What a full week! Here is my wrap-up from a great 2016 ESRI User Conference.
I haven't been here in many years, and I am glad I came. I learned much, and have some new ideas for workshops and classes, and how IGIS can be more of service to ANR, and I got started on ArcGIS Pro - ESRI's eventual replacement for ArcGIS Desktop. Pro has a completely new user interface that is very clear; you can visualize, edit, and perform analysis in both 2D and 3D; it is super fast via multithreading & 64-bit processing (finally), and it has new icons and a bunch of new processing tools. A bunch of very cool stuff comes with 1.3 soon.
Day 1: Monday was spent in big-picture, inspirational talks from camera beautiful GIS people. 15,000 in the audience, 10 massive screens. I loved it, I felt like I was at a really intense but sedate rock concert. Note to ESRI: could you put the chairs any closer together? The highlight was speaker keynote Andrea Wulf, talking about her obsession with Alexander Von Humboldt. Note to self: get the book. In addition to the big picture stuff, Day 1 is ESRI's chance to highlight this year's software improvements as we continue the voyage away from the desktop workflow: Pro, integrated 3D, green design, Apps, seamless integration with the web.
Day 2: Tuesday focused on workshops. I picked four workshops from the Spatial Statistics Team at ESRI. These were led by Lauren Bennett and her crew (Flora Vale, Jenora D'Acosta). Uniformly fantastic. I had downloaded Pro the night before, and with some trepidation got started and followed along. I am happy to report that it seems very intuitive. I have read elsewhere about worries that there is loss of cartographic control, and I will look into that. I learned about the Spatial Stats toolbox in Pro, and some very new capacity in optimization of pattern analysis (you know how difficult it is to pick that distance kernel), and in the new space-time cube capabilities. The space-time capabilities make very complex analyses doable, and are very exciting, but still a bit constraining if you don't know how to update the code. Oh yeah, and space-time uses netCDF format.
Day 3: For Wednesday's workshops I chose workshops that would help me update class labs: Python + Raster analysis; Site suitability in Pro; Cost Connectivity in Pro; and some crazy cool prediction tool called Empirical Baysien Kriging, which I will be checking out. I guess EBK has been around for awhile, but now implemented in ESRI software. The new suite of tools in site suitability + connectivity are going to be key. Kevin M. Johnston and Elizabeth Graham led the Site Suitability and Connectivity, and Eric Krause led the Kriging workshop.
Day 4: All day was spent in Pix4D immersion with the excellent Pix4D support/training team. Pix4D is the gold standard for drone imagery workflow; it also serves as the backend engine for ESRI's Drone2Map application, which I have not tried. Most of the morning was spent in basics: workflow basics, application domains, super wow factor examples like 0.5cm resolution imagery processing. We also looked at workflow and best practices, accuracy, and some example projects. The room was full of 50+ people, many with specific questions about a range of projects. Got to hang out a bit with Greg Crustinger, who is now at Parrot. Even more excited now about our new Sequoia cameras.
Thoughts:
- Little Italy has some great restaurants.
- We need to move to Pro soon. Probably not in time for Fall's class, but soon. GIF and IGIS workshops are going to have to get updated.
- I need to get more in touch with imagery analysis in Pro. Especially with the segmentation and classification part.
- I want to recreate the workflow for site suitability + locate regions + cost connectivity soon.
- The ability to perfom complex analyses in a GUI is increasingly easy, but is that a good thing? We have to be increasingly vigilant about training the fundamentals as well.
- One frustration about these workshops that I bet my workshop participants share - the data all is perfect, and ready to go. We need to keep talking about where to get data, and how to wrangle it into shape.
- Could drones mean the resurrection of photogrammetry? At least in the classroom?
Trends:
- Hyper granularity: how do we processes these increasingly fine resolution datasets?
- Global to local focus in modeling: GWR, optimized Getis-Ord, empirical baysien kriging all try to deal with and model local variability across a complex study area;
- Incorporation of permutations and distribution functions in modeling has been made way easier;
- Big Data, multidimensional data, temporal data: ESRI is really trying to be a better informatics platform for research;
- ESRI seems to be increasingly relying on external and open standards for new data formats/products; this is a great trend;
- Decision-making: all these analyses need to support decision-making; communication remains critical, tools for web-based interaction continue to expand.
Last week we held another bootcamp on Spatial Data Science. 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 moderndata formats and tools (GeoJSON, GDAL). On Day 2 we focused on open analytical tools for spatial data. We focused on Python (i.e. PySAL, NumPy, PyCharm, iPython Notebook), and R tools. Day 3 was dedicated to the web stack, and visualization via ESRI Online, CartoDB, and Leaflet. 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. Thanks to everyone!
/span>The annual AAG conference is rolling into town next week, and several of us will be there.
- Kelly and Jenny will be presenting;
- Kelly: Disentangling drivers of change in California Forests: management and climate
- Jenny: Spatial Data Science for Collaborative Geospatial Research
- Alice is a discussant on THREE panels; and
- I am a discussant on the Historical Ecology session.
Former kellylabbers will also be in force:
- John Connors is presenting (and organizing, and morderating, and all kinds of things):
- Disentangling Diversity: Agrobiodiversity, Livelihoods, and Food Security in the Kilombero Valley, Tanzania
- Desheng Liu will be there:
- Reconstructing Land Cover Trajectories from Dense MODIS Time Series
Have a great time everyone! (If I have missed anyone, let me know!)
We had a great day today exploring ESRI open tools in the GIF. We had a full class of 30 participants, and two great ESRI instructors (leaders? evangelists?) John Garvois and Allan Laframboise, and we worked through a range of great online mapping (data, design, analysis, and 3D) examples in the morning, and focused on using ESRI Leaflet API in the afternoon. Here are some of the key resources out there.
- Main ESRI Open Information: http://www.esri.com/software/open
- Slide deck from today: http://slides.com/alaframboise/geodev-hackerlabs#/
- Afternoon example using Leaflet: http://esri.github.io/esri-leaflet/
- ESRI's developer toolkits: https://developers.arcgis.com/en/, including
- ESRI's javascript API: https://developers.arcgis.com/javascript/beta/
Great Stuff! Thanks Allan and John
Register now for the March 2016 Spatial Data Science Bootcamp at UC Berkeley!
We live in a world where the importance and availability of spatial data are ever increasing. Today’s marketplace needs trained spatial data analysts who can:
- compile disparate data from multiple sources;
- use easily available and open technology for robust data analysis, sharing, and publication;
- apply core spatial analysis methods;
- and utilize visualization tools to communicate with project managers, the public, and other stakeholders.
To help meet this demand, International and Executive Programs (IEP) and the Geospatial Innovation Facility (GIF) are hosting a 3-day intensive Bootcamp on Spatial Data Science on March 23-25, 2016 at UC Berkeley.
With this Spatial Data Science Bootcamp for professionals, you will learn how to integrate modern Spatial Data Science techniques into your workflow through hands-on exercises that leverage today's latest open source and cloud/web-based technologies. We look forward to seeing you here!
To apply and for more information, please visit the Spatial Data Science Bootcamp website.
Limited space available. Application due on February 19th, 2016.
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