Golden Software Blog

Helping you learn more about the latest product information, tips, tricks, techniques, and customer stories so you can visualize data and communicate results with ease.

Gotta Plot 'em All!

A wild Zubat appeared!

Last month was the launch of Pokemon GO, an augmented reality (AR) mobile game from Niantic, the makers of the popular AR game Ingress. I must confess I've caught the fever, but I haven't caught them all! I am admittedly not a 'gamer,' and this is my first experience with Pokemon. I'm no Pokemaster, but I have fun catching new Pokemon while walking around downtown Golden on my lunch breaks, around the park, or around Denver. I haven't tried my luck battling at any Gyms yet, so I guess you could call me a casual player.

Continue reading
  2366 Hits
1 Comment
2366 Hits
  1 Comment

How to show areas of overlap of two contour maps in Surfer 13

I communicated with a user recently who wanted to find the area of overlap of one specific contour line on one contour map with a specific contour line on another contour map. In his case the first contour map was temperature and the second was rainfall. He wanted to find the area where temperature was above one value and rainfall was above another value. Whether this was for agriculture or for some other purpose I’m not sure, but it got me thinking that there could be many applications for a use like this. For example, you may have a contour map of density of one endangered species, and another for a second endangered species, and you’re trying to identify high populations of both in order to create a wildlife refuge. Or maybe you have population of people on one contour map and energy use on another, and you want to find areas with low population but high energy usage so you can send conservationists into that area to notify the population of smart practices. The uses are endless!

So that said, below are the steps to determine the area where two specific contour levels on two different maps intersect. In this case, I’ll be finding the area in Colorado where temperature is greater than 12oC and precipitation is less than 50 hundredths of inches, which may indicate an area that is more prone to wildfires. The data used in this article was obtained from NOAA. January 2015 – November 2015 data was averaged and then gridded in order to produce the attached grids.

Continue reading
  5500 Hits
9 Comments
Recent Comments
Katie Yoder
Hi Leo, Surfer does not support the creation of standard legends for contour maps so the legend at the bottom of this map was cre... Read More
Monday, 18 September 2017 09:49
Katie Yoder
Hi Leo. Yes, it is possible to overlay more than two maps in Surfer. In fact, to my knowledge there is not a limit on the number... Read More
Tuesday, 19 September 2017 11:02
Jennifer Woodson
Hi Leon, It didn't parse my formula correctly either. Maybe an image will work. Please see below. Thanks! Jennifer... Read More
Wednesday, 17 August 2016 12:42
5500 Hits
  9 Comments

Modeling Groundwater Resources in Surfer

We are pleased to present another story detailing the application of Surfer in the industry.

This story comes from former Golden Software team member, Jared King, who now works as a hydrogeologist for Knight Piésold. Mr. King and the Knight Piésold team were tasked to characterize groundwater resources for a potential mining area. An important component of the mining process, water is used for mineral processing, metal recovery, dust mitigation, and the basic needs for on-site workers. Even more importantly, a thorough understanding of groundwater resources is a major factor in understanding the environmental impact of the mine on those resources.

Continue reading
  3137 Hits
5 Comments
Recent Comments
Blakelee Mills
Hi Armandt - I can't speak to the methodology used, but let me reach out to the author to see if he can provide some insight.... Read More
Tuesday, 30 January 2018 08:54
Blakelee Mills
Hi Armandt - you can view the full article here http://www.goldensoftware.com/surfer-case-studies/modeling-groundwater-resources-s... Read More
Monday, 29 January 2018 09:14
3137 Hits
  5 Comments

UK Votes to Leave EU

The United Kingdom (UK) voted on the United Kingdom European Union membership referendum, commonly referred to as the Brexit vote, on June 23, 2016. This referendum was to gauge citizen support for whether or not to remain a member of the European Union (EU), an economic and political partnership involving 28 European countries. Overall, the UK voted 51.9% to leave the EU, with 71.8% turnout. The world reacted when the news was announced on June 24. I've spent the last two weeks reading about this historic vote and what it means for the people of the UK, the EU, and the rest of the globe. It has already had some effects on international economic markets. It remains to be determined how it will affect the future, but I find this to be a fascinating time for trade, politics, economics, and international relations.

The first thing that interested me was the demographic breakdown of the vote. Various exit and other polls were done with information about how different demographics voted. I sifted through the information available at Lord Ashcroft Polls, and noticed some clear correlations between education level and age and how an individual in the poll voted. Older voters, less educated voters, and less employed voters were more likely to vote to leave the EU. I wondered if those in less-than-ideal socioeconomic situations were looking for anything different that may help provide a higher quality of life. Another issue that caught my attention was when voters made their decisions. Nearly 25% of those polled made their decision within the week before casting their votes! Just over 1/3 always knew how they would vote. The remaining ~40% made their minds up in the last 6+ months. To me, this shows some uncertainty about how to vote or perhaps uncertainty about what the effects of the vote would be on the individual and UK.

Continue reading
  2729 Hits
2 Comments
Recent Comments
Jennifer Woodson
Hi, I had listed the bars in reverse order, but it is fixed now. Thanks for catching that! Jennifer Woodson... Read More
Thursday, 21 July 2016 10:21
2729 Hits
  2 Comments

Visualizing the Bolder Boulder

On Memorial Day 2016, the 38th annual Bolder Boulder 10K race took place in Boulder, Colorado. As the 3rd largest road race in the country (2nd largest 10K), this race brings a flock of amateur and professional runners alike to Boulder every Memorial Day. Last year, 45,000 people finished the race (52,015 participated), and 70,000 spectators descended on the city, as well. Golden Software founder Pat Madison runs this race each year with his daughter Emily Madison, and my husband and various other friends and family members have run it regularly as well. Since this race is near and dear to my heart, I thought it would be fun to plot up some maps and graphs of various Bolder Boulder statistics.

This map of the 50 largest road races in 2015 shows a symbol at the location of each race. The symbol is sized by the total number of finishers in the race, and colored based on the distance of the race. Purple coloring indicates the state hosts one or more of these races.

Continue reading
  2513 Hits
0 Comments
2513 Hits
  0 Comments

Subscribe To Our Blog

Most Popular

As many of us earth and atmospheric scientists already know, seismic activity in Oklahoma has increa...
I recently took a trip to Tennessee to attend the 14th annual Bonnaroo Music and Arts Festival. The ...
Today's Surfer 13 new feature series article discusses querying attributes of objects in base map la...

Exceeding expectations

Go to top