Co-registration of an Antarctic digital elevation model with SSM/I brightness temperatures

The Special Sensor Microwave/Imager (SMM/I) instrument provides daily measures of microwave brightness temperatures Tb over the polar regions. Data are available from 1987 to the present and have a demonstrated utility for sea-ice studies. In this paper we investigate applications to polar ice sheets with a view towards correlating patterns of Tb with ice-sheet elevation. We go on to discuss the Tb signature of processes linked to temperature anomalies and accumulation zone boundaries.Our approach consists of combining SSM/I Tb values provided on CD-ROM by the National Snow and Ice Data Center (NSIDC) with a digital elevation model (DEM) of Antarctica derived originally from the Scott Polar Research Institute Antarctic Map Folio. We focused on 37 GHz data which is mapped onto a 316 × 332 polar stereographic grid at 25 km resolution. The DEM consists of a 281 × 281 array of elevation values with a 20 km resolution. The DEM was resampled to be compatible with the SSM/I data by transforming the elevation data from the original projection place to geodetic coordinates. The elevation data were than transformed onto the SSM/I projection plane. Elevation data were interpolated to yield ice-sheet surface heights at 25 km intervals coinciding with SSM/I point Tb assignments.By co-registering the two data sets, it is possible to “drape” the brightness temperature data over the elevation data. The resulting image highlights the relationship (and variations) between ice-sheet topography and brightness temperature.

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Co-registration of an Antarctic digital elevation model with SSM/I brightness temperatures

Annals of Glaciology ◽

10.1017/s0260305500012660 ◽

1993 ◽

Vol 17 ◽

pp. 93-97 ◽

Cited By ~ 2

Author(s):

J.D. Wilson ◽

K.C. Jezek

Keyword(s):

Brightness Temperature ◽

Digital Elevation Model ◽

Ice Sheet ◽

Polar Regions ◽

Cd Rom ◽

Brightness Temperatures ◽

Digital Elevation ◽

Elevation Data ◽

Polar Ice Sheets ◽

Elevation Model

The Special Sensor Microwave/Imager (SMM/I) instrument provides daily measures of microwave brightness temperatures Tb over the polar regions. Data are available from 1987 to the present and have a demonstrated utility for sea-ice studies. In this paper we investigate applications to polar ice sheets with a view towards correlating patterns of Tb with ice-sheet elevation. We go on to discuss the Tb signature of processes linked to temperature anomalies and accumulation zone boundaries. Our approach consists of combining SSM/I Tb values provided on CD-ROM by the National Snow and Ice Data Center (NSIDC) with a digital elevation model (DEM) of Antarctica derived originally from the Scott Polar Research Institute Antarctic Map Folio. We focused on 37 GHz data which is mapped onto a 316 × 332 polar stereographic grid at 25 km resolution. The DEM consists of a 281 × 281 array of elevation values with a 20 km resolution. The DEM was resampled to be compatible with the SSM/I data by transforming the elevation data from the original projection place to geodetic coordinates. The elevation data were than transformed onto the SSM/I projection plane. Elevation data were interpolated to yield ice-sheet surface heights at 25 km intervals coinciding with SSM/I point Tb assignments. By co-registering the two data sets, it is possible to “drape” the brightness temperature data over the elevation data. The resulting image highlights the relationship (and variations) between ice-sheet topography and brightness temperature.

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Assessment of a TanDEM-X Digital Elevation Model of the Greenland Ice Sheet and its Zonation for Winter 2015/16

10.5194/egusphere-egu2020-6739 ◽

2020 ◽

Author(s):

Sabine Baumann ◽

Birgit Wessel ◽

Martin Huber ◽

Silke Kerkhoff ◽

Achim Roth

Keyword(s):

Remote Sensing ◽

Digital Elevation Model ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Polar Regions ◽

Digital Elevation ◽

And Performance ◽

Remote Sensing Symposium ◽

Global Sea Level ◽

Elevation Model

The Greenland Ice Sheet (GIS) was the largest contributor to global sea level rise in the 2005 to 2016 period (Meredith et al. in press). Therefore, it is one of the biggest players influencing our climate and monitoring and understanding of its mechanisms and development are of highest relevance.Means to observe and measure such large areas are remote sensing. The Tandem-X mission of DLR and Airbus consists of two satellites (TerraSAR-X and TanDEM-X) that are flying in single pass formation, mapping the Earth in interferometric SAR X-band with a resolution of 12m (Zink et al. 2014). The mission has been flying in this constellation since 2010. Due to the satellite constellation and the SAR system, digital elevation models (DEMs) can be created in high resolution, unaffected by the availability of daylight and the presence of clouds.All data acquired between 2010 to 2014 (Rizzoli et al. 2017) were compled to a global elevation model. Besides this global product, several time slices were created for the GIS (Wohlfart et al. 2018). In this project, we created a DSM mosaic from winter 2015/16 acquisitions, more precisely using more than 2000 DEM scenes (Fritz at al. 2011) from end of October 2015 to beginning of February 2016.One issue of a SAR system is the penetration of the signal into snow. Additionally, water surfaces appear dark in the images due to low backscatter towards the sensor. Therefore, we used winter scenes to minimize the height error.We created an almost seamless DSM out of these scenes for 2015/16. Second, we used SAR features to delineate different snow zones. For this purpose, we used the amplitude, the height error map, and additionally ICESat and ICE Bridge data.&#160;References Fritz, T.; Rossi, C.; Yague-Martinez, N.; Rodriguez Gonzalez, F.; Lachaise, M.; Breit H. Interferometric processing of TanDEM-X data, IGARSS 2011, Vancouver, July 2011Meredith, M.; Sommerkorn M.; Cassotta S.; Derksen C.; Ekaykin A.; Hollowed A.; Kofinas G.; Mackintosh A.; Melbourne-Thomas J.; Muelbert M.M.C.; Ottersen G.; Pritchard H.; and Schuur E.A.G.; 2019: Polar Regions. In: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate [H.-O. Po&#776;rtner, D.C. Roberts, V. Masson-Delmotte, P. Zhai, M. Tignor, E. Poloczanska, K. Mintenbeck, A. Alegri&#769;a, M. Nicolai, A. Okem, J. Petzold, B. Rama, N.M. Weyer (eds.)]. In press.Rizzoli, P.; Martone, M.; Gonzalez, C.; Wecklich, C.; Tridon, D.B.; Br&#228;utigam, B.; Bachmann, M.; Schulze, D.; Fritz, T.; Huber, M.; et al. Generation and performance assessment of the global TanDEM-X digital elevation model. ISPRS J. Photogramm. Remote Sens. 2017, 132, 119&#8211;139.Wohlfart, C.; Wessel, B.; Huber, M.; Leichtle, T.; Abdullahi, S.; Kerkhoff, S.; Roth, A. TanDEM-X DEM derived elevation changes of the Greenland Ice Sheet. In Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain, 22&#8211;27 July 2018.Zink, M.; Bachmann, M.; Br&#228;utigam, B.; Fritz, T.; Hajnsek, I.; Krieger, G.; Moreira, A.; Wessel, B. TanDEM-X: The New Global DEM Takes Shape. IEEE GRSM 2014, 2, 8&#8211;23.

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Assessing Optimal Digital Elevation Model Selection for Active River Area Delineation Across Broad Regions

10.21203/rs.3.rs-311838/v1 ◽

2021 ◽

Author(s):

Shizhou Ma ◽

Karen Beazley ◽

Patrick Nussey ◽

Chris Greene

Keyword(s):

High Resolution ◽

Digital Elevation Model ◽

Smoothing Algorithm ◽

Processing Efficiency ◽

Spatial Approach ◽

Digital Elevation ◽

Elevation Data ◽

Computer Based ◽

Lidar Dem ◽

Elevation Model

Abstract The Active River Area (ARA) is a spatial approach for identifying the extent of functional riparian area. Given known limitations in terms of input elevation data quality and methodology, ARA studies to date have not achieved effective computer-based ARA-component delineation, limiting the efficacy of the ARA framework in terms of informing riparian conservation and management. To achieve framework refinement and determine the optimal input elevation data for future ARA studies, this study tested a novel Digital Elevation Model (DEM) smoothing algorithm and assessed ARA outputs derived from a range of DEMs for accuracy and efficiency. It was found that the tested DEM smoothing algorithm allows the ARA framework to take advantage of high-resolution LiDAR DEM and considerably improves the accuracy of high-resolution LiDAR DEM derived ARA results; smoothed LiDAR DEM in 5-meter spatial resolution best balanced ARA accuracy and data processing efficiency and is ultimately recommended for future ARA delineations across large regions.

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Automated Conflation of Digital Elevation Model with Reference Hydrographic Lines

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9050334 ◽

2020 ◽

Vol 9 (5) ◽

pp. 334

Author(s):

Timofey E. Samsonov

Keyword(s):

Spatial Analysis ◽

Digital Elevation Model ◽

Spatial Data ◽

Drainage Network ◽

Map Generalization ◽

Data Types ◽

Digital Elevation ◽

Elevation Data ◽

Elevation Model ◽

Different Sources

Combining misaligned spatial data from different sources complicates spatial analysis and creation of maps. Conflation is a process that solves the misalignment problem through spatial adjustment or attribute transfer between similar features in two datasets. Even though a combination of digital elevation model (DEM) and vector hydrographic lines is a common practice in spatial analysis and mapping, no method for automated conflation between these spatial data types has been developed so far. The problem of DEM and hydrography misalignment arises not only in map compilation, but also during the production of generalized datasets. There is a lack of automated solutions which can ensure that the drainage network represented in the surface of generalized DEM is spatially adjusted with independently generalized vector hydrography. We propose a new method that performs the conflation of DEM with linear hydrographic data and is embeddable into DEM generalization process. Given a set of reference hydrographic lines, our method automatically recognizes the most similar paths on DEM surface called counterpart streams. The elevation data extracted from DEM is then rubbersheeted locally using the links between counterpart streams and reference lines, and the conflated DEM is reconstructed from the rubbersheeted elevation data. The algorithm developed for extraction of counterpart streams ensures that the resulting set of lines comprises the network similar to the network of ordered reference lines. We also show how our approach can be seamlessly integrated into a TIN-based structural DEM generalization process with spatial adjustment to pre-generalized hydrographic lines as additional requirement. The combination of the GEBCO_2019 DEM and the Natural Earth 10M vector dataset is used to illustrate the effectiveness of DEM conflation both in map compilation and map generalization workflows. Resulting maps are geographically correct and are aesthetically more pleasing in comparison to a straightforward combination of misaligned DEM and hydrographic lines without conflation.

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DEMNAS: MODEL DIGITAL KETINGGIAN NASIONAL UNTUK APLIKASI KEPESISIRAN

OSEANA ◽

10.14203/oseana.2018.vol.43no.4.2 ◽

2018 ◽

Vol 43 (4) ◽

Author(s):

Marindah Yulia Iswari ◽

Kasih Anggraini

Keyword(s):

Remote Sensing ◽

Digital Elevation Model ◽

Spatial Resolution ◽

Digital Data ◽

Coastal Hazards ◽

Remote Sensing Images ◽

Geospatial Information ◽

Digital Elevation ◽

Elevation Data ◽

Elevation Model

DEMNAS : NATIONAL DIGITAL ELEVATION MODEL FOR COASTAL APPLICATION. DEM is a digital data which contain information about elevation. In Indonesia, DEM can be generated from elevation points or contours in RBI (Rupabumi Indonesia). DEM can be performed to research of coastal application i.e. inundation or tsunami. DEM can help to analyze vulnerability or evacuation zone for coastal hazards. DEMNAS is one product of BIG (Geospatial Information Agency) which consist of elevation data from remote sensing images. DEMNAS data has not been widely used and is still being developed but DEMNAS has an advantage of spatial resolution. DEMNAS has spatial resolution 0.27 arc-second, which is bigger than the spatial resolution of global DEM.

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HydroSHEDS v2.0 – Refined global river network and catchment delineations from TanDEM-X elevation data

10.5194/egusphere-egu21-9277 ◽

2021 ◽

Author(s):

Bernhard Lehner ◽

Achim Roth ◽

Martin Huber ◽

Mira Anand ◽

Günther Grill ◽

...

Keyword(s):

High Resolution ◽

Digital Elevation Model ◽

Multiple Scales ◽

Environmental Conservation ◽

The Arctic ◽

River Networks ◽

Northern Latitude ◽

Digital Elevation ◽

Elevation Data ◽

Elevation Model

Since its introduction in 2008, the HydroSHEDS database (www.hydrosheds.org) has transformed large-scale hydro-ecological research and applications worldwide by offering standardized spatial units for hydrological assessments. At its core, HydroSHEDS provides digital hydrographic information that can be applied in Geographic Information Software (GIS) or hydrological models to delineate river networks and catchment boundaries at multiple scales, from local to global. Its various data layers form the basis for applications in a wide range of disciplines including environmental, conservation, socioeconomic, human health, and sustainability studies.Version 1 of HydroSHEDS was derived from the digital elevation model of the Shuttle Radar Topography Mission (SRTM) at a pixel resolution of 3 arc-seconds (~90 meters at the equator). It was created using customized processing and optimization algorithms and a high degree of manual quality control. Results are available at varying resolutions, ranging from 3 arc-seconds (~90 m) to 5 minutes (~10 km), and in nested sub-basin structures, making the data uniquely suitable for applications at multiple scales. A suite of related data collections and value-added information, foremost the HydroATLAS compilation of over 50 hydro-environmental attributes for every river reach and sub-basin, continuously enhance the versatility of the HydroSHEDS family of products. Yet version 1 of HydroSHEDS shows some important limitations. In particular, coverage above 60&#176; northern latitude (i.e., largely the Arctic) is missing for the 3 arc-second product and is of low quality for coarser products because no SRTM elevation data are available for this region. Also, some areas are affected by inherent data gaps or other errors that could not be fully resolved at the time of creating version 1 of HydroSHEDS.Today, the TanDEM-X dataset (TerraSAR-X add-on for Digital Elevation Measurement), created in partnership between the German Aerospace Agency (DLR) and Airbus, offers a new digital elevation model covering the entire global land surface including northern latitudes. In a collaborative project, this dataset is used to extract HydroSHEDS v2.0, following the same basic specifications as version 1. DLR is processing the original 12 m resolution TanDEM-X data to create a hydrologically pre-conditioned version at 3 arc-second resolution. In this step, corrections with high-resolution vegetation and settlement maps are applied to reduce distortions caused by vegetation cover and in built-up areas. Following this preprocessing, refined hydrological optimization and correction algorithms are used to derive the drainage pathways, including improved &#8216;stream-burning&#8217; techniques that incorporate recent data products such as high-resolution terrestrial open water masks and improved tracing of drainage pathways as center lines in global lake and river maps. The resulting HydroSHEDS v2.0 database will provide river networks and catchment boundaries at full global coverage. Release of the data under a free license is scheduled for 2022, with regions above 60&#176; northern latitude being completed first in 2021.

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Synergetic merging of Cartosat-1 and RAMP to generate improved digital elevation model of Schirmacher oasis, east Antarctica

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-8-517-2014 ◽

2014 ◽

Vol XL-8 ◽

pp. 517-524 ◽

Cited By ~ 7

Author(s):

S. D. Jawak ◽

A. J. Luis

Keyword(s):

Digital Elevation Model ◽

Accuracy Assessment ◽

East Antarctica ◽

Interpolation Methods ◽

Digital Elevation ◽

Schirmacher Oasis ◽

Elevation Data ◽

Interpolation Techniques ◽

Elevation Model ◽

Better Than

Available digital elevation models (DEMs) of Antarctic region generated by using radar altimetry and the Antarctic digital database (ADD) indicate elevation variations of up to hundreds of meters, which necessitates the generation of local DEM and its validation by using ground reference. An enhanced digital elevation model (eDEM) of the Schirmacher oasis region, east Antarctica, is generated synergistically by using Cartosat-1 stereo pair-derived photogrammetric DEM (CartoDEM)-based point elevation dataset and multitemporal radarsat Antarctic mapping project version 2 (RAMPv2) DEM-based point elevation dataset. In this study, we analyzed suite of interpolation techniques for constructing a DEM from RAMPv2 and CartoDEM-based point elevation datasets, in order to determine the level of confidence with which the interpolation techniques can generate a better interpolated continuous surface, and eventually improves the elevation accuracy of DEM from synergistically fused RAMPv2 and CartoDEM point elevation datasets. RAMPv2 points and CartoDEM points were used as primary data for various interpolation techniques such as ordinary kriging (OK), simple kriging (SK), universal kriging (UK), disjunctive kriging (DK) techniques, inverse distance weighted (IDW), global polynomial (GP) with power 1 and 2, local polynomial (LP) and radial basis functions (RBF). Cokriging of 2 variables with second dataset was used for ordinary cokriging (OCoK), simple cokriging (SCoK), universal cokriging (UCoK) and disjunctive cokriging (DCoK). The IDW, GP, LP, RBF, and kriging methods were applied to one variable, while Cokriging experiments were employed on two variables. The experiment of dataset and its combination produced two types of point elevation map categorized as (1) one variable (RAMPv2 Point maps and CartoDEM Point maps) and (2) two variables (RAMPv2 Point maps + CartoDEM Point maps). Interpolated surfaces were evaluated with the help of differential global positioning system (DGPS) points collected from study area during the Indian Scientific Expedition to Antarctic (ISEA). Accuracy assessment of the RAMPv2 DEM, CartoDEM, and combined eDEM (RAMPv2 + CartoDEM) by using DGPS as ground reference data shows that eDEM achieves much better accuracy (average elevation error 8.44 m) than that of existing DEM constructed by using only CartoDEM (13.57 m) or RAMPv2 (41.44 m) alone. The newly constructed eDEM achieves a vertical accuracy of about 7 times better than RAMPv2 DEM and 1.5 times better than CartoDEM. After using accurate DGPS data for accuracy assessment, the approximation to the actual surface of the eDEM extracted here is much more accurate with least mean root mean square error (RMSE) of 9.22 m than that constructed by using only CartoDEM (RMSE = 14.15 m) point elevation data and RAMPv2 (RMSE = 69.48 m) point elevation data. Our results indicate that, the overall trend of accuracy for the interpolation methods for generating continuous elevation surface from CartoDEM + RAMPv2 point elevation data, based on RMSE, is as follows: GP1 > IDW > GP2 > OK > LP2 > DK > LP1 > RBF > SK > UK. In case of cokriging interpolation methods, OCoK yields more accurate eDEM with the least RMSE of 8.16 m, which can be utilized to generate a highly accurate DEM of the research area.. Based on this work, it is inferred that GP2 and OCok interpolation methods and synergistic use of RAMPv2 and CartoDEM-based point elevation datasets lead to a highly accurate DEM of the study region. This research experiment demonstrates the stability (w.r.t multi-temporal datasets), performance (w.r.t best interpolation technique) and consistency (w.r.t all the experimented interpolation techniques) of synergistically fused eDEM. On the basis of average elevation difference and RMSE mentioned in present research, the newly constructed eDEM may serve as a benchmark for future elevation models such as from the ICESAT-II mission to spatially monitor ice sheet elevation.

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