I spent two days at the California Economic Summit, held this year in Ontario, heart of the "inland empire". I learned much about this region of the state that I know mostly as freeways connecting water polo games, or as endless similar roads through malls and housing developments. It is more populous, diverse, and vibrant than I had realized. The conference itself was very different from any that I have been to. Hardly any presentations, but break-out groups, passionate, inspiring panelists, tons of networking, good overviews, multiple perspectives, and no partisanship.
Here are some interesting facts about California that I did not know:
- 80% of CEQA lawsuits are related to urban infill development. Shocking. We need infill development as a sensible solution to a growing California.
- 1 in 3 children in the Central Valley live in poverty. 1 in 4 kids live in poverty in the inland empire. These rates are WORSE than they have been ever.
- The Bay Area is an anomaly in terms of education, income, health, voting rates, broadband adoption. The Bay Area is not representative of the state!
- Think of a west-east line drawn across the state to demark the population halfway line. Where might it be? No surprise it is moving south. Now it runs almost along Wilshire Blvd in LA!
- Empowering the Latino community in the state is going to be key in continued success.
- Broadband adoption around the state is highly variable: Latino, poor and disabled communities are far below other communities in terms of adoption.
- The first beer made with recyled water has been made by Maverick's Brewing Company.
- Dragon Fruit might be the new water-wise avocado. Good anti-oxidents, massive vitamin C, good fiber, etc. They taste a bit like a less sweet kiwi, with a bit of texture from the seeds. I don't think I'd like the quac, however.
- In 15 years, the state will be in a deficit of college graduates needed to meet skilled jobs. Those 2030 graduates are in 1st grade now, so we can do some planning.
- Access, affordability, and attainability are the cornerstones of our great UC system.
In every session I attended I heard about the need for, and lack of collaboration between agencies, entities, people, in order to make our future better. Here is my wordle cloud of discussion topics, from my biased perspective, or course.
/span>Hello World!
There are several GIS classes to chose from in the spring. So far we have:
Lower division:
- ESPM 72 Geographic Information Systems *Not sure who is teaching this yet*
Upper division:
- Chambers, J GEOG 185 Earth System Remote Sensing
Graduate:
- O'Sullivan, D GEOG 187 Geographic Information Analysis
- Biging, G & Radke, J ESPM 210 Spatial Data Analysis for Natural Resources
- deValpine, P ESPM 215 Hierarchical Statistical Modeling in Environmental Science (some spatial data analysis)
- Radke, J LDARC 221 Quantitative Methods in Environmental Planning
- Dronova, I LDARC 221 Applied Remote Sensing
- Wang, I ESPM 290 Special Topics in Environmental Science: Spatial Ecology
Email me with others.
Thanks!
Been addicted to the ESRI fire feed for its integration of numerous data sources.
Here is the Valley Fire currently, and the rain that just hit us has moved north.
For more: http://www.esri.com/services/disaster-response/wildlandfire/latest-news-map
/span>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.
Our 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!
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