System and method for importing NetCDF data

#Methods and systems disclosed herein relate generally to accessing and importing data, and more particularly to accessing Network Common Data Format (NetCDF) datasets and importing those datasets into geospatial map displays.

#NetCDF is an Application Programming Interface (API) that is used to manage array-based scientific data in a machine-independent format. A variety of data types are typically stored in NetCDF files such as single-point observations, time series, regular-spaced grids, and satellite or radar images. The API is intended to provide a common data access method for all applications that generate and/or make use of NetCDF data.

#Oceanographers plan and monitor the use of underwater gliders to collect environmental data and use numerical model forecasts stored in NetCDF files to study the effects of environmental forces on glider missions. The datasets provided within a numerical model forecast range from two-dimensional scalar to four-dimensional vector information. Physical aspects provided in these datasets that affect vehicle mission planning and monitoring include temperature, salinity and current magnitude and direction. Being able to import these datasets into a Geospatial Information System (GIS) for analysis is crucial to safe and successful operation of these vehicles.

#Referring now to the drawings, in which like numerals represent like elements, aspects of the exemplary embodiments will be described in connection with the drawing set.

#FIG. 1 is a schematic block diagram of one embodiment of the system of the present embodiment;

#FIG. 2 is a flowchart of one embodiment of the method of the present embodiment;

#The problems set forth above as well as further and other problems are solved by the present teachings. These solutions and other advantages are achieved by the various embodiments of the teachings described herein below.

#Referring now to FIG. 1, system 300 for populating a map in a geospatial environment from NetCDF data can include, but is not limited to including, characteristics processor 303 automatically determining characteristics 311 of the NetCDF data 107, display processor 309 automatically displaying characteristics 311 for interactive modification of characteristics 311, and scalar/vector processor 321 automatically distinguishing NetCDF data 107 that are scalar values from NetCDF data 107 that are vector values and setting S/V flag 315 accordingly. Characteristics processor 303 can automatically determine the extent of NetCDF data 107, and can automatically determine the resolution of NetCDF data 107. System 300 can further include index map processor 310 automatically creating index map 317 in computer memory, data extractor 323 automatically extracting a subset of NetCDF data 107 based on modified characteristics 313 and index map 317, the subset being extracted in three or four dimensions, depending on the value of S/V flag 315, i.e. whether the NetCDF data are scalar values or vector values, respectively. The four dimensions can include u and v components of the vector values, depth, and time. The three dimensions can include a scalar value, depth, and time. Data extractor 323 can automatically provide extracted subset 319 to geospatial environment 329 to create map 327. System 300 can still further include table-of-contents processor 325 automatically manipulating table of contents 330 in geospatial environment 329 by creating TOC info 331 to reference extracted subset 319 directly. NetCDF data 107 can include a plurality of files. Data extractor 323 can automatically perform time-depth averaging on the extracted subset, export extracted subset 319 to a KML format, request from the geospatial environment the u and v components associated with each of the depths at each of the times, calculate a magnitude and a direction of the vector values based on the u and v components, create two-dimensional arrays, and automatically compute time-depth averages over the extracted subset, storing intermediate values of the time-depth averages in the two-dimensional arrays. Table-of-contents processor 325 can identify extracted subset 319 as a string representative of a hierarchy, and can store the string in table of contents 330 according to the hierarchy.

#Referring now primarily to FIG. 2, method 350 for populating map 327 (FIG. 1) in geospatial environment 329 (FIG. 1) from NetCDF data 107 (FIG. 1), which can optionally include a plurality of files, can include, but is not limited to including, the steps of automatically determining 351 characteristics 303 (FIG. 1) of NetCDF data 107 (FIG. 1), automatically displaying 353 characteristics 311 (FIG. 1) for interactive modification of characteristics 311 (FIG. 1), automatically distinguishing 355 NetCDF data 107 (FIG. 1) that are scalar values from NetCDF data 107 (FIG. 1) that are vector values, automatically creating 357 index map 317 (FIG. 1) in computer memory, automatically extracting 359 a subset of NetCDF data 107 (FIG. 1) based on modified characteristics 313 (FIG. 1) and index map 317 (FIG. 1), the subset 319 (FIG. 1) being extracted in three or four dimensions, depending on whether NetCDF data 107 (FIG. 1) are scalar values or vector values, respectively. The four dimensions can include, but are not limited to including u and v components of the vector values, depth, and time. The three dimensions can include, but are not limited to including a scalar value, depth, and time. Method 350 can further include the steps of automatically providing 361 extracted subset 319 (FIG. 1) to geospatial environment 329 (FIG. 1) to create map 327 (FIG. 1), and automatically manipulating 363 table of contents 330 (FIG. 1) in geospatial environment 329 (FIG. 1) to reference extracted subset 319 (FIG. 1) directly. Method 350 can optionally include the steps of automatically determining the extent of NetCDF data 107 (FIG. 1) and automatically determining the resolution of NetCDF data 107 (FIG. 1). Method 350 can further optionally include the steps of automatically performing time-depth averaging on extracted subset 319 (FIG. 1), automatically exporting extracted subset 319 (FIG. 1) to a KML format, automatically storing extracted subset 319 (FIG. 1) on a computer-readable medium, requesting from geospatial environment 329 (FIG. 1) the u and v components associated with each of the depths at each of the times, calculating a magnitude and a direction of the vector values based on the u and v components, automatically creating two-dimensional arrays, and automatically computing time-depth averages over extracted subset 319 (FIG. 1), storing intermediate values of the time-depth averages in the two-dimensional arrays. The step of manipulating can include, but is not limited to including, the steps of identifying extracted subset 319 (FIG. 1) as a string representative of a hierarchy, and storing the string in table of contents 330 according to the hierarchy.