Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial

Plan your drone photogrammetry workflow for farming

You start by setting clear objectives: what maps do you need and why? Decide if you want simple orthomosaics for field scouting, NDVI maps for crop vigor, or DEMs for drainage planning. Pick the crop type, season, and key zones first—those choices drive camera, flight timing, and how precise your control points must be.

Next, match gear and software to those goals. Choose between RGB and multispectral sensors, and plan battery swaps and staging so flights finish within the day’s weather window. If you’ll process images yourself, follow a guide like Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial to turn raw shots into useful maps. Make sure processing needs (time, PC specs, storage) fit your flight plan.

Finally, set a simple file and data routine before you launch. Name flights by date, field, and pass number. Log battery times, wind, and anomalies. Treat data handling like packing a lunch: good records save time when re-processing or comparing seasons.

Choose flight pattern and altitude

Pick a flight pattern that matches your goals. Use a straight grid (lawnmower) for most orthomosaics; add a cross-hatch or double-grid for 3D detail or taller crops. Keep turns slow and consistent to reduce blur and improve overlap.

Altitude sets your GSD and coverage. Fly lower for fine detail and higher for speed and coverage. Use this quick guide as a starting point and adjust for your camera and field:

Altitude (m)	Approx. GSD (cm/pixel)	Use case
30	1–2	Detailed plant-level checks, small plots
60	3–5	Standard scouting, vigor maps
120	6–10	Large fields, fast surveys

Set overlap and ground control points

Aim for strong overlap so the software finds ties between images—about 75% frontlap and 60% sidelap for most crop maps. Bump overlap for wind, variable terrain, or 3D work.

Ground control points (GCPs) anchor maps to real-world coordinates. Place high-contrast targets at field corners and a few inside. Use RTK/PPK drones if available; otherwise survey GCPs with a survey-grade GPS. For small fields, 5–8 well-placed GCPs is a good start; scale up for larger or complex plots.

Check local rules and safety

Before you fly, confirm permissions, file any NOTAMs, and follow line-of-sight and altitude limits. Watch for people, livestock, power lines, and sudden weather shifts. If in doubt, pause the mission—safety and legal compliance keep your project running.

Set your drone and camera settings for Metashape

You want clean, sharp images for photogrammetry. Pick a camera with consistent exposure and a lens with low distortion. Fly when light is steady—early morning or late afternoon often gives soft shadows. Keep steady speed and fixed height so each image has similar scale; this makes alignment in Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial faster and more reliable.

Aim for 75–80% forward overlap and 60–70% side overlap for crops. High overlap gives Metashape more matching points and fewer holes. Lock your camera to manual exposure, turn off auto white balance and in-camera sharpening, and keep GPS tags if available (they speed georeferencing but don’t replace GCPs).

Choose your shutter, ISO, and manual exposure

Pick a shutter speed that freezes motion—use 1/500s or faster if wind or drone vibration is possible; 1/250s can work higher up. Motion blur kills tie points, so prefer sharpness over low noise.

Keep ISO as low as practical (ISO 100–200 in daylight). Increase ISO rather than slowing shutter if light drops. Set aperture near the lens sweet spot (often f/5.6–f/8). Consistent manual exposure across frames is more important than perfect settings for each shot.

Light Condition	Shutter Speed	ISO Range	Aperture	Tip
Bright sun	1/500–1/2000s	100–200	f/5.6–f/8	Fast shutter to remove vibration blur
Overcast	1/250–1/500s	200–400	f/5.6–f/8	Raise ISO before slowing shutter
Low light (dawn/dusk)	1/125–1/250s	400–800	f/4–f/5.6	Increase overlap if shutter slows

Use RAW or high-quality JPEG files

Shoot RAW when possible for more latitude fixing exposure and color without losing detail—this helps Metashape produce natural textures and reduce stitching errors. High-quality JPEG can work if storage or transmission is limited; use the highest JPEG quality and test tie point density in Metashape before committing to large flights.

Calibrate camera and lenses

Run a lens calibration session before major surveys. Capture a checkerboard or textured scene at multiple angles and distances to derive a lens profile and distortion parameters. Upload calibration photos into Metashape or use your camera’s profile so the software corrects vignetting and distortion during alignment.

Import and organize your images in Metashape

Create a project file and add your photos into Metashape. Save a new project in a clear folder, then use Add Photos or drag-and-drop. If you’re following Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial, treat this step like laying a foundation—sloppy input means extra work later. Check that images load with their EXIF tags and GPS coordinates if available.

Inspect images quickly and remove or flag blurry, overexposed, or propeller-obstructed frames. If you have geotags, verify coordinate systems and make sure your chunk gets the right projection before alignment.

Organize using chunks or groups for separate flights, sensors, or dates so you can process sections independently and later merge results. Back up original photos and the project file before heavy processing.

Create a project and add photos

Open Metashape → File → New, save your project file, then Add Photos. Decide whether to import RAW or JPEG (RAW = more detail, larger files). For multispectral sensors, add calibration/reflectance files together. Confirm camera parameters in the import dialog.

Group images by flight or sensor

Group images by flight line, sensor type, or mission date. Create a chunk for each flight or a folder in the workspace. For multispectral or thermal sensors, group by sensor and band order and keep calibration panels and metadata in the same folder.

Name files and folders clearly

Adopt a simple naming pattern like FlightIDDateSensorAltitude (e.g., F0320250612R10120m). Use short, consistent tags so you can sort and filter quickly.

Element	Example	Notes
Flight ID	F03	Short code for mission
Date	20250612	YYYYMMDD for sorting
Sensor	R10	e.g., RGB, MS, thermal
Altitude	120m	Flight height or GSD

Align your photos with SfM in Metashape

Alignment is the backbone of your project. When you align photos, Metashape finds matching features and builds a sparse point cloud. Good alignment saves time later when you build the dense cloud and orthomosaic—follow Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial if you need exact menu steps.

Before Align, pick settings that match your flight and crop patterns. For smooth, feature-rich fields choose High Accuracy or Medium for quicker checks. Raise the Key point limit and Tie point limit if crops repeat patterns. After alignment, inspect the sparse cloud and camera positions and fix floating cameras or clusters with odd reprojection errors.

Run photo alignment and find tie points

Workflow → Align Photos: set Accuracy, Pair preselection, and key/tie point limits. Use Generic Preselection for mixed angles and Reference Preselection if you have GPS tags. Let Metashape extract features and match them across frames; more reliable tie points mean better camera poses.

Filter poor cameras and tie points

Use Gradual Selection to remove bad tie points by Reprojection Error, Reconstruction Uncertainty, and Projection Accuracy. Remove high-error points, then inspect camera markers and disable or delete cameras that sit far from the rest or have few tie points. Re-run Optimize Cameras if you remove many points or cameras.

Set coordinate system and units

Open the Reference pane and pick a coordinate system (local UTM or national grid). Set units to meters unless you need feet. Add your GCPs and paste coordinates so tie points and camera positions lock to real-world locations.

Parameter	Typical Setting	Why it matters
Accuracy	Medium to High	Balances speed and precision
Key point limit	40,000–100,000	More points help in repetitive fields
Tie point limit	0–10,000	Controls memory and matching detail
Pair preselection	Generic / Reference	Speeds matching using tags

Build a dense cloud and generate DEM for your fields

Turn aligned photos into a dense point cloud to fill in detail. Choose a quality that matches needs: higher quality gives more points but costs time and memory—run a test on a strip first.

Clean and refine the cloud before making a surface. Use filters to remove noise, but be careful: aggressive filtering can remove low vegetation and ground detail. Mark areas where you need bare-earth versus areas where vegetation height should be preserved.

Generate the DEM from ground-classified points. A DEM provides elevation per pixel for drainage planning, elevation maps, and variable-rate seeding. Follow the workflow and refer to Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial for step-by-step guidance.

Create dense point cloud and choose quality

Open Build Dense Cloud after alignment. Pick a Quality level (Low, Medium, High, Ultra) and a Depth Filtering setting (Mild, Moderate, Aggressive). Use GPU when available. For hundreds of images start with Medium and increase only where detail matters; Ultra can exhaust RAM.

Quality	Detail level	Typical use	Time/memory
Low	Low	Quick checks, preview	Fast, low RAM
Medium	Medium	Field-scale DEMs	Moderate
High	High	Canopy and row detail	Slower, more RAM
Ultra	Very high	Small plots needing max detail	Very slow, high RAM

Classify ground points for DEM

Run Classify Ground Points and set cell size and max angle to match terrain. For flat, tilled fields pick larger cell sizes; for uneven ground pick smaller cells. Manually edit classes where crops or residue hide the ground. Export a preview DEM and compare it to your orthomosaic to catch errors before final export.

Export DEM as GeoTIFF

When the DEM looks right, Export DEM as GeoTIFF. Set the correct CRS, pixel resolution, and no-data value. Pick compression if you want smaller files and test in your GIS or farm management platform to confirm heights and CRS.

Generate an orthomosaic for your crop mapping

Build an orthomosaic from overlapped images and a DEM/DSM. Align photos, build a dense cloud, and generate elevation models so pixels can be projected onto the surface and merged into one continuous image. Crop to field boundaries to keep files manageable.

If you want detailed menu steps, use Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial to match settings quickly. That tutorial acts as a practical checklist while you process fields.

Merge tiles and set blending options

When orthomosaics are tiled, merge them to remove seams and color shifts. Choose a blending mode to smooth boundaries:

Blending Mode	When to use	Result
Mosaic	Normal flights with consistent exposure	Sharp seams, best detail
Average	Varying exposure across tiles	Smooth color transitions
Linear	Gentle edge blending needed	Tapered seams, natural look
Max	Favor clearest pixels when some tiles are bad	Keeps best pixels, may change tone

Test a small area before reprocessing a full field.

Choose resolution and coordinate system

Choose output resolution based on GSD and analysis needs: 1–5 cm/pixel for plant-level indices; 10–30 cm/pixel for general field boundaries. Higher resolution increases file size and processing time—match resolution to end use.

Set the coordinate system (CRS) before export so georeference stays correct. Use UTM or the local CRS farmers expect, and check the EPSG code. Confirm GCP coordinates match the chosen CRS.

Export orthomosaic with georeference

Export as GeoTIFF and include CRS, world file, and overviews. Name files clearly and attach metadata about processing settings and GSD so maps drop into GIS or farm software without extra steps.

Create vegetation index maps and multispectral outputs

Decide what you want from multispectral data: crop stress, vigor, or canopy cover. Pick the right bands (usually Red and NIR) and export format like GeoTIFF. Following Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial helps keep the processing order repeatable.

Prepare images and metadata: keep filenames consistent and record camera calibration, flight altitude, and reflectance panel readings. These details matter for accurate reflectance outputs.

Plan map use: spatial resolution, mosaic vs per-tile, and projection. Run a small pilot area first to catch issues early.

Import multispectral bands and align

Bring bands into the project as separate channels or stacked images—name them clearly (e.g., IMG001NIR.tif, IMG001RED.tif). Align bands using tie points or camera positions. Use a reference band (often Green or Red) and warp others to match. Check misalignment by blinking bands or overlaying RGB and NIR.

Compute NDVI and other indices

Calculate NDVI with (NIR – Red) / (NIR Red). Clip values to the valid range and convert to a displayable scale (e.g., 0–255 or 0–10000). Use masks to exclude bare soil and water.

Compute other indices like GNDVI, SAVI, or VARI depending on crop and conditions. Run batch processing for many orthomosaics and check histograms; apply light smoothing if maps look speckled.

Index	Formula (brief)	Input Bands	Typical Use
NDVI	(NIR – Red) / (NIR Red)	NIR, Red	Vegetation vigor and stress
GNDVI	(NIR – Green) / (NIR Green)	NIR, Green	Nitrogen content, chlorophyll
SAVI	((NIR – Red)/(NIR Red 0.5)) (1 0.5)	NIR, Red	Reduces soil brightness effects
VARI	(Green – Red) / (Green Red – Blue)	Green, Red, Blue	Vegetation from visible bands when NIR absent

Export index maps for analysis

Export GeoTIFF with appropriate bit depth (16-bit for precision, 8-bit for quick viewing). Set correct CRS/EPSG and include metadata and clear filenames noting index, scale, and date.

Model your 3D crop canopy and measure height

Turn flight images into a 3D model using high-overlap images, GCPs if available, and photo alignment to get a dense cloud. For a guided walk-through, see Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial.

Export or generate a DSM and DEM and keep the coordinate system consistent. Clean the dense cloud to remove stray points before building surfaces for cleaner canopy height outputs. Use a field mask to limit processing to the crop area and check for holes or spikes before measurement.

Build mesh and texture for the canopy

Build a mesh from the dense cloud with settings that favor sufficient faces but keep file size manageable. Choose arbitrary surface type for complex canopies and smooth gently to remove noise without losing plant tips. Add a texture from original images, using high-resolution textures and a blending mode that preserves natural color. Export as OBJ or FBX if needed for external analysis.

Derive canopy height model from DSM and DEM

Create a CHM by subtracting DEM from DSM (CHM = DSM − DEM). Ensure both rasters share projection and cell size. Post-process CHM with light smoothing and clip to your field mask. Convert units (meters or centimeters) and compute stats—mean, max, percentiles. Negative values usually indicate misalignment or incorrect ground points.

Measure canopy volume and gaps

Compute volume by integrating CHM above ground inside plot polygons (sum of cell height × cell area). For gaps, threshold CHM (e.g., < 0.2 m) and count contiguous low-height patches to get area and patch size. Always report cell size and thresholds for reproducibility.

Input	Process	Output
Aligned photos GCPs	Dense cloud → Mesh → Texture	Textured mesh (OBJ/FBX)
Dense cloud → Interpolated surface	Generate DSM and DEM	Raster DSM, DEM
DSM − DEM	Smoothing masking	CHM → height, volume, gap stats

Estimate yield and export results for farm use

Transform imagery into actionable yield maps using orthomosaics, CHMs, and indices to build per-plot estimates. Follow Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial for georeferencing and dense point cloud steps. Calibrate your model with ground data: canopy metric → biomass → yield, keeping clear units and date stamps.

Aggregate pixels to the required scale: clip rasters to field boundaries and compute per-plot averages or percentiles. Produce both raster outputs and vector summaries, using consistent CRS and pixel size so maps align in farm systems. Name files with farm, field, date, and sensor for tracking.

Prepare files for farm use: convert predictions to expected units and formats, add attributes like yieldtha, confidence, and sample_count to shapefiles, and export GeoTIFFs and shapefiles so agronomists and machines can read them. Keep copies of raw metrics and model parameters.

Use canopy metrics and indices for models

Choose metrics such as NDVI, NDRE, canopy height, canopy cover, and point cloud density counts. Combine vigor indices and structural metrics as features in regression or machine-learning models, highlight strongest predictors, and drop redundant variables. Prepare a clean per-plot table, scale or normalize values across dates and sensors, and train/test with matched ground yields. Track RMSE and bias and update models with new ground data.

Export shapefiles and GeoTIFFs for GIS

Use widely accepted formats: GeoTIFF for rasters and Shapefile or GeoPackage for vectors. Set spatial reference (CRS), pixel size, and nodata values before export. Save metadata with projection, acquisition date, sensor, and processing steps.

Name and compress smartly—use clear field names and include attributes like yieldtha, date, and sensor_id. Compress GeoTIFFs with LZW if needed and test files in the target farm platform; reproject first if the platform expects a different CRS.

Validate results with ground samples

Collect ground truth by sampling yields or biomass at representative plots with GPS (sub-meter or RTK). Match each sample to map pixels or polygons and compute RMSE, bias, and R². If errors are high, recalibrate coefficients, add samples, or include weather and soil layers.

Metric	Typical Use	Best Export Format
NDVI, NDRE	Vegetation vigor and stress	GeoTIFF (raster)
Canopy Height, Cover	Biomass and yield proxy	GeoTIFF Shapefile (field stats)
Per-field summaries	Prescription maps	Shapefile / GeoPackage

Frequently asked questions

• How do I begin Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial?
• Open Metashape and make a new project.
• Import your field images.
• Set the correct CRS.
• Add GCPs if you have them.
• Align photos to start processing.
• What camera and flight settings should you use?
• Fly steady and slow.
• Keep 70–80% overlap.
• Use consistent manual exposure.
• Shoot nadir and some oblique shots.
• Use RAW or high-quality JPEG.
• How do you align photos quickly and well?
• Choose High or Medium accuracy for best results.
• Set key point limit ~40k (adjust for repetitive crops).
• Use reference preselection if GPS-tagged.
• Run Align Photos and check for misaligned frames.
• How do you produce NDVI or plant index maps in Metashape?
• Build the orthomosaic first.
• Export multispectral bands or use band math.
• Compute NDVI = (NIR – Red) / (NIR Red).
• Export the index as GeoTIFF and validate with ground truth.
• How do you export accurate maps for your farm?
• Use GCPs or RTK data.
• Build dense cloud and orthomosaic with proper CRS.
• Set export resolution (cm/pixel) and file formats.
• Export GeoTIFFs and DEMs and verify geolocation and color balance.

Quick step-by-step (compact) — Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial

• Plan flight: pattern, altitude, overlap, and GCP layout.
• Fly with manual exposure, RAW if possible, and labeled files.
• Create project in Metashape → Add Photos → Verify camera params.
• Align Photos (Medium/High), inspect sparse cloud, filter tie points.
• Build Dense Cloud (start Medium), classify ground, generate DEM.
• Build Orthomosaic (choose blending, crop to AOI) and export GeoTIFF.
• Import multispectral bands, align bands, compute NDVI and other indices.
• Build DSM/DEM → CHM = DSM − DEM → derive height, volume, gaps.
• Calibrate yield models with ground samples, export rasters and shapefiles.
• Archive project, export metadata, and document processing steps.

(Use the full Agisoft Metashape for Agriculture: Step-by-Step Processing Tutorial as a menu-level checklist when you process your first fields.)