Mapping Nature with Precision: Geospatial Study & Environmental Protection in Northern Saudi Arabia

Client & Location

• Client: National Center of Environmental Compliance (NCEC)

• Region: Hafar Al-Batin, Northern Saudi Arabia

• Ecosystem: Open sandy areas, localized dense vegetation, salinity-prone soils

  
  

Objectives

• Capture high-resolution geospatial data for site-specific restoration.

• Achieve positional accuracy ≤15 cm (RGB GSD ~5 cm/pixel).

• Fly in spring to assess vegetation health at peak signal.

• Deliver actionable outputs: DEMs, vegetation health maps, 25 cm contours, and soil salinity indicators.

  
  

Scope & Deliverables

• Classified LiDAR point clouds (ground/vegetation/structures)

• 10 cm resolution DEMs & hillshades

• 25 cm contour lines for grading, water-flow, and erosion control

• Vegetation indices (e.g., NDVI, SAVI) and salinity risk mapping

• Composite environmental models combining LiDAR + multispectral layers

Project Overview

The National Center of Environmental Compliance (NCEC) commissioned NineTenths to deliver a high-precision geospatial survey in the Hafar Al-Batin desert region (≈360 km²). The objective: generate decision-grade data to plan and monitor large-scale environmental rehabilitation—restoring degraded ecosystems, enhancing biodiversity, and supporting sustainable vegetation cover.

To meet these goals, NineTenths integrated drone-based LiDAR with multispectral imaging, tied to a dense network of RTK ground control points (GCPs). This fusion approach delivered both structural intelligence (terrain, micro-topography, canopy height) and physiological intelligence (vegetation vigor, stress, and salinity signals). The outcome is a defensible, repeatable geospatial baseline that allows NCEC to plan, prioritize, and monitor restoration actions with far greater certainty than traditional survey methods.

Aerial View

The survey area included open sandy expanses, interdune corridors, and localized patches of shrub and grass cover. These conditions are ideal for LiDAR: laser returns penetrate gaps in canopy to resolve ground elevations, while multispectral bands reveal where vegetation is thriving or stressed. The resulting mosaics and point clouds provide a single source of truth for ecologists, engineers, and field teams.

Methodology

Flight Planning

Custom flight corridors balanced coverage, density, and efficiency while maintaining robust image overlap and LiDAR swath consistency. Operations were scheduled in early-morning windows to avoid thermal turbulence, crosswinds, and dust bursts common to desert climates. Contingency buffers were built into the schedule to accommodate weather holds and airspace coordination.

Field Operations & Equipment

Each mission cycle followed a standardized playbook: pre-flight GCP verification, airframe and sensor checks, battery rotations, and data-offload QA. A dedicated spotter supported the PIC (pilot-in-command) during low-angle sun and dust conditions. Mobile shade and filtered cases were used to protect optics and electronics.

Aerial Survey Equipment

• Aerial Survey Equipment

  • Primary LiDAR platform:  DJI Matrice 350 RTK + Zenmuse L2

  • Multispectral platform: DJI Mavic 3 Multispectral (RGB + Red, Green, NIR, Red-Edge)

  • Survey control: Survey-grade RTK GNSS for GCP establishment (≤2 cm)

    
    

• LiDAR Survey

  • Altitude: ~148–150 m | Speed: 7–8 m/s

  • Point density: ~270 pts/m², resolving subtle terrain undulations and under-canopy ground.

    Returns were classified into ground/vegetation/structure, providing the foundation for 10 cm DEMs and 25 cm contours aligned to restoration design needs (berms, swales, flow controls).

Multispectral Survey

Multispectral flights captured bands tailored to NDVI/SAVI computation, enabling mapping of vigor vs. stress, likely moisture deficits, and salinity influence. Cross-checking spectral patterns with LiDAR-derived terrain (slope/aspect/curvature) helped explain vegetation condition in relation to hydrology and micro-relief.

Ground Control

60+ GCPs were established using RTK GNSS, achieving ≤2 cm absolute accuracy. Control points were distributed across terrain and land-cover types to reduce residual bias and ensure stable registration of both LiDAR and imagery products.

Processing & Analysis

• Point-cloud classification into ground/vegetation/structures

• DEM generation at 10 cm with quality filters for outliers

• 25 cm contours optimized for hydrologic planning and grading

• Radiometric corrections and NDVI/SAVI vegetation maps

• Salinity-risk surfaces inferred from spectral response + terrain derivatives

• LiDAR–multispectral fusion to build composite environmental models ready for field decision-making

Technology Stack

• DJI Matrice 350 RTK + Zenmuse L2 LiDAR

• DJI Mavic 3 Multispectral

• RTK GNSS for GCPs

• Specialized LiDAR & multispectral analytics software

Results & Impact

• Precision surpassed: RGB GSD 4.9 cm; multispectral 8.3 cm; positional accuracy ≤15 cm requirement met.

• Under-canopy terrain: High point density resolved micro-topography where photogrammetry alone falls short, improving hydrologic design.

• Vegetation insights: NDVI/SAVI clarified degraded vs. recoverable zones, guiding species selection, planting density, and protection measures.

• Salinity targeting: Hotspots identified for pre-planting amelioration, reducing seedling failure and rework.

• Actionable contours: 25 cm contours supported water-flow management, erosion control, and site grading plans that directly impact survival rates.

Use Cases by Sector

• Environmental Rehabilitation: Prioritize planting zones with the highest recovery potential; stage soil treatments and protection fencing where indices indicate stress.

• Oil & Gas Right-of-Way: Use DEM/contours to design micro-drainage and reduce erosive flows; monitor vegetation recovery along access corridors.

• Municipal & Infrastructure: Plan low-impact access routes; evaluate flood-prone micro-basins; quantify sand encroachment risks.

• Conservation & Rangelands: Track biodiversity proxies via vegetation heterogeneity; identify refugia and regeneration fronts for targeted stewardship.

Workflow & QA

Quality was enforced through multi-stage validation:

• Cross-validation between LiDAR DEM and image-based surfaces at independent checkpoints.

• GCP-anchored residual analysis to confirm absolute accuracy.

• Versioned data handling with metadata, calibration reports, and processing logs packaged alongside deliverables for auditability and future replication.

Timeline & Team

The end-to-end program (mobilization → control → flights → processing) was delivered in a compressed multi-week window aligned to spring phenology. A cross-functional team—UAV pilots, geodesists, LiDAR specialists, and remote-sensing analysts—worked under a single project manager to keep planning, operations, and analytics tightly integrated, cutting cycle time and minimizing rework.

Strategic Relevance (Vision 2030)

This project advances Vision 2030 priorities for sustainable land management and biodiversity by replacing fragmented, slow legacy surveys with fast, safe, repeatable drone workflows. The approach lowers cost and risk while increasing spatial and thematic resolution, giving policymakers and field teams a shared, measurable baseline for transparent progress reporting.

Challenges & Mitigation

• Desert weather: Early-morning sorties minimized wind/dust; standby windows absorbed dust events without schedule slippage.

• Scale (~360 km²): Staggered missions and multi-aircraft rotations maintained throughput with continuous battery and data cycles.

• Data volume: Terabytes of LiDAR/imagery were managed with cloud storage and high-performance processing, ensuring predictable turnaround.

Future Monitoring & ROI

Because all datasets are geodetically consistent, NCEC can repeat flights to quantify year-on-year change—vegetation gains, salinity reduction, erosion control effectiveness—turning the baseline into a living monitoring system. This improves investment allocation, boosts survival rates, and documents measurable ecological return on investment.

Conclusion

By integrating LiDAR, multispectral imaging, and RTK ground control, NineTenths delivered a defensible data foundation for NCEC’s rehabilitation program. The outputs—10 cm DEMs, 25 cm contours, vegetation-health and salinity-risk maps, and fused environmental models—now guide planting, water management, and erosion control across Hafar Al-Batin. Beyond meeting technical specs, this work proves how precision geospatial technology accelerates ecological recovery in arid environments and supports the national sustainability goals of Saudi Vision 2030.

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