학술논문

Leveraging metadata conventions to improve usability of an ease-grid 2.0 passive microwave data product
Document Type
Conference
Source
2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) Geoscience and Remote Sensing Symposium (IGARSS), 2017 IEEE International. :5197-5200 Jul, 2017
Subject
Aerospace
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Geoscience
Power, Energy and Industry Applications
Signal Processing and Analysis
Metadata
Geology
Microwave imaging
Microwave FET integrated circuits
Microwave integrated circuits
Usability
Standards
Passive microwave remote sensing
Software tools
Geophysical image processing
Geospatial analysis
Language
ISSN
2153-7003
Abstract
Since 1978, a series of Earth-observing, satellite-borne passive microwave sensors has produced a rich record of microwave brightness temperatures. Passive microwave sensors can see through most clouds and collect measurements both day and night, which is especially useful in high latitudes during polar night. Passive microwave measurements are used to derive significant and meaningful climate records of many parameters, including the dramatic decline in Arctic sea ice. Earlier revisions of this significant climate record have been produced as flat, binary, gridded arrays with minimal or no file-level metadata and no machine-readable geolocation. Developed for many applications in polar regions, data were projected to polar azimuthal and global cylindrial projections that users found difficult to handle in standard mapping software packages. Funded by the NASA MEaSUREs program, we are using state-of-the-art image reconstruction techniques to produce a Calibrated Enhanced-Resolution Passive Microwave Equal-Area Scalable Earth Grid 2.0 Brightness Temperature (CETB) Earth System Data Record (ESDR) that leverages the improved EASE-Grid 2.0 projection definitions and netCDF-CF metadata conventions to improve usability of the data products. We describe our approach to defining file-level metadata that is intelligible to standard software packages, including open source netCDF Operators (NCO) and Geospatial Data Abstraction Library (gdal), and the commercial ESRI ArcMap geospatial mapping tool.