A high‐accuracy map of global terrain elevations

Yamazaki, Dai; Ikeshima, Daiki; Tawatari, Ryunosuke; Yamaguchi, Tomohiro; O’Loughlin, Fiachra; Neal, Jeffrey; Sampson, Chris; Kanae, Shinjiro; Bates, Paul

doi:10.1002/2017gl072874

Cited by 996 publications

(829 citation statements)

References 45 publications

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“…Applying the RFS has two major advantages: first, it reduces run times as data exchange and computations need to be performed for a smaller number of cells; second, using RFS in large-scale applications with sufficient channel information reduces the dependency on the accuracy of remotely sensed 2-D elevation data such as Shuttle Rader Topographic Mission (SRTM) data (Farr et al, 2007). Recent research showed that such global data sets contain strong vertical bias as well as systematic and random noise (Yamazaki et al, 2017). In particular, simulating flow over vertically irregular terrain resulting in supercritical regimes is contraindicated for LFP because of its use of the LIE.…”

Section: The Computational Framework Glofrimmentioning

confidence: 99%

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

et al. 2017

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Abstract. We here present GLOFRIM, a globally applicable computational framework for integrated hydrologicalhydrodynamic modelling. GLOFRIM facilitates spatially explicit coupling of hydrodynamic and hydrologic models and caters for an ensemble of models to be coupled. It currently encompasses the global hydrological model PCR-GLOBWB as well as the hydrodynamic models Delft3D Flexible Mesh (DFM; solving the full shallow-water equations and allowing for spatially flexible meshing) and LISFLOOD-FP (LFP; solving the local inertia equations and running on regular grids). The main advantages of the framework are its open and free access, its global applicability, its versatility, and its extensibility with other hydrological or hydrodynamic models. Before applying GLOFRIM to an actual test case, we benchmarked both DFM and LFP for a synthetic test case. Results show that for sub-critical flow conditions, discharge response to the same input signal is near-identical for both models, which agrees with previous studies. We subsequently applied the framework to the Amazon River basin to not only test the framework thoroughly, but also to perform a first-ever benchmark of flexible and regular grids on a large-scale. Both DFM and LFP produce comparable results in terms of simulated discharge with LFP exhibiting slightly higher accuracy as expressed by a Kling-Gupta efficiency of 0.82 compared to 0.76 for DFM. However, benchmarking inundation extent between DFM and LFP over the entire study area, a critical success index of 0.46 was obtained, indicating that the models disagree as often as they agree. Differences between models in both simulated discharge and inundation extent are to a large extent attributable to the gridding techniques employed. In fact, the results show that both the numerical scheme of the inundation model and the gridding technique can contribute to deviations in simulated inundation extent as we control for model forcing and boundary conditions. This study shows that the presented computational framework is robust and widely applicable. GLOFRIM is designed as open access and easily extendable, and thus we hope that other large-scale hydrological and hydrodynamic models will be added. Eventually, more locally relevant processes would be captured and more robust model inter-comparison, benchmarking, and ensemble simulations of flood hazard on a large scale would be allowed for.

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Section: The Computational Framework Glofrimmentioning

confidence: 99%

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

et al. 2017

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“…This study used the MERIT DEM that Yamazaki et al (2017) produced by removing multiple error components from existing space-borne DEMs. The original MERIT DEM was developed with 3 arc second resolution by merging several baseline DEMs (Fig.…”

Section: Demmentioning

confidence: 99%

“…Iwahashi et al (2015) tried to create polygon data of terrain classification by object-based area segmentation (Baatz and Schäpe 2000) using the geometric signatures of Iwahashi and Pike (2007). In the current study, we develop this approach and introduce a trial of a new procedure of polygon-based classification using 280 m DEMs interpolated from the multi-error-removed improved-terrain DEM (MERIT DEM; Yamazaki et al 2017).…”

Section: Introductionmentioning

confidence: 99%

Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification

Iwahashi

Kamiya²,

Matsuoka

et al. 2018

Prog Earth Planet Sci

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Polygon-based terrain classification data were created globally using 280 m digital elevation models (DEMs) interpolated from the multi-error-removed improved-terrain DEM (MERIT DEM). First, area segmentation was performed globally with the logarithmic value of slope gradient and the local convexity calculated from the DEM. Next, by adding surface texture, k-means clustering was performed globally and the polygons were grouped into 40 clusters. Then, we tried to reclassify these 40 clusters into geomorphologic terrain groups. In this study, we attempted reclassification and grouping using local information from Japan as a test case. The 40 clusters were compared with Japanese geological and geomorphological data and were then reclassified into 12 groups that had different geomorphological and geological characteristics. In addition, large shape landforms, mountains, and hills were subdivided by using the combined texture. Finally, 15 groups were created as terrain groups. Cross tabulations were performed with geological or lithological maps of California and Australia in order to investigate if the Japanese grouping of the clusters was also meaningful for other regions. The classification is improved from previous studies that used 1-km DEMs, especially for the representation of terrace shapes and landform elements smaller than 1 km. The results were generally suitable for distinguishing bedrock mountains, hills, large highland slopes, intermediate landforms (plateaus, terraces, large lowland slopes), and plains. On the other hand, the cross tabulations indicate that in the case of gentler landforms under different geologic provinces/climates, similar topographies may not always indicate similar formative mechanisms and lithology. This may be solved by locally replacing the legend; however, care is necessary for mixed areas where both depositional and erosional gentle plains exist. Moreover, the limit of the description of geometric signatures still appears in failure to detect narrow valley bottom plains, metropolitan areas, and slight rises in gentle plains. Therefore, both global and local perspectives regarding geologic province and climate are necessary for better grouping of the clusters, and additional parameters or higher resolution DEMs are necessary. Successful classification of terrain types of geomorphology may lead to a better understanding of terrain susceptibility to natural hazards and land development.

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“…In the intertidal zone, we found abundant unevenness due to artificial water channels, and found that it was necessary to use elevation to determine the intertidal zone. 4 …”

Section: Resultsmentioning

confidence: 99%

“…Iwahashi et al [3] developed polygon data for global terrain classification using a combination of slope gradient, surface texture, and local convexity of the 280 m DEM interpolated from the Multi-Error-Removed Improved-Terrain (MERIT) DEM [4] . The results were generally suitable for distinguishing bedrock mountains, hills, large highland slopes, intermediate landforms (plateaus, terraces, and large lowland slopes), and plains.…”

Section: Introductionmentioning

confidence: 99%

Classification of topography in artificially modified alluvial plains using DEMs

Iwahashi¹,

Nakano²,

Yamazaki³

2018

EasyChair Preprints

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Abstract-We developed classification schemes for topography in the artificially modified alluvial plains. In order to determine the ground conditions in such areas, it is important to define the distributions of low rises such as natural levees and gentle fans. We searched for geometric signatures which did not over-emphasize the influences of artificial unevenness and were thus useful for revealing low rises on alluvial plains. Based on our findings using the highly accurate DEM for the Nobi plain, we concluded that Height Above Nearest Drainage (HAND) was most useful for detecting natural levees and gentle fans. Then we used HAND and slope gradient to produce terrain classification data for the Central Plain of Thailand using MERIT DEM in consideration to future development of global data.

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A high‐accuracy map of global terrain elevations

Cited by 996 publications

References 45 publications

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

GLOFRIM v1.0 – A globally applicable computational framework for integrated hydrological–hydrodynamic modelling

Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification

Classification of topography in artificially modified alluvial plains using DEMs

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