January, 2026

Enhanced Forest Inventories for Habitat Mapping: A Case Study in the Sierra Nevada Mountains of California

Traditional forest inventory systems, originally designed to quantify merchantable timber volume, often lack the spatial resolution and structural detail required for modern multi-resource ecosystem management. In this manuscript, we present an Enhanced Forest Inventory (EFI) and demonstrate its utility for high-resolution wildlife habitat mapping.

The project area covers 270,000 acres of the Eldorado National Forest in California’s Sierra Nevada. By integrating 118 ground-truth Forest Inventory and Analysis (FIA) plots with multi-modal remote sensing data (LiDAR, aerial photography, and Sentinel-2 satellite imagery), we developed predictive models for key forest attributes.

Our methodology employed a two-tier segmentation approach, partitioning the landscape into approximately 575,000 reporting units with an average size of 0.5 acre to capture forest heterogeneity. We utilized an Elastic-Net Regression framework and automated feature selection to relate remote sensing metrics to ground-measured variables such as basal area, stems per acre, and canopy cover.

These physical metrics were translated into functional habitat attributes to evaluate suitability for two focal species: the California Spotted Owl (Strix occidentalis occidentalis) and the Pacific Fisher (Pekania pennanti).

Our analysis identified 25,630 acres of nesting and 26,622 acres of foraging habitat for the owl, and 25,636 acres of likely habitat for the fisher based on structural requirements like large-diameter trees and high canopy closure. The results demonstrate that Enhanced Forest Inventories provide a critical bridge between forestry and conservation ecology, offering forest managers a spatially explicit tool to monitor ecosystem health and manage vulnerable species in complex environments.

October, 2025

The Use and Importance of Airborne LiDAR metrics in High Resolution Forest Inventory Development

At SilviLaser 2025 (a key event for showcasing leading applications of laser scanning and related technologies in forest ecosystem assessment and management), Tesera presented "The Use and Importance of Airborne LiDAR metrics in High Resolution Forest Inventory Development," highlighting our innovative insights in this field.

May, 2025

Large Scale Change Detection using Remote Sensing Data

At the annual Statistical Society of Canada Meeting, Tesera presented on “Large Scale Change Detection using Remote Sensing Data”. This presentation explored the use of remote sensing data, such as satellite imagery, for large-scale forest change detection. 

April, 2025

A Predictive Accuracy Comparison of HRIS vs. Conventional Ground Plot-based Forest Inventory

Over multiple projects and diverse forest conditions, HRIS is more accurate (than a conventional ground plot-based inventory) providing significant increases in predictive accuracy (RMSE). We conducted RMSE comparisons for inventory projects in both natural forest conditions and managed forest conditions (plantations). Across several forest attributes, HRIS provides substantial accuracy improvements over diverse forest conditions.   .