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NV5 Geospatial Blog

Each month, NV5 Geospatial posts new blog content across a variety of categories. Browse our latest posts below to learn about important geospatial information or use the search bar to find a specific topic or author. Stay informed of the latest blog posts, events, and technologies by joining our email list!



New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

New ENVI Agent, IDL Agent, and GeoAgent Quick Guides

6/9/2026

The recent release of ENVI® Agent, IDL® Agent, and GeoAgent™ revolutionize how users interact with geospatial software. These agentic AI applications act as partners to plan, simplify, and execute complex workflows. Knowing where to start can be challenging for new users. To this end, we developed three new quick guides to... Read More >

Introducing NISAR Data Support

Introducing NISAR Data Support

6/5/2026

The release of ENVI® SARscape 6.3 in April 2026 includes preliminary support for NASA-ISRO SAR (NISAR) data. The NISAR mission is a joint Earth-observing satellite project between NASA and the Indian Space Research Organization designed to monitor changes in the planet’s land and ice surfaces using advanced radar imaging. It... Read More >

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

Monitoring Illegal Mining in the Amazon: Turning Persistent Data Into Actionable Insight

5/28/2026

Illegal mining over decades has constituted one of the most persistent and complex socio-environmental problems in the Brazilian Amazon. In recent years, with the increasingly intensive use of mechanized extraction, the associated environmental impacts—such as deforestation, intense soil disturbance, river siltation, and mercury... Read More >

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

From Answers to Action: Why ENVI and IDL Agents Go Beyond General AI

4/20/2026

As generative AI tools like Claude and Gemini continue to gain traction, many organizations are asking the same question: Can general purpose AI actually support real geospatial workflows, or does it stop at surface-level answers? That question was front and center in our recent webinar, Meet Your New Partners in Science: ENVI... Read More >

Mapping Earthquake Deformation in Taiwan With ENVI

Mapping Earthquake Deformation in Taiwan With ENVI

12/15/2025

Unlocking Critical Insights With ENVI® Tools Taiwan sits at the junction of major tectonic plates and regularly experiences powerful earthquakes. Understanding how the ground moves during these events is essential for disaster preparedness, public safety, and building community resilience. But traditional approaches like field... Read More >

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Native OPeNDAP support in IDL

Anonym

OPeNDAP is an acronym for "Open-source Project for a Network Data Access Protocol." From the OPeNDAP website: “OPeNDAP provides software which makes local data accessible to remote locations regardless of local storage format.” Through Unidata’s netCDF-4 library, IDL 8.2 includes native support for OPeNDAP, though currently only on Mac OS X and Linux. Joe Lee of The HDF Group has created an example of using OPeNDAP with a community-generated IDL client. I’d like to modify (and slightly expand) his example to instead use the native OPeNDAP support in IDL 8.2. Start with the URL to an AIRS level 3 standard daily product file (HDF-EOS format) hosted on The HDF Group’s OPeNDAP-enabled server:

 IDL> url = 'http://eosdap.hdfgroup.uiuc.edu:8080/opendap/data/NASAFILES/hdf4/AIRS.2008.10.27.L3.RetStd001.v5.2.2.0.G08303124144.hdf' 

Access the file at this URL using netCDF library calls. Open the file with NCDF_OPEN, which returns an identifier (a long integer) for the file:

 IDL> file_id = ncdf_open(url)

What’s in this file? Use NCDF_INQUIRE to find the number of variables, dimensions and attributes:

 IDL> info = ncdf_inquire(file_id) IDL> help, info ** Structure <85778ac>, 4 tags, length=16, data length=16, refs=1: NDIMS           LONG                26 NVARS           LONG               274 NGATTS          LONG                 0 RECDIM          LONG                -1

There are 274 variables in this file. Use NCDF_VARIDSINQ to get identifiers for all the variables:

 IDL> var_ids = ncdf_varidsinq(file_id) IDL> help, var_ids VAR_IDS         LONG      = Array[274]

Use NCDF_VARINQ to get information about the last variable in the file:

 IDL> help, ncdf_varinq(file_id, var_ids[-1]) ** Structure <85779ec>, 5 tags, length=40, data length=40, refs=1: NAME            STRING    'TopographyU274' DATATYPE        STRING    'FLOAT' NDIMS           LONG                 2 NATTS           LONG                 3 DIM             LONG      Array[2]

Extract data from this last variable in the remote file to your IDL session. Use NCDF_VARID to get an identifier for the variable, by name (note that this string is case-sensitive), and NCDF_VARGET to actually get the data, which will be stored locally in the variable topo.

 IDL> topo_id = ncdf_varid(file_id, 'TopographyU274') IDL> ncdf_varget, file_id, topo_id, topo IDL> help, topo TOPO            FLOAT     = Array[360, 180]

We’ve successfully pulled data from the remote file into IDL! To properly visualize these data, also get their geographic coordinates:

 IDL> latitude_id = ncdf_varid(file_id, 'LatitudeU271') IDL> longitude_id = ncdf_varid(file_id, 'LongitudeU272') IDL> ncdf_varget, file_id, latitude_id, latitude IDL> ncdf_varget, file_id, longitude_id, longitude IDL> help, longitude, latitude LONGITUDE       FLOAT     = Array[360] LATITUDE        FLOAT     = Array[180]

Then close the file:

 IDL> ncdf_close, file_id

Visualize these topography data as a contour plot in a map projection:

 IDL> m = map('Miller Cylindrical', $ > color='gray', $ > label_color='black', $ > label_position=0, $ ; move labels to edges > title='AIRS.2008.10.27.L3 Topography') IDL> nlevels = 11 IDL> levels = findgen(nlevels)*500 + 250 ; meters IDL> g = contour(topo, longitude, latitude, $ > overplot=m, $ >   c_value=levels, $ >   rgb_table=33, $ >   background_color='dark blue', $ >   /fill, $ >   grid_units='degrees') IDL> c = mapcontinents(color='white') IDL> cb = colorbar(target=g, $ >   position=[0.2, 0.13, 0.85, 0.15], $ >   title='Elevation (m)')

and save the visualization to a PNG file:

 IDL> p.save, 'idl_opendap_ex.png', resolution=150 

The result (click to embiggen): AIRS topography retrieved via OPeNDAP with IDL Grab the source code for this example from here.

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