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Portland, OR, United States

Byrd K.B.,Western Geographic Science Center | O'Connell J.L.,University of California at Berkeley | Di Tommaso S.,University of California at Berkeley | Kelly M.,University of California at Berkeley
Remote Sensing of Environment

There is a need to quantify large-scale plant productivity in coastal marshes to understand marsh resilience to sea level rise, to help define eligibility for carbon offset credits, and to monitor impacts from land use, eutrophication and contamination. Remote monitoring of aboveground biomass of emergent wetland vegetation will help address this need. Differences in sensor spatial resolution, bandwidth, temporal frequency and cost constrain the accuracy of biomass maps produced for management applications. In addition the use of vegetation indices to map biomass may not be effective in wetlands due to confounding effects of water inundation on spectral reflectance. To address these challenges, we used partial least squares regression to select optimal spectral features in situ and with satellite reflectance data to develop predictive models of aboveground biomass for common emergent freshwater marsh species, Typha spp. and Schoenoplectus acutus, at two restored marshes in the Sacramento-San Joaquin River Delta, California, USA. We used field spectrometer data to test model errors associated with hyperspectral narrowbands and multispectral broadbands, the influence of water inundation on prediction accuracy, and the ability to develop species specific models. We used Hyperion data, Digital Globe World View-2 (WV-2) data, and Landsat 7 data to scale up the best statistical models of biomass. Field spectrometer-based models of the full dataset showed that narrowband reflectance data predicted biomass somewhat, though not significantly better than broadband reflectance data [R2=0.46 and percent normalized RMSE (%RMSE)=16% for narrowband models]. However hyperspectral first derivative reflectance spectra best predicted biomass for plots where water levels were less than 15cm (R2=0.69, %RMSE=12.6%). In species-specific models, error rates differed by species (Typha spp.: %RMSE=18.5%; S. acutus: %RMSE=24.9%), likely due to the more vertical structure and deeper water habitat of S. acutus. The Landsat 7 dataset (7 images) predicted biomass slightly better than the WV-2 dataset (6 images) (R2=0.56, %RMSE=20.9%, compared to R2=0.45, RMSE=21.5%). The Hyperion dataset (one image) was least successful in predicting biomass (R2=0.27, %RMSE=33.5%). Shortwave infrared bands on 30m-resolution Hyperion and Landsat 7 sensors aided biomass estimation; however managers need to weigh tradeoffs between cost, additional spectral information, and high spatial resolution that will identify variability in small, fragmented marshes common to the Sacramento-San Joaquin River Delta and elsewhere in the Western U.S. © 2014 . Source

Schmidtlein M.C.,California State University, Sacramento | Wood N.J.,Western Geographic Science Center
Applied Geography

Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches. © 2014 The Authors. Source

Wood N.,Western Geographic Science Center | Jones J.,Western Geographic Science Center | Schelling J.,Building | Schmidtlein M.,California State University, Sacramento
International Journal of Disaster Risk Reduction

Tsunami vertical-evacuation (TVE) refuges can be effective risk-reduction options for coastal communities with local tsunami threats but no accessible high ground for evacuations. Deciding where to locate TVE refuges is a complex risk-management question, given the potential for conflicting stakeholder priorities and multiple, suitable sites. We use the coastal community of Ocean Shores (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, multi-criteria decision analysis for framing the locational problem of TVE siting. We demonstrate a mixed-methods approach that uses potential TVE sites identified at community workshops, geospatial analysis to model changes in pedestrian evacuation times for TVE options, and statistical analysis to develop metrics for comparing population tradeoffs and to examine influences in decision making. Results demonstrate that no one TVE site can save all at-risk individuals in the community and each site provides varying benefits to residents, employees, customers at local stores, tourists at public venues, children at schools, and other vulnerable populations. The benefit of some proposed sites varies depending on whether or not nearby bridges will be functioning after the preceding earthquake. Relative rankings of the TVE sites are fairly stable under various criteria-weighting scenarios but do vary considerably when comparing strategies to exclusively protect tourists or residents. The proposed geospatial framework can serve as an analytical foundation for future TVE siting discussions. © 2014. Source

Wood N.,Western Geographic Science Center | Jones J.,Western Geographic Science Center | Schmidtlein M.,California State University, Sacramento | Schelling J.,Building | Frazier T.,Binghamton University State University of New York
International Journal of Disaster Risk Reduction

Successful evacuations are critical to saving lives from future tsunamis. Pedestrian-evacuation modeling related to tsunami hazards primarily has focused on identifying areas and the number of people in these areas where successful evacuations are unlikely. Less attention has been paid to identifying evacuation pathways and population demand at assembly areas for at-risk individuals that may have sufficient time to evacuate. We use the neighboring coastal communities of Hoquiam, Aberdeen, and Cosmopolis (Washington, USA) and the local tsunami threat posed by Cascadia subduction zone earthquakes as a case study to explore the use of geospatial, least-cost-distance evacuation modeling for supporting evacuation outreach, response, and relief planning. We demonstrate an approach that uses geospatial evacuation modeling to (a) map the minimum pedestrian travel speeds to safety, the most efficient paths, and collective evacuation basins, (b) estimate the total number and demographic description of evacuees at predetermined assembly areas, and (c) determine which paths may be compromised due to earthquake-induced ground failure. Results suggest a wide range in the magnitude and type of evacuees at predetermined assembly areas and highlight parts of the communities with no readily accessible assembly area. Earthquake-induced ground failures could obstruct access to some assembly areas, cause evacuees to reroute to get to other assembly areas, and isolate some evacuees from relief personnel. Evacuation-modeling methods and results discussed here have implications and application to tsunami-evacuation outreach, training, response procedures, mitigation, and long-term land use planning to increase community resilience. © 2016. Source

Peters J.,Western Geographic Science Center | Wood N.,Western Geographic Science Center | Wilson R.,California Geological Survey | Miller K.,California Governors Office of Emergency Services
Natural Hazards

Tsunami-evacuation planning in coastal communities is typically based on maximum evacuation zones for a single scenario or a composite of sources; however, this approach may over-evacuate a community and overly disrupt the local economy and strain emergency-service resources. To minimize the potential for future over-evacuations, multiple evacuation zones based on arrival time and inundation extent are being developed for California coastal communities. We use the coastal city of Alameda, California (USA), as a case study to explore population and evacuation implications associated with multiple tsunami-evacuation zones. We use geospatial analyses to estimate the number and type of people in each tsunami-evacuation zone and anisotropic pedestrian evacuation models to estimate pedestrian travel time out of each zone. Results demonstrate that there are tens of thousands of individuals in tsunami-evacuation zones on the two main islands of Alameda, but they will likely have sufficient time to evacuate before wave arrival. Quality of life could be impacted by the high number of government offices, schools, day-care centers, and medical offices in certain evacuation zones and by potentially high population density at one identified safe area after an evacuation. Multi-jurisdictional evacuation planning may be warranted, given that many at-risk individuals may need to evacuate to neighboring jurisdictions. The use of maximum evacuation zones for local tsunami sources may be warranted given the limited amount of available time to confidently recommend smaller zones which would result in fewer evacuees; however, this approach may also result in over-evacuation and the incorrect perception that successful evacuations are unlikely. © 2016 The Author(s) Source

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