Light Detection and Ranging (LiDAR) is an active remote sensing system with lasers. When LiDAR sends out laser pulses, it waits for the lasers to bounce off its target surface. Then, LiDAR calculates the time it took for the lasers to return. These time differences are then used to assemble 3D reconstructions of surfaces and objects. LiDAR devices are more commonly attached to airplanes, but recently, the International Space Station started collecting and sharing laser-ranging data of Earth’s surface.
We apply a variety of algorithms to analyze, clean, and process LiDAR data to generate high-resolution surfaces, such as digital elevation models and canopy height models. We apply these models in our assessments of forest stratification and biomass estimation.
Orbiting above our forests and fields, satellites collect multispectral images of our Earth below. Unlike standard photography, satellite imagery captures radiant energy outside the range of human vision. Satellites also provide high-resolution spatial and temporal data. We use satellite images to monitor changing landscapes and classify forest types.
Satellite Imaging collects data from multiple seasons. It captures changes in phenological events like leaves turning color in the fall. It records harvesting, deforestation, and other shifts on land cover. We fed satellite images into spatial models to produce a variety of outputs, such as forest type classification and CO2 estimates across a project area and its neighboring properties.
Synthetic Aperture Radar (SAR) is an active data collection method. SAR produces energy. The energy loses strength as it interacts with the Earth’s surface. When the energy reflects back, SAR records the change in the energy. Unlike satellite imagery, whose interpretation is similar to photography, SAR data is responsive to surface characteristics like moisture and structure, requiring a different approach for interpretation.
SAR provides finer resolution images compared to conventional beam-scanning radars. Additionally, SAR can capture images under almost all-weather conditions, regardless of cloud cover.
We use SAR data in projects located in areas with frequent cloud cover and remote areas where LiDAR data is not available.
Our field measurements undergo rigorous, peer-reviewed equations to calculate carbon storage over time. We measure thousands of trees and compile our data using the USDA Forest Service’s models. These incredibly detailed models are calibrated for each tree to account for the subtlest of differences.
When NASA calibrated their own remote sensing technology, they turned to our data to ensure their technology had the numbers right.
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