Geology topics

Susan K. Greenlee

Publications and source records attributed to Susan K. Greenlee.

9 recordsLinked to original sources

USGS2013

A conceptual prototype for the next-generation national elevation dataset

In 2012 the U.S. Geological Survey's (USGS) National Geospatial Program (NGP) funded a study to develop a conceptual prototype for a new National Elevation Dataset (NED) design with expanded capabilities to generate and deliver a suite of bare earth and above ground feature information over the United States. This report details the research on identifying operational requirements based on prior research, evaluation of what is needed for the USGS to meet these requirements, and development of a possible conceptual framework that could potentially deliver the kinds of information that are needed to support NGP's partners and constituents. This report provides an initial proof-of-concept demonstration using an existing dataset, and recommendations for the future, to inform NGP's ongoing and future elevation program planning and management decisions. The demonstration shows that this type of functional process can robustly create derivatives from lidar point cloud data; however, more research needs to be done to see how well it extends to multiple datasets.

Open-File Report↗

USGS2012

Creation of digital contours that approach the characteristics of cartographic contours

The capability to easily create digital contours using commercial off-the-shelf (COTS) software has existed for decades. Out-of-the-box raw contours are suitable for many scientific applications without pre- or post-processing; however, cartographic applications typically require additional improvements. For example, raw contours generally require smoothing before placement on a map. Cartographic contours must also conform to certain spatial/logical rules; for example, contours may not cross waterbodies. The objective was to create contours that match as closely as possible the cartographic contours produced by manual methods on the 1:24,000-scale, 7.5-minute Topographic Map series. This report outlines the basic approach, describes a variety of problems that were encountered, and discusses solutions. Many of the challenges described herein were the result of imperfect input raster elevation data and the requirement to have the contours integrated with hydrographic features from the National Hydrography Dataset (NHD).

Scientific Investigations Report↗

USGS2011

New land surface digital elevation model covers the Earth

Land surface elevation around the world is reaching new heights—as far as its description and measurement goes. A new global digital elevation model (DEM) is being cited as a significant improvement in the quality of topographic data available for Earth science studies. Land surface elevation is one of the Earth's most fundamental geophysical properties, but the accuracy and detail with which it has been measured and described globally have been insufficient for many large-area studies. The new model, developed at the U.S. Geological Survey's (USGS) EROS Data Center (EDC), has changed all that.

Eos, Earth and Space Science News↗

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↗

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↗

USGS2006

CLICK: The new USGS center for LIDAR information coordination and knowledge

Elevation data is rapidly becoming an important tool for the visualization and analysis of geographic information. The creation and display of three-dimensional models representing bare earth, vegetation, and structures have become major requirements for geographic research in the past few years. Light Detection and Ranging (lidar) has been increasingly accepted as an effective and accurate technology for acquiring high-resolution elevation data for bare earth, vegetation, and structures. Lidar is an active remote sensing system that records the distance, or range, of a laser fi red from an airborne or space borne platform such as an airplane, helicopter or satellite to objects or features on the Earth’s surface. By converting lidar data into bare ground topography and vegetation or structural morphologic information, extremely accurate, high-resolution elevation models can be derived to visualize and quantitatively represent scenes in three dimensions. In addition to high-resolution digital elevation models (Evans et al., 2001), other lidar-derived products include quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass (Lefsky et al., 2002), and models of urban areas such as building footprints and three-dimensional city models (Maas, 2001).

Photogrammetric Engineering and Remote Sensing↗

USGS2005

Collection and analysis of high-resolution elevation data for the Lincoln Lidar Project, Lincoln, Nebraska, 2004

The Lincoln Lidar Project was a partnership developed between the U.S. Geological Survey National Center for Earth Resources Observations and Science (EROS), Lancaster County and the city of Lincoln, Nebraska. This project demonstrated a successful planning, collection, analysis and integration of high-resolution elevation information using Light Detection and Ranging, (Lidar) data. This report describes the partnership developed to collect local Lidar data and transform the data into information useable at local to national levels. This report specifically describes project planning, quality assurance, processing, transforming raw Lidar points to useable data layers, and visualizing and disseminating the raw and final products.

Nebraska↗

USGS2002

The national elevation data set

The NED is a seamless raster dataset from the USGS that fulfills many of the concepts of framework geospatial data as envisioned for the NSDI, allowing users to focus on analysis rather than data preparation. It is regularly maintained and updated, and it provides basic elevation data for many GIS applications. The NED is one of several seamless datasets that the USGS is making available through the Web. The techniques and approaches developed for producing, maintaining, and distributing the NED are the type that will be used for implementing the USGS National Map (http://nationalmap.usgs.gov/).

Photogrammetric Engineering and Remote Sensing↗

USGS2000

Basin level statistical properties of topographic index for North America

For land–atmosphere interaction studies several Topmodel based land-surface schemes have been proposed. For the implementation of such models over the continental (and global) scales, statistical properties of the topographic indices are derived using GTOPO30 (30-arc-second; 1 km resolution) DEM data for North America. River basins and drainage network extracted using this dataset are overlaid on computed topographic indices for the continent and statistics are extracted for each basin. A total of 5020 basins are used to cover the entire continent with an average basin size of 3640 km 2 . Typically, the first three statistical moments of the distribution of the topographic indices for each basin are required for modeling. Departures of these statistical moments to those obtained using high resolution data have important implications for the prediction of soil-moisture states in the hydrologic models and consequently on the dynamics of the land–atmosphere interaction. It is found that a simple relationship between the statistics obtained at the 1 km and 90 m resolutions can be developed. The mean, standard deviation, skewness, L-scale and L-skewness all show approximate linear relationships between the two resolutions making it possible to use the moment estimates from the GTOPO30 data for hydrologic studies by applying a simple linear downscaling scheme. This significantly increases the utility value of the GTOPO30 datasets for hydrologic modeling studies.

Advances in Water Resources↗