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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!



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 >

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

Blazing a trail: SaraniaSat-led Team Shapes the Future of Space-Based Analytics

10/13/2025

On July 24, 2025, a unique international partnership of SaraniaSat, NV5 Geospatial Software, BruhnBruhn Innovation (BBI), Netnod, and Hewlett Packard Enterprise (HPE) achieved something unprecedented: a true demonstration of cloud-native computing onboard the International Space Station (ISS) (Fig. 1). Figure 1. Hewlett... Read More >

NV5 at ESA’s Living Planet Symposium 2025

NV5 at ESA’s Living Planet Symposium 2025

9/16/2025

We recently presented three cutting-edge research posters at the ESA Living Planet Symposium 2025 in Vienna, showcasing how NV5 technology and the ENVI® Ecosystem support innovation across ocean monitoring, mineral exploration, and disaster management. Explore each topic below and access the full posters to learn... Read More >

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

Monitor, Measure & Mitigate: Integrated Solutions for Geohazard Risk

9/8/2025

Geohazards such as slope instability, erosion, settlement, or seepage pose ongoing risks to critical infrastructure. Roads, railways, pipelines, and utility corridors are especially vulnerable to these natural and human-influenced processes, which can evolve silently until sudden failure occurs. Traditional ground surveys provide only periodic... Read More >

Geo Sessions 2025: Geospatial Vision Beyond the Map

Geo Sessions 2025: Geospatial Vision Beyond the Map

8/5/2025

Lidar, SAR, and Spectral: Geospatial Innovation on the Horizon Last year, Geo Sessions brought together over 5,300 registrants from 159 countries, with attendees representing education, government agencies, consulting, and top geospatial companies like Esri, NOAA, Airbus, Planet, and USGS. At this year's Geo Sessions, NV5 is... 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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