Operationalize best-in-class science and data for valuable insights

Leverage state-of-the-art methods developed by Pyrologix, a Vibrant Planet Company, such as WildEST, and FlamMap and FSim, pioneered by the USFS Missoula Fire Sciences Laboratory.

Understand drought probability and intensity based on modeled historical and projected future precipitation, classified by intensity.

See the likelihood and exposure of forests to widespread tree mortality during periods of low water availability and warm temperatures.

Using an ensemble of machine learning and AI packages, Vibrant Planet transforms imagery from sources including the National Agriculture Imagery Program, remote sensing and satellite imagery, existing lidar, and more.

Our models harmonize dozens of these datasets to build a more temporally and spatially consistent view of a vegetation structure, including a synthetic Canopy Height Model (CHM), canopy cover estimates, and a mapping of canopy dominant trees.

The result is a wall-to-wall vegetation map at fine scale, updated regularly.

Together with topography, vegetation type, and the precise, current, and 3D synthetic CHM, we apply algorithms that group biophysically homogeneous polygons.

Based on ownership and/or similar controlling interests, we subdivide these homogenous polygons into management units that will respond similarly to treatments.

From homes and utility lines to carbon, and aspen groves and Threatened and Endangered species, we help quantify the relative importance of the values across a landscape. This allows a fair comparison between them, including tradeoffs of management decisions.

We employ a risk and opportunity-based framework to quantify the relative value of resources and assets, including their contributions to safety, how irreplaceable they are, and their uniqueness in a landscape.

When considered in concert with our hazard and treatment modeling, our processing optimizes the treatment mix across the area of interest to maximize risk reduction and ecological benefit.

We’re helping land managers understand how treatments impact ecosystem health, assess current risk to threatened and endangered species habitat, and weigh tradeoffs of different treatment mixes.

For example, land managers can see how watershed restoration could be best led by beaver activity, or how species like wolverine may respond to human intervention in landscapes.

We recognize that water is an asset, a habitat, and a risk factor. Land managers and their partners need to anticipate the cumulative impacts of treatments and disturbance to the multiple roles of water. By combining remote sensing, physics-based models, and machine learning we are developing new methods to quantify changes to water quality, water availability, and post-disturbance risks like debris flows and flash floods. Our approach to connectivity across the landscape lets land managers prioritize forest projects that reduce the risk of sedimentation in downstream water supply reservoirs and high-quality habitat streams.

We’re exploring and quantifying the benefits of innovative, ecological forest management. This can lead to a dramatic reduction in wildfire and drought hazard, address forest health, and retain healthy living ecosystems that provide essential ecosystem services such as carbon storage and sequestration to protect us against the worst impacts of climate change.

In partnership with CTrees, we're serving users with 5-meter resolution above ground biomass carbon data, and exposing current storage to hazard and risk, to demonstrate the cost of ‘no-action’.