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Summary statistics for elevation

Summary statistics for elevation

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In this work we have used SRTM 90 and 30m, ASTER 30m and 60 cm Google Earth (GE) based elevation data generated using online tool Terrain Zonum, validation was performed with respect to Survey of India (SOI) toposheet. These results are important for those areas where limited field data are available. It also provides a benchmark for validation of...

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Context 1
... overall statistics of elevation is maximum, minimum, mean and standard deviation of elevation values are obtained to examine differences in elevation in different DEM. Results are presented in Table 2. Table 2, there is a little change in the computed statistics for elevation where the percentage change around 0.54 % between the highest (from SRTM 90m and ASTER 30m) and lowest (from GE) value for the maximum elevation where maximum elevation values exhibited 2770m computed from the SRTM 90m and ASTER 30m DEM, and 2768m computed from the 30m SRTM DEM. ...
Context 2
... overall statistics of elevation is maximum, minimum, mean and standard deviation of elevation values are obtained to examine differences in elevation in different DEM. Results are presented in Table 2. Table 2, there is a little change in the computed statistics for elevation where the percentage change around 0.54 % between the highest (from SRTM 90m and ASTER 30m) and lowest (from GE) value for the maximum elevation where maximum elevation values exhibited 2770m computed from the SRTM 90m and ASTER 30m DEM, and 2768m computed from the 30m SRTM DEM. This indicates that with the digital elevation models that have smallest cell size the maximum elevation becomes slightly underestimated. ...

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Citations

... In relation to the assessment, a clear formulation of the comparison method to be followed is lacking, but the majority of the papers offer a ranking of the GDEM analyzed (e.g., [65,[107][108][109][110]), although very few propose some kind of procedure to combine various analysis perspectives in a metric that allows ordering of the analyzed GDEMs ( [68,111]). There are numerous cases in which several criteria are used, but without resulting in an ordering of the available GDEM. ...
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From an extensive search of papers related to the comparison of Global Digital Elevation Models (hereinafter GDEMs), an analysis is carried out that aims to answer several questions such as: Which GDEMs have been compared? Where have the comparisons been made? How many comparisons have been made? How have the assessments been carried out? Which is the GDEM option with the lowest RMSE? Analysis shows that SRTM and ASTER are the most popular GDEMs, that the countries where more comparisons have been made are Brazil, India, and China, and that the main type of reference data for evaluations is the use of points surveyed by GNSS techniques. A variety of criteria have been found for the comparison of GDEMs, but the most used are the RMSE and the standard deviation of the elevation error. There are numerous criteria with a more user-centric character in thematic areas, such as morphometry, geomorphology, erosion, etc. However, in none of the thematic areas does there exist a standard method of comparison. This limits the possibilities of establishing a ranking of GDEMs based on their user-focused quality. In addition, the methods and reference data set are not adequately explained or shared, which limits the interoperability of the studies carried out and the ability to make robust comparisons between them.
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