High Resolution Inventory Solutions (HRIS)

With the availability of high resolution remote-sensed data, web accessible devices, cloud hosting and machine learning techniques, a new generation of inventory approaches and solutions are available to better manage your forest and natural resource assets.

Tesera’s High Resolution Inventory Solutions (HRIS) are an integrated blend of Enhanced Forest Inventory (EFI) and Individual Tree Inventory (ITI) capabilities under a single unique and powerful inventory.

We use remote sensing data, LiDAR, hyperspectral / multispectral satellite imagery, ground plot data (along with terrain and other data) to provide a more accurate, scalable, timely and cost-effective inventory.

Infographic explaining HRIS features for forest management, including better species and site productivity estimates, inventory updates, comprehensive high-resolution inventory, growth and yield forecasts, and scalable production.

How do we start?

Tesera recommends a Discovery Sprint, as an innovative process to quickly scope a potential forest inventory solution.

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Overview of HRIS Process

INPUTS

Tesera provides the specifications for the acquisition, timing, geolocation and compilation of these inputs.

  • Compiled ground sample plot data

  • Classified LiDAR point cloud

  • Hyperspectral and multispectral imagery

  • Orthorectified aerial imagery, DSM-orthomosaic tiled imagery, True (DTM) orthomosaic tiled imagery

  • Disturbance polygons, land cover polygons, land use polygons, roads polylines and polygons

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PROCESS

  • Acquisition of base data

  • Processing of sample ground plots and feature data

  • Selection of features

  • Machine Learning-based AI

  • Area segmentation

  • Processing and segmentation of feature data

  • Prediction of attributes 

  • Compilation of the HRIS Inventory

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OUTPUTS

  • HRIS Inventory geospatial data and forest attributes (in any standard Client specified GIS format)

  • Optional data products: Predicted streams & wet area polygons, Contour polylines, Aspect rasters (slope and direction), Digital terrain and surface model rasters, Canopy height model rasters, Hillshade rasters, Individual tree crown polygons, Colourized infrared rasters, among many others…


Why HRIS?

Less cost and effort on timber cruising and ground sampling

Timber cruising and ground sampling is primarily done because conventional inventories are too unreliable and low resolution for operational purposes. HRIS reduces the expense, time and human resources associated with cruising and ground sampling.

Align forecasts and inventory with market opportunities

HRIS enables more reliable planning and layouts that lead to improved forecasting, and a better match with market forecasts. HRIS enables the alignment of market and forecasts, while maximizing productivity opportunities across your supply chain.

More efficient road, cutblock, harvest planning and scheduling

Laying out roads and cutblocks, along with harvest planning and scheduling is fundamental to a company’s operations. A reliable forest and natural resource inventory results in better planning and layouts that decrease costs and improve operations in the field.

Better sustainability and silviculture investments

The efficiency and sustainability of a company's operations ultimately rests in its ability to match market and forecasts. HRIS enables more reliable planning and layouts to better align forecasts with current and future outcomes.

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BETTER FOR
MANAGERS

Access to high resolution inventory data provides a more reliable view of resources on the landscape. It enables better management decisions and margins, guided by sustainable environmental stewardship principles.

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BETTER FOR
COMPANIES

An inventory is a critical measure of the value of a company, and key to efficient and effective management of its natural capital and environmental assets. It is the first step in optimizing supply chains to meet changing market demand.

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BETTER FOR
COMMUNITIES

A reliable inventory fosters collaboration and understanding, crucial for informed community decisions regarding local ecosystems, economies, environmental attributes, and carbon biomass.