Post-Katrina Land-Cover, Elevation, and Volume Change Assessment along the South Shore of Lake Pontchartrain, Louisiana, U.S.A.

Geospatial Assessment of Recovery Rates Following a Tornado Disaster

“…Contrary to this, intense winds are more likely to snap vegetation destroying it; thus, recovery is much slower [47], [48]. Additionally, the speed of vegetation regeneration depends on plant size before the disaster, as smaller plants tend to recover quicker than large trees [13], [47]- [49]. Typically, larger vegetation will take several years, if not decades, for complete restoration based on tree size [47].…”

“…Geospatial techniques have been employed in a variety of postdisaster analyses from wildfires, hurricanes, or tsunamis (e.g., Splinter et al [10], Rodgers et al [11], Barnes et al [12], Reif et al [13], and Mitri and Gitas [14]), focusing on vegetative and urban recovery. Lin et al [15] and Chou et al [16] uncovered spatial disparities in vegetative recovery rates one and six years after the landslide, respectively, using a recovery index and NDVI images (produced from SPOT imagery).…”

“…This method could be useful in distinguishing damaged and recovered regions after the disaster by taking into account the minor deviations in index values that can occur annually. Unlike the aforementioned analyses, Reif et al [13] employed hyperspectral imagery, decisionbased classification, and LIDAR data, noting volume increases (decreases) in bare soil and low vegetation (structures and medium and tall vegetation) three years after Hurricane Katrina. Focusing solely on urban recovery, Ward et al [18] found recovery disparities using a Geographic Information Systems (GIS)-based spatial recovery index three years after Hurricane Katrina, loosely connecting recovery and social vulnerability.…”

“…One aspect, however, that has only recently become researched is postdisaster recovery utilizing remote-sensing methodologies (e.g., Splinter et al [10], Rodgers et al [11], Barnes et al [12], Reif et al [13], and Mitri and Gitas [14]). While these and other studies have shown that evaluation of postdisaster recovery is possible, only non-geospatial assessments focusing on migration and economic perspectives have been utilized in examining recovery rates from tornado disasters.…”

Evaluating Resilience-Centered Development Interventions with Remote Sensing

“…However, this requires indirect observations and the use of proxies [19], as demonstrated in recent studies on vulnerability [37,38], resilience [39], damage [40,41], and recovery [42]. In addition, recent studies showed that most of the developed proxies for damage and recovery assessments can be extracted through LC and LU monitoring [43,44], increasingly through the use of ML techniques [20]. The growing sophistication of image-based extraction of both physical and non-physical indicators of recovery, and thus resilience, suggests a possible role in impact evaluation, which we tested in this work.…”