Jeffrey J. Danielson

Mr. Jeffrey J. Danielson

United States Geological Survey, Reston, VA 20192, USA
orcid

Research Focus & Metrics

Academic Career Length

28Years (1999-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 December 1999 in International Journal of Water Resources Development
Verified
Journal Article
Closed access
AWAaron T. Wolf
Aaron T. Wolf
JNJeffrey A. Natharius
Jeffrey A. Natharius
JDJeffrey J. Danielson
Jeffrey J. Danielson
BWBrian S. Ward
Brian S. Ward
JPJan K. Pender
Jan K. Pender
It is becoming acknowledged that water is likely to be the most pressing environmental concern of the next century. Difficulties in river basin management are only exacerbated when the resource crosses international boundaries. One critical aid in the assessment of international waters has been the Register of International Rivers a compendium which listed 214 international waterways that cover 47% of the earth's continental land surface. The Register, though, was last updated in 1978 by the now defunct United Nations Department of Economic and Social Affairs. The purpose of this paper is to update the Register in order to reflect the quantum changes that have taken place over the last 22 years, both in global geopolitics and in map coverage and technology. By accessing digital elevation models at spatial resolutions of 30 arc seconds, corroborating at a unified global map coverage of at least 1:1 000 000, and superimposing the results over complete coverage of current political boundaries, we are able to provide a new register which lists 261 international rivers, covering 45.3% of the land surface of the earth (excluding Antarctica). This paper lists all international rivers with their watershed areas, the nations which share each watershed,their respective territorial percentages, and notes on changes in or disputes over international boundaries since 1978.

1 December 2016 in Journal of Coastal Research
Verified
Journal Article
Closed access
JDJeffrey J. Danielson
Jeffrey J. Danielson
SPSandra Poppenga
Sandra Poppenga
JBJohn C. Brock
John C. Brock
GEGayla A. Evans
Gayla A. Evans
DTDean J. Tyler
Dean J. Tyler
JBJohn A. Barras
John A. Barras
Danielson, J.J.; Poppenga, S.K.; Brock, J.C.; Evans, G.A.; Tyler, D.J.; Gesch, D.B.; Thatcher, C.A., and Barras, J.A., 2016. Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database. In: Brock, J.C.; Gesch, D.B.; Parrish, C.E.; Rogers, J.N., and Wright, C.W. (eds.), Advances in Topobathymetric Mapping, Models, and Applications. Journal of Coastal Research, Special Issue, No. 76, pp. 75–89. Coconut Creek (Florida), ISSN 0749-0208. During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastal inundation 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 Elevatio...

9 February 2022 in Estuarine, Coastal and Shelf Science
Verified
Journal Article
Closed access
JEJoanna Ellison
Joanna Ellison
KBKevin Buffington
Kevin Buffington
Karen ThorneKaren Thorne
Karen Thorne
DGDean Gesch
Dean Gesch
JIJeffrey Reed Irwin
Jeffrey Reed Irwin
JDJeffrey J. Danielson
Jeffrey J. Danielson

13 June 2016 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Verified
Journal Article
Open access
PDF file
DGDean Gesch
Dean Gesch
MOM. Oimoen
M. Oimoen
JDJeffrey J. Danielson
Jeffrey J. Danielson
DMD. Meyer
D. Meyer
The ASTER Global Digital Elevation Model Version 3 (GDEM v3) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009 and GDEM Version 2 (v2) in 2011. The absolute vertical accuracy of GDEM v3 was calculated by comparison with more than 23,000 independent reference geodetic ground control points from the U.S. National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v3 is 8.52 meters. This compares with the RMSE of 8.68 meters for GDEM v2. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v3 mean error of −1.20 meters reflects an overall negative bias in GDEM v3. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover type to provide insight into how GDEM v3 performs in various land surface conditions. While the RMSE varies little across cover types (6.92 to 9.25 meters), the mean error (bias) does appear to be affected by land cover type, ranging from −2.99 to +4.16 meters across 14 land cover classes. These results indicate that in areas where built or natural aboveground features are present, GDEM v3 is measuring elevations above the ground level, a condition noted in assessments of previous GDEM versions (v1 and v2) and an expected condition given the type of stereo-optical image data collected by ASTER. GDEM v3 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v3 has elevations that are higher in the canopy than SRTM. The overall validation effort also included an evaluation of the GDEM v3 water mask. In general, the number of distinct water polygons in GDEM v3 is much lower than the number in a reference land cover dataset, but the total areas compare much more closely.

31 July 2012 in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Verified
Journal Article
Open access
PDF file
DGDean Gesch
Dean Gesch
MOM. Oimoen
M. Oimoen
ZZZ. Zhang
Z. Zhang
DMD. Meyer
D. Meyer
JDJeffrey J. Danielson
Jeffrey J. Danielson
The ASTER Global Digital Elevation Model Version 2 (GDEM v2) was evaluated over the conterminous United States in a manner similar to the validation conducted for the original GDEM Version 1 (v1) in 2009. The absolute vertical accuracy of GDEM v2 was calculated by comparison with more than 18,000 independent reference geodetic ground control points from the National Geodetic Survey. The root mean square error (RMSE) measured for GDEM v2 is 8.68 meters. This compares with the RMSE of 9.34 meters for GDEM v1. Another important descriptor of vertical accuracy is the mean error, or bias, which indicates if a DEM has an overall vertical offset from true ground level. The GDEM v2 mean error of –0.20 meters is a significant improvement over the GDEM v1 mean error of –3.69 meters. The absolute vertical accuracy assessment results, both mean error and RMSE, were segmented by land cover to examine the effects of cover types on measured errors. The GDEM v2 mean errors by land cover class verify that the presence of aboveground features (tree canopies and built structures) cause a positive elevation bias, as would be expected for an imaging system like ASTER. In open ground classes (little or no vegetation with significant aboveground height), GDEM v2 exhibits a negative bias on the order of 1 meter. GDEM v2 was also evaluated by differencing with the Shuttle Radar Topography Mission (SRTM) dataset. In many forested areas, GDEM v2 has elevations that are higher in the canopy than SRTM.