five

IISD Experimental Lakes Area: Bathymetry Data Package, 1968-2025

收藏
DataCite Commons2026-01-16 更新2026-05-03 收录
下载链接:
https://portal.edirepository.org/nis/mapbrowse?packageid=edi.1276.6
下载链接
链接失效反馈
官方服务:
资源简介:
The IISD Experimental Lakes Area (IISD-ELA) bathymetry data package provides bathymetric data on IISD-ELA lakes in a variety of formats and degrees of processing. The data package has been organized into four parts: tabular, geospatial, maps, and additional metadata. Tabular data include cumulative and interval values for area and volume at specific depth ranges, summary statistics (perimeter, surface area, total volume, mean depth, and maximum depth), and metadata for the lakes (such as water level on date of survey and methods used to collect and process the data). Geospatial data are suitable for map-making and geospatial analysis. The geospatial folder includes raw coordinate data (CSV) and processed geospatial outputs: contour lines (geodatabase and geopackage), lake polygons (geodatabase and geopackage), and raster DEMs (geodatabase and TIFF). Maps are provided in PDF format in black and white or colour. Where current maps are not available, historical maps have been provided, which are black and white scans. Additional metadata files include the Info Sheet PDF, which provides details for interpreting column names and understanding surveying and processing methods. A materials overview CSV table is provided, outlining which data types are available for each lake. A lake polygon metadata CSV table specifies which satellite imagery providers and dates were used to refine lake polygon outlines. The data package is ongoing - updated data will be provided as more lakes are surveyed and data processed. If current data do not exist for the lake you are interested in, please get in touch with us - we may be able to add a survey of that lake to our bathymetry survey schedule.
提供机构:
Environmental Data Initiative
创建时间:
2026-01-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作