Spatial Variability of Landscape Pattern Change Following a Ponderosa Pine Wildfire in Northeastern New Mexico, USA

Relationships between fire severity and post-fire landscape pattern following a large mixed-severity fire in the Valle Vidal, New Mexico, USA

“…Maps and frequency distributions of the metrics, however, revealed areas of the landscape that experienced large changes in pattern. We suspected that spatial variability of changes in landscape pattern was associated with fire severity, but that hypothesis was not explored in Hayes and Robeson (2009). The present study extends the moving-window method to examine pattern variability within specific levels of fire severity.…”

“…MPS, PD, PR, and MSI were analyzed for pre-and post-fire forest patches using the movingwindow method implemented in FRAGSTATS 3.3 (Fig. 4) (McGarigal et al, 2002;Hayes and Robeson, 2009). A moving window of 15 × 15 Landsat ETM+ pixels (450 m 2 ) was used to calculate each metric for the area within the moving window, with the result assigned to the center pixel (focus) stored in a new image file.…”

“…In this study, a moving-window approach is used to integrate the two approaches (patch-based and raster data) for landscape analysis by calculating a raster dataset of landscape metric values. The moving-window approach has been used to identify areas within landscapes that have metric values well below or above averages for the landscape as a whole-such locations could go unnoticed ("averaged out") using the typical summaryvalue approach (Riitters et al, 2000(Riitters et al, , 2002Wade et al, 2003;Lung and Schaab, 2006;Hayes and Robeson, 2009). Using this approach for the Valle Vidal following the Ponil Complex Fire (hereafter Ponil Fire), we found that there was little or no change in pattern when averaging over the entire landscape (Hayes and Robeson, 2009).…”

Factors influencing national scale wildfire susceptibility in Canada

“…While short-term effects of fire include changes to landscape pattern (Hayes and Robertson, 2009), wildlife habitat (Emlen, 1970;Whelan et al, 2002), soil (Giovannini et al, 2001), and air quality (Hardy et al, 2001), the long-term effects drive ecological processes (Whelan, 1995) and impact carbon cycling (Kasischke et al, 1995).…”

Mapping Tree Density in Forests of the Southwestern USA Using Landsat 8 Data

“…Few studies have assessed the landscape or regional patterns of structural diversity in coniferous forests of the southwestern USA using remote sensing. Most of the studies for the region have focused on understanding fire activity patterns rather than understanding the distribution of a particular forest structural property [51][52][53][54][55]. The literature that is available for similar forest types in other locations is limited to areas with little variation in elevation range in Colorado [56], areas dominated by a single species in Yellowstone National Park [20], closed-canopy forests in Oregon [57], forests with uniform age and species composition in Oregon [58], and intensely managed forests in Idaho, Texas, and New Brunswick Province (Canada) [21,59,60].…”