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MARIE NEVERMAN WETLAND RESTORATION
Project Type: Wetland Spatial Mapping & Hydrological Monitoring
Location: South Kaipara Head, Auckland
Application: Restoration monitoring and ecological change assessment
Overview
MappLab is supporting an ongoing ecological mapping programme at the Marie Neverman Wetland Reserve, a freshwater and coastal wetland system owned and managed by the Native Forest Restoration Trust. The site is undergoing hydrological restoration following the repair of a damaged weir. An initial high-resolution aerial capture was completed prior to the repair, establishing a measurable baseline of wetland extent, water levels, and vegetation patterns.
This dataset forms the reference point for future mapping after reflooding, enabling structured monitoring of ecological change over time.
Marie Neverman Wetland Reserve – Wetland Baseline & Change Monitoring (ongoing)

Approach
Using RTK-enabled aerial mapping and photogrammetric processing, the wetland was captured as a high-resolution georeferenced orthomosaic and 3D point cloud terrain model, establishing a detailed spatial baseline of the site.
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Elevation data enables analysis of surface gradients, water flow pathways, and controlled flooding scenarios to support hydrological planning and restoration design.
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The 3D model helps identify suitable habitat zones, including potential sites for future birdlife translocations based on elevation, vegetation structure, and water distribution.
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Pre-intervention mapping establishes a measurable baseline, allowing future changes in water distribution, vegetation response, and habitat improvement to be quantified over time.

Project Impact
The baseline mapping establishes a repeatable framework for long-term ecological monitoring.
For restoration managers and stakeholders, the spatial dataset supports:
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Measurement of hydrological change
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Monitoring of vegetation dynamics
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Evidence-based reporting
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Improved restoration planning
This project demonstrates how applied aerial mapping supports wetland restoration management by converting landscape change into measurable spatial data for monitoring and informed decision-making.
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