Suitability of spaceborne digital elevation models of different scales in topographic analysis: an example from Kerala, India

Thomas, Jobin; Prasannakumar, V.; Vineetha, P.

doi:10.1007/s12665-014-3478-0

Cited by 29 publications

(13 citation statements)

References 90 publications

(101 reference statements)

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“…Previous research has suggested topography factors should be derived from high-resolution topography information (such as 1 : 10 000 or topography contour maps with finer resolutions; Thomas et al, 2015). Topography factors based on topography maps with coarser resolutions (such as 1 : 50 000 or 30 m DEM) in the mountainous and hilly areas have large uncertainties (S. Y. .…”

Section: Sensitivity Analysis Of Topography Factors Derived From Diffmentioning

confidence: 99%

“…Previous studies have shown that the resolution of topography data source largely affected the calculated slope steepness, length, and soil loss. Thomas et al (2015) showed that the range of LS factor values derived from four sources of DEM (20 m DEM generated from 1 : 50 000 topographic maps, 30 m DEM from Advanced Spaceborne Thermal Emission and Reflection Radiometer -ASTER, 90 m DEM from SRTM, and 250 m DEM from global multi-resolution terrain elevation data -GMTED) were considerably different, which suggested the grid resolutions of factor layers are critical and determined by the data resolution used to derive the factor. S. Y. compared data sources including topographic maps at 1 : 2000, 1 : 10 000, and 1 : 50 000 scales and 30 m DEM from the ASTER V1 dataset and reported that slope steepness generated from the 30 m ASTER dataset was 64 % lower than the reference value generated from the 1 : 2000 topography map (2 m grid) for a mountainous watershed.…”

Section: The Uncertainty Of the Assessmentmentioning

confidence: 99%

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Regional soil erosion assessment based on a sample survey and geostatistics

Yin

Zhu

Wang

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Soil erosion is one of the most significant environmental problems in China. From 2010 to 2012, the fourth national census for soil erosion sampled 32 364 PSUs (Primary Sampling Units, small watersheds) with the areas of 0.2–3 km2. Land use and soil erosion controlling factors including rainfall erosivity, soil erodibility, slope length, slope steepness, biological practice, engineering practice, and tillage practice for the PSUs were surveyed, and the soil loss rate for each land use in the PSUs was estimated using an empirical model, the Chinese Soil Loss Equation (CSLE). Though the information collected from the sample units can be aggregated to estimate soil erosion conditions on a large scale; the problem of estimating soil erosion condition on a regional scale has not been addressed well. The aim of this study is to introduce a new model-based regional soil erosion assessment method combining a sample survey and geostatistics. We compared seven spatial interpolation models based on the bivariate penalized spline over triangulation (BPST) method to generate a regional soil erosion assessment from the PSUs. Shaanxi Province (3116 PSUs) in China was selected for the comparison and assessment as it is one of the areas with the most serious erosion problem. Ten-fold cross-validation based on the PSU data showed the model assisted by the land use, rainfall erosivity factor (R), soil erodibility factor (K), slope steepness factor (S), and slope length factor (L) derived from a 1 : 10 000 topography map is the best one, with the model efficiency coefficient (ME) being 0.75 and the MSE being 55.8 % of that for the model assisted by the land use alone. Among four erosion factors as the covariates, the S factor contributed the most information, followed by K and L factors, and R factor made almost no contribution to the spatial estimation of soil loss. The LS factor derived from 30 or 90 m Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) data worsened the estimation when used as the covariates for the interpolation of soil loss. Due to the unavailability of a 1 : 10 000 topography map for the entire area in this study, the model assisted by the land use, R, and K factors, with a resolution of 250 m, was used to generate the regional assessment of the soil erosion for Shaanxi Province. It demonstrated that 54.3 % of total land in Shaanxi Province had annual soil loss equal to or greater than 5 t ha−1 yr−1. High (20–40 t ha−1 yr−1), severe (40–80 t ha−1 yr−1), and extreme (> 80 t ha−1 yr−1) erosion occupied 14.0 % of the total land. The dry land and irrigated land, forest, shrubland, and grassland in Shaanxi Province had mean soil loss rates of 21.77, 3.51, 10.00, and 7.27 t ha−1 yr−1, respectively. Annual soil loss was about 207.3 Mt in Shaanxi Province, with 68.9 % of soil loss originating from the farmlands and grasslands in Yan'an and Yulin districts in the northern Loess Plateau region and Ankang and Hanzhong districts in the southern Qingba mountainous region. This methodology provides a more accurate regional soil erosion assessment and can help policymakers to take effective measures to mediate soil erosion risks.

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Section: Sensitivity Analysis Of Topography Factors Derived From Diffmentioning

confidence: 99%

Section: The Uncertainty Of the Assessmentmentioning

confidence: 99%

Regional soil erosion assessment based on a sample survey and geostatistics

Yin

Zhu

Wang

et al. 2018

Hydrol. Earth Syst. Sci.

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“…5 and ''Appendix''). The RMSE measures are paid more attention in comparing the performance of the interpolation methods (Thomas et al 2015). Except for the data in entire 2005, the IDW has the worst performance because it has the highest RMSE values in other three phases; the next are OK and UK, they have similar performance because they have almost the same RMSE values in all the phases; SK has the best performance because it has the lowest RMSE values in all the phases except for entire 2005.…”

Section: Measures Definitionmentioning

confidence: 99%

Rectification methods comparison for the ASTER GDEM V2 data using the ICESat/GLA14 data in the Lvliang mountains, China

et al. 2015

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ASTER GDEM data have high spatial resolution and wide coverage, which are significant in topographic analysis and geographic study. ICESat/GLA14 data can improve the vertical accuracy of ASTER GDEM data based on its abundant points with high vertical accuracy. It is essential to seek a proper rectification method for ASTER GDEM data. In this research, taking the Lvliang Mountains of China as the study area, proper rectification method is explored for the latest version of the ASTER GDEM data (ASTER GDEM V2 data). The ICESat/ GLA14 data are regarded as the real data, so the difference between the two datasets is the vertical error data. The key to rectify the ASTER GDEM V2 data is to seek an appropriate interpolation method to simulate a proper surface for the vertical error data. Through analysis and comparison, four interpolation methods including inverse distance weighted (IDW) method, ordinary kriging (OK) method, simple kriging (SK) method and universal kriging (UK) method are first chosen from numerous interpolation methods. Through comparing the vertical error histograms, the samples and the characteristics of the four interpolation methods, the ICESat/GLA14 data in 2005 are selected as the benchmark to rectify the ASTER GDEM V2 data. Then, the vertical error data are calculated using the difference value between the ASTER GDEM V2 data and the ICESat/GLA14 data. Under optimal configuration the vertical error, the chosen four interpolation methods are used to simulate the surface of the vertical error data. Finally, the rectified results for ASTER GDEM V2 data are achieved by adding the interpolated results to the ASTER GDEM V2 data, and the accuracy of the rectified results is appraised using the ground control points on the topographic maps. The research results show that (1) Accuracy of the rectified results is different by using various interpolation methods. The RMSE value range for all the rectified results is 19.5-26.7 m. (2) Among the four methods, SK is the best; the next are OK and UK methods, which have approximately similar performance, but the UK method is a little worse; on the whole, the IDW method has the worst performance. (3) This research not only provides the optimal parameters for different interpolation methods, but also obtains the appropriate rectification method for ASTER GDEM V2 data using ICESat/GLA14 data, which is beneficial for broader range of applications using ASTER GDEM V2 data in topographic and geographic research.

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“…This study, however, was aimed at comparing the methods of model preparation, and not transformations related to mining activity. The topic of design and comparison of terrain models in areas of mining activity has also been present in scientific studies by [10,11], whereas the issue of differences between models of the same terrain, resulting from different input data, was dealt with by the following authors: [12]. Subsidence of terrain above galleries of underground mines, as well as the problem of paludification and lake density in these areas, also with a comparison of terrain models from different periods, was the subject of research conducted in the Upper Silesian Industrial Region [13].…”

Section: Introductionmentioning

confidence: 99%

Transformations of Landscape Topography of the Bełchatów Coal Mine (Central Poland) and the Surrounding Area Based on DEM Analysis

Jaskulski

Nowak

2019

IJGI

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The authors analyze topography changes related to the construction and operation of the Bełchatów Brown Coal Open Mine and Power Plant, one of Europe’s larger open-pit mines, situated in central Poland. In order to achieve this, a DEM (Digital Elevation Model) is prepared, based on archival materials from the pre-investment period. Source materials include German topographical maps, issued in 1944 by the Supreme High Command of the German Army (Oberkommando des Heeres/Generalstab). The second model of the same area is prepared based on DEM data included in the Topographical Database available by CODGiK (Main Centre of Geodetic and Cartographic Documentation). The preparation of two terrain models from different periods make it possible to evaluate the changes in the morphometry. Both models are compared using ArcGIS (ESRI) tools. The comparative analysis of the models allows for observing topography changes resulting from anthropogenic transformations related to the construction of the Brown Coal Open Mine Bełchatów and Power Plant complex.

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Suitability of spaceborne digital elevation models of different scales in topographic analysis: an example from Kerala, India

Cited by 29 publications

References 90 publications

Regional soil erosion assessment based on a sample survey and geostatistics

Regional soil erosion assessment based on a sample survey and geostatistics

Rectification methods comparison for the ASTER GDEM V2 data using the ICESat/GLA14 data in the Lvliang mountains, China

Transformations of Landscape Topography of the Bełchatów Coal Mine (Central Poland) and the Surrounding Area Based on DEM Analysis

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