Mapping

One thing that often annoys me is the over-formality and over-professionalization of the GIS community on the Internet

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One thing that often annoys me is the over-formality and over-professionalization of the GIS community on the Internet. There isn’t a lot out there for mapping hobbyists, most things and services are directed towards professional planners and scientists. Too much is devoted to expensive commercial tools and experts, and not enough towards open source and hobbyists.

While data has become much widely available on the internet and ESRI should be commended for it’s adoption of open formats like ArcMap REST/Services, WMS, ESRI Shapefiles, and Geopackages, the expansion of data access hasn’t come with a lot of good podcasts or blogs for the hobbyist interested in open technology. There are a wealth of QGIS tutorials and information on GRASS and GDAL but it seems like most of the podcasts and websites on GIS still a very much aimed at the high-brow, professional class rather then the curious hobbyist looking to make maps for his or her own use.

The wonder material we all need but is running out – BBC Future

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The wonder material we all need but is running out – BBC Future

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Natural rubber is a uniquely tough, flexible and highly waterproof material. It puts tyres on our vehicles, soles on our shoes, it makes seals for engines and refrigerators, insulates wires and other electrical components. It is used in condoms and clothing, sports balls and the humble elastic bands. Over the past year it has played a pivotal role in the pandemic in personal protective equipment worn by doctors and nurses around the world.

In fact, rubber is deemed to be a commodity of such global importance that it is included on the EU's list of critical raw materials.

Unfortunately, there are signs the world might be running out of natural rubber. Disease, climate change and plunging global prices have put the world's rubber supplies into jeopardy. It has led scientists to search for a solution before it's too late.

Often when people think about GIS and mapping, they think about it in a very scientific and professional concept

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Often when people think about GIS and mapping, they think about it in a very scientific and professional concept. While science is an important to understanding our world, I think it’s kind of nice that I am able to look at things in an non-scientific and non-professional way, having learned my skills entirely by doing and working with the technology rather then through formal education. It allows me to see more of the art of what I am looking at, rather then being overly concern with the methods.

I’ve been looking through my Leaflet mapping code, and realized the system by default lists over 100 layers

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I’ve been looking through my Leaflet mapping code, and realized the system by default lists over 100 layers. That’s probably too much and the way the code is written in an incremental piece-by-piece fashion, it’s really hard to maintain. So I am working on converting it over a flat-file CSV spreadsheet, then I can just iterate through that and pull the layers I actually need or think would be useful for a map. Also, I want more flexibility on base layers vs overlays — often there are layers I would like to add in a dual pane mode, but can’t do under the current design of code, such as National Land Cover vs Aerial Photo or NLCD 2001 vs 2016 to better track land use changes.

Remote Sensing, Satellite Images, Satellite Imagery

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How to Interpret a False-Color Satellite Image – Earth Imaging Journal: Remote Sensing, Satellite Images, Satellite Imagery

In our photo-saturated world, it’s natural to think of the images on NASA’s Earth Observatory website as snapshots from space. But most aren’t. Though they may look similar, photographs and satellite images are fundamentally different. A photograph is made when light is focused and captured on a light-sensitive surface such as film or a charge-coupled device in a digital camera. A satellite image is created by combining measurements of the intensity of certain wavelengths of light that are visible and invisible to human eyes.

Why does the difference matter? When we see a photo where the colors are brightened or altered, we think of it as artful (at best) or manipulated (at worst). We also have that bias when we look at satellite images that don’t represent the Earth’s surface as we see it. “That forest is red,” we think, “so the image can’t possibly be real.”

In reality, a red forest is just as real as a dark green one. Because satellites collect information beyond what human eyes can see, images made from other wavelengths of light look unnatural to us. We call these false-color images. To understand what they mean, it’s necessary to understand exactly what a satellite image is.