Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin–Upper Tons Basin, Indian Himalayas

Das, Sayantan; Patel, Priyank Pravin; Sengupta, Somasis

doi:10.1186/s40064-016-3207-0

Cited by 81 publications

(23 citation statements)

References 137 publications

(151 reference statements)

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“…In the present work, ASTER GDEM v2, is used as downloaded from the LP DAAC at one arc sec resolution (30 m) [41]. In comparison with other free DEMs, Aster GDEM has lower RMS errors in mountainous areas [42,43] and since Greece is such an area we decided to use it for the watersheds extraction. Aster GDEM was clipped to the extent of the study area of Greece and re-projected to the Hellenic Geodetic Reference System '87 (HGRS'87).…”

Section: Drainage Basins Extractionmentioning

confidence: 99%

Evidence of Hierarchy in the Drainage Basins Size Distribution of Greece Derived from ASTER GDEM-v2 Data

Vallianatos

Kouli

2019

Applied Sciences

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The drainage basins of Greece are analyzed in terms of hierarchy and discussed in view of Tsallis Entropy. This concept has been successfully used in a variety of complex systems, where fractality, memory and long-range interactions are dominant. The analysis indicates that the statistical distribution of drainage basins' area in Greece, presents a hierarchical pattern that can be viewed within the frame of non-extensive statistical physics. Our work was based on the analysis of the ASTER GDEM v2 Digital Elevation Model of Greece, which offers a 30 m resolution, creating an accurate drainage basins' database. Analyzing the drainage size (e.g., drainage basin area)-frequency distribution we discuss the connection of the observed power law exponents with the Tsallis entropic parameters, demonstrating the hierarchy observed in drainage areas for the set created for all over Greece and the subsets of drainages in the internal and external Hellenides that are the main tectonic structures in Greece. Furthermore, we discuss in terms of Tsallis entropy, the hierarchical patterns observed when the drainages are classified according to their relief or the Topographic Position Index (TPI). The deviation of distribution from power law for large drainages area is discussed.Appl. Sci. 2020, 10, 248 2 of 18 activity. As a result the complex interaction between earth's surface and tectonic processes plays a key role in geomorphological evolution [7]. Tectonic activity generates complex relief that controls surface processes such as erosion patterns, drainage network development, sedimentary basin growth, and local climate [8][9][10][11][12]. Moreover, erosion, transport and sedimentation induce large mass transfer that changes the dynamical equilibrium of orogenic wedges and trigger mechanical actions [8,13]. The continuous evolution of the aforementioned processes, in a dynamical non-linear feedback indicates a system in a dynamical non-equilibrium stage where long-range interactions and memory effects are dominant.In this context, geomorphologists have studied the evolution of drainages in time and found it to be driven by local conditions due to erosion, natural damming, tectonic motion, as well as volcanic activity [14][15][16]. A drainage basin is an area of land that drains all the streams and rainfall to a common outlet such as the outflow of a reservoir, mouth of a bay, or any point along a stream channel. Drainage basins as conceptual or physical entities are used in water management [17,18], landsliding processes control [19] and flood control [20,21].According to Strahler and Strahler [22], the development of a drainage system (i.e., a stream network and its drainage basin) can be described as follows: Initially, the stream is established on a land surface dominated by landforms of tectonic activity. In a next stage, the channels are deepening due to gradation resulting in steep gorges while the stream tributaries extend into the land carrying out a drainage basin and transforming the landscape into a fluvial landform...

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Section: Drainage Basins Extractionmentioning

confidence: 99%

Evidence of Hierarchy in the Drainage Basins Size Distribution of Greece Derived from ASTER GDEM-v2 Data

Vallianatos

Kouli

2019

Applied Sciences

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“…Another advantage is that the SRTM images are not affected by clouds. However, the SRTM, as the ASTER, is also not able to penetrate the vegetation (Das et al, 2016;Sefercik, 2012).…”

Section: The Gdemsmentioning

confidence: 99%

Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data

Monteiro

Fonte

Lima

2018

Journal of Hydrology and Hydromechanics

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Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data.

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“…Many studies have evaluated the vertical elevation accuracy of various DEM datasets using ground truth points of known accurate elevations [14] and pairwise comparisons of different DEMs and/or their surface derivatives (e.g., slope and aspect) by means of conventional statistical metrics, such as root mean square error (RMSE) or mean difference (MD) [25,69]. Other researchers have assessed different DEMs' vertical accuracy by evaluating the channel network-derived geomorphometric parameters [69][70][71][72].…”

Section: Introductionmentioning

confidence: 99%

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

et al. 2019

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Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and –0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.

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Evaluation of different digital elevation models for analyzing drainage morphometric parameters in a mountainous terrain: a case study of the Supin–Upper Tons Basin, Indian Himalayas

Cited by 81 publications

References 137 publications

Evidence of Hierarchy in the Drainage Basins Size Distribution of Greece Derived from ASTER GDEM-v2 Data

Evidence of Hierarchy in the Drainage Basins Size Distribution of Greece Derived from ASTER GDEM-v2 Data

Improving the positional accuracy of drainage networks extracted from Global Digital Elevation Models using OpenstreetMap data

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

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