system handling
- +High-detail mesh reconstruction that carries into orthomosaic creation
- +Clear training materials for repeatable drone topography outputs
- –Workflow complexity rises with oblique imagery and mixed capture geometry
- –Limited built-in tools for point cloud classification workflows compared to specialized stacks
- –Automation depth depends on external scripting rather than native orchestration
- –Processing setup requires careful tuning to avoid dataset-specific failures
Best for: Fits when teams need fast photogrammetry outputs for orthomosaic and terrain surfaces with disciplined control and CRS handling.
WebODM
open-sourceOpen source drone mapping software for orthomosaics, point clouds, elevation models, and contour generation.
Task-based web UI for monitoring and re-running photogrammetry jobs on the same server.
WebODM is built around an end-to-end processing chain that takes aligned imagery through dense reconstruction and then produces exportable geospatial artifacts. The system supports georeferencing via ground control points or GNSS metadata, and it can generate surface models that GIS tools can ingest. Operators get a web UI for monitoring runs and retrieving outputs, which reduces manual handoffs between flight storage and GIS editing.
- +Self-hosted pipeline keeps processing control and data locality
- +Web UI monitors long photogrammetry runs and trackable outputs
- +Georeferencing workflows support control points and coordinate systems
- +Exportable artifacts integrate into GIS and QA routines
- –Performance and output quality depend on server capacity tuning
- –Reprocessing requires pipeline familiarity and consistent configuration discipline
- –Automation depends on operational setup rather than turnkey integrations
- –Oblique-heavy datasets can require careful capture and alignment settings
Best for: Fits when teams need repeatable, self-managed photogrammetry outputs for GIS workflows.
DroneMapper RAPID
SMBDesktop photogrammetry software for processing drone imagery into orthomosaics, elevation models, point clouds, and contour maps.
A rapid processing path that prioritizes deliverable turnaround from mission imagery to terrain outputs.
DroneMapper RAPID targets drone topography work that needs fast turnaround from imagery into deliverables for field teams and GIS workflows. It emphasizes a streamlined photogrammetry pipeline that converts captures into usable surfaces like orthomosaics and elevation outputs.
- +Rapid photogrammetry to orthomosaic and elevation outputs for tight mapping schedules
- +Repeatable capture workflow reduces variation between missions at different sites
- +Terrain deliverable outputs support contour generation and cross-section profiling
- +Export-ready outputs fit common GIS review and field annotation cycles
- –Fewer advanced point cloud classification and refinement steps than heavier pipelines
- –Limited control point adjustment depth for highly constrained ground control networks
- –Batch automation depends on a narrower set of workflow variables
- –Georeferencing quality can lag when RTK or PPK metadata is inconsistent
Best for: Fits when mapping teams need fast terrain deliverables with a repeatable capture and output workflow.
ArcGIS Drone2Map
enterpriseDesktop photogrammetry software that turns drone imagery into orthomosaics, digital surface models, point clouds, and contour products for mapping workflows.
ArcGIS-native publishing and processing flow that keeps photogrammetry outputs aligned with ArcGIS data management.
ArcGIS Drone2Map is a drone topography tool that converts aerial imagery into geospatial outputs managed through ArcGIS workflows.
- +Tight ArcGIS workflow so deliverables land in the same GIS environment
- +Ground control point and coordinate reference system management supports repeatable georeferencing
- +Repeatable processing jobs fit multi-site photogrammetry pipelines
- +Python scripting support adds automation for batch processing
- –Less flexible for non-ArcGIS delivery patterns than standalone photogrammetry tools
- –Oblique imagery handling and advanced reconstruction tuning can feel gated by defaults
- –Point cloud classification and derivative tuning take more setup than simpler UIs
- –Hardware and licensing constraints can limit quick ad hoc processing
Best for: Fits when GIS teams need GIS-native orthomosaic and terrain outputs with automation and batch processing.
WingtraCLOUD
vertical specialistDrone mapping software for survey workflows that produces maps, elevation models, and measurement outputs from Wingtra and other survey missions.
Wingtra mission-to-processing project linkage that keeps deliverable review tied to each flight run.
WingtraCLOUD centers on managing Wingtra drone missions and photogrammetry outputs with workflow controls tied to that flight ecosystem. The system provides project organization, upload and processing orchestration, and quality checks for deliverable generation like orthomosaics and surface models.
- +Mission and processing workflow stays closely aligned with Wingtra flight operations
- +Project-based handling keeps outputs grouped per flight run and revision cycle
- +Quality review steps connect inspection to processing outputs
- +Collaboration workflows reduce manual file routing between team members
- –Workflow depth depends on Wingtra-centered flight and capture formats
- –API and automation surface is limited for non-Wingtra photogrammetry pipelines
- –Advanced downstream options for point editing and reprocessing can feel indirect
- –Large-scale bulk processing needs careful operational planning to avoid bottlenecks
Best for: Fits when mapping teams standardize on Wingtra hardware and want managed photogrammetry deliverables with controlled review.
Virtual Surveyor
vertical specialistTerrain analysis and surveying software built to extract topographic deliverables from drone maps and point clouds.
Template-based processing recipes let teams standardize settings across projects and keep deliverables consistent.
Virtual Surveyor is built around managing survey projects end to end, so the same processing settings can be reused across captures for a site or corridor. It handles georeferencing inputs that feed into downstream products, which keeps coordinate reference decisions consistent when multiple datasets are stitched into a final deliverable. Core outputs align with typical drone topography needs, including orthomosaics and elevation products derived from reconstructed geometry. It is ranked within this set for teams that want controlled workflows rather than ad hoc exports.
- +Project workflow keeps georeferencing choices consistent across outputs
- +Template-driven processing reduces repeated manual configuration work
- +Deliverable set covers orthomosaics and elevation surfaces
- +Dataset organization supports repeat sites and batch processing
- –Automation centers on templates instead of external API triggers
- –Config complexity increases for nonstandard capture setups
- –Advanced custom pipeline changes require tighter workflow alignment
- –Collaboration controls can feel limited for large distributed teams
Best for: Fits when survey teams need repeatable drone mapping deliverables with consistent georeferencing.
Sentera FieldAgent
vertical specialistDrone data software that supports mapping, elevation analysis, and terrain-related workflows across agriculture and land-focused operations.
FieldAgent workflow ties field execution steps to repeatable mapping deliverables, reducing re-capture loops.
Sentera FieldAgent supports drone capture planning, data collection workflows, and analytics for agricultural mapping tasks tied to field boundaries. It organizes projects around repeatable field execution with photo and sensor capture collection steps that feed downstream mapping deliverables.
- +Field-first workflow links capture, review, and map output for repeat missions
- +Structured project execution supports consistent results across crews and days
- +Workflow steps reduce missed captures and speed up map-ready completion
- +Agronomy-focused deliverables align to common field operations decisions
- –Limited emphasis on advanced photogrammetry pipeline controls versus general mapping suites
- –External processing and data exports can feel heavier for non-agronomy workflows
- –Point cloud workflows and vectorization depth are not the primary focus
- –Mission-level tuning for capture geometry is less granular than specialized mapping tools
Best for: Fits when farm and service teams need repeatable field capture workflows with mapping deliverables.
Conclusion
After evaluating 10 drone topography software, 3DF Zephyr stands out as our overall top pick — it scored highest across our combined criteria of features, ease of use, and value, which is why it sits at #1 in the rankings above.
Use the comparison table and detailed reviews above to validate the fit against your own requirements before committing to a tool.
How to Choose the Right Drone Topography Software
Drone topography software turns drone imagery into georeferenced terrain products such as orthomosaics and elevation surfaces, and this guide covers WebODM, DroneDeploy, Propeller Aero, senseFly eMotion, and the other six tools ranked alongside them.
The selection focuses on repeatable photogrammetry pipelines, reconstruction and georeferencing control, and the operational mechanics teams use to process many flights into consistent outputs.
WebODM leads the list for monitored, self-managed job reruns on the same server, while RealityCapture earns attention for integrating control point adjustment into the reconstruction stage.
ArcGIS Drone2Map is included for teams that need ArcGIS-native publishing flows, and OpenDroneMap is included for stage-driven processing that exposes intermediate artifacts for deterministic reruns.
Drone Topography Software for photogrammetry-to-terrain pipelines and controlled georeferenced outputs
Drone topography software runs photogrammetry pipelines that produce dense reconstruction outputs, then converts those results into mapping deliverables such as orthomosaics and terrain surfaces tied to coordinate reference system choices.
The operational difference shows up in how tools structure processing and control: WebODM uses a task-based web UI to monitor and re-run photogrammetry jobs on the same server, while OpenDroneMap uses a stage-driven workflow that exposes intermediate artifacts for inspection and deterministic reruns across AOIs.
This category also varies by how georeferencing is managed inside the pipeline. RealityCapture bundles control point adjustment into the reconstruction stage before dense output, and ArcGIS Drone2Map keeps the publishing and processing flow aligned with ArcGIS data management so the deliverables land in the same GIS environment.
Processing control, automation depth, and inspection points for terrain deliverables
Teams lose time when drone topography software hides intermediate processing results and forces full re-runs to validate changes. The tools that surface job state, break processing into stages, or tie processing tightly to mission context reduce rework.
Operational control also matters when deliverables must stay consistent across many flights, varied capture overlap, and repeatable georeferencing. WebODM and OpenDroneMap both focus on rerun mechanics, while RealityCapture and ArcGIS Drone2Map focus on keeping reconstruction and publishing aligned to the workflow the team already uses.
Rerun mechanics and job observability for photogrammetry outputs
WebODM uses a task-based web UI to monitor and re-run photogrammetry jobs on the same server. OpenDroneMap uses a stage-driven workflow that exposes intermediate artifacts for inspection and deterministic reruns across AOIs.
Controlled dense reconstruction settings for large, mixed-overlap datasets
SimActive Correlator3D applies region and tiling based dense reconstruction settings to keep matching quality stable across large sites. 3DF Zephyr provides camera calibration and reconstruction quality controls that keep dense cloud and mesh results consistent across datasets.
Repeatability through workflow templates versus built-in recon control
Virtual Surveyor uses template-based processing recipes so teams standardize settings and keep deliverables consistent. RealityCapture bundles a control point adjustment workflow into reconstruction before dense output to reduce disconnects between control handling and surface generation.
Integration into existing GIS publishing or flight operations
ArcGIS Drone2Map keeps photogrammetry outputs aligned with ArcGIS data management so deliverables land inside the same GIS environment. WingtraCLOUD links Wingtra mission runs to processing so each deliverable review stays tied to a flight run.
Field-to-map execution patterns for repeat missions
Sentera FieldAgent ties field execution steps to repeatable mapping deliverables to reduce recapture loops for farming and service workflows. DroneMapper RAPID focuses on a rapid processing path that prioritizes deliverable turnaround from mission imagery to terrain outputs.
Choose a pipeline shape based on where control must live in the workflow
Drone topography software choices usually differ by where processing control is applied and how much of that control is exposed for iteration. WebODM and OpenDroneMap emphasize rerun determinism through observable jobs or stage outputs, while RealityCapture and ArcGIS Drone2Map emphasize keeping reconstruction and publishing aligned to a defined flow.
The next set of decisions should separate self-managed photogrammetry processing from mission-managed or GIS-native publishing. Then teams should match automation expectations to the available triggers, since Virtual Surveyor and WingtraCLOUD both center on their own orchestration instead of an open API-driven model.
Decide where iteration happens: job rerun versus stage inspection
If iteration is mainly about monitoring and rerunning the same self-managed server workflow, WebODM fits because it provides a task-based web UI for long photogrammetry runs and trackable outputs. If iteration requires validating intermediate artifacts across AOIs and reusing those outputs, OpenDroneMap fits because it runs as a stage-driven pipeline that exposes intermediate artifacts for inspection and deterministic reruns.
Pick a reconstruction control philosophy: dense matching stability versus calibration control
If stable dense matching on large, mixed-overlap captures is the priority, SimActive Correlator3D applies region and tiling based dense reconstruction settings that keep matching quality stable. If consistency depends on maintaining camera calibration and reconstruction quality controls across datasets, 3DF Zephyr focuses on calibration and produces consistent dense cloud, mesh, and orthomosaic products.
Match control point handling to how georeferencing discipline is enforced
If control point adjustment must be integrated directly into reconstruction before dense output, RealityCapture fits because its control point adjustment workflow is tightly integrated into the reconstruction stage. If the team needs consistent georeferencing choices across deliverable types using repeatable workflow recipes, Virtual Surveyor fits because its template-based processing recipes standardize settings across projects.
Align delivery targets to GIS or mission context
If outputs must land in an ArcGIS-managed environment with batch processing aligned to ArcGIS data management, ArcGIS Drone2Map fits because it keeps publishing and processing aligned with the ArcGIS ecosystem. If outputs must stay grouped per flight run and review must map back to Wingtra operations, WingtraCLOUD fits because mission and processing linkage stays tight per Wingtra project.
Choose automation expectations based on orchestration boundaries
If automation will be driven by external orchestration that triggers processing events, WebODM’s self-managed pipeline control and job-based monitoring generally reduces manual coordination. If automation depends on internal workflow templates or vendor mission workflows, Virtual Surveyor and WingtraCLOUD center on their own orchestration models and provide less direct automation surface for non-native pipelines.
Who should buy this category of Drone Topography Software
Teams that scale mapping output across many flights need consistent processing control, not just a way to generate orthomosaics. The software family also separates into self-managed photogrammetry processing stacks, GIS-native publishing flows, and field or mission anchored execution systems.
The best fit depends on whether deliverable consistency comes from rerun determinism, dense matching configuration, or workflow templates tied to a defined capture pattern.
GIS teams that publish into ArcGIS-managed datasets
ArcGIS Drone2Map fits because it keeps photogrammetry outputs aligned with ArcGIS data management and supports repeatable georeferencing through ground control point and coordinate reference system management.
Self-managed photogrammetry teams running on controlled compute
WebODM fits because it stays self-hosted and uses a web UI to monitor and re-run photogrammetry jobs on the same server while preserving data locality.
Mapping teams that need reconstruction stability across large mixed-overlap sites
SimActive Correlator3D fits because it applies region and tiling based dense reconstruction settings to keep matching quality stable across uneven overlap and large sites.
Survey teams that standardize deliverables via repeatable recipes
Virtual Surveyor fits because template-based processing recipes standardize settings across projects and reduce repeated manual configuration for consistent georeferencing deliverables.
Operations teams that tie deliverables to field or flight execution
Sentera FieldAgent fits because it links field execution steps to repeatable mapping deliverables for farm and service workflows, while WingtraCLOUD fits because it links Wingtra mission runs to processing and keeps review tied to each flight.
Common pitfalls when selecting Drone Topography Software
Drone topography software selection often fails when teams assume all tools treat processing iteration and georeferencing discipline the same way. The differences show up in how reruns are handled, how dense matching is configured, and how much control point workflow depth is built into reconstruction.
The next pitfalls focus on mismatches between operational reality and what each tool actually exposes in its workflow boundaries.
Choosing a tool that hides intermediate artifacts when the workflow needs deterministic stage validation
OpenDroneMap fits when intermediate artifacts must be inspected and AOI processing rerun deterministically, while WebODM supports monitored reruns but is structured around job monitoring rather than exposed stage outputs.
Underestimating the time cost of dense matching parameter tuning on new capture patterns
SimActive Correlator3D can keep dense reconstruction quality stable with region and tiling settings, but matching parameter tuning takes time for each new camera and capture pattern.
Treating template-based automation as equivalent to external API-driven orchestration
Virtual Surveyor centers on template-based processing recipes for standardized deliverables, while its automation centers on templates instead of external API triggers.
Forcing an orthomosaic and elevation workflow into a pipeline that lacks classification and refinement depth
RealityCapture and ArcGIS Drone2Map concentrate on reconstruction and publishing workflows, while tool choices like 3DF Zephyr and SimActive Correlator3D emphasize controls that keep dense outputs consistent before downstream classification.
Assuming rapid turnaround means enough refinement for constrained ground control networks
DroneMapper RAPID prioritizes fast photogrammetry to orthomosaic and elevation outputs, but it has limited control point adjustment depth for highly constrained ground control networks.
How We Selected and Ranked These Tools
We evaluated WebODM, SimActive Correlator3D, and the other eight tools on processing control visibility, reconstruction and georeferencing workflow fit, and how consistently teams can rerun work with predictable outputs. Features accounted for 40% of the score, and ease and value each accounted for 30% of the score.
WebODM led the list because the task-based web UI enables monitoring and repeat re-runs on the same server, which supports controlled job iteration and trackable outputs. The final ranking also reflected how each tool’s workflow boundaries affect repeatability, since OpenDroneMap exposes stage outputs for deterministic reruns while RealityCapture integrates control point adjustment into reconstruction before dense output.
Frequently Asked Questions About Drone Topography Software
How do WebODM and OpenDroneMap differ when rerunning large batches on the same server?
Which tool best maintains dense matching quality across mixed-overlap datasets: SimActive Correlator3D or 3DF Zephyr?
When should RealityCapture be chosen over Propeller Aero workflows for control point handling and CRS alignment?
How do ArcGIS Drone2Map and DroneDeploy handle orthomosaic and terrain derivatives for GIS publishing?
What breaks if input coordinate reference system metadata is inconsistent in RealityCapture or ArcGIS Drone2Map?
How does data migration work when moving projects between WebODM and Virtual Surveyor?
Which integration path is more suitable for automation via scripting and API style hooks: OpenDroneMap or ArcGIS Drone2Map?
How do SSO and RBAC controls typically differ between cloud-oriented platforms like DroneDeploy and self-hosted pipelines like OpenDroneMap?
When is field-to-deliverable continuity the deciding factor: Sentera FieldAgent or WingtraCLOUD?
Tools reviewed
Primary sources checked during evaluation.
Referenced in the comparison table and product reviews above.
Funding and competing interests
This study was co-funded by several of the vendors assessed in it. No single vendor funded it. Funders could propose the market studied.
They had no role in selecting vendors, setting or weighting criteria, analysing data or drawing conclusions, and they received the same factual-accuracy check as every other vendor assessed.
Market definition, inclusion rules and criteria weights were fixed by an editor before research began and did not change afterwards. Editorial process →
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