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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!



Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

Not All Supernovae Are Created Equal: Rethinking the Universe’s Measuring Tools

6/3/2025

Rethinking the Reliability of Type 1a Supernovae   How do astronomers measure the universe? It all starts with distance. From gauging the size of a galaxy to calculating how fast the universe is expanding, measuring cosmic distances is essential to understanding everything in the sky. For nearby stars, astronomers use... Read More >

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

Using LLMs To Research Remote Sensing Software: Helpful, but Incomplete

5/26/2025

Whether you’re new to remote sensing or a seasoned expert, there is no doubt that large language models (LLMs) like OpenAI’s ChatGPT or Google’s Gemini can be incredibly useful in many aspects of research. From exploring the electromagnetic spectrum to creating object detection models using the latest deep learning... Read More >

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

From Image to Insight: How GEOINT Automation Is Changing the Speed of Decision-Making

4/28/2025

When every second counts, the ability to process geospatial data rapidly and accurately isn’t just helpful, it’s critical. Geospatial Intelligence (GEOINT) has always played a pivotal role in defense, security, and disaster response. But in high-tempo operations, traditional workflows are no longer fast enough. Analysts are... Read More >

Thermal Infrared Echoes: Illuminating the Last Gasp of a Dying Star

Thermal Infrared Echoes: Illuminating the Last Gasp of a Dying Star

4/24/2025

This blog was written by Eli Dwek, Emeritus, NASA Goddard Space Flight Center, Greenbelt, MD and Research Fellow, Center for Astrophysics, Harvard & Smithsonian, Cambridge, MA. It is the fifth blog in a series showcasing our IDL® Fellows program which supports passionate retired IDL users who may need support to continue their work... Read More >

A New Era of Hyperspectral Imaging with ENVI® and Wyvern’s Open Data Program

A New Era of Hyperspectral Imaging with ENVI® and Wyvern’s Open Data Program

2/25/2025

This blog was written in collaboration with Adam O’Connor from Wyvern.   As hyperspectral imaging (HSI) continues to grow in importance, access to high-quality satellite data is key to unlocking new insights in environmental monitoring, agriculture, forestry, mining, security, energy infrastructure management, and more.... Read More >

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Base 60 encoding of positive floating point numbers in IDL

Anonym

Here is an example of representing numbers efficiently using a restricted set of symbols. I am using a set of 60 symbols (or characters) to encode floating point numbers as strings of any selected length. The longer the strings are, the more precise the numbers will potentially be.

 

Here is an example of a representation, this is restricted to positive numbers, in order to keep the example short.

 
IDL> a=[14.33, 3.1415, 12345]
IDL> a
       14.330000       3.1415000       12345.000
IDL> base60(a)
FotV*
FdiDx
HdzS*
IDL> base60(a, precision=8)
FotV**aO
FdiDx*^c
HdzS****
IDL> base60(base60(a)) - a
 -4.5533356836102712e-006 -4.6258149324351905e-006    -0.016666666666424135
IDL> base60(base60(a, precision=8)) - a
 -9.2104102122902987e-012 -4.6052051061451493e-013 -7.7159711509011686e-008
 
In this example, it can be seen that the 5-digit representations are not as close to the original numbers as the 8-digit representations.
 
The code example for the base60 function is listed below.
;
; Converts from a numeric type to a base 60 representation
; Converts from a base 60 string to a floating point representation
; PRECISION is only used to determine how many symbols to use when encoding,
; and is ignored for decoding.
function Base60, input, precision=precision
  compile_opt idl2,logical_predicate
 
  ; set default precision of 5 digits for encoding only
  if ~keyword_set(precision) then precision = 5
 
  ; base 60 symbology
  symbols = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!@#$%^&*'
  base = strlen(symbols)
 
  ; fast conversion from symbol to value
  lut = bytarr(256)
  lut[byte(symbols)] = bindgen(base)
 
  if isa(input, /string) then begin
    ; convert from base60 string to float
    ; find exponent first
    scale = replicate(double(base),n_elements(input)) ^ $
      (lut[byte(strmid(input,0,1))] - base/2)
    res = dblarr(n_elements(input))
    for i=max(strlen(input))-1,1,-1 do begin
      dig = lut[byte(strmid(input,i,1))]
      res += dig
      res /= base
    endfor
    res *= scale
  endif else begin
    ; convert from float to base60 strings
    ; encode exponent(scale) first
    ex = intarr(n_elements(input))
    arr = input
    dbase = double(base)
    repeat begin
      dec = fix(arr ge 1)
      ex += dec
      arr *= dbase ^ (-dec)
      inc = fix(arr lt 1/dbase)
      ex -= inc
      arr *= dbase ^ inc
    endrep until array_equal(arr lt 1 and arr ge 1/dbase,1b)
    if max(ex) ge base/2 || min(ex) lt -base/2 then begin
      message, 'Number is outside representable range'
    endif
    bsym = byte(symbols)
    res = string(bsym[reform(ex+base/2,1,n_elements(ex))])
    for i=1,precision-1 do begin
      arr *= base
      fl = floor(arr)
      arr -= fl
      res += string(bsym[reform(fl,1,n_elements(fl))])
    endfor
  endelse
  return, res
end
 
 
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