Mapping Forests with Avata 2 | Mountain Tips
Mapping Forests with Avata 2 | Mountain Tips
META: Learn how the DJI Avata 2 transforms mountain forest mapping with obstacle avoidance and weather resilience. Real case study with pro tips inside.
TL;DR
- Avata 2's obstacle avoidance proved essential when sudden fog rolled through a 2,400-meter elevation mapping mission
- D-Log color profile captured 14 stops of dynamic range under challenging forest canopy lighting
- Completed 47 hectares of detailed forest mapping in a single morning session
- ActiveTrack maintained subject lock on wildlife despite dense tree coverage
The Challenge: Mapping Remote Mountain Forests
Forest mapping at elevation presents unique obstacles that ground most consumer drones. Dense canopy coverage blocks GPS signals. Rapidly changing weather creates visibility hazards. Uneven terrain makes traditional surveying impossible.
The Avata 2 changes this equation entirely.
During a recent project in the Pacific Northwest's Cascade Range, I needed to map 47 hectares of old-growth forest for a conservation assessment. The terrain featured steep slopes exceeding 35 degrees, mixed conifer coverage, and elevation changes of 800 meters across the survey area.
This case study breaks down exactly how the Avata 2 performed—including an unexpected weather event that tested every safety system onboard.
Pre-Flight Planning for Mountain Terrain
Understanding the Environment
Mountain forests demand respect. Before launching, I spent 90 minutes analyzing topographic maps, identifying potential obstacles, and planning flight corridors between the tallest Douglas firs.
Key planning considerations included:
- Wind patterns at ridge lines versus valley floors
- Sun angle for optimal D-Log exposure
- GPS signal strength under dense canopy
- Emergency landing zones every 200 meters
Configuring the Avata 2 for Forest Work
The Avata 2's compact form factor—185mm diagonal with propeller guards—makes it ideal for navigating between trees. I configured the following settings before launch:
- Obstacle avoidance: Set to "Bypass" mode rather than "Brake"
- Return-to-home altitude: 120 meters (above tallest trees)
- Maximum speed: Limited to 8 m/s for precision control
- Video settings: 4K/60fps in D-Log for maximum post-processing flexibility
Pro Tip: Always set your return-to-home altitude 20 meters higher than the tallest obstacle in your flight area. In mountain forests, this often means the RTH altitude exceeds your actual flying height.
The Flight: When Weather Changed Everything
Morning Conditions
Launch conditions at 0630 were ideal. Temperature sat at 12°C, humidity at 65%, and wind speeds barely registered at 2 m/s. The Avata 2's sensors showed full GPS lock with 18 satellites despite partial canopy coverage.
The first 45 minutes of mapping proceeded flawlessly. The drone's Hyperlapse mode captured stunning time-compressed footage of the forest canopy, while I manually flew transect lines for the survey data.
The Weather Shift
At 0718, conditions changed rapidly.
A fog bank rolled up the valley with zero warning. Visibility dropped from 2 kilometers to under 100 meters in approximately four minutes. This is where the Avata 2's obstacle avoidance system earned its reputation.
The drone's downward and forward vision sensors immediately detected the visibility change. Rather than continuing blindly, the system:
- Automatically reduced speed to 3 m/s
- Increased sensor sensitivity
- Provided haptic feedback through the controller
- Displayed a visibility warning on the goggles
I initiated a controlled descent to 15 meters above ground level, where visibility improved slightly. The obstacle avoidance system navigated around seven tree trunks during the descent without any manual intervention.
Expert Insight: The Avata 2's binocular vision sensors detect obstacles at distances up to 30 meters in optimal conditions. In fog, this range decreases to approximately 8-12 meters—still sufficient for safe navigation at reduced speeds.
Technical Performance Analysis
Obstacle Avoidance in Dense Environments
The Avata 2 uses a combination of downward vision sensors and forward-facing binocular cameras. During this mission, the system logged 23 obstacle detection events and executed 19 autonomous avoidance maneuvers.
| Metric | Performance |
|---|---|
| Detection events | 23 |
| Autonomous avoidance | 19 |
| Manual override required | 4 |
| False positives | 0 |
| Collision incidents | 0 |
The four manual overrides occurred when I intentionally flew closer to subjects than the default safety margins allowed. The system correctly identified the obstacles but deferred to pilot input when I pushed through the warnings.
Subject Tracking Through Canopy
During the survey, I encountered a black-tailed deer moving through the understory. This provided an unplanned opportunity to test ActiveTrack in challenging conditions.
The Avata 2 maintained subject lock for 3 minutes 47 seconds despite:
- 12 complete visual occlusions behind tree trunks
- Subject speed changes from stationary to 25 km/h
- Elevation changes of 40 meters
- Dappled lighting conditions
ActiveTrack lost the subject only when the deer entered a dense thicket where no flight path existed. The system correctly identified the tracking loss and held position rather than attempting to follow into an obstacle-dense area.
D-Log Performance Under Canopy
Forest canopy creates extreme dynamic range challenges. Bright sky visible through gaps can be 14 stops brighter than shadowed forest floor.
D-Log captured this range effectively. In post-processing, I recovered detail from:
- Overexposed sky areas (reduced by 2.5 stops)
- Deep shadow regions (lifted by 3 stops)
- Mid-tone bark textures (enhanced without noise)
The 1/1.3-inch sensor showed minimal noise even in lifted shadows, maintaining usable detail at ISO equivalents up to 3200.
QuickShots for Efficient Documentation
While manual flying captured the survey data, QuickShots provided rapid documentation of specific features. The Avata 2's automated flight modes proved particularly useful for:
- Dronie: Establishing scale of individual old-growth specimens
- Circle: Documenting crown structure of significant trees
- Helix: Creating dramatic reveals of forest clearings
Each QuickShot executed with full obstacle avoidance active. The system modified flight paths three times during Circle shots to avoid branches that entered the planned trajectory.
Common Mistakes to Avoid
Flying too fast in dense environments. The obstacle avoidance system needs time to detect and respond. Speeds above 10 m/s in forests dramatically increase collision risk.
Ignoring weather forecasts. Mountain weather changes rapidly. Check forecasts for your specific elevation, not just the nearest town in the valley.
Setting return-to-home too low. A RTH altitude below tree height creates a collision hazard during automated returns. Always add a safety margin.
Neglecting battery temperature. Cold mountain mornings reduce battery performance by up to 30%. Keep batteries warm until launch.
Forgetting ND filters. Bright conditions above the canopy require ND filtration for proper exposure. Carry a range from ND8 to ND64.
Post-Mission Results
The completed survey delivered:
- 47 hectares of mapped forest
- 2,847 individual images for photogrammetry
- 67 minutes of 4K video documentation
- 3 complete battery cycles
- Zero incidents despite adverse weather
The conservation team used this data to identify 12 old-growth specimens exceeding 400 years in age and document 3 previously unknown wildlife corridors.
Frequently Asked Questions
Can the Avata 2 fly safely in rain?
The Avata 2 lacks an official IP rating for water resistance. Light mist, as encountered during this mission, posed no problems. However, active rain creates risks for the exposed motors and vision sensors. Avoid flying in precipitation heavier than light fog.
How does battery life change at high elevation?
Expect approximately 15-20% reduction in flight time at elevations above 2,000 meters. Thinner air requires higher motor speeds to maintain lift, increasing power consumption. Plan missions accordingly and carry additional batteries.
What's the best obstacle avoidance mode for forest flying?
"Bypass" mode works best for experienced pilots in forests. This setting allows the drone to navigate around obstacles while maintaining general heading. "Brake" mode stops forward progress entirely upon detection, which can interrupt mapping runs and reduce efficiency.
Final Thoughts on Mountain Forest Mapping
The Avata 2 proved itself as a capable tool for demanding environmental work. Its combination of compact size, robust obstacle avoidance, and high-quality imaging makes it uniquely suited for forest environments where larger drones cannot operate safely.
The unexpected fog event demonstrated that the safety systems work as advertised. When conditions deteriorated, the drone's automated responses provided crucial seconds for decision-making and prevented what could have been a costly loss.
For conservation work, forestry assessment, or wilderness documentation, the Avata 2 delivers professional results in environments that challenge even experienced pilots.
Ready for your own Avata 2? Contact our team for expert consultation.