Articles written in Journal of Earth System Science
Volume 124 Issue 6 August 2015 pp 1343-1357
The Shuttle Radar Topography Mission (SRTM) carried out in February 2000 has provided near global topographic data that has been widely used in many fields of earth sciences. The mission goal of an absolute vertical accuracy within 16 m (with 90% confidence)/RMSE $\sim$10 m was achieved based on ground validation of SRTM data through various studies using global positioning system (GPS). We present a new and independent assessment of the vertical accuracy of both the X- and C-band SRTM datasets using data from the International GNSS Service (IGS) network of high-precision static GPS stations. These stations exist worldwide, have better spatial distribution than previous studies, have a vertical accuracy of 6 mm and constitute the most accurate ground control points (GCPs) possible on earth; these stations are used as fiducial stations to define the International Terrestrial Reference Frame (ITRF). Globally, for outlier-filtered data (135 X-band stations and 290 C-band stations), the error or difference between IGS and SRTM heights exhibits a non-normal distribution with a mean and standard error of 8.2 ± 0.7 and 6.9 ± 0.5 m for X- and C-band data, respectively. Continent-wise, Africa, Australia and North America comply with the SRTM mission absolute vertical accuracy of 16 m (with 90% confidence)/RMSE $\sim$10 m. However, Asia, Europe and South America have vertical errors higher than the SRTM mission goal. At stations where both the X- and C-band SRTM data were present, the root mean square error (RMSE) of both the X- and C-bands was identical at 11.5 m, indicating similar quality of both the X- and C-band SRTM data.
Volume 125 Issue 5 July 2016 pp 909-917
Global Shuttle Radar Topography Mission (SRTM) data products have been widely used in EarthSciences without an estimation of their accuracy and reliability even though large outliers exist in them.The global 1 arc-sec, 30 m resolution, SRTM C-Band (C-30) data collected in February 2000 has beenrecently released (2014–2015) outside North America. We present the first global assessment of thevertical accuracy of C-30 data using Ground Control Points (GCPs) from the International GNSS Service(IGS) Network of high-precision static fiducial stations that define the International Terrestrial ReferenceFrame (ITRF). Large outliers (height error ranging from –1285 to 2306 m) were present in the C-30dataset and 14% of the data were removed to reduce the root mean square error (RMSE) of the datasetfrom ∼187 to 10.3 m which is close to the SRTM goal of an absolute vertical accuracy of RMSE ∼10 m.Globally, for outlier-filtered data from 287 GCPs, the error or difference between IGS and SRTM heightsexhibited a non-normal distribution with a mean and standard error of 6.5 ± 0.5 m. Continent-wise,only Australia, North and South America complied with the SRTM goal. At stations where all the XandC-Band SRTM data were present, the RMSE of the outlier-filtered C-30 data was 11.7 m. However,the RMSE of outlier-included dataset where C- and X-Band data were present was ∼233 m. The resultssuggest that the SRTM data must only be used after regional accuracy analysis and removal of outliers.If used raw, they may produce results that are statistically insignificant with RMSE in 100s of meters.
Volume 130 All articles Published: 6 March 2021 Article ID 0051 Research article
The study of the Earth's topographic surface using digital topography is an important component of many problems in the Earth Sciences. The 30-m Shuttle Radar Topography Mission (SRTM) and the Advanced Land Observing Satellite (ALOS) global digital topography datasets have been the most recently available global digital topography datasets. Most users directly download the data/DEMs in their native form assuming a vertical error close to their mission goals. We demonstrate, through the use of 221 dual-frequency static Global Positioning System (GPS) independent ground control points, that the datasets typically have outliers and voids that increase the error by an order of magnitude. Filtering the voids, outliers, and correcting systematic errors significantly improved the vertical accuracy of the datasets. We concluded from our study that the ALOS data generated the most accurate DEM in the Indian subcontinent. This finding needs to be tested and confirmed worldwide for generating the best DEMs.
Volume 131, 2022
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