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Planning the survey.

Mission planning is where the work earns its money. Get it right and a 20-hectare cooperative survey takes one battery and produces clean usable imagery. Get it wrong and the same survey takes three batteries, has stitching gaps, and the client questions whether the work was worth what they paid. This page is the reference for getting it right — concrete numbers, decision rules, and the small set of things that genuinely matter for cohort-default builds doing real Mindanao agricultural surveys.

Version 1.0 · Updated 05·2026 Author: Lumipad Engineering License: CC-BY-SA-4.0 Languages: EN · TL · CEB
8
Planning sections
75/65
Frontlap/sidelap, cohort default
60–80 m
Survey altitude (5" NDVI build)
~30 min
Planning time per mission
How to read this page

Plan from requirements down, not from drone capabilities up.

The most common mission planning mistake is starting with "what can my drone do" and producing a plan that fits. The right starting point is "what does the client need" — then working through whether and how the drone can deliver it. Most missions that go badly were planned in the wrong direction. The pages that follow walk top-down: requirements first (Section 1), then the technical decisions that follow from them (Sections 2-7), and finally the mechanical step of generating mission files (Section 8).

The page is structured as a long-form reference; read top-to-bottom your first time through to build the planning vocabulary, then return to specific sections as missions come up. Cohort default planning takes about 30 minutes per mission for a typical cooperative survey; complex missions can take longer. The downloadable kit at the top of this page provides templates that compress most of this into form-filling.

Section 01 Before any technical decision

Requirements first.

The client's actual need, expressed in their language, before any drone-side planning. Resolution requirements derive from this; altitude, overlap, battery count, and timing all derive from resolution. Skipping the requirements conversation produces missions that satisfy the drone but not the client — the most common mode of mission failure in alumni reports.

The conversation with the client (or partner cooperative, or your own farm if you're flying for yourself) covers four things:

Question What you're really asking Translation to drone-side decisions What "I don't know" means
1
What problem are you trying to solve? "Are crops healthy enough?" "Is irrigation reaching uniformly?" "Is there fungal damage?"
Determines which spectral bands matter, what resolution is needed, what processing pipeline produces useful output.
If the client can't articulate the problem, the mission is premature. Help them clarify before flying — a flight without a clear problem is a flight without clear success criteria.
2
What area do you need surveyed? Specific boundaries; total hectares; whether subdivided into fields or one continuous AOI.
Determines flight time, battery count, mission file complexity. A 5-ha plot is a single battery; a 50-ha cooperative is multiple batteries and possibly multiple flying days.
Walk the boundary together if possible. Map apps are unreliable in remote barangays. A boundary the client agrees on, walked physically, is ground truth.
3
What level of detail do you need to see? "Whole-field health" vs "individual tree" vs "individual disease symptom on a single leaf."
Determines required GSD (ground sample distance) — see Section 2. Whole-field is ~5cm/pixel; individual tree is ~2cm/pixel; leaf-level is ~0.5cm/pixel.
If unclear, ask: "If you could see X but not Y in the imagery, would that be enough?" Concrete examples help clients articulate tacit needs.
4
When do you need the results? Timeline for delivery; whether they want raw imagery or processed analysis; format expectations.
Determines mission urgency, post-processing time budget, what to prioritise during the flight day.
If "as soon as possible" — clarify whether that means "this week" or "today after the flight." Different operations.

The "what's normal" baseline question

Often missing from the explicit requirements but worth asking: "What does a healthy version of this field look like to you?" Many clients can't articulate disease symptoms in the abstract but can describe the contrast with healthy crops they've seen.

This is also where a client may reveal that they have prior survey data ("the agriculture office did this last year") which becomes a useful baseline. Two surveys six months apart show change; one survey alone shows only a snapshot. Ask whether earlier baseline data exists.

Documenting requirements. Write the requirements down before planning begins. The download kit at the top of this page includes an AOI checklist form trainees use during cohort training. The form's value is partly in the answers and partly in forcing the conversation that produces them.

Some requirements you cannot satisfy with cohort default builds. Be honest about that in the requirements conversation, not after a failed mission. A client wanting 0.5 cm/pixel resolution across a 50 ha cacao plantation is asking for something a cohort default 5" build cannot reasonably deliver. Either suggest scaling down the resolution, scaling down the area, or referring them to a partner with research-grade equipment.

Section 02 The core mission math

Resolution & altitude.

The relationship between flight altitude and ground sample distance (GSD) is the single piece of math that drives most other planning decisions. Higher altitude = wider coverage per flight line = fewer batteries = faster mission, but worse resolution. Pick altitude from required GSD, not from convenience.

The GSD formula:

GSD (cm/pixel) = (sensor pitch in μm × altitude in m) / (focal length in mm × 10)

For the cohort default NDVI camera (Runcam Phoenix 2 with NDVI conversion, ~3.0 μm sensor pitch, 2.1 mm focal length):

Altitude GSD What you can see Lines per hectare (75% sidelap)
30 m
~4.3 cm/pixel High-resolution survey; individual trees clearly distinguishable; large weeds visible.
Use for: small high-value plots, individual tree health assessment, detailed disease scouting.
~12 lines per ha · long mission times
60 m
~8.6 cm/pixel Standard cohort survey resolution; tree canopies visible as distinct shapes; healthy/stressed regions clear.
Use for: cohort default for cooperative surveys, NDVI overlays at plot scale, irrigation pattern analysis.
~6 lines per ha · cohort default
80 m
~11.4 cm/pixel Extended cohort survey; canopy-level resolution; field-scale patterns clear.
Use for: large cooperative areas, low-detail NDVI snapshot, time-budget-constrained missions.
~4 lines per ha
100 m
~14.3 cm/pixel Wide-area survey; field-pattern detail only; no individual tree resolution.
Use for: very large areas, regional overviews. Above 120m without specific authorization risks CAAP RPL violations.
~3 lines per ha
120 m
~17.1 cm/pixel CAAP standard maximum without RPL Class 4 authorisation. Field-scale patterns only.
Use for: regulatory ceiling for VLOS commercial work without specific permits.
~3 lines per ha · don't exceed without authorisation

The cohort default: 60-80 m altitude for most NDVI surveys with cohort default 5" build. This produces 8.6-11.4 cm/pixel resolution — sufficient for cooperative-scale crop health assessment, with manageable flight times for typical 5-20 ha AOIs.

Deviate from the default only with reason:

  • Lower (30-50m) if the client needs individual-tree assessment or if the AOI is small enough that flight time isn't a constraint.
  • Higher (90-120m) if the AOI is large (>30 ha) or time-constrained, and field-scale rather than tree-scale resolution suffices.

Required overlap interacts with altitude. Lower altitudes need more flight lines for the same coverage (because each line covers a narrower strip of ground). Section 3 covers the overlap math; the lines-per-hectare column above is calculated using cohort default 75% sidelap.

Section 03 The photogrammetry foundation

Coverage & overlap.

Aerial imagery for photogrammetric stitching needs overlap between adjacent images — both along the flight path (frontlap) and between adjacent flight lines (sidelap). The overlap is what lets the processing software identify common features and stitch images together. Insufficient overlap produces stitching gaps; excessive overlap wastes flight time. Cohort default is 75% frontlap and 65% sidelap.

The two overlaps:

  • Frontlap (also called forward overlap or end overlap) — the percentage of consecutive images along a single flight line that overlap. The drone is flying forward; consecutive images of the ground share a percentage of pixels.
  • Sidelap (also called side overlap) — the percentage of overlap between adjacent flight lines. Not consecutive images on one line; rather, the right edge of line N's images overlaps with the left edge of line N+1's images.

Both are expressed as percentages and both are commonly somewhere between 60-85%. The cohort defaults:

Setting Cohort default When to increase When to decrease
FL
Frontlap (along path) How much consecutive captures along one flight line overlap.
75%
85% in tall canopy (cacao, coconut) where occlusion is high · 80% on first cohort missions while learning
65% in sparse vegetation (rice paddies, open fields) where stitching has fewer features to match
SL
Sidelap (between lines) How much adjacent flight lines overlap each other.
65%
75% in difficult terrain (slopes, irregular shapes) where flight precision is harder
55% in flat open terrain · 60% if mission is time-budget-constrained

Why these specific values? 75/65 is in the sweet spot where cohort default builds reliably produce stitchable imagery with WebODM (the cohort default processing tool) without excessive flight time. Higher values (85/75) produce more reliable stitching but increase flight time by ~30%; lower values (65/55) cut flight time but increase the rate of stitching failures, which costs more time on re-flights than was saved.

The capture interval calculation — how often the camera should fire — derives from frontlap and flight speed:

Capture interval (s) = (footprint_length × (1 - frontlap)) / flight_speed
where footprint_length = (sensor_height_in_pixels × GSD_in_m) / 1

For the cohort default at 60m altitude (GSD 0.086 m/pixel), Runcam Phoenix 2 sensor (~720 vertical pixels), and 75% frontlap:

  • Footprint length = 720 × 0.086 = 61.9 m
  • At 5 m/s flight speed: capture interval = (61.9 × 0.25) / 5 = ~3.1 seconds
  • At 8 m/s flight speed: capture interval = (61.9 × 0.25) / 8 = ~1.9 seconds

The mission planner generates these values automatically; you don't need to calculate manually. But understanding the relationship helps when you need to debug a mission with stitching gaps — they often come down to one of these inputs being miscalibrated.

Sidelap and flight line spacing. The lines-per-hectare numbers in Section 2 assume cohort default 65% sidelap. If you change sidelap, recalculate. The formula:

Line spacing (m) = footprint_width × (1 - sidelap)
where footprint_width = (sensor_width_in_pixels × GSD_in_m) / 1

For 60m altitude, Runcam sensor (~1280 horizontal pixels), 65% sidelap:

  • Footprint width = 1280 × 0.086 = 110 m
  • Line spacing = 110 × 0.35 = 38.5 m
  • Lines per ha = 100m / 38.5m ≈ 2.6 lines (round up to 3 for safety)

The cohort coverage-math spreadsheet (in the download kit) has these calculations built in for the cohort default cameras and several alternatives. Plug in your altitude, AOI dimensions, and target overlap; it produces line count, line spacing, and total mission distance.

Section 04 How the drone moves through the AOI

Flight patterns.

Four flight patterns are commonly used for survey work. Lawnmower (parallel back-and-forth lines) is the cohort default and works for ~85% of missions. The alternatives — perimeter-first, spiral, terrain-following — solve specific problems where the lawnmower doesn't work well. Pick the simplest pattern that gets the coverage you need.

Pattern How it works When to use When to avoid
LWN
Lawnmower (parallel lines) Drone flies back and forth across the AOI in evenly-spaced parallel lines. Camera captures continuously.
Default for any roughly rectangular AOI. Cohort default for cooperative surveys.
Avoid when AOI is genuinely circular or radially-symmetric (use spiral); avoid for very narrow strips (use perimeter); avoid in steep terrain (use terrain-following).
PRM
Perimeter-first Drone flies the boundary of the AOI first, capturing the edges; then fills the interior with a smaller lawnmower pattern.
Long thin AOIs (river-edge plots, road-corridor surveys). Boundary-critical surveys (fence-line inspection, parcel verification).
Avoid for compact rectangular AOIs (lawnmower is faster). Avoid for AOIs with very irregular boundaries that can't be flown smoothly.
SPR
Spiral Drone starts at the centre and spirals outward, or starts at the edge and spirals inward. Each loop covers a wider/narrower band.
Circular AOIs (irrigation circles, point-source pollution surveys). Centre-most-important AOIs.
Most missions don't need this; lawnmower is simpler and gives the same data quality. Spiral is harder to plan correctly and harder to recover from mid-mission interruption.
TRR
Terrain-following Drone follows the terrain elevation, maintaining constant altitude above ground rather than constant absolute altitude. Requires elevation map upload.
Mountainous AOIs (Bukidnon highlands, hill-country coffee farms) where flat-flight altitude would put parts of the AOI too close to ground or too far.
Avoid for flat AOIs (no benefit, more complex). Avoid if you don't have reliable elevation data for the AOI; bad terrain data is worse than flat flight.

The lawnmower direction matters

For most AOIs, lawnmower lines should run perpendicular to the dominant wind direction. Reasons:

  • The drone's ground speed varies more on lines parallel to wind (faster downwind, slower upwind). This creates inconsistent capture intervals and patchy frontlap.
  • Crosswind flight has more consistent ground speed. Capture intervals stay steady.
  • Heading correction (yaw to maintain track) is easier on perpendicular lines than parallel ones.

Check the wind direction at the start of mission planning. If conditions change, adjust the line direction. Cohort default mission planners (in the download kit) include wind-direction inputs that auto-rotate the lawnmower pattern.

Pattern selection by AOI shape:

  • Square or roughly rectangular (most cooperative plots) — lawnmower, lines perpendicular to wind.
  • Long thin (river edge, road corridor, irrigation channel) — perimeter-first, then narrow lawnmower if interior detail needed.
  • Circular (irrigation pivot, pond perimeter) — spiral OR lawnmower over a square that contains the circle (lawnmower simpler).
  • Irregular polygon — lawnmower over the bounding rectangle. Trim the resulting imagery to the actual AOI in post-processing. Simpler than trying to fly the irregular shape exactly.
  • Mountainous or significantly sloped — terrain-following lawnmower if elevation data is reliable; otherwise lawnmower with conservative altitude (above the highest point + safety margin).

For cohort default missions, expect to use lawnmower 85-90% of the time. The other patterns are tools for specific situations, not first choices.

Section 05 The constraint that determines mission feasibility

Battery budgeting.

Cohort default 5" build with a 1500 mAh 4S pack flies for ~10 minutes of usable mission time. Each mission needs to fit within that envelope or be split across multiple batteries. Underestimating battery time is the most common reason cohort missions abort mid-flight — get this right at planning time, not in the air.

The mission time budget breaks down into:

  • Pre-mission (after takeoff, before first capture line): ~30 seconds for climb, GPS lock confirmation, transit to first waypoint.
  • Capture phase: total flight distance / flight speed. This is the bulk of the mission.
  • Return-to-home: the drone needs to fly from the end of the mission back to landing. ~30-60 seconds depending on AOI distance from launch point.
  • Safety margin: 20% reserve, hard rule. Never plan to land at empty.

For cohort default 5" build with cohort default 1500 mAh 4S pack:

Phase Typical duration Battery used Notes
PRE
Pre-mission setup Takeoff, climb to mission altitude, transit to first waypoint.
~30 seconds
~5% of pack capacity
Add 30 more seconds if AOI is more than 100m from launch point.
CAP
Capture phase Flying the planned mission lines, capturing imagery.
~7-9 minutes
~70% of pack capacity
This is where the mission gets done. Plan to maximise this phase relative to the others.
RTH
Return to home + landing From end of mission to safe landing.
~30-60 seconds
~5% of pack capacity
Longer if AOI is far from launch point or weather changed mid-mission.
RES
Safety reserve Remaining capacity at landing. Hard rule, not optional.
≥ 20% of pack
Never less than 20%
Buffer for unexpected wind, GPS issues, emergency landings. Don't consume this except in real emergencies.

Translation to flight distance. At cohort default 5 m/s flight speed, ~7-9 minutes of capture phase = 2,100-2,700 meters of flight distance. Working backward from the mission's total flight distance:

Battery count needed = ceiling( total_mission_distance_m / 2400 )

For 20 ha AOI at 60m altitude, 65% sidelap, 5 m/s = ~3,200 m total mission
→ 3200 / 2400 = 1.33 → 2 batteries needed

Practical battery counts for typical cohort missions:

  • 1-5 ha plot: 1 battery, sometimes 2 if very high resolution required
  • 10-15 ha cooperative plot: 2 batteries
  • 20-30 ha cooperative survey: 3 batteries
  • 40-50 ha large cooperative: 4-5 batteries; consider splitting across two flying days
  • >50 ha: definitely multi-day; reconsider whether higher altitude can reduce flight time

The cohort recommendation: always carry one more battery than your plan calls for. A 3-battery mission becomes a 4-battery flight day. The extra pack covers test flights at the start, equipment problems, and the occasional re-fly of a section that didn't capture cleanly. Adds ~₱2,500 of pack on the truck for the day; saves a return trip to the site.

Battery age affects budget

Cohort default 1500 mAh packs after ~50 cycles deliver closer to 1300 mAh of usable capacity. After ~100 cycles, ~1100 mAh. The mission planning above assumes fresh packs; aged packs need a reduction in mission length proportional to capacity loss.

Practical rule: track each pack's cycle count in the fleet logbook. When a pack drops below 80% of new capacity (typically ~70 cycles), retire it from mission work and use only for training/practice. Don't mix new and aged packs in the same mission — it complicates the math and creates risk.

Section 06 When you fly is as important as how you fly

Timing.

Sun angle, wind windows, crop growth stage, and seasonal patterns all affect mission outcomes. NDVI imagery in particular is sensitive to sun angle — flying at the wrong time of day produces shadows that wreck the analysis. For cohort default Mindanao operations, the prime survey window is roughly 10 AM to 2 PM, with weather and seasonal modifications.

Sun angle for NDVI:

  • Below 30° from horizontal (early morning, late afternoon): long shadows, low light, NDVI values compressed by shadow noise. Avoid for serious analysis work.
  • 30°-50° (mid-morning, mid-afternoon): workable but shadows still significant. Acceptable for ground-truth-supplemented analysis.
  • 50°-80° (late morning to early afternoon): cohort default range. Shadows minimised; uniform illumination across canopy; NDVI values most reliable.
  • Near 90° (solar noon, equatorial regions): excellent illumination but sometimes too much glare on shiny canopies (banana, coconut). Brief mid-day pause possible if specular reflection dominates imagery.

For Mindanao (latitude ~7° N), solar noon happens around 11:45-12:15 depending on season. Sun angle exceeds 50° from approximately 9:30 AM to 2:30 PM year-round. The cohort default flight window is 10:00 AM to 2:00 PM — comfortably inside the high-sun band, with a 30-minute buffer on each end for setup and teardown.

Time Sun angle (Mindanao) Suitability Notes
06-08
Early morning Before sun reaches 30° from horizontal.
Avoid for NDVI work. Workable for visual surveys where shadows are useful (counting plant structure, height-from-shadow analysis).
Wind is typically calm — useful if wind is the limiting factor.
08-10
Mid-morning ramp Sun rising from 30° to 50°.
Marginal NDVI; acceptable for less critical surveys. Shadows decreasing.
Wind starting to pick up but typically still moderate.
10-14
Prime survey window Sun above 50°; cohort default range.
Best for NDVI; shadows minimal; illumination uniform. Use for all serious analysis missions.
Wind is typically peak in this window. Wind handling skills matter more here.
14-16
Mid-afternoon ramp-down Sun dropping from 50° toward 30°.
Acceptable to ~3 PM; shadows increase noticeably toward 4 PM.
Heat-of-day winds peak; afternoon thunderstorms possible during wet season.
16-18
Late afternoon Sun below 30°.
Avoid for NDVI; suitable only for visual or shadow-dependent surveys.
Wind dropping; calmest conditions of the day approach.

Wind windows. The cohort default 5" build flies acceptably up to ~25 km/h sustained wind; struggles above that; doesn't fly safely above ~35 km/h. The Mindanao wind pattern in agricultural regions:

  • Morning (6-9 AM): typically calm; light land-breeze in coastal regions.
  • Mid-day to afternoon (10 AM-3 PM): wind increases as land heats; sea breezes develop in coastal regions; thermal updrafts in inland regions. Peak typically 12-2 PM.
  • Late afternoon to evening (4-6 PM): wind moderates as temperature drops.

This creates tension with the prime survey window (10 AM-2 PM = peak wind). The compromise is usually: fly during the high-sun window, accept that wind handling will be needed, and abort if wind exceeds the build's capability rather than push through.

Seasonal patterns:

  • Dry season (December-May): most reliable flying weather. Steady winds, predictable patterns, low rainfall risk. Best for major missions.
  • Wet season (June-November): afternoon thunderstorms common; mornings often cloudy; wind patterns less predictable. Plan missions for early in the window (10-11 AM), be ready to abort if weather develops.
  • Typhoon season (July-October peak): occasional total no-fly periods of 2-7 days as systems pass through. Build mission schedules with 2-week flexibility windows during this period.

Crop growth stage matters too

NDVI values vary across the crop's growth cycle. Surveys at different stages show different things:

  • Early growth (post-planting, pre-canopy-closure): bare soil dominates, NDVI low and patchy. Useful for stand establishment assessment.
  • Mid-growth (canopy closing, vigorous growth): NDVI rising rapidly. Best for irrigation pattern analysis.
  • Peak growth (full canopy, pre-flowering): NDVI peaks, most spatial variation visible. Best for stress detection and disease scouting.
  • Senescence (post-flowering, maturation): NDVI declining as crops mature. Useful for harvest timing.

Discuss growth stage with the client during requirements gathering (Section 1). A survey timed wrong for the question being asked produces ambiguous data.

Section 07 Required pre-mission discipline

Safety planning.

Mission planning isn't complete until the safety plan is documented. Line-of-sight requirements, emergency landing zones, observer placement, and proximity considerations are all easier to think through at planning time than to figure out in the air. The cohort safety planning template (in the download kit) walks through the standard checklist.

Visual line of sight (VLOS). Philippine CAAP regulations require the pilot to maintain visual line of sight with the drone during commercial operations (without specific Beyond-VLOS authorisation). Practical implications for mission planning:

  • Maximum useful distance from pilot: ~500 m for cohort default builds. At 500 m, the drone is a small dot but still visible. Beyond this, visual contact gets unreliable.
  • If AOI extends beyond 500 m from a single pilot position: split the mission into multiple flights from different launch points within the AOI, OR use a mobile observer (Section 7's observer placement notes).
  • If visual contact is lost during a mission: this is failsafe territory. RTH is the fallback. Re-establishing contact via observer is the recovery path. See safety.html for full procedure.

Emergency landing zones. Identify before the mission. Two questions:

  1. If something goes wrong mid-mission (low battery warning, link loss, motor issue), where can the drone land safely?
  2. Are these zones inside the AOI, on the way to/from RTH, or outside the mission corridor entirely?

For typical cooperative surveys: cleared areas around the launch point, harvested fields, dirt roads, and open grassland all work. Avoid: water, dense canopy (drone gets stuck), populated areas, structures, livestock pens. Mark landing zones on the AOI map. Cohort training includes practising landings to specific marked zones, not just back to the takeoff point.

Observer placement. For larger missions, an observer in addition to the pilot adds significant safety:

Mission size Recommended observer setup Why Cohort default
S
Small (≤ 5 ha, single battery) Optional observer; pilot can manage solo.
Drone always within easy visual range; mission length short enough that pilot fatigue isn't a factor.
Solo OK with experienced pilot; cohort cell observer encouraged for first solo missions.
M
Medium (5-15 ha, 1-2 batteries) One observer recommended, separate from pilot.
Pilot focuses on configurator and active flying; observer scans for hazards (livestock, people approaching, weather changes).
Observer is typically a cohort cell member or local from the partner cooperative.
L
Large (15-30 ha, 2-3 batteries) One observer required; second observer at distant boundary if AOI exceeds easy LOS.
Multiple roles: visual contact assistant, weather/wind monitor, communication relay if needed.
Two observers if AOI shape demands; pre-mission briefing sets each observer's role.
XL
Extra-large (>30 ha, 3+ batteries) Multiple observers; consider splitting mission across days; consider multiple launch points.
Mission becomes a coordinated operation. Pre-mission briefing is more substantial.
Document each observer's station and role on the safety plan; rotate roles to manage attention fatigue.

Proximity considerations. The mission shouldn't bring the drone unsafely close to:

  • People — minimum 30m horizontal separation from non-participants (CAAP requirement). For cohort default lawnmower patterns, plan AOI boundaries so flight lines don't pass over occupied areas.
  • Structures — minimum 30m horizontal separation from buildings, towers, telephone wires. Telephone wires in particular are easy to miss visually until the drone is too close.
  • Livestock and pets — drone noise spooks animals; plan flight paths to avoid sustained overhead presence over enclosures.
  • Other drones or aircraft — if any other drone operations are happening in the AOI vicinity, coordinate. Two drones in the same area without coordination is a collision risk.
  • Restricted airspace — verify the AOI isn't inside or near no-fly zones (airports, military installations, prisons, certain government facilities). The CAAP NoTAM map covers most of these; safety.html has full reference.

The cohort safety planning template includes a checklist that covers all of these systematically. Filling it out takes ~10 minutes; doing it badly causes hours of avoidable problems.

Section 08 Translating planning into the FC's language

Mission file generation.

With requirements, altitude, overlap, pattern, battery budget, timing, and safety planning complete, the final step is generating the actual mission file the FC will execute. This is the most mechanical step in the planning process — most of the decisions have been made; the file is just a structured record of them. INAV and ArduPilot use different formats; both are workflow-compatible with cohort default tools.

The cohort workflow uses two tools depending on FC firmware:

  • For INAV (cohort default 5"/7" builds): INAV Configurator's mission planning tab, or UgCS for more sophisticated planning. INAV mission files use the .mission format.
  • For ArduPilot (cohort default 10" builds): Mission Planner standalone application, or QGroundControl for cross-platform work. Format is .waypoints.

The basic mission file workflow (INAV):

  1. Open INAV Configurator, connect to the FC via USB or Bluetooth.
  2. Navigate to the Mission Control tab.
  3. Drop a starting waypoint at the planned launch point. Type: WAYPOINT. Altitude: cohort default mission altitude (60-80m).
  4. For lawnmower patterns: use the planning tool's "Survey" feature. Define the AOI polygon by clicking corners on the map; specify altitude, sidelap, and flight speed. The tool auto-generates the lawnmower lines.
  5. Add a final RTH waypoint at the end of the mission. Type: RTH.
  6. Verify the mission visually: line spacing looks right, AOI is fully covered, no waypoints in invalid positions (over water, structures, etc.).
  7. Save the mission file to disk (for backup) and upload to the FC.

What to verify before flight:

Check What to verify Common mistake Fix
1
Altitude consistency All capture waypoints at the same altitude (unless intentionally varying for terrain).
Mission planner sometimes generates waypoints at different altitudes if the AOI was clicked across varying terrain.
Open the waypoint list; manually set all altitudes to the planned value.
2
Speed consistency All flight legs use the planned mission speed (typically 5 m/s for cohort defaults).
Default speed values vary across mission planners; some default to 10 m/s which is too fast for capture.
Set per-waypoint speed values explicitly; or set a global speed parameter.
3
Trigger settings Camera trigger interval matches the planned interval from Section 3.
If using time-based capture: forgetting to set the interval. If using distance-based: forgetting to enable.
Verify in the Camera tab; calculate from Section 3 if uncertain.
4
RTH waypoint present Mission ends with an explicit RTH command, not just the last capture line.
Forgetting RTH means the drone hovers indefinitely at the last waypoint after capture ends.
Add an RTH waypoint as the final entry in the mission.
5
Mission saved locally Mission file saved to laptop disk before upload.
Forgetting to save means a planning crash costs the whole mission.
Save before upload; name files {client}-{date}-{altitude}.mission.

Offline mission planning

Many cohort flying locations don't have reliable cellular data. The mission planner tools handle this in different ways:

  • INAV Configurator: caches map tiles. Plan the mission with map data while online (at home, before traveling); the cached tiles work offline at the site. Cache covers ~30km radius around any location you've previously loaded.
  • Mission Planner (ArduPilot): similar map caching; specifically download the AOI tiles before traveling.
  • UgCS: requires online for initial planning but generates self-contained mission files that don't need the planner during flight.

The cohort default workflow: plan missions at home or at the cohort office before traveling to the field. The trip to the field is for executing missions, not planning them. Don't plan complex missions on a phone in a remote barangay — too easy to miss inputs without the bigger screen and reliable network.

Saving missions for re-use. Recurring surveys (monthly NDVI of the same cooperative, quarterly yield estimation) re-use the same AOI. Save the mission file with version control: {client}-{date}-{altitude}.mission. Next survey, load the existing file, update the date, verify nothing about the AOI has changed (new structures, new vegetation), upload.

Cohort engineering maintains a shared mission template repository for partner cooperatives that have signed on for recurring surveys. Alumni working with these partners pull templates from the shared repo rather than re-planning from scratch each time.

Numbers worth memorising

Six numbers that show up in every mission plan.

Cohort default values for the most-referenced inputs in mission planning. Useful for quick mental math when scoping a new mission.

75/65
Frontlap / sidelap
Cohort default for stitchable imagery
60–80 m
Survey altitude
5" NDVI build · 8.6-11.4 cm/pixel GSD
5 m/s
Cohort default flight speed
Slower if higher overlap; faster if larger AOI
~2,400 m
Per-battery distance
Capture phase, cohort default 1500 mAh 4S
10 AM-2 PM
Prime survey window
Sun ≥50° from horizontal in Mindanao
20%
Battery reserve
Hard rule, never violate
Real mission planning cases

Four cases from cohort and partner-org missions.

Specific situations where mission planning decisions had measurable impact on outcomes. Each is a real case from Lumipad engineering or partner-org operations in 2024-2025.

"22-hectare cacao cooperative — first paid client mission."

Cohort 02 alumna, post-graduation

The plan: 60m altitude, 75/65 overlap, 5 m/s, 2 batteries with 1 spare on the truck. The result: clean stitched NDVI in 2.5 batteries (afternoon thunderstorm threatened mid-mission, cut one line short, re-flown next morning with the spare). What worked: requirements conversation upfront identified the cooperative's actual question (uniformity of fertiliser application across 4 newly-planted hectares); altitude and overlap were chosen to answer it. Lesson: requirements drive the rest; stick to defaults until they don't fit.

"Stitching gaps in delivered imagery."

Partner-org's third mission, late 2024

Mission flown at 80m, 65/55 overlap (operator chose to save flight time on a large 35-ha AOI). Result: stitched output had visible gaps along several flight-line boundaries; client unhappy. Cause: 55% sidelap was insufficient given the operator's actual flight precision (line tracking varied ~5m off planned). Fix on next mission: 65/65 overlap, accepted ~25% longer flight time. No stitching gaps. Lesson: don't cut overlap to save time on first missions; build the experience first, optimise after.

"Mountain-side coffee farm at 1,200m elevation."

Cohort 02 alumnus, Bukidnon highland mission

The AOI sloped from ~1,150m to ~1,250m elevation across 8 ha. Flat-altitude mission would have meant 100m AGL at the bottom and 0m AGL at the top — clearly unworkable. The fix: terrain-following mission using elevation data downloaded from Mission Planner's terrain database. Mission ran at constant 60m AGL throughout. Result: usable imagery, no proximity issues. Lesson: in mountainous AOIs, terrain-following is worth the extra setup time.

"Recurring monthly survey for a 12-ha rice cooperative."

Cohort 03 alumna, ongoing engagement

Same AOI surveyed monthly for growth tracking. The setup: mission file saved on first survey (60m, 75/65, lawnmower); subsequent surveys load the same file with updated date in filename. Each subsequent survey takes ~15 min planning vs ~30 min for original (just verifying nothing changed about the AOI). Lesson: recurring surveys benefit massively from version-controlled mission templates. The cohort recommended workflow uses git-tracked mission files for partner orgs running recurring missions.

Frequently asked

Questions worth answering carefully.

What if the client wants resolution we can't deliver with cohort default builds? +

Be honest about the limit, don't overpromise, and offer alternatives. Three responses depending on the gap:

  • If they want 2x our resolution: explain the trade-off (lower altitude, more flight time, smaller area covered per battery). They might accept the smaller AOI; they might decide field-scale resolution is sufficient after all.
  • If they want 5x our resolution: cohort default 5" build with NDVI rig genuinely can't deliver. Offer to refer them to a partner with research-grade equipment, or to scale the AOI down to a representative sample they can extrapolate from.
  • If they want capabilities we don't have (thermal imaging, multispectral beyond NIR, RTK precision): same — refer or redirect. The cohort's honest-about-limits reputation is more valuable than any single mission.

Cohort 02 had two cases where alumni declined missions outside their capability and referred them to a partner research lab. Both clients came back later for cohort-default work after their research-grade need was met. Honest scope-setting builds long-term relationships.

How do I plan a mission for an AOI I haven't walked physically? +

Walking the AOI before the mission day is the cohort default. When that's genuinely not possible (urgent client, distant location), the second-best workflow:

  1. Use satellite imagery: Google Earth or similar gives you AOI shape, surrounding hazards (power lines, roads, structures), terrain. Plan the mission against this.
  2. Talk to someone who knows the site: the client, a cooperative member, anyone familiar. They'll mention things satellite imagery misses (livestock paths, recent construction, seasonal flooding patterns).
  3. Arrive early on mission day: 60-90 minutes before planned takeoff. Walk the AOI yourself; verify the satellite-based plan; adjust if needed.
  4. Be prepared to abort or modify the mission: if site reality differs significantly from the plan, don't fly the bad plan. Re-plan; postpone if necessary.

Distance-only planning (Google Earth from another city, fly remotely) has produced bad outcomes in alumni reports. The "walk-the-site" discipline isn't bureaucratic — it's how missions stay safe and produce usable output.

What's the relationship between this page and the proposed mission-planner-tool.html? +

This page (missions.html) is the conceptual reference: how to think about mission planning. The proposed mission-planner-tool.html is a future interactive tool — a web-based mission planner specific to cohort default builds, generating mission files directly without the operator needing to use INAV Configurator's mission tab.

Until that tool ships, the workflow is: read this page, use INAV Configurator (or Mission Planner for ArduPilot) for the actual file generation, refer to the downloadable spreadsheet templates for the math.

The conceptual content here will remain useful even after mission-planner-tool.html ships — the tool automates the mechanical parts but doesn't replace the planning thinking.

How does mission complexity scale with AOI size? +

Roughly linearly for flight time, more than linearly for planning effort. Specifically:

  • Flight time scales with area (a 20-ha AOI takes ~2x the flight time of a 10-ha AOI at the same altitude and overlap).
  • Battery count scales similarly — 2x the area = 2x the batteries (within the cohort default flight envelope).
  • Planning effort scales with complexity, not just size. A 50-ha rectangular AOI is barely more effort to plan than a 20-ha rectangular AOI; a 20-ha irregular AOI with terrain variation is more effort than a 50-ha rectangle.
  • Mission risk scales with both size and complexity. Larger missions have more chances for things to go wrong (weather window narrowing, equipment fatigue, observer attention drift).

Cohort recommendation: cap individual missions at ~30 ha for cohort default operators in their first year. Larger AOIs split across multiple flying days. The risk reduction is worth the operational overhead.

Should I plan for backup imagery in case primary capture fails? +

For high-stakes missions, yes. The cohort approach: fly the planned mission first; review imagery before leaving the site; re-fly any areas with capture issues using the spare battery. The 30-minute review-on-site is much cheaper than a return trip to the cooperative the next day.

Practical workflow for on-site review:

  1. Pull SD card, plug into laptop in the truck.
  2. Quickly scroll through capture sequence; verify nothing obviously wrong (heavy blur, missing frames, exposure failures).
  3. If a section looks suspect: re-fly that section with the spare battery before packing up.
  4. Don't process for stitching at the site (that's a longer post-flight task); just verify capture happened.

For low-stakes or recurring missions (your own farm, monthly cooperative survey), the on-site review can be skipped — re-flying next month if needed is acceptable. For paid client missions, especially first-time clients or distant sites, on-site review is worth the 30 minutes.

What if the AOI overlaps with a no-fly zone or restricted airspace? +

This is a regulatory question more than a planning one — see safety.html for the full reference. Practical implications for mission planning:

  • Verify before planning: check the CAAP NoTAM map for the AOI. Some no-fly zones are easy to miss (small private airfields, certain government facilities).
  • If the AOI is fully inside a no-fly zone: mission is illegal without specific authorisation. Don't plan it; explain to client; they may need to seek authorisation themselves before you can fly.
  • If the AOI overlaps a no-fly zone partially: plan to fly only the legal portion. Document the boundary clearly. Don't plan flight lines that cross into the restricted area.
  • If the AOI is near (within ~5 km of) restricted airspace: still legal but coordinate with the relevant authority (airport tower, military installation contact). Some require notification before flight.

This is one area where cutting corners has serious consequences. CAAP enforcement has been increasing; alumni working in regulated areas should default to over-compliance, not under-compliance.

What's the cohort recommendation for mission planning software for partner orgs? +

Three options depending on the partner org's context:

  • INAV Configurator built-in mission planning: free, sufficient for most cohort default work, Mission Control tab in any modern INAV Configurator version. Cohort default for individual alumni.
  • UgCS: commercial mission planner, more sophisticated features (multi-aircraft missions, advanced terrain following, mission optimization). ~$200/year for the basic edition. Worth it for partner orgs running fleets.
  • QGroundControl: free, cross-platform, works with both INAV (limited) and ArduPilot (full). Good for ArduPilot fleets; more complex setup than Mission Planner.

For a single alumna or small team: INAV Configurator is fine. For a partner org running 5+ drones: UgCS pays for itself in mission planning efficiency within the first quarter. Mission planner choice is more about workflow scale than capability for cohort default work.

How do I learn to plan well? Where does the skill come from? +

Three sources, in roughly this order of importance:

  • Reading missions go right and wrong: alumni Slack publishes post-mission reports. Reading these is the highest-leverage learning. The pattern of what worked and what didn't becomes visible across many missions.
  • Planning your own missions, even small ones: planning a survey of your own family's farm is a low-stakes way to develop the skill. Mistakes are cheap. The next paid mission benefits from the practice.
  • Working through the planning kit's spreadsheet: the kit's coverage-math spreadsheet has worked examples for typical cohort missions. Working through them builds the math intuition that makes mental estimation faster.

Mission planning is a skill that develops over the first year of post-graduation work. Cohort 02 alumni at the 12-month mark report planning competently in 15-20 minutes for typical missions; same alumni at the 3-month mark were taking 45-60 minutes. The skill compounds with practice.