X

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!



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 >

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

Comparing Amplitude and Coherence Time Series With ICEYE US GTR Data and ENVI SARscape

12/3/2025

Large commercial SAR satellite constellations have opened a new era for persistent Earth monitoring, giving analysts the ability to move beyond simple two-image comparisons into robust time series analysis. By acquiring SAR data with near-identical geometry every 24 hours, Ground Track Repeat (GTR) missions minimize geometric decorrelation,... Read More >

Empowering D&I Analysts to Maximize the Value of SAR

Empowering D&I Analysts to Maximize the Value of SAR

12/1/2025

Defense and intelligence (D&I) analysts rely on high-resolution imagery with frequent revisit times to effectively monitor operational areas. While optical imagery is valuable, it faces limitations from cloud cover, smoke, and in some cases, infrequent revisit times. These challenges can hinder timely and accurate data collection and... Read More >

Easily Share Workflows With the Analytics Repository

Easily Share Workflows With the Analytics Repository

10/27/2025

With the recent release of ENVI® 6.2 and the Analytics Repository, it’s now easier than ever to create and share image processing workflows across your organization. With that in mind, we wrote this blog to: Introduce the Analytics Repository Describe how you can use ENVI’s interactive workflows to... Read More >

Deploy, Share, Repeat: AI Meets the Analytics Repository

Deploy, Share, Repeat: AI Meets the Analytics Repository

10/13/2025

The upcoming release of ENVI® Deep Learning 4.0 makes it easier than ever to import, deploy, and share AI models, including industry-standard ONNX models, using the integrated Analytics Repository. Whether you're building deep learning models in PyTorch, TensorFlow, or using ENVI’s native model creation tools, ENVI... Read More >

1345678910Last
17029 Rate this article:
5.0

Why Can’t I “Get” My Data

Anonym

While working on a recent project, I needed to pull some data off of an ESRI server using a REST API. This is by no means a novel task, but just like many of you, this is not something I do on a daily basis. In preparation for this task, I brushed up on my IDLnetURL objects and read through the subsequent documentation. I felt as though I was adequately prepared and it was off to the races. First, I coded up my “get” call to obtain the geometry of the region I was working in (for this example I will use Utah).

oURL = obj_new('IDLnetURL')

oURL->SetProperty, $

  url_scheme='https', $

  url_host = 'sampleserver6.arcgisonline.com',$

  url_path = 'arcgis/rest/services/USA/MapServer/2/query?
text=Utah&geometryType=esriGeometryEnvelope&spatialRel
=esriSpatialRelIntersects&f=pjson'

Cords_Json = oUrl->Get(/string_array, /BUFFER)

Cords_Json = JSON_PARSE(strjoin(Cords_Json))

GeomJson = JSON_SERIALIZE(((Cords_Json['features'])[0])['geometry'])

This worked great and the next step was to find all the vectors that fell within the given region (for this example I will use counties). However, when I went back to my trusty “get” command it fell apart. 

oURL = obj_new('IDLnetURL')

oURL->SetProperty, $

  url_scheme='https', $

  url_host = 'sampleserver6.arcgisonline.com',$

  url_path = 'arcgis/rest/services/USA/MapServer/3/query?geometry='+GeomJson+'&geometryType=esriGeometryPolygon&spatialRel
=esriSpatialRelContains&outFields=*&f=json'

County_Json = oUrl->Get(/string_array)

Instead of nicely formed JSON it was HTML, and incomplete HTML at that. I found this perplexing until I realized that the “get” request has a return character limit of 2,048. This posed a problem given that in my region there are 29 vectors and each one has complex geometry with hundreds of vertices. So it was back to the drawing boards.

When performing a request-response from a client to a server, there are two options for returning data.  There is the “get” method and the “post” method. There are several subtle differences when it comes to these two methods, but for our purpose the main thing to note is that “get” returns the data you request embedded within the URL and because of that there is a limit on how long it can be. On the other hand, “post” returns it with the body of the request and thus does not have a limit. So as I’m sure you’ve already figured out, the “post” method was the answer to my problem.

oURL = obj_new('IDLnetURL')

oURL->SetProperty, $

  url_scheme='https', $

  url_host = 'sampleserver6.arcgisonline.com',$

  url_path = 'arcgis/rest/services/USA/MapServer/3/query?f
=json'

data = 'geometry='+GeomJson+'&geometryType=esriGeometryPolygon&spatialRel
=esriSpatialRelContains&outFields=*'

County_Json = oURL->Put(data, /POST, /BUFFER)

By using the “post” method over the “get” method, I was able to retrieve all of the counties and their names.

; get county names

County_Json = JSON_PARSE(County_Json, /TOSTRUCT)

County_Names = strarr(n_elements(County_Json.features))

for i = 0, n_elements(County_Json.features)-1 do County_Names[i] = (County_Json.features)[i].Attributes.name

print, County_Names, FORMAT='(a)'

Please login or register to post comments.