USGS HydroSHEDS 5 Degree Tile Index Map

I frequently use the HydroSHEDS dataset from the USGS for projects requiring a DEM outside of the United States. HydroSHEDS is a contrived acronym for Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales, meaning the digital elevation model comes from the Shuttle Radar Topography Mission (SRTM). SRTM mounted an InSAR array on Space Shuttle Endeavour during STS-99 in 2000 to collect elevation data from latitudes 56°S to 60°N. Although SRTM has less global coverage and less spatial resolution than the ASTER GDEM, SRTM has better vertical accuracy, making it more attractive for hydrologic applications like HydroSHEDS.

The 90 meter (or 3 arc second) gridded data products from HydroSHEDS are distributed in tiles that are 5 degrees by 5 degrees in size. This includes a void-filled DEM, a hydrologically conditioned DEM, and a flow direction grid. For reasons unknown, there is no index map of the 5 degree tiles available on the USGS website. Since it’s difficult to determine exactly which tiles fall in a given extent, I decided to make the map I needed:

HydroSHEDS 5 degree index map (click for full size, 935K PNG)
HydroSHEDS 5 degree index map (click for full size, 935K PNG)

Each tile in this map is labeled with the concatenated tile name representing the coordinates of the lower-left corner of each tile. For example, the tile for Rhode Island is “n40w075” with a lower left corner at 40°N latitude and 75°W longitude.

The fact that the tiles are measured in degrees means that this is an excellent case for using the plate carrée equirectangular projection, which has horizontal and vertical units of degrees. This is, of course, equivalent to what ArcMap shows when setting a data frame’s coordinate system to a “geographic” projection.

For convenience, you can also download the index in shapefile or GeoJSON format.

Introduction to ArcPython lecture

For the third year running, I returned to Brown to give a guest lecture about using Python in GIS for GEOL1320: Introduction to Geographic Information Systems for Environmental Applications. I’ve used ArcPython extensively in my work at Cadmus, and it’s exciting and heartening to be invited to lecture to GIS novices about the topic.

Nonetheless, the lecture is a challenge. I don’t have any formal experience teaching undergraduates. Moreover, it’s practically impossible to teach a programming language (even one as intuitive as Python) in an 80 minute time slot, let alone its nuanced GIS applications. Thus my strategy has been to think of the lecture as an icebreaker: a way to take away the barriers and scare-factor associated with getting started with Python. After a brief introduction, I showcased a few real-world examples of how I’ve used ArcPython in my work. Then the whole class worked through a live demo, doing a fairly simple task—adding fields to a feature class—using progressively more complex Python commands. Eventually, we even packed the final tool into a Python custom toolbox connected to a separate .py script file.

This year was definitely the most successful yet. The fact that students typed the commands themselves in a lab-format class made for a more engaging and effective class versus students watching me type in a lecture-format class. I hope these GIS novices got a good sense of what is possible with ArcPython. My slides are attached below.

Download slides (1.8MB .pptx)
Download slides (1.8MB .pptx)

Review: The Mars Trilogy, by Kim Stanley Robinson

The Mars Trilogy

Science fiction is a difficult genre to get right. Bad scifi frequently fills bookshelves and movie theaters: predictable dystopian stories with a “chosen one” protagonist (e.g. Divergent, The Maze Runner, Jupiter Ascending), or scifi premises shoehorned into action/horror movies with unsatisfactory endings and better special effects than acting (e.g. Sunshine, In Time). Since the in-universe science drives their plots, these stories can rapidly feel dated as real-life technological progress obviates the speculative inventions of yesteryear.

One approach to avoiding these issues is brevity. Timeless short stories like The Last Question and Nightfall by Isaac Asmiov, The Ten Billion Names of God by Arthur C. Clarke, Harrison Bergeron by Kurt Vonnegut, and We Can Remember It For You Wholesale (on which Total Recall is based) by Philip K. Dick explore how individual scientific advances affect society and the characters. Other technologies play unimportant parts in the overall story, avoiding the deus ex machina tropes of more expansive speculative futures.

Hard science fiction adopts a different approach. Instead of relying on brevity, hard science stands on realism. Gone are unexplained warp drives and magic laser blasters; hard science fiction limits itself to technologies that could have believably evolved from present day, and explains how they work. The Mars trilogy by Kim Stanley Robinson represents a tremendous achievement in this subgenre, exploring the speculative terraforming and colonization of the fourth planet by the “First Hundred” human colonists and their descendants.

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