Global multi-resolution terrain elevation data 2010 (GMTED2010)

Danielson, Jeffrey J.; Gesch, Dean B.

doi:10.3133/ofr20111073

Cited by 1,041 publications

(749 citation statements)

References 1 publication

Supporting

Mentioning

741

Contrasting

Unclassified

Order By: Relevance

“…An overview is given in Tables A2 and A3. (Danielson et al, 2011) Average over the ground pixel area. …”

Section: Auxiliary Informationmentioning

confidence: 99%

“…For this reason, only observations with moderate cloud fractions (f eff lower than 30 %) are used, unless it can be assumed that the cloud cover is mostly situated below the SO 2 layer, i.e., a typical situation for volcanic plumes injected into the upper troposphere or lower stratosphere. The surface height (z s ) is determined for each pixel by interpolating the values of a high-resolution digital elevation map, GMTED2010 (Danielson and Gesch, 2011).…”

Section: Cloudsmentioning

confidence: 99%

See 1 more Smart Citation

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

et al. 2017

View full text Add to dashboard Cite

Abstract. The TROPOspheric Monitoring Instrument (TROPOMI) onboard the Copernicus Sentinel-5 Precursor (S-5P) platform will measure ultraviolet earthshine radiances at high spectral and improved spatial resolution (pixel size of 7 km × 3.5 km at nadir) compared to its predecessors OMI and GOME-2. This paper presents the sulfur dioxide (SO 2 ) vertical column retrieval algorithm implemented in the S-5P operational processor UPAS (Universal Processor for UV/VIS Atmospheric Spectrometers) and comprehensively describes its various retrieval steps. The spectral fitting is performed using the differential optical absorption spectroscopy (DOAS) method including multiple fitting windows to cope with the large range of atmospheric SO 2 columns encountered. It is followed by a slant column background correction scheme to reduce possible biases or across-track-dependent artifacts in the data. The SO 2 vertical columns are obtained by applying air mass factors (AMFs) calculated for a set of representative a priori profiles and accounting for various parameters influencing the retrieval sensitivity to SO 2 . Finally, the algorithm includes an error analysis module which is fully described here. We also discuss verification results (as part of the algorithm development) and future validation needs of the TROPOMI SO 2 algorithm.

show abstract

“…An overview is given in Tables A2 and A3. (Danielson et al, 2011) Average over the ground pixel area. …”

Section: Auxiliary Informationmentioning

confidence: 99%

Section: Cloudsmentioning

confidence: 99%

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

et al. 2017

View full text Add to dashboard Cite

show abstract

“…For the land masses north of 60°N., the GMTED2010 dataset (Danielson and Gesch, 2011) was used. The GMTED2010 dataset itself is a hybrid of the best global DEM data available at the time of its creation and has a resolution of 7.5 arc-seconds, with the exception of Greenland where the resolution is 30 arcseconds.…”

Section: Datamentioning

confidence: 99%

“…The HYDRO1k database was developed from the Global 30 ArcSecond Elevation (GTOPO30) DEM (Gesch and others, 1999), which has a 30-arc-second resolution (about 1 kilometer at the equator). With the completions of the Shuttle Radar Topography Mission (SRTM) DEM (Farr and Kobrick, 2000) and the Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) dataset (Danielson and Gesch, 2011), production of a highresolution hydrologic derivative database for the entire globe became possible.…”

Section: Introductionmentioning

confidence: 99%

Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database

Verdin¹

2017

Data Series

View full text Add to dashboard Cite

“…In figure 4 the axis represents the geographical longitude and latitude. The road coordinates were obtained from OpenStreetMap, while the elevation data are from GMTED 2010 database [26]. It is evident that the tunnel route (black) is a lot shorter than the alternative route because it crosses the mountain ridge (the white route in figure 4).…”

Section: Extraurban Case Study -Karawanks Tunnelmentioning

confidence: 99%

Modeling an impact of road geometric design on vehicle energy consumption

2017

View full text Add to dashboard Cite

Abstract. Some roads connect traffic origins and destinations directly, some use winding, indirect routes. Indirect connections result in longer distances driven and increased fuel consumption. A similar effect is observed on congested roads and mountain roads with many changes in altitude. Therefore a framework to assess road networks based on energy consumption is proposed. It has been shown that road geometry has significant impact on overall traffic energy consumption and emissions. The methodology presented in the paper analyzes impact of traffic volume, shares of vehicle classes, road network configuration on the energy used by the vehicles. It can be used to optimize energy consumption with efficient traffic management and to choose optimum new road in the design phase. This is especially important as the energy consumed by the vehicles shortly after construction supersedes the energy spent for the road construction.

show abstract

Global multi-resolution terrain elevation data 2010 (GMTED2010)

Cited by 1,041 publications

References 1 publication

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

Sulfur dioxide retrievals from TROPOMI onboard Sentinel-5 Precursor: algorithm theoretical basis

Hydrologic Derivatives for Modeling and Analysis—A new global high-resolution database

Modeling an impact of road geometric design on vehicle energy consumption

Contact Info

Product

Resources

About