Assessment of Ponderosa Pine Vigor Using Four-Band Aerial Imagery in South Central Oregon: Crown Objects to Landscapes

Abstract

Ponderosa pine is an integral part of the forested landscape in the western US; it is the dominant tree species on landscapes that provide critical ecosystem services. Moderate drought tolerance allows it to occupy the transition zone between forests, open woodlands, and grasslands. Increases in stand density resulting from wildfire suppression, combined with lengthening, intensifying, and more frequent droughts have resulted in reduced tree vigor and stand health in dry ponderosa pine throughout its range. To address a management need for efficient landscape-level surveys of forest health, we used Random Forests to develop an object-oriented classification of individual tree crowns (ITCs) into vigor classes using existing, agency-acquired four-band aerial imagery. Classes of tree vigor were based on quantitative physiological and morphological attributes established in a previous study. We applied our model across a landscape dominated by ponderosa pine with a variety of forest treatments to assess their impacts on tree vigor and stand health. We found that stands that were both thinned and burned had the lowest proportion of low-vigor ITCs, and that stands treated before the 2014–2016 drought had lower proportions of low-vigor ITCs than stands treated more recently (2016). Upland stands had significantly higher proportions of low-vigor trees than lowland stands. Maps identifying the low-vigor ITCs would assist managers in identifying priority stands for treatment and marking trees for harvest or retention. These maps can be created using already available imagery and GIS software.

Mitigating the Mistletoe Menace: Biotechnological and Smart Management Approaches

“…To make this possible, detection algorithms would need precision in screening and classifying mistletoes, which might face challenges resulting from the huge diversity of mistletoes, their growth stages, geographical settings, climates, canopy structures, size, density, etc. [ 86 , 378 , 379 , 380 , 381 , 382 , 383 ]. Moreover, many mistletoe species are known to mimic their hosts in foliar structures [ 139 ].…”

Assessing Tree Water Balance after Forest Thinning Treatments Using Thermal and Multispectral Imaging

“…The goal of management actions in these dense, overcrowded stands is to reduce the risk of stand replacing high-intensity wildfire by reducing stand density to increase resilience. Assessments of the effectiveness of these treatments have focused on bole and branchlet diameter growth [12], sapflow [13], elongation growth, needle chlorosis [14,15], and remotely sensed spectral and thermal metrics [16][17][18][19]. In this paper, we tested the capability of assessing these field metrics with drone-based imagery for individual trees in three different stand densities-moderate and light thinnings and a unthinned control.…”

“…These factors result in lower VNIR, especially NIR, relative to deciduous canopies [25,26]. The Normalized Difference Vegetation Index (NDVI) has been successfully used in a variety of agricultural and wildland vegetation mapping applications [16,[27][28][29]. However, it tends to saturate at high biomass levels [30], which has led to the development of alternatives such as the Enhanced Vegetation Index (EVI).…”

“…Recent research has demonstrated greater effectiveness of a simple green-red index in tracking conifer phenology and carbon up-take [31][32][33]. Stress in conifer crowns has been detected with four-band VNIR imagery [16], VNIR and thermal infrared (TIR) [18], hyperspectral data coupled with lidar [34], and red-edge (691-730 nm) data [35]. Thermographic instruments became widely available in the 1960s [36].…”

Monitoring Fine-Scale Forest Health Using Unmanned Aerial Systems (UAS) Multispectral Models

“…At both the individual tree level and at the level of forest stands or landscapes these indicators measure conditions, or the changes in them using a range of variables. These variables include crown vigor [6,39,40]; structural characteristics such as tree height, growing stock, or crown size [25]; phenology; water content; defoliation [18,41]; canopy discoloration; and fragmentation [9,42]. Two prevailing techniques exist for conducting these assessments of forest health using modern, high-resolution, imagery: (1) aerial surveys or (2) digital image classification.…”