SEARCH · USGS Science

Results for “Remote Sensing Information”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 811 records · Page 45Linked to original sources

USGS2015

EAARL-B coastal topography: Chandeleur Islands, Louisiana, 2012: seamless (bare earth and submerged)

These remotely sensed, geographically referenced elevation measurements of light detection and ranging ( lidar )-derived seamless (bare-earth and submerged) topography datasets were produced by the U.S. Geological Survey ( USGS ), St . Petersburg Coastal and Marine Science Center, St . Petersburg, Florida. This project provides datasets acquired on August 7 and 8, 2012, for a portion of the Chandeleur Islands, Louisiana. An innovative airborne lidar system, known as the second-generation Experimental Advanced Airborne Research Lidar ( EAARL -B), was used during data acquisition. The EAARL -B system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometers) lidar designed to map nearshore bathymetry, topography, and vegetation structure simultaneously. For more information about similar projects, please visit the Lidar for Science and Resource Management Web site.

Louisiana↗

USGS2022

Multi-species amphibian monitoring across a protected landscape: Critical reflections on 15 years of wetland monitoring in Grand Teton and Yellowstone national parks

Widespread amphibian declines were well documented at the end of the 20th century, raising concerns about the need to identify individual and interactive contributors to this global trend. At the same time, there was growing interest in the use of amphibians as ecological indicators. In the United States, wetland and amphibian monitoring programs were launched in some national parks as a necessary first step to evaluating the status and trends of amphibian populations within some of North America’s most protected areas. In Grand Teton and Yellowstone national parks, a multi-species amphibian monitoring program was launched by many of the authors in 2006 and continues to this day. This Viewpoint Article serves as a self-evaluation of our journey from conception through implementation of an ongoing, long-term monitoring program. This self-evaluation should provide a framework and guidance for other monitoring programs. We address whether we are fulfilling the program’s main objective of describing status and trends of the four amphibian species, discuss how a one-size-fits-all monitoring approach does not serve all species equally, and describe opportunities to bolster our core work using emerging statistical approaches and thoughtful integration of remote sensing and molecular tools. We also describe how the data generated over the program’s first 15 years have been useful beyond our initial goal of characterizing status and trend. Notably, our integration of climate datasets has allowed us to describe wetland and species-specific amphibian responses to variations in climate drivers. Documenting climate links to amphibian occurrence and their primary habitats has allowed us to identify which species, habitat types, and subregions within this large, protected landscape are most vulnerable to anticipated climate change. Recognizing that tools and threats change over time, it will be important to adapt our original monitoring design to maximize opportunities and use of resulting information. Maintaining engagement by multiple stakeholders and expanding our funding portfolio will also be necessary to sustain our program into the future. Finally, collaboration has become standard for long-term, cross-jurisdictional, landscape-scale monitoring. We argue that collaborative monitoring facilitates resource sharing, leveraging of limited funds, completion of work, and mutual learning. Such collaboration also increases the efficacy of conservation.

Wyoming↗

USGS1991

Comparison of three different methods to merge multiresolution and multispectral data: Landsat TM and SPOT panchromatic

The merging of multisensor image data is becoming a widely used procedure because of the complementary nature of various data sets. Ideally, the method used to merge data sets with high-spatial and high-spectral resolution should not distort the spectral characteristics of the high-spectral resolution data. This paper compares the results of three different methods used to merge the information contents of the Landsat Thematic Mapper (TM) and Satellite Pour l'Observation de la Terre (SPOT) panchromatic data. The comparison is based on spectral characteristics and is made using statistical, visual, and graphical analyses of the results. The three methods used to merge the information contents of the Landsat TM and SPOT panchromatic data were the Hue-Intensity-Saturation (HIS), Principal Component Analysis (PCA), and High-Pass Filter (HPF) procedures. The HIS method distorted the spectral characteristics of the data the most. The HPF method distorted the spectral characteristics the least; the distortions were minimal and difficult to detect. -Authors

Photogrammetric Engineering and Remote Sensing↗

USGS2021

Testing a generalizable machine learning workflow for aquatic invasive species on Rainbow Trout (Oncorhynchus mykiss) in northwest Montana

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Alberta, British Columbia, Montana↗

USGS2005

Estimating stand structure using discrete-return lidar: an example from low density, fire prone ponderosa pine forests

The ponderosa pine forests of the Colorado Front Range, USA, have historically been subjected to wildfires. Recent large burns have increased public interest in fire behavior and effects, and scientific interest in the carbon consequences of wildfires. Remote sensing techniques can provide spatially explicit estimates of stand structural characteristics. Some of these characteristics can be used as inputs to fire behavior models, increasing our understanding of the effect of fuels on fire behavior. Others provide estimates of carbon stocks, allowing us to quantify the carbon consequences of fire. Our objective was to use discrete-return lidar to estimate such variables, including stand height, total aboveground biomass, foliage biomass, basal area, tree density, canopy base height and canopy bulk density. We developed 39 metrics from the lidar data, and used them in limited combinations in regression models, which we fit to field estimates of the stand structural variables. We used an information–theoretic approach to select the best model for each variable, and to select the subset of lidar metrics with most predictive potential. Observed versus predicted values of stand structure variables were highly correlated, with r 2 ranging from 57% to 87%. The most parsimonious linear models for the biomass structure variables, based on a restricted dataset, explained between 35% and 58% of the observed variability. Our results provide us with useful estimates of stand height, total aboveground biomass, foliage biomass and basal area. There is promise for using this sensor to estimate tree density, canopy base height and canopy bulk density, though more research is needed to generate robust relationships. We selected 14 lidar metrics that showed the most potential as predictors of stand structure. We suggest that the focus of future lidar studies should broaden to include low density forests, particularly systems where the vertical structure of the canopy is important, such as fire prone forests.

Colorado↗

USGS2011

Tracking change over time

Landsat satellites capture images of Earth from space-and have since 1972! These images provide a long-term record of natural and human-induced changes on the global landscape. Comparing images from multiple years reveals slow and subtle changes as well as rapid and devastating ones. Landsat images are available over the Internet at no charge. Using the free software MultiSpec, students can track changes to the landscape over time-just like remote sensing scientists do! The objective of the Tracking Change Over Time lesson plan is to get students excited about studying the changing Earth. Intended for students in grades 5-8, the lesson plan is flexible and may be used as a student self-guided tutorial or as a teacher-led class lesson. Enhance students' learning of geography, map reading, earth science, and problem solving by seeing landscape changes from space.

General Information Product↗

USGS2021

Piping plovers demonstrate regional differences in nesting habitat selection patterns along the U.S. Atlantic coast

Habitat studies that encompass a large portion of a species’ geographic distribution can explain characteristics that are either consistent or variable, further informing inference from more localized studies and improving management successes throughout the range. We identified landscape characteristics at Piping Plover nests at 21 sites distributed from Massachusetts to North Carolina and compared habitat selection patterns among the three designated U.S. recovery units (New England, New York–New Jersey, and Southern). Geomorphic setting, substrate type, and vegetation type and density were determined in situ at 928 Piping Plover nests (hereafter, used resource units) and 641 random points (available resource units). Elevation, beach width, Euclidean distance to ocean shoreline, and least-cost path distance to low-energy shorelines with moist substrates (commonly used as foraging habitat) were associated with used and available resource units using remotely sensed spatial data. We evaluated multivariate differences in habitat selection patterns by comparing recovery unit-specific Bayesian networks. We then further explored individual variables that drove disparities among Bayesian networks using resource selection ratios for categorical variables and Welch’s unequal variances t-tests for continuous variables. We found that relationships among variables and their connections to habitat selection were similar among recovery units, as seen in commonalities in Bayesian network structures. Furthermore, nesting Piping Plovers consistently selected mixed sand and shell, gravel, or cobble substrates as well as areas with sparse or no vegetation, irrespective of recovery unit. However, we observed significant differences among recovery units in the elevations, distances to ocean, and distances to low-energy shorelines of used resource units. Birds also exhibited increased selectivity for overwash habitats and for areas with access to low-energy shorelines along a latitudinal gradient from north to south. These results have important implications for conservation and management, including assessment of shoreline stabilization and habitat restoration planning as well as forecasting effects of climate change.

Connecticut, Delaware, Maryland, Massachusetts, ne↗

USGS2009

Erosional history of Cape Halkett and contemporary monitoring of bluff retreat, Beaufort Sea coast, Alaska

Cape Halkett is located along the Beaufort Sea at the end of a low-lying tundra landscape. The area has been subject to major modifications over the last century as a result of erosion and migration of the coastline inland. Long-term mean annual erosion rates (1955-2009) for the entire cape are 7.6 m/yr, with a gradual increase in rates over the first five time periods of remotely sensed imagery analyzed and a large increase during the most recent time period. Division of the cape into three distinct coastal zones shows very different erosional patterns: the northeast-facing segment (Zone 1) showing a consistent and large increase; the southeast-facing segment (Zone 3) showing a gradual increase with recent, heightened erosion rates; and the east-facing segment (Zone 2) showing decreased rates due to the reformation of a sand and gravel spit. Monitoring of bluff erosion with time-lapse photography, differential GPS surveys, terrestrial and bathymetric surveys, and water level, sea and permafrost temperature data provide insights into the processes driving contemporary patterns of erosion and will provide valuable information for the prediction of future shoreline positions.

Alaska↗

USGS2025

Mapping ecological states in the upper Colorado River basin: Implications for fire management

Spatially explicit information on ecosystem dynamics that offers a mechanistic understanding of ecological processes can benefit environmental management. Broad-scale maps based on state-and-transition models provide valuable insight into transitions among ecological states resulting from specific drivers within areas sharing similar climatic and edaphic characteristics ecological sites (ES). We aimed to quantify ecological dynamics of two ES groups in the Upper Colorado River Basin from 1986 to 2022 through annual maps of ecological states and assess potential drivers of observed state change. This region comprises important sagebrush shrublands and pinyon-juniper woodlands affected by non-native annual grass invasion, wildfires, and drought-induced tree mortality. Using field-based and remote sensing data, we modeled vegetation states using random forest models and mapped the states annually from 1986 to 2022. To demonstrate the utility of the state maps for monitoring and management, we used this time series of maps to investigate the influences of fire and drought on state occurrence. Our findings revealed a statistically significant increase in states invaded by non-native annual species (Invaded state), which replaced Grassland and Shrubland states, while Shrubland states decreased significantly, transitioning to invaded and Woodland states. Invaded states had the highest likelihood of burning, followed by Woodlands. Drought was associated with increased area of Grassland and Bare states, but with decreased area of invaded and Shrubland states. These results indicate an accelerating fire cycle is potentially leading to ongoing regional environmental degradation. Despite increasing drought conditions during the study period, the invaded states continued to increase in area, indicating additional underlying mechanisms. Our reproducible, broad-scale, ecologically-driven state mapping process enhances understanding of how drought, fire, and invasion by non-native plants can transform semiarid landscapes of the western USA.

Arizona, Colorado, New Mexico, Utah, Wyoming↗

USGS2015

Integrating multiple distribution models to guide conservation efforts of an endangered toad

Species distribution models are used for numerous purposes such as predicting changes in species’ ranges and identifying biodiversity hotspots. Although implications of distribution models for conservation are often implicit, few studies use these tools explicitly to inform conservation efforts. Herein, we illustrate how multiple distribution models developed using distinct sets of environmental variables can be integrated to aid in identification sites for use in conservation. We focus on the endangered arroyo toad ( Anaxyrus californicus ), which relies on open, sandy streams and surrounding floodplains in southern California, USA, and northern Baja California, Mexico. Declines of the species are largely attributed to habitat degradation associated with vegetation encroachment, invasive predators, and altered hydrologic regimes. We had three main goals: 1) develop a model of potential habitat for arroyo toads, based on long-term environmental variables and all available locality data; 2) develop a model of the species’ current habitat by incorporating recent remotely-sensed variables and only using recent locality data; and 3) integrate results of both models to identify sites that may be employed in conservation efforts. We used a machine learning technique, Random Forests, to develop the models, focused on riparian zones in southern California. We identified 14.37% and 10.50% of our study area as potential and current habitat for the arroyo toad, respectively. Generally, inclusion of remotely-sensed variables reduced modeled suitability of sites, thus many areas modeled as potential habitat were not modeled as current habitat. We propose such sites could be made suitable for arroyo toads through active management, increasing current habitat by up to 67.02%. Our general approach can be employed to guide conservation efforts of virtually any species with sufficient data necessary to develop appropriate distribution models.

California↗

USGS2010

Landsat Thematic Mapper Image Mosaic of Colorado

The U.S. Geological Survey (USGS) Rocky Mountain Geographic Science Center (RMGSC) produced a seamless, cloud-minimized remotely-sensed image spanning the State of Colorado. Multiple orthorectified Landsat 5 Thematic Mapper (TM) scenes collected during 2006-2008 were spectrally normalized via reflectance transformation and linear regression based upon pseudo-invariant features (PIFS) following the removal of clouds. Individual Landsat scenes were then mosaicked to form a six-band image composite spanning the visible to shortwave infrared spectrum. This image mosaic, presented here, will also be used to create a conifer health classification for Colorado in Scientific Investigations Map 3103. An archive of past and current Landsat imagery exists and is available to the scientific community (http://glovis.usgs.gov/), but significant pre-processing was required to produce a statewide mosaic from this information. Much of the data contained perennial cloud cover that complicated analysis and classification efforts. Existing Landsat mosaic products, typically three band image composites, did not include the full suite of multispectral information necessary to produce this assessment, and were derived using data collected in 2001 or earlier. A six-band image mosaic covering Colorado was produced. This mosaic includes blue (band 1), green (band 2), red (band 3), near infrared (band 4), and shortwave infrared information (bands 5 and 7). The image composite shown here displays three of the Landsat bands (7, 4, and 2), which are sensitive to the shortwave infrared, near infrared, and green ranges of the electromagnetic spectrum. Vegetation appears green in this image, while water looks black, and unforested areas appear pink. The lines that may be visible in the on-screen version of the PDF are an artifact of the export methods used to create this file. The file should be viewed at 150 percent zoom or greater for optimum viewing.

Scientific Investigations Map↗

USGS1978

Metropolitan land cover inventory using multiseasonal Landsat data

As a part of the Pacific Northwest Land Resources Inventory Demonstration Project (PNLRIDP), planners from State, regional, and local agencies in Oregon are working with scientists from the EROS Data Center (USGS), Ames Research Center (NASA), and the Jet Propulsion Laboratory (California Institute of Technology) to obtain practical training and experience in the analysis of remotely sensed data collected from air and spacecraft. A 4,000 km2 area centered on metropolitan Portland was chosen as the demonstration site, and a four-date Landsat temporal overlay was created which contained January, April, July, and October data collected in 1973. Digital multispectral analysis of single dates and two-date combinations revealed that the spring-summer and summer-fall combinations were the most satisfactory for land cover inventory. Residential, commercial and industrial, improved open space, water, forested, and agriculture land cover categories were obtained consistently in the majority of classification iterations. Census tract and traffic zone boundaries were digitized and registered with the Landsat data to facilitate integration of the land cover information with socioeconomic and environmental data already available to Oregon planners.

Open-File Report↗

USGS2013

Landsat surface reflectance quality assurance extraction (version 1.7)

The U.S. Geological Survey (USGS) Land Remote Sensing Program is developing an operational capability to produce Climate Data Records (CDRs) and Essential Climate Variables (ECVs) from the Landsat Archive to support a wide variety of science and resource management activities from regional to global scale. The USGS Earth Resources Observation and Science (EROS) Center is charged with prototyping systems and software to generate these high-level data products. Various USGS Geographic Science Centers are charged with particular ECV algorithm development and (or) selection as well as the evaluation and application demonstration of various USGS CDRs and ECVs. Because it is a foundation for many other ECVs, the first CDR in development is the Landsat Surface Reflectance Product (LSRP). The LSRP incorporates data quality information in a bit-packed structure that is not readily accessible without postprocessing services performed by the user. This document describes two general methods of LSRP quality-data extraction for use in image processing systems. Helpful hints for the installation and use of software originally developed for manipulation of Hierarchical Data Format (HDF) produced through the National Aeronautics and Space Administration (NASA) Earth Observing System are first provided for users who wish to extract quality data into separate HDF files. Next, steps follow to incorporate these extracted data into an image processing system. Finally, an alternative example is illustrated in which the data are extracted within a particular image processing system.

Techniques and Methods↗

USGS1984

REMOTE SENSING IN NORTHERN ARIZONA: S. P. CINDER CONE AND LAVA FLOW.

The objective of this poster paper is to present a site-specific atlas showing a wide variety of remote sensing data sets collected for the area of S. P. Mountain and lava flow (basaltic-andesite) in north-central Arizona. The data set to be displayed includes a number of radar images, representing three wavelength regions (1-, 3- and 25-cm), multiple incidence angles, look directions, and polarization combinations, in addition to thermal infrared scanner imagery, multispectral scanner imagery, aerial and ground photography, micro- and macro topography, and four-frequency, multipolarization radar scatterometer spectra. The expression of different surface units on the S. P. lava flow are effectively displayed on the ERIM four-channel images by the registration and combination of the four bands. Multi-color imagery of band combinations demonstrate the information content of multi-channel SAR imagery as well as the suitability of extending data manipulation methods developed for Landsat data to SAR data.

Conference Paper↗

USGS2021

Urbanization impacts on evapotranspiration across various spatio-temporal scales

Urbanization has been shown to locally increase the nighttime temperatures creating urban heat islands, which partly arise due to evapotranspiration (ET) reduction. It is unclear how the direction and magnitude of the change in local ET due to urbanization varies globally across different climatic regimes. This knowledge gap is critical, both for the key role of ET in the energy and water balance accounting for the majority of local precipitation, and for reducing the urban heat island effect. We explore and assess the impacts of urbanization on monthly and mean annual ET across a range of landscapes from local to global spatial scales. Remotely sensed land cover and ET available at 1 km resolution are used to quantify the differences in ET between urban and surrounding non-urban areas across the globe. The observed patterns show that the statistically significant difference between urban and non-urban ET can be estimated to first order as a function of local hydroclimate, with arid regions seeing increased ET, and humid regions showing decreased ET. Cities under cold climates also evaporate more than their non-urban surroundings during the winter, as the urban micro-climate has increased energy availability resulting from human activities. Increased ET in arid cities arises from municipal water withdrawals and increased irrigation during drought conditions. These results can help inform planners to improve the integration of environmental conditions into the design and management of urban landscapes.

Earth's Future↗

USGS2021

Managed aquifer recharge suitability—Regional screening and case studies in Jordan and Lebanon

The U.S. Geological Survey, at the request of the U.S. Agency for International Development, led a 5-year regional project to develop and apply methods for water availability and suitability mapping for managed aquifer recharge (MAR) in the Middle East and North Africa region. A regional model of surface runoff for the period from 1984 to 2015 was developed to characterize water availability using remote sensing data on climate, vegetation, and topography in Jordan, Lebanon, and surrounding areas. Surface runoff was accumulated to characterize potential streamflow available for MAR and these data were combined with land surface slope to prepare a regional screening map of MAR suitability, illustrating suitability mapping concepts and methods. The application of the methods is demonstrated by the evaluation of water availability and suitability for potential MAR in study areas in Jordan and Lebanon. Locations suitable for MAR are present in both Jordan and Lebanon, but limitations exist in both countries, related primarily to water availability in Jordan and land areas of suitable terrain in Lebanon. An additional feasibility study including field investigations would likely provide decision makers with essential information for further development of the use of MAR in Jordan, Lebanon, and the region.

Open-File Report↗

USGS2015

Spatially explicit spectral analysis of point clouds and geospatial data

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software package PySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python , it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Computers & Geosciences↗

USGS2015

Southern Salish Sea Habitat Map Series: Admiralty Inlet

In 2010 the Environmental Protection Agency, Region 10 initiated the Puget Sound Scientific Studies and Technical Investigations Assistance Program, designed to support research in support of implementing the Puget Sound Action Agenda. The Action Agenda was created in response to Puget Sound having been designated as one of 28 estuaries of national significance under section 320 of the U.S. Clean Water Act, and its overall goal is to restore the Puget Sound Estuary's environment by 2020. The Southern Salish Sea Mapping Project was funded by the Assistance Program request for proposals process, which also supports a large number of coastal-zone- and ocean-management issues. The issues include the recommendations of the Marine Protected Areas Work Group to the Washington State Legislature (Van Cleve and others, 2009), which endorses a Puget Sound and coast-wide marine conservation needs assessment, gap analysis of existing Marine Protected Areas (MPA) and recommendations for action. This publication is the first of four U.S. Geological Survey Scientific Investigation Maps that make up the Southern Salish Sea Mapping Project. The remaining three map blocks to be published in the future, located south of Admiralty Inlet, are shown in figure 1. Puget Sound is a deep, fjord-type estuary covering an area of 2,330 km 2 in the Pacific Northwest region of the United States (fig. 1). It is connected to the ocean by the Strait of Juan de Fuca, a turbulent passage approximately 160 km in length and 22 km wide at its west end, expanding to over 40 km wide at its east end (Thomson, 1994). During the Pleistocene, the area was occupied several times by lobes of continental ice, resulting in a complex basin-fill of glacial and interglacial deposits that are locally as thick as 1100 m (Johnson and others, 2001). The last glaciation, called the Fraser glaciation, began after 28,800±740 14 C yr B.P. when ice started a slow expansion (Clague, 1981). At peak advance the westward Juan de Fuca lobe reached the edge of the continental shelf through the Juan de Fuca Strait shortly before 14,460±200 14 C yr B.P. (Herzer and Bornhold, 1982). The southward Puget lobe advanced to its terminal position in Puget Sound by around 14,150 14 C yr B.P. (Porter and Swanson, 1998). Ice retreated from its maximum to northern Whidbey Island by 13,650±350 14 C yr B.P. (Dethier and others, 1995). Retreating glaciers resulted in a thick sequence of ice-contact, glacial-marine sediment, and early post-glacial sediments (Linden and Schurrer, 1988). These deposits have experienced the effects of a marine transgression followed by regression, resulting in a sea-level several tens of meters lower than the present day (Linden and Schurrer, 1988). A second transgression brought sea level to about the present level by around 5,470±120 14 C yr B.P. (Clague and others, 1982) establishing the present oceanographic and geologic environment Puget Sound is separated into four interconnected basins; Whidbey, Central (Main), Hood Canal, and South (Thomson, 1994). The Whidbey, Central, and Hood Canal basins are the three main branches of the Puget Sound estuary and are separated from the Strait of Juan de Fuca by a double sill at Admiralty Inlet. The Admiralty Inlet map area includes the Inlet and a portion of the Whidbey Basin (fig. 1). The shallower South Basin is separated by a sill at Tacoma Narrows and is highly branched with numerous finger inlets. Flow within Puget Sound is dominated by tidal currents of as much as 1 m/s at Admiralty Inlet, reducing to approximately 0.5 m/s in the Central Basin (Lavelle and others, 1988). The lack of silt and clay-sized sediments in the Admiralty Inlet map area is likely a result of the strong currents (see Ground-Truth Studies for the Admiralty Inlet Map Area, sheet 3). The subtidal component of flow reaches approximately 0.1 m/s and is driven by density gradients arising from the contrast in salty ocean water at the entrance and freshwater inputs from stream flow (Lavelle and others, 1988). The total freshwater input to Puget Sound is approximately 3.4 x 10 6 m 3 /day, primarily from the Skagit River (Cannon, 1983). The subtidal circulation mostly consists of a two-layered flow in the basins with fresher water exiting at the surface and saltier water entering at depth (Ebbesmeyer and Cannon, 2001). In general, surface waters flow north and deeper waters flow south; variations arise from wind effects that can drive a surface current in the same direction as the wind, and a baroclinic response in the lower layer to about 100-m depth (Matsuura and Cannon, 1997). Oceanographic properties are influenced by temporal forcing parameters such as reduced stream flow during the 2000-01 drought that increased surface salinity and decreased differences between surface and bottom waters (Newton and others, 2003). On offshore seismic-reflection profiles, Pleistocene strata (excluding latest Pleistocene glacial and post-glacial deposits) form a distinct seismic unit, bounded below by pre-Tertiary or Tertiary basement and above by typically flat-lying latest Pleistocene to Holocene deposits that fill in erosional or depositional relief (Johnson and others, 2001). Cores from central Puget Sound have accumulation rates that range from 85 to 1200 mg/cm 2 /yr, or 0.12 to 2.4 cm/yr; the highest accumulation rates are near the southern end of central Puget Sound (Carpenter and others, 1985). Carpenter and others (1985) un-weighted arithmetic mean of accumulation rates for central Puget Sound deeper stations is 480±340 (± one standard deviation) mg/cm 2 /yr. Lavelle and others (1985) also found rates as high as 1200 mg/cm 2 /yr over the past approximately 70 years in cores in the Central Basin off of and north and south of Elliott Bay. Puget Sound basin rates are comparable to rates in midshelf silt deposits on the Washington coast north of the Columbia River (Nittrouer and others, 1979). The deep subtidal (in other words, below SCUBA depths) habitats of Puget Sound are relatively poorly known. A few subtidal surveys exist for several habitat types from the 1960s and 1970s (reviewed in Dethier, 1990), using grab and box core data. The Dethier (1990) review divides habitat up into Coast and Marine Ecological Classification Standard (CMECS) substrate, water column energy, and depth zones but does not attempt to map these habitats, rather it is an inventory of habitats found in the area and the flora and fauna associated with each habitat. The approach of the Southern Salish Sea Mapping project is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data (the undersea equivalent of satellite remote-sensing data in terrestrial mapping), acoustic backscatter, seafloor video, seafloor photography, and bottom-sediment sampling data. This approach is based in part on methods presented and data collection and product needs identified at the Washington State Seafloor Mapping Workshop (Washington State Seafloor Mapping Workshop Steering Committee, 2008), attended by coastal and marine managers and scientists. The map products display seafloor geomorphology and substrate, and identify potential marine benthic habitats. It is emphasized that the more interpretive habitat and geology maps rely on the integration of multiple, new high-resolution datasets and that mapping at small scales would not be possible without such data. Oceanographic current and wave data is not included in this analysis, however, the accompanying geographic information system (GIS) data set is designed and intended to be combined with oceanographic and biologic data sets assembled by others in the future and some of the GIS data has already been incorporated in the unpublished Nature Conservancy Benthic Habitats of Puget Sound database. This publication includes four map sheets, explanatory text, and a descriptive pamphlet. Each map sheet is published as a portable document format (PDF) file. ESRI ArcGIS compatible geotiffs (for example, bathymetry) and shapefiles (for example video observation points) will be available for download in the data catalog associated with this publication (Cochrane, 2015). An ArcGIS Project File with the symbology used to generate the map sheets is also provided. For those who do not own the full suite of ESRI GIS and mapping software, the data can be read using ESRI ArcReader, a free viewer that is available at http://www.esri.com/software/arcgis/arcreader/index.html .

Washington↗