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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!



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 >

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List extensions, part II

Anonym

(Note: This is the second part of Ron Kneusel’s discussion of his extensions to the IDL 8 list datatype.) At this point, we have extended the List class in several ways. Now, let's take a quick look at using the List class to do some symbolic math in IDL. Download the files dx_plot.pro and dx.pro. Since they use both list_extensions.pro and lisp.pro, make sure you have these, as well. This small application accepts a symbolic expression as an S-expression (the Function) and calculates the first derivative symbolically; it then plots the derivative. Before we start, note that DX_PLOT is an example of how to create an IDL application using objects. Now, let's consider a plot of the derivative of:

y = 3 cos(5x2)

which as an S-expression is written as:

(* 3 (cos (* 5 (^ x 2))))

The derivative is computed in the function DX (in dx.pro) which accepts a list representing the entered S-expression, calls DX_DERIV and then passes the derivative output list to DX_INFIX which converts it to a fully parenthesized infix expression. No simplification of the output of DX_DERIV is performed, but this does not matter since IDL will interpret it properly anyway. (For the moment we are ignoring how this happens, but see the file lambda.pro. More on LAMBDA in a future post.) The derivative is found using the standard rules:

 function dx_deriv, f compile_opt idl2 on_error, 2 case 1 of (~is_list(f)) : ans = (size(f,/type) ne 7) ? '0' : (f eq 'x') ? '1' : '0' (f[0] eq '+') : ans = list('+', dx_deriv(f[1]), dx_deriv(f[2])) (f[0] eq '-') : ans = list('-', dx_deriv(f[1]), dx_deriv(f[2])) (f[0] eq '*') : ans = list('+', list('*', dx_deriv(f[1]), f[2]), list('*', f[1], dx_deriv(f[2]))) (f[0] eq '/') : ans = list('/', list('-', list('*', dx_deriv(f[1]), f[2]), list('*', dx_deriv(f[2]), f[1])), list('*', f[2], f[2])) (f[0] eq 'sin') : ans = list('*', list('cos', f[1]), dx_deriv(f[1])) (f[0] eq 'cos') : ans = list('*', list('_', list('sin', f[1])), dx_deriv(f[1])) (f[0] eq 'tan') : ans = list('*', list('sec^2', f[1]), dx_deriv(f[1])) (f[0] eq 'exp') : ans = list('*', list('exp', f[1]), dx_deriv(f[1])) (f[0] eq 'ln') : ans = list('/', dx_deriv(f[1]), f[1]) (f[0] eq '_') : ans = list('_', dx_deriv(f[1])) (f[0] eq '^') : ans = list('*', list('*', f[2], list('^', f[1], list('-', f[2], 1))), dx_deriv(f[1])) else: ans = 'Syntax error!' endcase return, ans end

Note here how the IDL CASE statement is being used. In this form it operates exactly like the Lisp (cond ...) function which allows us to test conditions sequentially. Note also the recursive nature of the calls which automatically handle evaluating sublists and that we are using '_' (underscore) as negation reserving '-' (minus) exclusively for subtraction. Conversion to infix is done with DX_INFIX:

 function dx_infix, f compile_opt idl2 on_error, 2 case 1 of (~is_list(f)) : ans = f (f[0] eq '+') : ans = list(dx_infix(f[1]), '+', dx_infix(f[2])) (f[0] eq '-') : ans = list(dx_infix(f[1]), '-', dx_infix(f[2])) (f[0] eq '*') : ans = list(dx_infix(f[1]), '*', dx_infix(f[2])) (f[0] eq '/') : ans = list(dx_infix(f[1]), '/', dx_infix(f[2])) (f[0] eq '_') : ans = list('-', dx_infix(f[1])) (f[0] eq 'sin') : ans = list('sin(', dx_infix(f[1]),')') (f[0] eq 'cos') : ans = list('cos(', dx_infix(f[1]),')') (f[0] eq 'tan') : ans = list('tan(', dx_infix(f[1]),')') (f[0] eq 'sec^2') : ans = list('(1.0/cos(', dx_infix(f[1]),'))^2') (f[0] eq 'exp') : ans = list('exp(', dx_infix(f[1]),')') (f[0] eq 'ln') : ans = list('log(', dx_infix(f[1]),')') (f[0] eq '^') : ans = list(dx_infix(f[1]), '^', dx_infix(f[2])) else: ans = 'Syntax error!' endcase return, ans end

This function also makes use of the "cond" CASE statement and recursion. Lastly, the plot of the derivative is shown with the DX_PLOT application: Ron Kneusel's DX_PLOT window Since the derivative of y = 3cos(5x2) is, as an S-expression:

 ( (0 * (cos( (5 * (x ^ 2)) ))) + (3 * ( (- (sin( (5 * (x ^ 2)) ))) * ( (0 * (x ^ 2)) + (5 * ( (2 * (x ^ (2 - 1))) * 1))))))

It is not hard to add easy simplification rules to the output to remove things like multiply by 0 and 1. We leave this as an exercise for the reader. :) We have given here a potpourri of List examples. We hope that they are useful to you and encourage you to explore the power of IDL's List (and Hash!) classes. In a future post we will use List in implementing higher-order functions which brings some of the power of functional programming to IDL.

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