Defensible land decisions from complex environmental data for climate resilience.
SylvaStep helps municipalities, First Nations, land managers, conservation organizations, and partner firms turn forestry, wildfire, biodiversity, GIS, LiDAR, and remote-sensing data into clear priorities and practical action.
Mapping, imagery, terrain, vegetation, and change-detection workflows that turn complex spatial data into clear, decision-ready products for planning, monitoring, and land-risk assessment.
Analysis, modelling, and reporting workflows that turn environmental datasets into practical priorities, defensible assumptions, and clear recommendations for planning, monitoring, and investment decisions.
Field-aware planning, assessment, and reporting support for wildfire resilience, forest health, vegetation, habitat, and land-use decisions where technical judgment and defensible documentation matter.
Monitoring and feasibility support for restoration, carbon, biodiversity, and ecological recovery projects, including baselines, indicators, spatial analysis, and practical reporting frameworks.
SylvaStep brings professional land-management judgment together with advanced geospatial and environmental-data methods, helping clients move from complex information to defensible decisions, clear reports, and practical next steps.
Credible Expertise
Forestry, biology, wildfire, GIS, LiDAR, remote sensing, and environmental-data experience brought together in one focused technical practice.
Professional Accountability
Work grounded in professional designations, transparent assumptions, defensible methods, and clear documentation that clients can use with confidence.
Tailored Solutions
Lean, practical support for municipalities, First Nations, land managers, partner firms, and organizations that need decision-ready analysis rather than generic reports.
Current projects
Applied projects and technical development.
Discover the real‑world impact of our work. SylvaStep is actively supporting municipalities, First Nations, NGOs, and private-sector clients on applied projects involving climate resilience, land stewardship, restoration, carbon readiness, wildlife detection, and environmental decision support.
Mapping Snow Dynamics for Climate Change AnalysisFig. 1
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Fig. 1Snow mapping validation siteMore than 20 field test sites were manually installed to validate the snow mapping accuracy, based on observing daily snow conditions on the ground.
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Mapping Snow Dynamics for Climate Change Analysis
Client
St'át'imc First Nation
Location
Lillooet, BC
In-progress spatial analysis of snow dynamics and climate-related landscape indicators to support applied climate-change, hydrology, and resilience planning.
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Agroforestry, Restoration & Carbon Readiness Pilot
Client
Almost Heaven Farms & Kamala Foundation
Location
Nepal
In-progress support for agroforestry, restoration, carbon readiness, and ecological monitoring, including baselines, feasibility considerations, and decision-ready reporting.
Fig. 1This example uses the publicly available BAMBI thermal/RGB wildlife dataset and associated public model resources, which we gratefully acknowledge as a development benchmark. SylvaStep is adapting and retraining these resources for our own wildlife-monitoring objectives, improving detection and review workflows for our intended use cases. The BAMBI example is a development step only; our final operational workflow will use our own project-specific drone imagery, detection models, and crop-classification models once local survey data are available.Acknowledgement: BAMBI thermal/RGB wildlife dataset and public model resources.
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Thermal Drone Wildlife Detection & Survey Program
Client
St'át'imc First Nation
Location
Lillooet, BC
In-progress drone/RPAS and thermal-imagery work supporting wildlife detection, survey planning, monitoring, and field-informed environmental assessment.
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Ready to make defensible land-risk decisions?
Bring us a landscape, risk question, RFP, or project idea. SylvaStep can help clarify the technical path, data requirements, and decision-support options.