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    <title>A Step-by-Step Guide to Making 3D Maps with Satellite Imagery in R – Data Junk[i.e.]</title>
    <dc:date>2020-04-28T23:07:05+00:00</dc:date>
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    <dc:creator>nico.ash</dc:creator><description><![CDATA[Ever since I released rayshader to the public, there's been one question that comes up time and time again: "How do I use rayshader to overlay satellite imagery onto a 3D surface?" And I can see why: 3D maps with real satellite images are super cool, and there are few detailed tutorials out there on how it's done in R. Additionally, the process behind making this type of map can be intimidating for non-GIS experts, as it exposes you to all complexities of the GIS field: combining different datasets from separate sources—often each with their own distinct coordinate systems—into a single map. Not only that, but you have to also know where and how to get this data—not obvious to someone who doesn't do this regularly. So I'm going to walk you through how to obtain the data required to make these types of maps, as well as the R code used to generate them. In my opinion, the hardest part is all the manual work in downloading the data! Once that's done, the code required is short and straightforward, and rayshader makes visualizing elevation data in 3D a breeze. Let’s get started!]]></description>
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    <title>Announcing Libra - the Landsat imagery browser you will love | Development Seed</title>
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    <dc:creator>nico.ash</dc:creator><description><![CDATA[Superresolution (SR) is a class of techniques that enhance the resolution of an imaging system. In some SR techniques—termed optical SR—the diffraction limit of systems is transcended, while in others—geometrical SR—the resolution of digital imaging sensors is enhanced.]]></description>
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