Accessibility improved through metadata standardization.
The LTER Network Office (LNO) maintains a data archive on remote sensing that provides researchers within the LTER Network access to a variety of Earth observation imagery acquired from 1990 to 2000 and covering 25 LTER sites. To make the data more easily accessible, the LNO has started to standardize its metadata content and structure using the Ecological Metadata Language (EML). The following article describes the process and results of documenting the LNO remote sensing data archive in EML, and the registration of each EML instance in the LTER Metacat Data Catalog.
The LNO remote sensing data archive consist of roughly 400 individual data packages that include Earth observation imagery from the AVHRR, AVIRIS, Landsat TM/ETM, MODIS, and SPOT sensing platforms, in addition to various images from the Global Fiducial Library. The type of sensing platform and date of collection vary from site to site. Each package comprises the set of digital files for a specific date and location of collection from the sensing platform that the vendor distributes, including metadata, raster imagery, and any ancillary material associated with the collection. The archive file system is organized in order beginning with each site's three-letter acronym, the sensing platform, and the collection date. An example of the hierarchical structure for Landsat TM data collected on May 3, 2000 for the Sevilleta LTER is SEV/TM/20000503. This particular package contains nine raster files, three metadata files, and one JPEG browse image.
Generating the EML for the Sevilleta data for the data archive was done in two steps:
- An automated traversal of the file system to document all the remote sensing packages
- A manual update of nine EML documents with detailed metadata describing Landsat TM datasets covering the Sevilleta LTER
The metadata content documented in these two steps represent, respectively, "discovery" and "access" level EML-which are two of six categories of an ascending classification system developed by the LTER Network that is used to rate the metadata completeness of EML documents. Discovery level EML provides sufficient information for researchers to search and examine the remote sensing archive by browsing directly to the archive from the EML document; access level EML, which contains much richer metadata, enables automated searching and processing of the remote sensing data.
The LNO's remote sensing data archive has been documented successfully using EML and entered into the LTER Metacat Data Catalog. It contains 351 remote sensing data packages described by "discovery" level EML and nine packages described by "access" level EML, for a total of 360 EML documents. New or revised packages are harvested and inserted into the Metacat database on a weekly basis. The 360 documents represent the first comprehensive remote sensing data archive to exist in the Metacat database that is accessible to researchers within the LTER Network through various web-based or desktop applications.
The EML documents were first harvested and stored in the LTER Metacat Data Catalog (http://metacat.lternet.edu/das/lter/index.jsp) in January 2005. The documents' contents will be augmented with additional metadata as time permits, making the whole remote sensing archive "access" level compliant.