Geology topics

Sandra K. Poppenga

Publications and source records attributed to Sandra K. Poppenga.

15 recordsLinked to original sources

USGS2021

A comparison of Landsat 8 Operational Land Imager and Provisional Aquatic Reflectance science product, Sentinel–2B, and WorldView–3 imagery for empirical satellite-derived bathymetry, Unalakleet, Alaska

Satellite-derived bathymetry (SDB) based upon an empirical band ratio method is a cost-effective means for mapping nearshore bathymetry in coastal areas vulnerable to natural hazards. This is particularly important for the low-lying coastal community of Unalakleet, Alaska, that has been negatively affected not only by flooding, storm surge, and historically strong storms but also by high erosion rates stemming from the Unalakleet River and Norton Sound. The purpose of this study was to assess the viability of different satellite imagery, including Landsat 8 (L8) Operational Land Imager, Sentinel–2B, WorldView–3, and L8 Provisional Aquatic Reflectance science product, for deriving SDB for Unalakleet, Alaska. Correlations were performed between satellite imagery band ratios and topobathymetric (topobathy) light detection and ranging (lidar) and in situ single-beam sound navigation and ranging (sonar). The satellite imagery correlations with topobathy lidar did not yield as high of a linear relation with water depths as the satellite imagery correlations with the single-beam sonar. An extinction depth, where light no longer attenuates through the water column, was not identified because of the shallow depths within the topobathy lidar and single-beam sonar datasets. Although some single-beam soundings measured at 7 meters deep, the correlations with the SDB band ratios did not yield a strong linear relation. Satellite imagery band ratio correlations with Electronic Navigational Chart soundings did not yield a strong linear relation because of older source data. Less than optimal linear regressions were most likely due to the geography of Unalakleet, Alaska, a low-lying coastal community subject to high erosion rates from surrounding waters. This study is one of the first attempts to compare different satellite imagery band ratio correlations with topobathy lidar and in situ sonar to assess the viability for nearshore SDB for coastal Unalakleet, Alaska.

Alaska↗

USGS2018

Coastal National Elevation Database

The Coastal National Elevation Database (CoNED) Applications Project develops enhanced topographic (land elevation) and bathymetric (water depth) datasets that serve as valuable resources for coastal hazards research (Danielson and others, 2016; Thatcher and others, 2016). These datasets are used widely for mapping inundation zones from riverine flood events, hurricanes, and sea-level rise and for other Earth science applications, such as sediment transport, erosion, and storm impact models. CoNED is a U.S. Geological Survey (USGS) Coastal-Marine Hazards and Resources Program (formerly Coastal and Marine Geology Program) activity centered at the USGS Earth Resources Observation and Science Center and distributed at other USGS Science Centers. As part of the vision for a 3D Nation, the CoNED Project is working collaboratively with the USGS National Geospatial Program, the National Oceanic and Atmospheric Administration, and the U.S. Army Corps of Engineers through the Interagency Working Group on Ocean and Coastal Mapping to build integrated elevation models in the coastal zone by assimilating the land surface topography with littoral zone and continental shelf bathymetry. Several nongovernmental organizations and Federal agencies, including the Department of the Interior Pacific Islands Climate Adaptation Science Center, the National Park Service, the Nature Conservancy, the Louisiana Coastal Protection and Restoration Authority, and numerous academic institutions, partner to make CoNED a success.

Fact Sheet↗

USGS2018

Evaluating the potential for near-shore bathymetry on the Majuro Atoll, Republic of the Marshall Islands, using Landsat 8 and WorldView-3 imagery

Satellite-derived near-shore bathymetry (SDB) is becoming an increasingly important method for assessing vulnerability to climate change and natural hazards in low-lying atolls of the northern tropical Pacific Ocean. Satellite imagery has become a cost-effective means for mapping near-shore bathymetry because ships cannot collect soundings safely while operating close to the shore. Also, green laser light detection and ranging (lidar) acquisitions are expensive in remote locations. Previous research has demonstrated that spectral band ratio-based techniques, commonly called the natural logarithm approach, may lead to more precise measurements and modeling of bathymetry because of the phenomenon that different substrates at the same depth have approximately equal ratio values. The goal of this research was to apply the band ratio technique to Landsat 8 at-sensor radiance imagery and WorldView-3 atmospherically corrected imagery in the coastal waters surrounding the Majuro Atoll, Republic of the Marshall Islands, to derive near-shore bathymetry that could be incorporated into a seamless topobathymetric digital elevation model of Majuro. Attenuation of light within the water column was characterized by measuring at-sensor radiance and reflectance at different depths and calculating an attenuation coefficient. Bathymetric lidar data, collected by the U.S. Naval Oceanographic Office in 2006, were used to calibrate the SDB results. The bathymetric lidar yielded a strong linear relation with water depths. The Landsat 8-derived SDB estimates derived from the blue/green band ratio exhibited a water attenuation extinction depth of 6 meters with a coefficient of determination R 2 =0.9324. Estimates derived from the coastal/red band ratio had an R 2 =0.9597. At the same extinction depth, SDB estimates derived from WorldView-3 imagery exhibited an R 2 =0.9574. Because highly dynamic coastal shorelines can be affected by erosion, wetland loss, hurricanes, sea-level rise, urban development, and population growth, consistent bathymetric data are needed to better understand sensitive coastal land/water interfaces in areas subject to coastal disasters.

Majuro Atoll↗

USGS2018

One-meter topobathymetric digital elevation model for Majuro Atoll, Republic of the Marshall Islands, 1944 to 2016

Atoll and island coastal communities are highly exposed to sea-level rise, tsunamis, storm surges, rogue waves, king tides, and the occasional combination of multiple factors, such as high regional sea levels, extreme high local tides, and unusually strong wave set-up. The elevation of most of these atolls averages just under 3 meters (m), with many areas roughly at sea level. The lack of high-resolution topographic data has been identified as a critical data gap for hazard vulnerability and adaptation efforts and for high-resolution inundation modeling for atoll nations. Modern topographic survey equipment and airborne lidar surveys can be very difficult and costly to deploy. Therefore, unmanned aircraft systems (UAS) were investigated for collecting overlapping imagery to generate topographic digital elevation models (DEMs). Medium- and high-resolution satellite imagery (Landsat 8 and WorldView-3) was investigated to derive nearshore bathymetry. The Republic of the Marshall Islands is associated with the United States through a Compact of Free Association, and Majuro Atoll is home to the capital city of Majuro and the largest population of the Republic of the Marshall Islands. The only elevation datasets currently available for the entire Majuro Atoll are the Shuttle Radar Topography Mission and the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model Version 2 elevation data, which have a 30-m grid-cell spacing and a 8-m vertical root mean square error (RMSE). Both these datasets have inadequate spatial resolution and vertical accuracy for inundation modeling. The final topobathymetric DEM (TBDEM) developed for Majuro Atoll is derived from various data sources including charts, soundings, acoustic sonar, and UAS and satellite imagery spanning over 70 years of data collection (1944 to 2016) on different sections of the atoll. The RMSE of the TBDEM over the land area is 0.197 m using over 70,000 Global Navigation Satellite System real-time kinematic survey points for validation, and 1.066 m for Landsat 8 and 1.112 m for WorldView-3 derived bathymetry using over 16,000 and 9,000 lidar bathymetry points, respectively.

Majuro Atoll↗

USGS2016

Creating a Coastal National Elevation Database (CoNED) for science and conservation applications

The U.S. Geological Survey is creating the Coastal National Elevation Database, an expanding set of topobathymetric elevation models that extend seamlessly across coastal regions of high societal or ecological significance in the United States that are undergoing rapid change or are threatened by inundation hazards. Topobathymetric elevation models are raster datasets useful for inundation prediction and other earth science applications, such as the development of sediment-transport and storm surge models. These topobathymetric elevation models are being constructed by the broad regional assimilation of numerous topographic and bathymetric datasets, and are intended to fulfill the pressing needs of decision makers establishing policies for hazard mitigation and emergency preparedness, coastal managers tasked with coastal planning compatible with predictions of inundation due to sea-level rise, and scientists investigating processes of coastal geomorphic change. A key priority of this coastal elevation mapping effort is to foster collaborative lidar acquisitions that meet the standards of the USGS National Geospatial Program's 3D Elevation Program, a nationwide initiative to systematically collect high-quality elevation data. The focus regions are located in highly dynamic environments, for example in areas subject to shoreline change, rapid wetland loss, hurricane impacts such as overwash and wave scouring, and/or human-induced changes to coastal topography.

Journal of Coastal Research↗

USGS2016

Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database

During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastalinundation flooding from disastrous events. Because physical processes in coastal environments are controlled by the geomorphology of over-the-land topography and underwater bathymetry, many applications of geospatial data in coastal environments require detailed knowledge of the near-shore topography and bathymetry. In this paper, an updated methodology used by the U.S. Geological Survey Coastal National Elevation Database (CoNED) Applications Project is presented for developing coastal topobathymetric elevation models (TBDEMs) from multiple topographic data sources with adjacent intertidal topobathymetric and offshore bathymetric sources to generate seamlessly integrated TBDEMs. This repeatable, updatable, and logically consistent methodology assimilates topographic data (land elevation) and bathymetry (water depth) into a seamless coastal elevation model. Within the overarching framework, vertical datum transformations are standardized in a workflow that interweaves spatially consistent interpolation (gridding) techniques with a land/water boundary mask delineation approach. Output gridded raster TBDEMs are stacked into a file storage system of mosaic datasets within an Esri ArcGIS geodatabase for efficient updating while maintaining current and updated spatially referenced metadata. Topobathymetric data provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, and tsunami impact assessment. These detailed coastal elevation data are critical to depict regions prone to climate change impacts and are essential to planners and managers responsible for mitigating the associated risks and costs to both human communities and ecosystems. The CoNED methodology approach has been used to construct integrated TBDEM models in Mobile Bay, the northern Gulf of Mexico, San Francisco Bay, the Hurricane Sandy region, and southern California.

Journal of Coastal Research↗

USGS2016

Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Journal of Coastal Research↗

USGS2015

Evaluation of airborne lidar elevation surfaces for propagation of coastal inundation: the importance of hydrologic connectivity

Detailed information about coastal inundation is vital to understanding dynamic and populated areas that are impacted by storm surge and flooding. To understand these natural hazard risks, lidar elevation surfaces are frequently used to model inundation in coastal areas. A single-value surface method is sometimes used to inundate areas in lidar elevation surfaces that are below a specified elevation value. However, such an approach does not take into consideration hydrologic connectivity between elevation grids cells resulting in inland areas that should be hydrologically connected to the ocean, but are not. Because inland areas that should drain to the ocean are hydrologically disconnected by raised features in a lidar elevation surface, simply raising the water level to propagate coastal inundation will lead to inundation uncertainties. We took advantage of this problem to identify hydrologically disconnected inland areas to point out that they should be considered for coastal inundation, and that a lidar-based hydrologic surface should be developed with hydrologic connectivity prior to inundation analysis. The process of achieving hydrologic connectivity with hydrologic-enforcement is not new, however, the application of hydrologically-enforced lidar elevation surfaces for improved coastal inundation mapping as approached in this research is innovative. In this article, we propagated a high-resolution lidar elevation surface in coastal Staten Island, New York to demonstrate that inland areas lacking hydrologic connectivity to the ocean could potentially be included in inundation delineations. For inland areas that were hydrologically disconnected, we evaluated if drainage to the ocean was evident, and calculated an area exceeding 11 ha (~0.11 km 2 ) that could be considered in inundation delineations. We also assessed land cover for each inland area to determine the type of physical surfaces that would be potentially impacted if the inland areas were considered as part of a coastal inundation. A visual analysis indicated that developed, medium intensity and palustrine forested wetland land cover types would be impacted for those locations. This article demonstrates that hydrologic connectivity is an important factor to consider when inundating a lidar elevation surface. This information is needed for inundation monitoring and management in sensitive coastal regions.

Remote Sensing↗

USGS2014

Hydrologic enforcement of lidar DEMs

Hydrologic-enforcement (hydro-enforcement) of light detection and ranging (lidar)-derived digital elevation models (DEMs) modifies the elevations of artificial impediments (such as road fills or railroad grades) to simulate how man-made drainage structures such as culverts or bridges allow continuous downslope flow. Lidar-derived DEMs contain an extremely high level of topographic detail; thus, hydro-enforced lidar-derived DEMs are essential to the U.S. Geological Survey (USGS) for complex modeling of riverine flow. The USGS Coastal and Marine Geology Program (CMGP) is integrating hydro-enforced lidar-derived DEMs (land elevation) and lidar-derived bathymetry (water depth) to enhance storm surge modeling in vulnerable coastal zones.

Fact Sheet↗

USGS2014

Lidar point density analysis: implications for identifying water bodies

Most airborne topographic light detection and ranging (lidar) systems operate within the near-infrared spectrum. Laser pulses from these systems frequently are absorbed by water and therefore do not generate reflected returns on water bodies in the resulting void regions within the lidar point cloud. Thus, an analysis of lidar voids has implications for identifying water bodies. Data analysis techniques to detect reduced lidar return densities were evaluated for test sites in Blackhawk County, Iowa, and Beltrami County, Minnesota, to delineate contiguous areas that have few or no lidar returns. Results from this study indicated a 5-meter radius moving window with fewer than 23 returns (28 percent of the moving window) was sufficient for delineating void regions. Techniques to provide elevation values for void regions to flatten water features and to force channel flow in the downstream direction also are presented.

Scientific Investigations Report↗

USGS2013

Hydrography change detection: the usefulness of surface channels derived From LiDAR DEMs for updating mapped hydrography

The 1:24,000-scale high-resolution National Hydrography Dataset (NHD) mapped hydrography flow lines require regular updating because land surface conditions that affect surface channel drainage change over time. Historically, NHD flow lines were created by digitizing surface water information from aerial photography and paper maps. Using these same methods to update nationwide NHD flow lines is costly and inefficient; furthermore, these methods result in hydrography that lacks the horizontal and vertical accuracy needed for fully integrated datasets useful for mapping and scientific investigations. Effective methods for improving mapped hydrography employ change detection analysis of surface channels derived from light detection and ranging (LiDAR) digital elevation models (DEMs) and NHD flow lines. In this article, we describe the usefulness of surface channels derived from LiDAR DEMs for hydrography change detection to derive spatially accurate and time-relevant mapped hydrography. The methods employ analyses of horizontal and vertical differences between LiDAR-derived surface channels and NHD flow lines to define candidate locations of hydrography change. These methods alleviate the need to analyze and update the nationwide NHD for time relevant hydrography, and provide an avenue for updating the dataset where change has occurred.

Journal of the American Water Resources Associatio↗

USGS2010

Topographic Science

The mission of U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center Topographic Science is to establish partnerships and conduct research and applications that facilitate the development and use of integrated national and global topographic datasets. Topographic Science includes a wide range of research and applications that result in improved seamless topographic datasets, advanced elevation technology, data integration and terrain visualization, new and improved elevation derivatives, and development of Web-based tools. In cooperation with our partners, Topographic Science is developing integrated-science applications for mapping, national natural resource initiatives, hazards, and global change science. http://topotools.cr.usgs.gov/.

Fact Sheet↗

USGS2010

Using Selective Drainage Methods to Extract Continuous Surface Flow from 1-Meter Lidar-Derived Digital Elevation Data

Digital elevation data commonly are used to extract surface flow features. One source for high-resolution elevation data is light detection and ranging (lidar). Lidar can capture a vast amount of topographic detail because of its fine-scale ability to digitally capture the surface of the earth. Because elevation is a key factor in extracting surface flow features, high-resolution lidar-derived digital elevation models (DEMs) provide the detail needed to consistently integrate hydrography with elevation, land cover, structures, and other geospatial features. The U.S. Geological Survey has developed selective drainage methods to extract continuous surface flow from high-resolution lidar-derived digital elevation data. The lidar-derived continuous surface flow network contains valuable information for water resource management involving flood hazard mapping, flood inundation, and coastal erosion. DEMs used in hydrologic applications typically are processed to remove depressions by filling them. High-resolution DEMs derived from lidar can capture much more detail of the land surface than courser elevation data. Therefore, high-resolution DEMs contain more depressions because of obstructions such as roads, railroads, and other elevated structures. The filling of these depressions can significantly affect the DEM-derived surface flow routing and terrain characteristics in an adverse way. In this report, selective draining methods that modify the elevation surface to drain a depression through an obstruction are presented. If such obstructions are not removed from the elevation data, the filling of depressions to create continuous surface flow can cause the flow to spill over an obstruction in the wrong location. Using this modified elevation surface improves the quality of derived surface flow and retains more of the true surface characteristics by correcting large filled depressions. A reliable flow surface is necessary for deriving a consistently connected drainage network, which is important in understanding surface water movement and developing applications for surface water runoff, flood inundation, and erosion. Improved methods are needed to extract continuous surface flow features from high-resolution elevation data based on lidar.

Scientific Investigations Report↗

USGS2010

Using selective drainage methods to hydrologically-condition and hydrologically-enforce lidar-derived surface flow

The methods to extract surface flow from coarse elevation data are well documented; however, the methods to extract surface flow from high-resolution, high-vertical accuracy digital elevation models (DEMs) derived from light detection and ranging (lidar) are less documented, but yet more complex. As lidar data are increasingly used to generate DEMS, the demand for lidar-derived surface flow escalates. Thus, the US Geological Survey has developed semi-automated selective drainage methods to extract continuous surface flow from lidar-derived DEMs. This integrated network is important in understanding surface water movement and runoff, flood inundation, and erosion.

Conference Paper↗

USGS2009

Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

Scientific Investigations Report↗