Characterizing stand-replacing disturbance in western Alberta grizzly bear habitat, using a satellite-derived high temporal and spatial resolution change sequence

摘要

a- Blending satellite data produces accurate, high resolution, disturbance sequences. a- Validation of predicted dates of disturbance suggests an accuracy of 62%. a- Most disturbances are small in area and occur late in the growing season. a- Disturbance patterns at the scale of grizzly bear home ranges are highly variable. Timely and accurate mapping of anthropogenic and natural disturbance patterns can be used to better understand the nature of wildlife habitats, distributions and movements. One common approach to map forest disturbance is by using high spatial resolution satellite imagery, such as Landsat 5 Thematic Mapper (TM) or Landsat 7 Enhanced Thematic Mapper plus (ETM+) imagery acquired at a 30m spatial resolution. However, the low revisit times of these sensors acts to limit the capability to accurately determine dates for a sequence of disturbance events, especially in regions where cloud contamination is a frequent occurrence. As wildlife habitat use can vary significantly seasonally, annual patterns of disturbance are often insufficient in assessing relationships between disturbance and foraging behaviour or movement patterns. The Spatial Temporal Adaptive Algorithm for mapping Reflectance Change (STAARCH) allows the generation of high-spatial (30m) and -temporal (weekly or bi-weekly) resolution disturbance sequences using fusion of Landsat TM or ETM+ and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The STAARCH algorithm is applied here to generate a disturbance sequence representing stand-replacing events (disturbances over 1ha in area) for the period 2001-2008, over almost 6millionha of grizzly bear habitat along the eastern slopes of the Rocky Mountains in Alberta. The STAARCH algorithm incorporates pairs of Landsat images to detect the spatial extent of disturbances; information from the bi-weekly MODIS composites is used in this study to assign a date of disturbance (DoD) to each detected disturbed area. Dates of estimated disturbances with areas over 5ha are validated by comparison with a yearly Landsat-based change sequence, with producer's accuracies ranging between 15 and 85% (average overall accuracy 62%, kappa statistic of 0.54) depending on the size of the disturbance event. The spatial and temporal patterns of disturbances within the entire region and in smaller subsets, representative of the size of a grizzly bear annual home range, are then explored. Disturbance levels are shown to increase later in the growing season, with most disturbances occurring in late August and September. Individual events are generally small in area (<10ha) except in the case of wildfires, with, on average, 0.4% of the total area disturbed each year. The application of STAARCH provides unique high temporal and spatial resolution disturbance information over an extensive area, with significant potential for improving understanding of wildlife habitat use.