DEM是数字高程模型的英文简称(Digital Ele2vation Model)是流域地形、地物识别的重要原始资料。DEM 的原理是将流域划分为m 行n列的四边形(CELL),计算每个四边形的平均高程,然后以二维矩阵的方式存储高程。由于DEM 数据能够反映一定分辨率的局部地形特征,因此通过DEM 可提取大量的地表形态信息,这些信息包含流域网格单元的坡度、坡向以及单元格之间的关系等。同时根据一定的算法可以确定地表水流路径、河流网络和流域的边界。因此从DEM 提取流域特征,一个良好的流域结构模式是设计算法的前提和关键。
\n\n数据包括:
\n\n1:1KM基础DEM
\n\n根据中国1:25万等高线和高程点形成的数据,包括DEM、山影、坡度、坡向图
\n\n2、SRTM 1km DEM
\n\n切割自全球1KM的SRTM数据,包括DEM、山影、坡度、坡向图
\n\n3、Aster GDEM
\n\n根据30米Aster GDEM,拼接、切割、重采样成1KM
\n\n文件格式都为:geotiff
\n\n数据集投影：
\n\nProjection = Albers Conical Equal Area\",
\n\nGEOGCS[\"Krasovsky\",
\n\nDATUM[\"Krasovsky\", SPHEROID[\"Krasovsky\",6378245,298.3000003760163]],
\n\nPRIMEM[\"Greenwich\",0],
\n\nUNIT[\"degree\",0.0174532925199433]],
\n\nPROJECTION[\"Albers_Conic_Equal_Area\"],
\n\nPARAMETER[\"standard_parallel_1\",25],
\n\nPARAMETER[\"standard_parallel_2\",47],
\n\nPARAMETER[\"latitude_of_center\",0],
\n\nPARAMETER[\"longitude_of_center\",105],
\n\nPARAMETER[\"false_easting\",0],
\n\nPARAMETER[\"false_northing\",0],
\n\nUNIT[\"metre\",1,]
", "ds_source": "中国1:25万等高线和高程点、全球1KM的SRTM数据、30米Aster GDEM。
", "ds_process_way": "拼接、切割、重采样
", "ds_quality": "数据集通过严格的人工审核控制质量
", "ds_acq_start_time": null, "ds_acq_end_time": null, "ds_acq_place": "中国", "ds_acq_lon_east": 135.5, "ds_acq_lat_south": 17.8, "ds_acq_lon_west": 73.2, "ds_acq_lat_north": 53.86666666666667, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 19977150, "ds_files_count": 2, "ds_format": "GeoTIFF", "ds_space_res": "1000.0m", "ds_time_res": "", "ds_coordinate": "WGS84", "ds_projection": "Albers", "ds_thumbnail": "ba0e4b6b-8fef-4eec-9c84-81646f266282.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "None", "ds_from_station": null, "organization_id": "9c4867b1-5cb1-4de0-abeb-df42547bf41e", "ds_serv_man": "李红星", "ds_serv_phone": "0931-4967287", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.4510" ], "quality_level": 3, "publish_time": "2020-12-30 11:23:03", "last_updated": "2024-04-28 16:22:19", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.ncdc.Westdc.2020.393", "license": null, "i18n": { "en": { "title": "Data set of 1 km resolution DEM in China", "ds_format": "GeoTIFF", "ds_source": "1:250000 contour lines and elevation points in China, 1 km SRTM data in the world, 30 m aster GDEM
", "ds_quality": "Data set quality control through strict manual audit
", "ds_ref_way": "", "ds_abstract": "DEM (digital elevation model) is the abbreviation of digital elevation model, which is an important original data for watershed terrain and feature recognition. The principle of DEM is to divide the watershed into M rows and N columns of quadrilateral (cell), calculate the average elevation of each quadrilateral, and then store the elevation in a two-dimensional matrix. Because DEM data can reflect the local terrain features of a certain resolution, a large number of surface morphology information can be extracted by DEM, which includes the slope, slope direction and the relationship between cells. At the same time, the surface water flow path, river network and watershed boundary can be determined by certain algorithm. Therefore, to extract basin features from DEM, a good basin structure model is the premise and key of the design algorithm.
\nData include:
\n1: 1km basic DEM
\nData from 1:250000 contours and elevation points in China, including DEM, mountain shadow, slope and aspect map
\n2、SRTM 1km DEM
\nSRTM data cut from 1km around the world, including DEM, mountain shadow, slope and aspect map
\n3、Aster GDEM
\nSplicing, cutting and resampling to 1km according to 30m aster GDEM
\nThe file format is: geotif
\nDataset projection:
\nProjection = Albers Conical Equal Area\",
\nGEOGCS[\"Krasovsky\",
\nDATUM[\"Krasovsky\", SPHEROID[\"Krasovsky\",6378245,298.3000003760163]],
\nPRIMEM[\"Greenwich\",0],
\nUNIT[\"degree\",0.0174532925199433]],
\nPROJECTION[\"Albers_Conic_Equal_Area\"],
\nPARAMETER[\"standard_parallel_1\",25],
\nPARAMETER[\"standard_parallel_2\",47],
\nPARAMETER[\"latitude_of_center\",0],
\nPARAMETER[\"longitude_of_center\",105],
\nPARAMETER[\"false_easting\",0],
\nPARAMETER[\"false_northing\",0],
\nUNIT[\"metre\",1,]
", "ds_time_res": "", "ds_acq_place": "China", "ds_space_res": "1000.0m", "ds_projection": "Albers", "ds_process_way": "Splicing, cutting, resampling
", "ds_ref_instruction": "In order to respect intellectual property rights, protect the rights and interests of data authors, expand the services of data centers, and evaluate the application potential of data, data users are requested to clearly indicate the data source and data authors in the research results (including published papers, works, data products and unpublished research reports, data products, etc.) produced by using data. For data reprinted (secondary or multiple releases), the author must also indicate the source of the original data." } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "ds_topic_tags": [ "DEM" ], "ds_subject_tags": [ "自然地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "中国", "中国区域，" ], "ds_time_tags": [], "ds_contributors": [ { "true_name": "康建芳", "email": "kangjf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "吴立宗", "email": "wulizong@pric.org.cn", "work_for": "国家极地科学数据中心", "country": "中国" } ], "ds_managers": [ { "true_name": "敏玉芳", "email": "myf@lzb.ac.cn", "work_for": "中国科学院西北生态环境资源研究院", "country": "中国" } ], "category": "基础地理" }