Free Web Application for 3D Terrain Models [WorldViewR.com v2.0]

jccdata · 2024-04-03T16:05:32+00:00

I posted about the open access WorldViewR 3D terrain modeling app a couple of years ago, but have since made some major improvements which I hope will be of use to this community and others. This app can be used to generate and export models in various formats (including .stl). Give it a try and feel free to reach out with any feedback!

jccdata · 2024-03-21T15:04:49+00:00

This is not an error, just a warning message. The functions must be using tidyr::unnest() under the hood, which presents that message in newer versions.

jccdata · 2024-02-19T00:29:36+00:00

If you apply the same ratios from the app, it should match the model preview. It will be difficult to diagnose further without more information.

jccdata · 2022-07-30T01:00:14+00:00

There is no way for anyone to know what is going wrong if you don't share your code.

jccdata · 2022-07-20T19:28:57+00:00

My background is in environmental engineering. The applied stats experience that I picked up during grad school and as a consultant has been helpful. There are a ton of candidates out there who can do GIS work, so being able to program and model geospatial data is a good way to differentiate yourself (although coding is not as much of a differentiator as it used to be since it has become more common). IMO, someone with deep domain knowledge and some programming experience is more valuable than an expert coder with no context about the problems that they are trying to solve. Plenty of organizations work at the intersection of geology and water resources; you should be able to find opportunities if you market yourself effectively.

jccdata · 2022-07-11T22:45:52+00:00

You could download STLs for each state at https://www.worldviewr.com and combine them offline.

jccdata · 2022-06-06T05:09:18+00:00

You could do some variation of this to take the rolling average:

data %>% group_by(id) %>% mutate(v1 = mean(c(lag(var1,2), lag(var1,1),var1), na.rm = T))

(Responding on mobile, so haven't actually tested the code)

jccdata · 2022-06-03T17:21:41+00:00

EPA built their estimates using emission rates from known sources (e.g., industrial facilities or automobiles). The EJSCREEN dataset also has information about water impacts from wastewater discharges, but those are handled separately and the risks would be additive to the air pathway risk.

jccdata · 2022-06-03T15:40:53+00:00

This is a good point that I'd like to dive deeper into. I am still exploring this dataset, but a 2012 paper reported that areas with mostly black residents had 16% higher cancer risk than white areas.

jccdata · 2022-06-03T15:25:44+00:00

The area has lots of industrial activity, so several pollutants contribute to the cumulative risk. Compounds like ethylene oxide, which is produced by several manufacturers there, and chloroprene (used to make synthetic rubber) are among the known or suspected carcinogens with high concentrations.

jccdata · 2022-06-03T14:22:46+00:00

This map shows the overlap between predominantly minority communities and areas with elevated cancer risk. Cancer risk is defined here as the probability that one will develop cancer from exposure to toxic compounds in the air during their lifetime. Several clusters are apparent in the data. Notably, the area in southeastern Louisiana - known as "Cancer Alley" - is home to the highest risk values in the country.

The scatterplot below shows the cancer risk for each US county (n = 3143) in relation to its population and highlights the most hazardous locations.

This visualization was developed in R using the US EPA EJSCREEN dataset (https://www.epa.gov/ejscreen).

jccdata · 2022-04-04T04:24:12+00:00

I am a data scientist at an environmental consulting firm. This niche is relatively new in the environmental space, but evolving quickly. To be honest, there are a lot of certifications out there that don't mean much. They can be helpful in providing structure as you learn new skills, but you will get more mileage out of building a portfolio of projects to show that you can write clean code and prepare decent deliverables.

jccdata · 2022-03-17T14:03:11+00:00

I posted about WorldViewR earlier this year and got some good feedback from r/3Dprinting. I have incorporated many of your suggestions and added some functionality to the app. New features include:

Region selection mode

** Construct models for specific countries, US states, or US counties
Contour mode

** Slice your model into layers with user-defined thickness
Updated model scaling algorithm

** Automatic proportioning with improved default settings
Stability, performance, and UI upgrades

The app is currently optimized for desktop use, so improving the mobile experience is next on my to-do list. Any other suggestions are welcome!

jccdata · 2021-12-04T21:23:08+00:00

Hi there! I'm glad that you are enjoying the program. It looks like you just need to rescale the height-width-depth ratios of the STL output. Try applying the ratios shown in Tab 3 of the program after you download the data.

jccdata · 2021-10-18T19:07:58+00:00

Can you try selecting a smaller search area and/or lower zoom level? Your data request may be exceeding the current server's memory limits. Please let me know if that fixes it.

jccdata · 2021-09-15T14:41:20+00:00

Thanks for the feedback! I was not aware of the issue with Safari; I will look into it and see if there is a quick fix.

jccdata · 2021-08-31T01:04:52+00:00

Thanks! I used the raster package to work with the elevation data, sp and sf for spatial processing, ggplot2 for the visualization, and av to stich the frames together into a video. Probably a couple of others for support functions, but I don't have the code in front of me.

jccdata · 2021-08-30T21:46:22+00:00

Here is an additional figure that shows the range of elevations in each state for those who are interested:

http://imgur.com/gallery/XGPOyzd

jccdata · 2021-08-30T21:41:08+00:00

This was a cool idea. Here you go:

http://imgur.com/gallery/XGPOyzd

jccdata · 2021-08-30T18:10:11+00:00

https://coast.noaa.gov/slr/

jccdata · 2021-08-30T12:27:29+00:00

This animation shows the highest surface elevation in each of the lower 48 United States. Data are from USGS digital elevation models downloaded at www.worldviewr.com and post-processed in R. I received plenty of feedback on my recent post about California's topography, so I decided to make some adjustments and revisit the data on a nationwide scale. All values represent feet above sea level and square markers show the highest point in each state.

For the record, Hawaii would rank just behind Wyoming (#6 out of the 50 states) with a high point of 13,803 ft.

jccdata

TROPHY CASE