The Kitzmiller v. Dover Quiz!

Pretty cool: The Kitzmiller v. Dover Quiz

More about this topic here: https://ncse.ngo/articles/260

Chart Makers

Here are three options:

• RAWGraphs
• Chartbuilder
• Infogram

As always: user beware! Some of these 'free' ones / tiers can suddenly disappear or turn commerical.

IRB

Yep, the IRB process is both necessary & tedious.

• Excellent video here: Do you need an IRB??
• IRB Decision Tree (U. Wisconsin La Crosse)

GeoSpy

GeoSpy can geoference photographs without any spatial information & apparently it works quite well - more @ https://flowingdata.com/2025/01/23/geolocating-photos-automatically/

That's pretty cool & also scary...no hiding anymore from the AI...

EJAtlas - Global Atlas of Environmental Justice

This is very cool: https://ejatlas.org/

Open-Source Streetview

Google Streeview is obviously great, but (also) obviously a proprietary system. Here's a new open compilation of 10 million street-level images from 688 cities: https://ual.sg/project/global-streetscapes/

3D-PAWS

3D-PAWS =  a 3d-printed weather station!

• https://sites.google.com/ucar.edu/3dpaws/
• YouTube channel @ https://www.youtube.com/channel/UCaxlD_Ylp3ooI8ej8ACmJDg

Alternatives to Google Street View

Maps Mania has compiled a nice list of open-source alternatives to Google Street View, for example Panoramax, Mappillary, and KartaView. These apps can be useful to share your own street-level photos, for example for your own project.

More here: https://googlemapsmania.blogspot.com/2023/11/alternative-street-view.html

Common Sense Education

Common Sense Education is a large non-profit 'dedicated to improving the lives of all kids and families by providing the trustworthy information, education, and independent voice they need to thrive in the 21st century.'

There are lot's of players in that space directly or indirectly promoting some kind of agenda, so be careful! That being said, they seem to offer good educational materials related to digital citizenship and Edtech.

Communities in Crisis

Communities in Crisis shows the impacts of climate change on communities around the world. I like it: simple and effective. 

iPhone LiDAR

Hmm, maybe the excuse I need to upgrade my iPhone: Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences.

OSS and OSH/OSHW

Here's a great paper and some of the associated resources - it's pretty cool what you can do nowadays with open-source software and hardware. That being said: I have seen too many crappy weather stations for one reason or another (see pic below) - making consistemt and high-quality environmental measurements is complex, especially in harsh environments.

• Chan et al. (2021): Low-cost electronic sensors for environmental research: Pitfalls and opportunities
• http://www.freestation.org/home
• King's College London Geocomputation on GitHub

STEM Teaching & Open Pedagogy

Karen Cangialosi has some tools and ideas @ https://karencang.net/openped/

ArcGIS Field Maps

ArcGIS Field Maps is the new mobile data collection app from Esri - basically replacing the old Collector app. It all seems to work just fine as one would expect, but unfortunately my iPhone is too old to run the app. Here are some resources:

• Try data collection in ArcGIS Field Maps (the full workflow)
• Create a map for data collection in Field Maps (this is a little tedious using feature layers)
• Configure maps for the field (this should be obvious: offline mapping and downloadable map areas)
• Take Your Web Maps Offline with ArcGIS Field Maps (detailed PDF)
• Introducing smart forms in ArcGIS Field Maps (seems cool)

Data Journalism and Visualization with Free Tools

 Free self-directed MOOC: Data Journalism and Visualization with Free Tools

DIY Satellite Ground Station

 This looks like a fun project: DIY Satellite Ground Station

Mapillary

Mapillary is a nice open-source / crowd-source alternative to Google Street View. Get yourself the app and start contributing your own views of the world. Of course, you could stay inside Google and just use their Photo Sphere app.

Joe Kerski shares some idea on how to use Mapillary in Citizen science street level imagery and mapping with Mapillary and here's a nice tutorial on how to embed Mapillary in Esri Story Maps: Taking the Tour: Mapillary in Esri Story Maps.

I played around with the Mapillary app and collected a couple of sequence:

• Sachem Head
• Highland Pond

Not surprising this seems to work much better on flat and easy ground such as roads or dirt roads as opposed to the rocky ridge line of Sachem Head. Maybe a gimbal would work. The sequence export via geojson is pretty lame as you only get the location of the points, but not the associated photographs. Best to view your sequence inside Mapillary.

Is this useful? Sure! You can quickly and easily collect photographs of your research area and share them in a cool way with the rest of the world. If that's something that you want to do. It's also easy to compile sequences into an Esri Story map. It also makes for a fun activity with students - as long as they have a smartphone (and can download the app, create a Mapillary account, and there's Wifi available to upload the photographs).

Old Weather

Old Weather is a cool citizen science project to transcribe weather observations recorded by ships since the 1850s or so. Have a look at the Weather Time Machine for context and examples as a Story Map.

ArcGIS QuickCapture

Now we have a third option for mobile data collection via ArcGIS Online: ArcGIS QuickCapture. The basic workflow is well-explained in this step-by-step tutorial: Create a project from scratch.

Snow Depth Mapping using SfM and more

Goetz and Brenning (2019): Quantifying uncertainties in snow depth mapping from structure from motion photogrammetry in an alpine area. Water Resources Research, doi: 10.1029/2019WR025251.

Filhol et al. (2019): Time-lapse Photogrammetry of Distributed Snowdepth During Snowmelt. Water Resources Research, doi: 10.1029/2018WR024530. Ground-based, oblique with 3 cameras - easy in concept, but the details are complex. They make a good point: usually we either have high-frequency time series from point measurements or sporadic spatial data from satellites, UAVs, etc. Their approach tries to bridge that gap.