MERIT DEM은 기존 DEM (NASA SRTM3 DEM, JAXA AW3D DEM, Viewfinder Panoramas DEM)에서 주요 오류 구성요소를 제거하여 생성된 3초 해상도(~적도에서 90m)의 고정밀 전역 DEM입니다.
MERIT DEM은 여러 위성 데이터 세트와 필터링 기법을 사용하여 절대 편향, 스트라이프 노이즈, 스페클 노이즈, 나무 높이 편향을 분리합니다.
오류를 제거한 후 수직 정확도가 2m 이상인 지역이 39% 에서 58%로 증가했습니다. 지형 변동보다 높이 오류가 큰 평탄한 지역에서 상당한 개선이 있었으며, 하천 네트워크 및 언덕-계곡 구조와 같은 지형이 명확하게 표현되었습니다.
ODbL 1.0 라이선스: 상업적 사용은 허용되지만 MERIT DEM을 기반으로 하는 파생 데이터는 동일한 ODbL 라이선스에 따라 공개적으로 제공되어야 합니다. 예를 들어 MERIT DEM을 사용하여 홍수 위험 지도를 만들고 이를 기반으로 상업용 서비스를 제공하려면 OdBL 라이선스에 따라 위험 지도를 공개적으로 제공해야 합니다.
위 라이선스 약관은 MERIT DEM을 기반으로 한 '파생 데이터'에 적용되지만 MERIT DEM으로 만든 '제작된 작업 / 작품'(예: 학술지 논문의 그림)에는 적용되지 않습니다. 생성된 작업이 '파생 데이터'로 간주되지 않는 경우 사용자는 아트워크의 저작권을 보유할 수 있으며 라이선스를 할당할 수 있습니다.
데이터를 다운로드하고 사용하면 사용자는 이러한 라이선스 중 하나의 이용약관에 동의하는 것으로 간주됩니다. 이 무료 라이선스에도 불구하고 사용자는 저자의 명시적인 서면 허가 없이 다른 웹사이트에서 원래 형식으로 데이터를 전체적으로 재배포하지 않아야 합니다.
MERIT DEM의 저작권은 개발자가 보유합니다(2018, 모든 권리 보유).
인용
인용:
Yamazaki D., D. Ikeshima, R. Tawatari, T. Yamaguchi, F. O'Loughlin, J.C. Neal,
C.C. Sampson, S. Kanae & P.D. Bates. 전 세계 지형 고도의 정확도가 높은 지도입니다. Geophysical Research Letters, vol.44, pp.5844-5853, 2017.
MERIT DEM은 기존 DEM (NASA SRTM3 DEM, JAXA AW3D DEM, Viewfinder Panoramas DEM)에서 주요 오류 구성요소를 제거하여 생성된 3초 해상도 (~적도에서 90m)의 고정밀 전역 DEM입니다. MERIT DEM은 여러 …을 사용하여 절대 편향, 스트라이프 노이즈, 스펙클 노이즈, 트리 높이 편향을 분리합니다.
[null,null,[],[[["\u003cp\u003eMERIT DEM is a high-accuracy global digital elevation model (DEM) with a 3 arc-second resolution (~90m).\u003c/p\u003e\n"],["\u003cp\u003eIt improves accuracy by removing errors like absolute bias, stripe noise, and tree height bias from existing DEMs.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset covers the period from 1987 to 2017 and is available through Google Earth Engine.\u003c/p\u003e\n"],["\u003cp\u003eIt is licensed under CC-BY-NC 4.0 and ODbL 1.0, allowing for both non-commercial and commercial use with certain conditions.\u003c/p\u003e\n"],["\u003cp\u003eMERIT DEM was created by processing data from NASA SRTM3, JAXA AW3D, Viewfinder Panoramas, and other supplementary sources.\u003c/p\u003e\n"]]],[],null,["# MERIT DEM: Multi-Error-Removed Improved-Terrain DEM\n\nDataset Availability\n: 1987-01-01T00:00:00Z--2017-01-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [Dai Yamazaki (University of Tokyo)](http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/index.html)\n\nTags\n:\n[dem](/earth-engine/datasets/tags/dem) [elevation](/earth-engine/datasets/tags/elevation) [elevation-topography](/earth-engine/datasets/tags/elevation-topography) [merit](/earth-engine/datasets/tags/merit) [topography](/earth-engine/datasets/tags/topography) \n\n#### Description\n\nMERIT DEM a high accuracy global DEM at 3 arc second resolution (\\~90 m at\nthe equator) produced by eliminating major error components from existing DEMs\n(NASA SRTM3 DEM, JAXA AW3D DEM, Viewfinder Panoramas DEM).\n\nMERIT DEM separates absolute bias, stripe noise, speckle\nnoise and tree height bias using multiple satellite datasets and filtering techniques.\nAfter the error removal, land areas mapped with 2 m or better vertical accuracy\nwere increased from 39% to 58%. Significant improvements were found in flat regions\nwhere height errors larger than topography variability, and landscapes such as\nriver networks and hill-valley structures became clearly represented.\n\n'MERIT DEM was developed by processing the following products as baseline data:\n\n- [NASA SRTM3 DEM v2.1](https://dds.cr.usgs.gov/srtm/version2_1/SRTM3)\n- [JAXA AW3D - 30 m DEM v1](https://www.eorc.jaxa.jp/ALOS/en/aw3d30/index.htm)\n- [Viewfinder Panoramas DEM](http://www.viewfinderpanoramas.org/dem3.html)\n\nIn addition to the above baseline dems, these products were used as supplementary data:\n\n- [NASA-NSIDC ICESat/GLAS GLA14 data](https://nsidc.org/data/gla14)\n- [U-Maryland Landsat forest cover data](https://glad.earthengine.app/view/global-forest-change)\n- [NASA Global Forest height data](https://www.nasa.gov/topics/earth/features/forest-height-map.html)\n- [JAMSTEC/U-Tokyo G3WBM water body data](http://hydro.iis.u-tokyo.ac.jp/%7Eyamadai/G3WBM/index.html)\n\n### Bands\n\n**Bands**\n\n| Name | Pixel Size | Description |\n|-------|--------------|-------------------------------------------------------|\n| `dem` | 92.77 meters | Elevation in meters, referenced to EGM96 geoid model. |\n\n### Terms of Use\n\n**Terms of Use**\n\nCitation to the paper is adequate if you simply use MERIT DEM. If you\nasked for help for additional handling/editing of the dataset, or if your research\noutcome highly depends on the product, the developer would request co-authorship.\n\nMERIT DEM is licensed under a Creative Commons \"CC-BY-NC 4.0\" or\nOpen Data Commons \"Open Database License (ODbL 1.0)\". With a dual license, you\ncan choose an appropriate license for you.\n\nTo view a copy of these license, please visit:\n\n- [CC-BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/): Non-Commercial Use with less restriction.\n- [ODbL 1.0 license](https://opendatacommons.org/licenses/odbl/summary/): Commercial Use is OK, but the derived data based on MERIT DEM should be made publicly available under the same ODbL license. For example, if you create a flood hazard map using MERIT DEM and you would like to provide a COMMERCIAL service based on that, you have to make the hazard map PUBLICLY AVAILABLE under OdBL license.\n\nNote that the above license terms are applied to the \"derived data\" based\non MERIT DEM, while they are not applied to \"produced work / artwork\" created\nwith MERIT DEM (such as figures in a journal paper). The users may have a\ncopyright of the artwork and may assign any license, when the produced work\nis not considered as \"derived data\".\n\nBy downloading and using the data the user agrees to the terms and\nconditions of one of these licenses. Notwithstanding this free license, we ask\nusers to refrain from redistributing the data in whole in its original format\non other websites without the explicit written permission from the authors.\n\nThe copyright of MERIT DEM is held by the developers, 2018, all rights reserved.\n\n### Citations\n\nCitations:\n\n- Yamazaki D., D. Ikeshima, R. Tawatari, T. Yamaguchi, F. O'Loughlin, J.C. Neal,\n C.C. Sampson, S. Kanae \\& P.D. Bates. A high accuracy map of global\n terrain elevations. Geophysical Research Letters, vol.44, pp.5844-5853, 2017.\n\n [doi:10.1002/2017GL072874](https://doi.org/10.1002/2017GL072874)\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.Image('MERIT/DEM/v1_0_3');\n\nvar visualization = {\n bands: ['dem'],\n min: -3,\n max: 18,\n palette: [\n '000000', '478fcd', '86c58e', 'afc35e',\n '8f7131', 'b78d4f', 'e2b8a6', 'ffffff']\n};\n\nMap.setCenter(90.301, 23.052, 10);\n\nMap.addLayer(dataset, visualization, 'Elevation');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/MERIT/MERIT_DEM_v1_0_3) \n[MERIT DEM: Multi-Error-Removed Improved-Terrain DEM](/earth-engine/datasets/catalog/MERIT_DEM_v1_0_3) \nMERIT DEM a high accuracy global DEM at 3 arc second resolution (\\~90 m at the equator) produced by eliminating major error components from existing DEMs (NASA SRTM3 DEM, JAXA AW3D DEM, Viewfinder Panoramas DEM). MERIT DEM separates absolute bias, stripe noise, speckle noise and tree height bias using multiple ... \nMERIT/DEM/v1_0_3, dem,elevation,elevation-topography,merit,topography \n1987-01-01T00:00:00Z/2017-01-01T00:00:00Z \n-60 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [](https://doi.org/http://hydro.iis.u-tokyo.ac.jp/~yamadai/MERIT_DEM/index.html)\n- [](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/MERIT_DEM_v1_0_3)"]]
