I’ve loved this data for a while now, which you can download at The National Map Seamless Server from USGS. Not only is it visually stunning, it’s incredible for urban analysis. Looking at the images below, I think I actually like the simplified view of just imperviousness and the ocean/bay better than the map with hillshading and protected areas. I’m turning into a minimalist.
A client of mine wanted a fog extent map for the SF Bay Area. I searched and searched, but couldn’t find any vector data, so I created one from sifting through more than 1,600 satellite images taken over the past month, finding the ONE image that showed the furthest extent of fog. SF is pret-ty foggy this time of year, so it was a good series to work with. Then georectified this image, then digitized a polygon, then smoothed the polygon. A simple map showing this file is below, followed by a quick youtube video I compiled with all 1,600 or so images. You can download the source images from the Naval Research Laboratory Monterey Marine Meteorology Division by clicking here.
I just heard from a friend that the California Fish & Game Commission voted 3-2 to approve the Integrated Preferred Alternative as recommended. This is great news! Below is a map of the newly designated MPAs. Click on the map to get a more detailed version:
This is a great data set for global bathymetry from NOAA’s NGDC (National Geophysical Data Center). I really enjoy looking at the raw hillshade in grayscale, taking that single layer and trying to figure out how our world is put together, what influence moving plates have over topography and bathymetry, what influence massive bodies of water have over the rock and sand and soil beneath them. Can you figure out where the land ends and the ocean begins? It’s a bit more difficult than if we have visual hints to guide our eyes, but with a high enough resolution image, you can probably determine shorelines pretty easily. There are some great clues tucked away in the landscape/seascape. I still think it’s amazing the amount of information you can get out of one file. The source here is one global DEM, from which I created a couple hillshades, a topographic color ramp, and a bathymetric color ramp. That’s it, and the last image just shows these layers in a globular projection with a slight shadow effect courtesy of GIMP.
I’m currently working on a 3D flyover for a client, inevitably I do this task in Google Earth, but there are many things I don’t like about how the software functions, so, I’ve created some cartographic patches to make it more tolerable to view. Touring from one point to the next or down a path are very smooth, and that’s my main reason for using GE, so I’ve taken full advantage of that. But from there, I’ve tried to customize the rest. The first patch to take care of was the imagery. Google’s source has a huge cloud over the property, so I brought in a tiled NAIP overlay. The resolution isn’t terribly high, but that’s not necessary for the altitude of our flyover.
The second issue I had to deal with was showing protected lands polygons surrounding the focus property. A simple polygon overlay in GE produces pretty dismal results, as there are no applied shadows to show shaded relief and the property boundaries blur and become completely distracting at oblique views. So, my trick here was to build the protected lands polygons into the imagery tiles using ArcMap. I brought in NAIP imagery on the bottom, followed by the polygons, overlayed by an 85% transparent hillshade, but only showing the hillshade where it overlapped the polygons using Advanced Drawing Options in ArcMap. I didn’t want to double-up the shadows, and this little tool worked great. If you wanted to have some sense of the imagery on the protected lands as well, you could add a second layer of NAIP just below the hillshade and set that to 60%-70% transparent.
I’ve been starting to try to wrap my head around Open Source GIS tools lately, thinking about how we can use them for our projects. In this process, I’ve done a decent amount of research, lots of downloading and installing, troubleshooting installs, and figuring out how all of these puzzle pieces fit together. I come from a liberal arts education background and have always loved GIS because of its combination of science and art (heavy on the art). So, naturally, the past couple of weeks have been a whirlwind of understanding, black boxes of mystery have slowly opened up and revealed themselves. Within one of these boxes was the gdal2tiles tool from the OSGeo4W install. It quickly and easily takes large georeferenced images (jpg, png, tif, etc) and chops them up into manageable tile sizes at standard on-line mapping zoom levels. So instead of drawing and re-drawing a 50mb image of the Bay Area every time you pan to a new location , this allows you to draw small, seamless tiles, pieces of the whole image as you pan around. My test here is a 10-meter hillshade of the SF Bay Area at seven different zoom levels. Lots to build off of, lots of ideas going now, steamrolling ahead into the OS Geo world.
GreenInfo Network has worked diligently over the past few years compiling all federal, state, county, city, special district, and non-profit protected areas into one database for the state of California. The California Protected Areas Database (CPAD) v1.2 now contains 48 million acres of land in 47,000 parcels from over 800 agencies. You can download and review the data by visiting www.calands.org. And, the data can be seen and queried in all their interactive glory at the ParkInfo and California Department of Parks and Recreation sites. Hats off to Jason Jones, CPAD Project Manager for all of his hard work!
Click on the map below to Zoomify.
Google released the My Tracks application for Android phones a little while back, and I’ve been testing it out every chance I get. A couple screen shots and links below show a day of hiking around Big Basin State Park near Davenport, CA, and a day skiing at Alpine Meadows near Lake Tahoe. I was immediately impressed that it does an amazing job of accurately tracking your movement, having used both recreational Garmin units and gigantic, clunky, Trimble units in the past. Granted, I used the Trimble unit 8 years ago, so this is not a fair comparison. But I was able to start recording tracks and toss the phone into my jacket pocket and forget about it for the day. It kept a good signal both days, and we put in just over 5hrs of skiing this past weekend.
This brings we to my second impression. After you set your phone to record tracks, the screen will timeout according to your settings, but the phone will continue recording. This maintains battery life throughout the day, which is the one thing you hope for with Android applications, as the phone’s battery life is less than desirable. Okay, onto some links and screenshots…
I added a couple photos from our hike to the final map, placed at the blue markers
Notice the straight chairlift lines…
Tracks on the phone, stats page, and elevation (we got in 17 runs)
Tommy added a legend to the KML, and now we have it available for download right here. What’s best is that he spent some time and put county names, unemployment rates, and some more attribution into the info bubbles. This data set is powerful stuff, and we see that even though the unemployment rate is currently 7.9%, there are counties like Mackinac County in Northern Michigan that have an unemployment rate of 24.2%. Staggering numbers…
My former boss, Tommy Albo, imported centroids of unemployment data by county to Google Earth and quickly compiled this pretty amazing visualization. The numbers come from the Bureau of Labor Statistics and represent unemployment levels as of December, 2008. Download the original county data or a PDF map from Primary Data Source. This was all brought to our attention through The Society for Conservation GIS email list, and a post by Gina Clemmer at New Urban Research, Inc. Thanks to Tommy and Gina! Enough links? Okay, the goods are below. Notice the Southeast, Upper Midwest and the West Coast.
