geospatial matters
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Tuesday, September 1, 2015 at 1:59PM Here are the tag clouds from this year's GIS class: the why, how and what of our upcoming semester's projects. Word clouds from Wordle.
The Why: what are the key problems class members want to focus on...
The How: possible methods we will use...
The What: some of the datasets that might be used...
Monday, August 31, 2015 at 8:50AM Here in the Kelly Lab we talk a lot about effective ways to visualize data. How do we show the true weight and impact of those data we work with? How do we communicate uncertainty? I think this fellow Neil Halloran did a pretty great job with WWII. This short video is a combination of visualization and narration. While effective visualization on its own is ideal, I think the narration offers different avenues of talking about uncertainty in the data. Check out his video HERE.
Sunday, August 23, 2015 at 8:38PM 
Students, researchers, mappers, and big data enthusiasts took place in an exciting 2 day Google Earth Engine workshop this last week hosted by the GIF and the Google Earth Engine Team. We had an exiting overview of the latest and greatest research adventures from Google by Kelly lab alum Karin Tuxen-Bettman including advances in some of what Google Earth Outreach team is involved in...
Thursday, August 13, 2015 at 4:49PM August 20 & 21, 2015
Geospatial Innovation Facility @ Mulford Hall, UC Berkeley
What will you learn?
Led by instructors from Google Earth Outreach and Google Earth Engine, this workshop will teach highly practical tools which can be used to collect, host, analyze, visualize, and publish map data using the power of the cloud. Sessions will include hands-on experience at both beginner and advanced levels using Google Earth Engine, which brings together the world's satellite imagery — trillions of scientific measurements dating back almost 40 years — and makes it available online with tools for scientists, independent researchers, and nations to mine this massive warehouse of data to detect changes, map trends and quantify differences on the Earth's surface. Applications include: detecting deforestation, classifying land cover, estimating forest biomass and carbon, and mapping the world’s roadless areas. Learn more aat http://earthengine.google.org/.
Who should attend?
Researchers and educators at UC Berkeley and UC affiliates who meet one or more of the following should attend!
Cost & Registration
Attendance is free, but registration is required since space is limited. http://ucberkeley2015.earthoutreach.org/home
Thursday, August 13, 2015 at 10:08AM 
This is the island of Nihoa, northwest of Kauai, viewed in Google Maps. Hawaii on my mind. Anyway, it is a funny shot with mixed resolutions, bathymetry and optical imagery, and what looks to be a bordered image without its adjacent partner images. Web link: https://www.google.com/maps/@23.0606579,-161.8639537,39656m/data=!3m1!1e3Friday, July 17, 2015 at 11:22AM Check out the webinar: DRONES FOR THE EARTH SCIENCES: APPLICATIONS AND IMPLICATIONS, provided by the Board on Earth Science and Resources.
There are also links to the webinar UNEARTHING CITIZEN SCIENCE with Muki Hacklay.
Thursday, July 16, 2015 at 6:54AM Remote Sensing in Ecology and Conservation is a new, fully open access journal from Wiley and the Zoological Society of London. The journal will provide a forum for the rapid publication of peer-reviewed, multidisciplinary research from the interface between remote sensing science and ecology and conservation. The journal defines remote sensing in its broadest sense, including data acquisition by hand-held and fixed ground-based sensors, such as camera traps and acoustic recorders, and sensors on airplanes and satellites. The journal's intended audience includes ecologists, conservation scientists, policy makers, managers of terrestrial and aquatic systems, remote sensing scientists, and students.
Saturday, June 6, 2015 at 9:21AM 
Bootcamp participants outside historic Mulford HallOur bootcamp on Spatial Data Science has concluded. We had three packed days learning about the concepts, tools and workflow associated with spatial databases, analysis and visualizations.
Our goal was not to teach a specific suite of tools but rather to teach participants how to develop and refine repeatable and testable workflows for spatial data using common standard programming practices.
On Day 1 we focused on setting up a collaborative virtual data environment through virtual machines, spatial databases (PostgreSQL/PostGIS) with multi-user editing and versioning (GeoGig). We also talked about open data and open standards, and modern data formats and tools (GeoJSON, GDAL).
Analyzing spatial data is the best part! On Day 2 we focused on open analytical tools for spatial data. We focused on one particular class of spatial data analysis: pattern analysis, and used Python (i.e. PySAL, NumPy, PyCharm, iPython Notebook), and R Studio (i.e. raster, sp, maptools, rgdal, shiny) to look at spatial autocorrelation and spatial regression.
Wait, visualizing spatial data is the best part! Day 3 was dedicated to the web stack, and visualization. We started with web mapping (web stack, HTML/CSS, JavaScript, Leaflet), and then focused on web-based visualizations (D3). Web mapping is great, and as OpenGeo.org says: “Internet maps appear magical: portals into infinitely large, infinitely deep pools of data. But they aren't magical, they are built of a few standard pieces of technology, and the pieces can be re-arranged and sourced from different places.…Anyone can build an internet map."
All-in-all it was a great time spent with a collection of very interesting mapping professionals from around the country (and Haiti!). Thanks to everyone!
