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At least 181 records · Page 10Linked to original sources

Mapping rice areas of South Asia using MODIS multitemporal data

Our goal is to map the rice areas of six South Asian countries using moderate-resolution imaging spectroradiometer (MODIS) time-series data for the time period 2000 to 2001. South Asia accounts for almost 40% of the world's harvested rice area and is also home to 74% of the population that lives on less than $2.00 a day. The population of the region is growing faster than its ability to produce rice. Thus, accurate and timely assessment of where and how rice is cultivated is important to craft food security and poverty alleviation strategies. We used a time series of eight-day, 500-m spatial resolution composite images from the MODIS sensor to produce rice maps and rice characteristics (e.g., intensity of cropping, cropping calendar) taking data for the years 2000 to 2001 and by adopting a suite of methods that include spectral matching techniques, decision trees, and ideal temporal profile data banks to rapidly identify and classify rice areas over large spatial extents. These methods are used in conjunction with ancillary spatial data sets (e.g., elevation, precipitation), national statistics, and maps, and a large volume of field-plot data. The resulting rice maps and statistics are compared against a subset of independent field-plot points and the best available subnational statistics on rice areas for the main crop growing season (kharif season). A fuzzy classification accuracy assessment for the 2000 to 2001 rice-map product, based on field-plot data, demonstrated accuracies from 67% to 100% for individual rice classes, with an overall accuracy of 80% for all classes. Most of the mixing was within rice classes. The derived physical rice area was highly correlated with the subnational statistics with R 2 values of 97% at the district level and 99% at the state level for 2000 to 2001. These results suggest that the methods, approaches, algorithms, and data sets we used are ideal for rapid, accurate, and large-scale mapping of paddy rice as well as for generating their statistics over large areas.

South Asia↗

The automated reference toolset: A soil-geomorphic ecological potential matching algorithm

Ecological inventory and monitoring data need referential context for interpretation. Identification of appropriate reference areas of similar ecological potential for site comparison is demonstrated using a newly developed automated reference toolset (ART). Foundational to identification of reference areas was a soil map of particle size in the control section (PSCS), a theme in US Soil Taxonomy. A 30-m resolution PSCS map of the Colorado Plateau (366,000 km 2 ) was created by interpolating ∼5000 field soil observations using a random forest model and a suite of raster environmental spatial layers representing topography, climate, general ecological community, and satellite imagery ratios. The PSCS map had overall out of bag accuracy of 61.8% (Kappa of 0.54, p < 0.0001), and an independent validation accuracy of 93.2% at a set of 356 field plots along the southern edge of Canyonlands National Park, Utah. The ART process was also tested at these plots, and matched plots with the same ecological sites (ESs) 67% of the time where sites fell within 2-km buffers of each other. These results show that the PSCS and ART have strong application for ecological monitoring and sampling design, as well as assessing impacts of disturbance and land management action using an ecological potential framework. Results also demonstrate that PSCS could be a key mapping layer for the USDA-NRCS provisional ES development initiative.

Soil Science Society of America Journal↗

Strong-motion, site-effects and hazard issues in rebuilding Turkey: In light of the 17 August, 1999 earthquake and its aftershocks

The August 17, 1999 Izmit (Turkey) earthquake (Mw=7.4) will be remembered as one of the largest earthquakes of recent times that affected a large urban environment (U.S. Geological Survey, 1999). The shaking that caused the widespread damage and destruction was recorded only by a handful of accelerographs in the earthquake area operated by different networks. The characteristics of these records show that the recorded peak accelerations, even those from near field stations, are smaller than expected. On the other hand, smaller magnitude aftershocks yielded larger peak accelerations. This is attributed to the sparse networks, which possibly missed recording of larger motions during the main shock. As rebuilding of Turkey starts, strong-motion networks that yield essential data must be enlarged. In addition, attention must be paid to new developments elsewhere, such as earthquake zoning maps, earthquake hazard maps, liquefaction potentials and susceptibility. This paper aims to discuss these issues. Copyright??2000 IAHS.

International Journal for Housing Science and Its ↗

Intermediate-scale mapping

The U.S. Geological Survey has introduced an intermediate-scale map series (1:100,000 and 1:50,000) in response to the demand for maps at scales between the 1:24,000 and 1:250,000 standard series. The goal is to provide basic cartographic data at the level of detail and in the format selected by Federal, State, regional, county, and other users. A major innovation is the preparation of feature-separation drawings which provide great flexibility in constructing maps. The new series is designed with digitization in mind, ultimately to facilitate forming a digital cartographic data bas

Journal of Research of the U.S. Geological Survey↗

Accuracy of selected land use and land cover maps in the Greater Atlanta region, Georgia

The land use and land cover maps at 1:100000 scale and at 1:24 000 scale in the Greater Atlanta Region were tested for accuracy. At 1:100 000 scale, 381 points were selected using a stratified systematic unalined sampling technique. Of these 381 points, 343 points or 90 percent were found to be correct. At 1:24 000 scale, 71 points were tested for accuracy. Of these 71 points, 62 points or 87 percent were found to be accurate. Confidence intervals were determined based on the assumption that the data exhibited a binomial distribution. With 95-percent confidence the accuracy of the 1:100 000-scale maps was between 87 and 93 percent, and the accuracy of the 1:24 000-scale maps was between 79 and 96 percent. The accuracy of the interpretations was consistent from category to category.

Georgia↗

Infrasound and the avian navigational map

Birds can accurately navigate over hundreds to thousands of kilometres, and use celestial and magnetic compass senses to orient their flight. How birds determine their location in order to select the correct homeward bearing (map sense) remains controversial, and has been attributed to their olfactory or magnetic senses. Pigeons can hear infrasound down to 0??05 Hz, and an acoustic avian map is proposed consisting of infrasonic cues radiated from steep-sided topographic features. The source of these infrasonic signals is microseisms continuously generated by interfering oceanic waves. Atmospheric processes affecting the infrasonic map cues can explain perplexing experimental results from pigeon releases. Moreover, four recent disrupted pigeon races in Europe and the north-eastern USA intersected infrasonic shock waves from the Concorde supersonic transport. Having an acoustic map might also allow clock-shifted birds to test their homeward progress and select between their magnetic and solar compasses.

Journal of Navigation↗

Visible and near-infrared (0.4-2.5 μm) reflectance spectra of playa evaporite minerals

Visible and near-infrared (VNIR; 0.4&ndash;2.4 &mu;m) reflectance spectra were recorded for 35 saline minerals that represent the wide range of mineral and brine chemical compositions found in playa evaporite settings. The spectra show that many of the saline minerals exhibit diagnostic near-infrared absorption bands, chiefly attributable to vibrations of hydrogen-bonded structural water molecules. VNIR reflectance spectra can be used to detect minor hydrate phases present in mixtures dominated by anhydrous halite or thenardite, and therefore will be useful in combination with X ray diffraction data for characterizing natural saline mineral assemblages. In addition, VNIR reflectance spectra are sensitive to differences in sample hydration state and should facilitate in situ studies of minerals that occur as fragile, transitory dehydration products in natural salt crusts. The use of spectral reflectance measurements in playa studies should aid in mapping evaporite mineral distributions and may provide insight into the geochemical and hydrological controls on playa mineral and brine development.

Journal of Geophysical Research↗

Remote sensing of forest fire severity and vegetation recovery

Burned forested areas have patterns of varying burn severity as a consequence of various topographic, vegetation, and meteorological factors. These patterns are detected and mapped using satellite data. Other ecological information can be abstracted from satellite data regarding rates of recovery of vegetation foliage and variation of burn severity on different vegetation types. Middle infrared wavelengths are useful for burn severity mapping because the land cover changes associated with burning increase reflectance in this part of the electromagnetic spectrum. Simple stratification of Landsat Thematic Mapper data define varying classes of burn severity because of changes in canopy cover, biomass removal, and soil chemical composition. Reasonable maps of burn severity are produced when the class limits of burn severity reflectance are applied to the entire satellite data. Changes in satellite reflectance over multiple years reveal the dynamics of vegetation and fire severity as low burn areas have lower changes in reflectance relative to high burn areas. This results as a consequence of how much the site was altered due to the burn and how much space is available for vegetation recovery. Analysis of change in reflectance across steppe, riparian, and forested vegetation types indicate that fires potentially increase biomass in steppe areas, while riparian and forested areas are slower to regrow to pre-fire conditions. This satellite-based technology is useful for mapping severely burned areas by exploring the ecological manifestations before and after fire.

International Journal of Wildland Fire↗

A comparison of the IGBP DISCover and University of Maryland 1 km global land cover products

Two global 1 km land cover data sets derived from 1992-1993 Advanced Very High Resolution Radiometer (AVHRR) data are currently available, the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS) DISCover and the University of Maryland (UMd) 1 km land cover maps. This paper makes a preliminary comparison of the methodologies and results of the two products. The DISCover methodology employed an unsupervised clustering classification scheme on a per-continent basis using 12 monthly maximum NDVI composites as inputs. The UMd approach employed a supervised classification tree method in which temporal metrics derived from all AVHRR bands and the NDVI were used to predict class membership across the entire globe. The DISCover map uses the IGBP classification scheme, while the UMd map employs a modified IGBP scheme minus the classes of permanent wetlands, cropland/natural vegetation mosaic and ice and snow. Global area totals of aggregated vegetation types are very similar and have a per-pixel agreement of 74%. For tall versus short/no vegetation, the per-pixel agreement is 84%. For broad vegetation types, core areas map similarly, while transition zones around core areas differ significantly. This results in high regional variability between the maps. Individual class agreement between the two 1 km maps is 49%. Comparison of the maps at a nominal 0.5 resolution with two global ground-based maps shows an improvement of thematic concurrency of 46% when viewing average class agreement. The absence of the cropland mosaic class creates a difficulty in comparing the maps, due to its significant extent in the DISCover map. The DISCover map, in general, has more forest, while the UMd map has considerably more area in the intermediate tree cover classes of woody savanna/ woodland and savanna/wooded grassland.

International Journal of Remote Sensing↗

A self-trained classification technique for producing 30 m percent-water maps from Landsat data

Small bodies of water can be mapped with moderate-resolution satellite data using methods where water is mapped as subpixel fractions using field measurements or high-resolution images as training datasets. A new method, developed from a regression-tree technique, uses a 30 m Landsat image for training the regression tree that, in turn, is applied to the same image to map subpixel water. The self-trained method was evaluated by comparing the percent-water map with three other maps generated from established percent-water mapping methods: (1) a regression-tree model trained with a 5 m SPOT 5 image, (2) a regression-tree model based on endmembers and (3) a linear unmixing classification technique. The results suggest that subpixel water fractions can be accurately estimated when high-resolution satellite data or intensively interpreted training datasets are not available, which increases our ability to map small water bodies or small changes in lake size at a regional scale.

International Journal of Remote Sensing↗

Wetland classification in the United States

Wetland is part of a continuum of land types between deep water and dryland. Only one wetland classification was available for the United States prior to preparation of the new system described here, but numerous regional and special-purpose classifications are in use. The new classification is hierarchical, progressing from five systems (marine, estuarine, lacustrine, riverine, and palustrine) at the most general level to dominance types based on plant or animal communities at the most specific level. The system is currently in use for prototype maps of wetlands of the United States. It is hoped that it may be incorporated into a classification of all land.

Journal of Forestry↗

Using Landsat satellite data to support pesticide exposure assessment in California

Background The recent U.S. Geological Survey policy offering Landsat satellite data at no cost provides researchers new opportunities to explore relationships between environment and health. The purpose of this study was to examine the potential for using Landsat satellite data to support pesticide exposure assessment in California. Methods and Results We collected a dense time series of 24 Landsat 5 and 7 images spanning the year 2000 for an agricultural region in Fresno County. We intersected the Landsat time series with the California Department of Water Resources (CDWR) land use map and selected field samples to define the phenological characteristics of 17 major crop types or crop groups. We found the frequent overpass of Landsat enabled detection of crop field conditions (e.g., bare soil, vegetated) over most of the year. However, images were limited during the winter months due to cloud cover. Many samples designated as single-cropped in the CDWR map had phenological patterns that represented multi-cropped or non-cropped fields, indicating they may have been misclassified. Conclusions We found the combination of Landsat 5 and 7 image data would clearly benefit pesticide exposure assessment in this region by 1) providing information on crop field conditions at or near the time when pesticides are applied, and 2) providing information for validating the CDWR map. The Landsat image time-series was useful for identifying idle, single-, and multi-cropped fields. Landsat data will be limited during the winter months due to cloud cover, and for years prior to the Landsat 7 launch (1999) when only one satellite was operational at any given time. We suggest additional research to determine the feasibility of integrating CDWR land use maps and Landsat data to derive crop maps in locations and time periods where maps are not available, which will allow for substantial improvements to chemical exposure estimation.

California↗

Plant-based plume-scale mapping of tritium contamination in desert soils

Plant-based techniques were tested for field-scale evaluation of tritium contamination adjacent to a low-level radioactive waste (LLRW) facility in the Amargosa Desert, Nevada. Objectives were to (i) characterize and map the spatial variability of tritium in plant water, (ii) develop empirical relations to predict and map subsurface contamination from plant-water concentrations, and (iii) gain insight into tritium migration pathways and processes. Plant sampling [creosote bush, Larrea tridentata (Sessé & Moc. ex DC.) Coville] required one-fifth the time of soil water vapor sampling. Plant concentrations were spatially correlated to a separation distance of 380 m; measurement uncertainty accounted for <0.1% of the total variability in the data. Regression equations based on plant tritium explained 96 and 90% of the variation in root-zone and sub-root-zone soil water vapor concentrations, respectively. The equations were combined with kriged plant-water concentrations to map subsurface contamination. Mapping showed preferential lateral movement of tritium through a dry, coarse-textured layer beneath the root zone, with concurrent upward movement through the root zone. Analysis of subsurface fluxes along a transect perpendicular to the LLRW facility showed that upward diffusive-vapor transport dominates other transport modes beneath native vegetation. Downward advective-liquid transport dominates at one endpoint of the transect, beneath a devegetated road immediately adjacent to the facility. To our knowledge, this study is the first to document large-scale subsurface vapor-phase tritium migration from a LLRW facility. Plant-based methods provide a noninvasive, cost-effective approach to mapping subsurface tritium migration in desert areas.

Vadose Zone Journal↗

Distance sampling for Sonoran Desert tortoises

We used line transects and distance sampling in combination with radiotelemetry to estimate density of a desert tortoise (Gopherus agassizii) population in the Rincon Mountains near Tucson, Arizona, USA, as part of a long-term study evaluating the impact of urban development on tortoises. During 2000, 34 1-km transects were each sampled twice in the 368.5-ha study area. We observed 46 tortoises with midline carapace lengths ???150 mm (subadults and adults) plus 7 juveniles on transects. For subadults and adults, the encounter rate was 0.63 tortoises/km, and the mean proportion of tortoises observable during radiotelemetry, conducted concurrently with transect sampling, was 82%. Corrected mean density based on line transects and radiotelemetry was 0.523 tortoises/ha (CV = 22.99, 95% CI = 0.29-0.79), and absolute abundance in the study area was estimated to be 193 (CV = 23.0%, CI = 107-291). Using the 2 independent coverages of transects as separate samples, the Lincoln-Petersen mark-recapture estimator produced an abundance estimate of 224 subadult and adult tortoises (CV = 53.9%, CI = 72-440). Transects measured on the ground over uneven topography resulted in 3% smaller estimates of density when compared to analysis with transect lengths determined from coordinates plotted on a map. Distance sampling appears to be a feasible method of estimating density of Sonoran Desert populations of the desert tortoise, but transect lengths should be based on mapped rather than measured distances to prevent biases caused by uneven topography.

Arizona↗

Evaluation of remote mapping techniques for earthquake-triggered landslide inventories in an urban subarctic environment: A case study of the 2018 Anchorage, Alaska Earthquake

Earthquake-induced landslide inventories can be generated using field observations but doing so can be challenging if the affected landscape is large or inaccessible after an earthquake. Remote sensing data can be used to help overcome these limitations. The effectiveness of remotely sensed data to produce landslide inventories, however, is dependent on a variety of factors, such as the extent of coverage, timing, and data quality, as well as environmental factors such as atmospheric interference (e.g., clouds, water vapor) or snow and vegetation cover. With these challenges in mind, we use a combination of field observations and remote sensing data from multispectral, light detection and ranging (lidar), and synthetic aperture radar (SAR) sensors to produce a ground failure inventory for the urban areas affected by the 2018 magnitude (M w ) 7.1 Anchorage, Alaska earthquake. The earthquake occurred during late November at high latitude (∼61°N), and the lack of sunlight, persistent cloud cover, and snow cover that occurred after the earthquake made remote mapping challenging for this event. Despite these challenges, 43 landslides were manually mapped and classified using a combination of the datasets mentioned previously. Using this manually compiled inventory, we investigate the individual performance and reliability of three remote sensing techniques in this environment not typically hospitable to remotely sensed mapping. We found that differencing pre- and post-event normalized difference vegetation index maps and lidar worked best for identifying soil slumps and rapid soil flows, but not as well for small soil slides, soil block slides and rock falls. The SAR-based methods did not work well for identifying any landslide types because of high noise levels likely related to snow. Some landslides, especially those that resulted in minor surface displacement, were identifiable only from the field observations. This work highlights the importance of the rapid collection of field observations and provides guidance for future mappers on which techniques, or combination of techniques, will be most effective at remotely mapping landslides in a subarctic and urban environment.

Alaska↗

U.S. Geological Survey science for the Wyoming Landscape Conservation Initiative—2014 annual report

This is the seventh report produced by the U.S. Geological Survey (USGS) for the Wyoming Landscape Conservation Initiative (WLCI) to detail annual activities conducted by the USGS for addressing specific management needs identified by WLCI partners. In FY2014, there were 26 projects, including a new one that was completed, two others that were also completed, and several that entered new phases or directions. The 26 projects fall into several categories: (1) synthesizing and analyzing existing data to identify current conditions on the landscape and using the data to develop models for projecting past and future landscape conditions; (2) monitoring indicators of ecosystem conditions and the effectiveness of on-the-ground habitat projects; (3) conducting research to elucidate the mechanisms underlying wildlife and habitat responses to changing land uses; (4) managing and making accessible the large number of databases, maps, and other products being developed; and (5) coordinating efforts among WLCI partners, helping them use USGS-developed decision-support tools, and integrating WLCI outcomes with future habitat enhancement and research projects. The new (completed) project was the development and publication of a public outreach piece for visitors of Fossil Butte National Monument. The final product was a USGS Fact Sheet that capitalized on previously collected elk-monitoring data to interpret the ecology of the Monument&rsquo;s elk population and the importance of the Monument&rsquo;s habitats to this highly visible wildlife species. One of the completed projects entailed developing and evaluating a synthetic approach to high-resolution satellite imagery for use in effectiveness monitoring, which culminated in a journal article. The other completed project was a coalescing of two similar tasks under data and information management that pertain to Web application development and the development of outreach and graphic products into a single integrated project that focuses on developing and maintaining/upgrading Web applications and other tools for visualizing, mapping, and using geospatial data. Major accomplishments for FY2014 included several publications, including Part B of an energy resources map that (with Part A) depicts coal, wind, oil, gas, oil shale, uranium, and solar energy production in the WLCI region. Two published works associated with sage-grouse included a Wildlife Monograph on prioritizing species&rsquo; habitats across large landscapes, multiple seasons, and novel areas (using sage-grouse in Wyoming as an example), and a USGS Data Series report that includes both the data used in the habitat-prioritization models and the habitat prioritization models developed for sage-grouse. Our Science Team also published a framework for conducting large, collaborative projects that rely on geospatial data, and a paper that describes the efficacy of fusing satellite data collected at various resolutions for measuring and monitoring vegetation changes. These products are all invaluable tools for maximizing the efficiency and effectiveness of managing species of concern, conducting future landscape-scale assessments, and monitoring status and trends of landscape conditions. Other highlights of FY2014 included a renewed effort to gather and analyze wildlife and habitat status and trend data for the WLCI Interagency Monitoring Database (IAMD) to assess long-term trends and cumulative effects associated with land-use and climate changes. Water-monitoring efforts included drilling four new groundwater-monitoring wells in the Green and New Fork River basins near the proposed Normally Pressured Lance Formation energy development, and continued data collection at established water-monitoring sites. Three additional wells were sampled as part of the Wyoming Groundwater Monitoring Network, bringing the total to 19 Network wells sampled in the WLCI region since 2010. Combined, these water-monitoring efforts can help to identify potential changes in water quality or levels that may result from land-use changes. Major terrestrial monitoring accomplishments included processing satellite imagery from 1985&minus;2010 to develop a historical perspective of long-term vegetation changes, which can serve as a basis for monitoring current and future trends in sagebrush steppe. Such data are crucial tools for agencies tasked with sage-grouse management and conservation. The USGS WLCI Science Team also continued monitoring and testing methods for evaluating WLCI habitat treatments designed to promote aspen regeneration and enhance sage-grouse habitat, and to assess how those treatments influence invasive species distributions and ungulate herbivory. Highlights included analyzing field data collected to elucidate the relationships between sage-grouse habitat use and the proximity of energy infrastructure, and using new instruments to measure productivity responses of aspen woodlands to various factors. Numerous FY2014 accomplishments specifically addressed agency needs to manage and conserve Wyoming&rsquo;s wildlife species of concern. A pygmy rabbit habitat model and Wyoming distribution map were completed to identify factors associated with rabbit habitat occupancy. Previous work on sage-grouse population dynamics was expanded to better understand the factors that drive long-term viability of sage-grouse populations and to develop a tool that helps to identify key factors limiting sage-grouse persistence in Wyoming. Field work and data analyses continued for elucidating the relationships between sagebrush songbird abundance and productivity, the intensity of energy development, and community dynamics of nest predators. For the mule deer study, mixed mountain shrublands important to migrating and wintering mule deer were mapped and delivered to WLCI partners. Additionally, the relationships between energy development and crucial winter habitat for mule deer were evaluated, and a new phase of work was implemented to better understand relationships between plant phenology and mule deer migration movements. Finally, initial analyses of data collected to evaluate fish-community composition in relation to habitat quality indicate that water quality, as measured by concentrations of hydrocarbons, water temperature, and others parameters, has been diminished in subwatersheds with higher levels of energy development. Overall, the outcomes and products of these wildlife studies contribute significantly to the information and tools needed for addressing effects of land-use changes on Wyoming&rsquo;s species of concern. Finally, capabilities of the WLCI Web site and the USGS ScienceBase infrastructure were maintained and upgraded to help ensure access to and efficient use of all the WLCI data, products, assessment tools, and outreach materials that have been developed. Of particular note is the completion of three Web applications developed for mapping (1) the 1900&minus;2008 progression of oil and gas development;(2) the predicted distributions of Wyoming&rsquo;s Species of Greatest Conservation Need; and (3) the locations of coal and wind energy production, sage-grouse distribution and core management areas, and alternative routes for transmission lines within the WLCI region. Collectively, these applications tools provide WLCI planners and managers with powerful tools for better understanding the distributions of wildlife species and potential alternatives for energy development.

Wyoming↗

Comparison of age distributions estimated from environmental tracers by using binary-dilution and numerical models of fractured and folded karst: Shenandoah Valley of Virginia and West Virginia, USA

Measured concentrations of environmental tracers in spring discharge from a karst aquifer in the Shenandoah Valley, USA, were used to refine a numerical groundwater flow model. The karst aquifer is folded and faulted carbonate bedrock dominated by diffuse flow along fractures. The numerical model represented bedrock structure and discrete features (fault zones and springs). Concentrations of 3 H, 3 He, 4 He, and CFC-113 in spring discharge were interpreted as binary dilutions of young (0–8 years) water and old (tracer-free) water. Simulated mixtures of groundwater are derived from young water flowing along shallow paths, with the addition of old water flowing along deeper paths through the model domain that discharge to springs along fault zones. The simulated median age of young water discharged from springs (5.7 years) is slightly older than the median age estimated from 3 H/ 3 He data (4.4 years). The numerical model predicted a fraction of old water in spring discharge (0.07) that was half that determined by the binary-dilution model using the 3 H/ 3 He apparent age and 3 H and CFC-113 data (0.14). This difference suggests that faults and lineaments are more numerous or extensive than those mapped and included in the numerical model.

Virginia;West Virginia↗

Bayesian hierarchical modeling for probabilistic estimation of tsunami amplitude from far-field earthquake sources

Evaluation of tsunami disaster risk for a coastal region requires reliable estimation of tsunami hazard, for example, wave amplitude close to the shore. Observed tsunami data are scarce and have poor spatial coverage, and for this reason probabilistic tsunami hazard analysis (PTHA) traditionally relies on numerical simulation of “synthetic” tsunami generation and propagation toward the coast. Such an approach has been extensively studied in the past and it is widely recognized as an important disaster-risk mitigation tool. PTHA can not only provide less uncertain and spatially coherent hazard estimates in comparison with classical empirical data analysis which is restricted at the tide gauge stations, but also local inundation information. In this paper, we explore a purely statistical alternative to traditional PTHA for evaluation of tsunami amplitude hazard. Here, we use tide gauge measurements of tsunami amplitude along the western United States, specifically California and Oregon, and develop a spatial Bayesian hierarchical model (BHM) to assess tsunami hazard from far-field earthquake sources at various recurrence intervals. The configuration of our model incorporates latent Gaussian fields that utilize information on the distance between tide gauges as well as on the continental shelf width, that is, a covariate linked to potential dissipative effects on wave energy as the tsunami travels over shallow water. Through our BHM, we produce spatially continuous probabilistic maps of far-field tsunami hazard which can aid comprehensive tsunami disaster risk reduction and management.

California, Oregon, Washington↗