As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based methods have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (< = 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal-preand post-fire event-WorldView-2 imagery at 2 m spatial resolution. We first evaluated our approaching using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns(crown scale) and 15m by 15m fixed-area plots (inter-crown scale) with the post-fire aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.
In forest ecosystems, canopy openness affects understory light availability, plant growth, and tree species recruitment, thus shaping future forest composition, structure, and functional diversity. Foresters must correctly and quickly measure canopy openness to meet their management objectives. To help guide the selection of an appropriate method for measuring canopy openness, we compared three common techniques that vary in cost, complexity, and time required for measurements and data processing: smartphone-based hemispherical photography, spherical densiometer measurements, and direct measurements of solar radiation (using AccuPAR ceptometer). We measured canopy openness using these three methods on 28 permanent forest health monitoring plots in pine-oak forests of the Central Pine Barrens of Long Island in New York State. By analysis of variance and regression analyses, we found the three methods (particularly densiometer and hemispherical photographs) yielded broadly equivalent and strongly positively correlated descriptions of canopy openness. The direct measurements of solar radiation seemed to have a greater potential to detect subtle variation in forest understory light. Forest managers may sufficiently characterize canopy openness using quick and cheap methods (e.g., spherical densiometers) and avoid larger costs of devices for direct light measurements (e.g., ceptometers) and the larger data-processing times of hemispherical photography.
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