Mitigation of Spatial Effects on an Area-Based Lidar Forest Inventory (2024)

Abstract

Different sizes and shapes of field plots relative to raster grid cells were found to negatively affect lidar augmented forest inventory. This issue is called the “change of spatial support problem (COSP)” and caused biases and reduction in estimation efficiency (precision per number of plots). For a ∼14 000 km² study area in Oregon State, USA, we examined three different plot shapes, both fixed-radius and cluster plots, alongside grid cell sizes ranging from 5 to 70 m. Effect size varied with the magnitude of spatial mismatch between plots and raster grid cells. There was up to 15% bias and a 98% reduction in estimation efficiency. Fortunately, no negative effects were observed for circle (plots) versus square (grid cell) shaped regions with the same areas (m²). This study contributes to the sparse body of literature around change of spatial support in the area-based approach to lidar forest inventory and provides methods to easily avoid and mitigate negative effects. The simplest approach to avoid bias, although not always practical or feasible, is to exactly match the area (m²) of circular field plots and raster grid cells. Use of metrics robust to spatial effects, such as median height and height ratios, can also reduce change of spatial support effects. Finally, we demonstrate that attribution of plots directly from raster grid cells (the “raster-intersect” approach) is robust to change of spatial support and flexible in application, but sacrifices a small amount of predictive power (a glossary of technical terminology is also provided in the appendix).