Verification of the Vertical Error in C-Band SRTM DEM Using ICESat and Landsat-7, Otter Tail County, MN

Bhang, Kon Joon; Schwartz, Franklin W.; Braun, Alexander

doi:10.1109/tgrs.2006.885401

Cited by 138 publications

(95 citation statements)

References 16 publications

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“…This shift was removed by an adjustment of the reference coordinated from the SRTM DEM dataset. As the ICESat elevation is referred to the TOPEX/Poseidon Ellipsoid we subtracted the geoid height provided in the ICESat data records and applied a conversion to the WGS84 ellipsoid following [43] to obtain an elevation coherent with the elevation contained in the SRTM DEM dataset. The error ranges were estimated following [44].…”

Section: Vertical Elevation Differences Derived By Icesatmentioning

confidence: 99%

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

et al. 2015

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Frequently occurring landslides in Ethiopia endanger rapidly expanding settlements and infrastructure. We investigated a large landslide on the western escarpment of the Main Ethiopian Rift close to Debre Sina. To understand the extent and amplitude of the movements, we derived vectors of horizontal displacements by feature matching of very high resolution satellite images (VHR). The major movements occurred in two phases, after the rainy seasons in 2005 and 2006 reaching magnitudes of 48˘10.1 m and 114˘7.2 m, respectively. The results for the first phase were supported by amplitude tracking using two Envisat/ASAR scenes from the 31 July 2004 and the 29 October 2005. Surface changes in vertical direction were analyzed by subtraction of a pre-event digital elevation model (DEM) from aerial photographs and post-event DEM from ALOS/PRISM triplet data. Furthermore, we derived elevation changes using satellite laser altimetry measurement acquired by the ICESat satellite. These analyses allowed us to delineate the main landslide, which covers an area of 6.5 km 2 , shallow landslides surrounding the main landslide body that increased the area to 8.5 km 2 , and the stable area in the lower part of the slope. We assume that the main triggering factor for such a large landslide was precipitation cumulated over several months and we suspect that the slope failure will progress towards the foot of the slope.

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Section: Vertical Elevation Differences Derived By Icesatmentioning

confidence: 99%

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

et al. 2015

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“…where ICESat_elevation is the data referenced to the WGS84 ellipsoid, ICESat_elevation_Topex and EGM96_geoid are directly retrieved from ICESat/GLA14 data, and the 0.7 m is the offset from Topex ellipsoid to WGS84 ellipsoid [43]. Because of the impact of atmospheric conditions and heterogeneity in land surface, statistical analysis is usually indispensable to further remove some outliers caused by these factors.…”

Section: Icesat Data Processingmentioning

confidence: 99%

Monitoring the Fluctuation of Lake Qinghai Using Multi-Source Remote Sensing Data

Zhu

Jia

2014

Remote Sensing

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Abstract:The knowledge of water storage variations in ungauged lakes is of fundamental importance to understanding the water balance on the Tibetan Plateau. In this paper, a simple framework was presented to monitor the fluctuation of inland water bodies by the combination of satellite altimetry measurements and optical satellite imagery without any in situ measurements. The fluctuation of water level, surface area, and water storage variations in Lake Qinghai were estimated to demonstrate this framework. Water levels retrieved from ICESat (Ice, Cloud, and and Elevation Satellite) elevation data and lake surface area derived from MODIS (Moderate Resolution Imaging Spectroradiometer) product were fitted by linear regression during the period from 2003 to 2009 when the overpass time for both of them was coincident. Based on this relationship, the time series of water levels from 1999 to 2002 were extended by using the water surface area extracted from Landsat TM/ETM+ images as inputs, and finally the variations of water volume in Lake Qinghai were estimated from 1999 to 2009. The overall errors of water levels retrieved by the simple method in our work were comparable with other globally available test results with r = 0.93, MAE = 0.07 m, and RMSE = 0.09 m. The annual average rate of increase was 0.11 m/yr, which was very close to the results obtained from in situ measurements. High accuracy was obtained in the estimation of surface areas. The MAE and RMSE were only 6 km 2 , and 8 km 2 , respectively, which were even lower than the MAE and RMAE of surface area extracted from Landsat TM images. The estimated water volume variations effectively captured the trend of annual OPEN ACCESSRemote Sens. 2014, 6 10458 variation of Lake Qinghai. Good agreement was achieved between the estimated and measured water volume variations with MAE = 0.4 billion m 3 , and RMSE = 0.5 billion m 3 , which only account for 0.7% of the total water volume of Lake Qinghai. This study demonstrates that it is feasible to monitor comprehensively the fluctuation of large water bodies based entirely on remote sensing data.

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“…The advantage of the SRTMderived DEM is the homogeneous quality of topographic information due to consistency in data collection and analysis. This consistency overcomes the limitations of other global elevation datasets (for instance, ETOP05, GTOPO30, GLOBE), which are constructed using various techniques and datasets, and so have different accuracies in different regions (Bhang et al, 2007). The SRTM DEM is available on a 90 m × 90 m spatial grid and with less than 16 m absolute vertical height error (30 m × 30 m SRTM DEM is currently only available for continental US) (Farr and Kobrick, 2000;Falorni et al, 2005;Bhang et al, 2007).…”

Section: Introductionmentioning

confidence: 95%

Quantitative analysis of InSAR digital elevation models for identification of areas with different tectonic activities in southern Italy

Martino

Nico

2008

Earth Surf Processes Landf

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This work presents the results of a quantitative analysis of an interferometric SAR (InSAR) digital elevation model (DEM), obtained by the Shuttle Radar Topography Mission (SRTM). The analysis aims to identify additional parameters to recognize areas in southern Italy with different tectonic activities and behaviours. The axial zone of the Campania-Lucania Apennine and the Sila Massif in Calabria, Italy, characterized by quite different evolutionary histories, have been chosen as test areas sufficiently wide to validate observations on a sub-regional scale at least. Geomorphological information on the shape of palaeosurfaces has been used to estimate uplift and/or erosion amounts and rates. Palaeosurfaces are identified on the DEM as regions with an altitude higher than 1000 m a.s.l. and sub-planar land surfaces dipping less than 6°. Information about the shape of palaeosurfaces during the first stage of uplift and before the tectonic-induced block fragmentation has been extracted. A fragmentation index has been computed for these erosional surfaces. The first stage of this landscape evolution has been studied in terms of the geometric characteristics of fragmented blocks. The last erosional stage has been recognized in terms of both geometric characteristics and fragmentation index of the sub-horizontal land surfaces. Altitude and age of the palaeosurfaces, referred to ancient base-levels of the erosion, have been used to estimate the erosional rate.

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Verification of the Vertical Error in C-Band SRTM DEM Using ICESat and Landsat-7, Otter Tail County, MN

Cited by 138 publications

References 16 publications

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

Remote Sensing for Characterisation and Kinematic Analysis of Large Slope Failures: Debre Sina Landslide, Main Ethiopian Rift Escarpment

Monitoring the Fluctuation of Lake Qinghai Using Multi-Source Remote Sensing Data

Quantitative analysis of InSAR digital elevation models for identification of areas with different tectonic activities in southern Italy

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