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geospatial matters

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Saturday
Feb282015

10-year anniversary for the GIF

I'm musing, contemplating and writing on the decade 2005-2015, as this is the GIF's 10-year anniversary. What a decade it was. Here I'll post and add to some of the key events that helped transform mapping (and the GIF) in the last 10 years.

Key background events

  • 1996. Mapquest launched.
  • 1997. Skynet becomes self-aware.
  • May 2000. Selective Availabilility on GPS turned off, leading the way for GPS in smartphones.
  • The Scan Line Corrector (SLC) on the Landsat 7 ETM+ instrument failed May 31, 2003.
  • 2004. Open Street Map founded.
  • March 2004. Yahoo! maps launched, first slippy maps (click and drag to pan and zoom the map).
  • 2004. NASA releases WorldWind.
  • October 2004. Google acquires Where 2 allowing AJAX map tiling to a desktop client.
  • October 2004. Google acquires Keyhole.

What made 2005 such a crazy year

  • Google Maps launches in February, and goes mobile in April.
  • The first mashup: Paul Rademacher's Housingmaps.org. His original post on Craigslist asking for feedback: https://forums.craigslist.org/?ID=26638141
  • Google Maps API launches in June.
  • NASA's Blue Marble Next Generation released.
  • Google Earth launches in June.
  • Hurricane Katrina hits in August. Simple webmaps for the disaster proliferate, and ESRI and GE get on the scene.
  • Kellylab's first blog post in September.
  • GIF launches and hosts our first GIS Day in November with Michael Jones, formerly of Keyhole.
  • The back-up solar array drive on Landsat 5 began failing and was not able to provide the power needed to charge the batteries. November 26.

Where we are in 2015

We've gone through a number of transitions in the world of mapping:

  • Data have transitioned from being siloed, and found in clearinghouses to being open and provided through APIs.
  • We’ve moved from desktop computing to cloud computing.
  • Webmaps have transitioned from using proprietary stacks to networks with multiple open and proprietary options.
  • We’ve moved from imagery gathered monthly or seasonally to daily; footprints are smaller, and our focus has shifted from local focus to global coverage.
  • Our planimetric 2D view is changing with lidar and radar sensors.
  • Visualization has moved from static cartography or simple animations to dynamic interactive visualization.
  • Finally, mapped content is no longer anonymous or regulated, but highly personal and narrative.

Key GiF milestones:

  • 2005 GIIF (Geospatial Imaging and Informatics Facility) launches
  • 2006 OakMapper changes from ArcIMS to Google Earth API
  • 2008 GIIF becomes GIF
  • 2008 OakMapper 2.0 launches
  • 2008 SNAMP website launches
  • 2011 Cal-Adapt goes live
  • 2013 EcoEngine/HOLOS goes live
  • 2014 LandCarbon launches
  • 2014 GIF and Cal-Adapt go to the White House
  • 2014 vtm.berkeley.edu goes live, built from the HOLOS API
  • 2015 Spatial Data Science bootcamp in May

Onwards and upwards!

Saturday
Feb282015

A brief history of the digital map

Nice consise history of mapping from his lecture "The Ubiquitous Digital Map" by Gary Gale, Director of Global Ccommunity Programs, HERE.

http://www.vicchi.org/2013/02/19/the-ubiquitous-digital-map-abridged/

Thursday
Feb262015

Lidar + hyperspectral, ortho and field data released by NEON

http://www.neoninc.org/data-resources/get-data/airborne-dataFrom LASTools list:

The National Ecological Observatory Network (NEON) published this week airborne remote sensing data including full waveform and discrete return LiDAR data and LiDAR derivatives (DTM, DSM, CHM) as well as corresponding hyperspectral data, orthophotos, and field data on vegetation strucutre, foliar chemistry and ASD field spectra.

NEON Airborne Data Set
.

Wednesday
Feb252015

Questions about the Spatial Data Science Bootcamp? Read on!

In May, the GIF will be hosting a 3-day bootcamp on Spatial Data Science.

What is the significance of Spatial Data Science?

We live in a world where the importance and availability of spatial data is ever increasing, and the value of Spatial Data Science: big data tools, geospatial analytics, and visualization is on the rise. There are many new and distributed tools available to the geospatial professional, and the ability to efficiently evaluate and integrate the wide array of options is a critical skill for the 21st century marketplace.  Spatial Data Science offers a modern workflow that includes the integration of data from multiple sources and scales; with open-source and web-based technology for robust data analysis and publication; with core spatial concepts and application of spatial analysis methods; and allows for the collaborations of people – companies, scientists, policy-makers, and the public.

Why come to the GIF to learn about it?

The Geospatial Innovation Facility (GIF) at UC Berkeley is the premier research and educational facility in the Bay Area that focuses on a broad vision of Spatial Data Science. The GIF has a decade-long history of successful GIS and remote sensing research projects. The GIF has also trained many students, researchers, and community members in geospatial techniques and applications through our popular workshop series and private consultation. With more recent advances in web-based mapping capabilities, the GIF has been at the forefront of complex web-based spatial data informatics (web-based data sharing and visualization), such as the Cal-Adapt  tool, which provides a wealth of data and information about California’s changing climate. Participants will get the benefit of our decade-long focus on Spatial Data Science: collaborative project development, rigorous spatial analysis methods, successful interaction with clients, and delivery of results to project managers, the public, and other stakeholders.

What are the key elements of the Bootcamp?

This Bootcamp is designed to familiarize participants with some of the major advances in geospatial technology today: big data wrangling, open-source tools, and web-based mapping and visualization. You will learn how and when to implement a wide range of modern tools that are currently in use and under development by leading Bay Area mapping and geospatial companies, as well as explore a set of repeatable and testable workflows for spatial data using common standard programming practices. Finally, you will learn other technical options that you can call upon in your day-to-day workflows. This 3-day intensive training will jump start your geospatial analysis and give you the basic tools you need to start using open source and web-based tools for your own spatial data projects.  

Interested in integrating open source and web-based solutions into your GIS toolkit? Come join us at our May 2015 Bootcamp: Spatial Data Science for Professionals. Applications due: 3/16/2015. Sign up here!

Monday
Feb232015

Information on the GIST Minor and Graduate Certificate

Hi all,

Our gis.berkeley.edu website had to be taken down. Information on the GIST Minor and Graduate Certificate can be found here:

 Thanks!

Friday
Feb202015

List of Online Geospatial Data

From Sean's IGIS workshops this week.

Base Layers

Land Cover and Wildlife Habitat

Imagery

Soils

Climate and Weather Data

California Geopolitical Boundaries

Digital Elevation Models

Thursday
Feb192015

Geolunch Seminar Talk: Spatial Data Analysis with Python

Thanks to all who attended today!  Here is a link to the slides, and below are more links for some of the free resources that were highlighted.

Code Academy (programming tutorials): http://www.codecademy.com/
Coursera (full courses): https://www.coursera.org/courses?query=python
Python wiki pages: https://wiki.python.org/moin/BeginnersGuide/NonProgrammers
https://docs.python.org/2/tutorial/
Python at Berkeley (DLab): http://python.berkeley.edu/learning_resources.html
Python Books and Training: http://pythonbooks.revolunet.com/
http://www.learnpython.org/
ArcPy tutorials from ESRI: http://training.esri.com/gateway/index.cfm?fa=catalog.
webCourseDetail&courseid=2520

http://training.esri.com/gateway/index.cfm?fa=catalog.webCourseDetail&courseid=2523

List of spatial Python packages: https://github.com/SpatialPython/spatial_python/blob/master/packages.md

If you are a graduate student, check out the graduate student-led workshops for Spring 2015: http://goo.gl/forms/rUceY1I67n

Tuesday
Feb172015

Turf: Advanced geospatial analysis for browsers and node

Mapbox introduced a new javascript library for spatial analysis called Turf.js. On the "Guides to getting started" page, it claims that Turf "helps you analyze, aggregate, and transform data in order to visualize it in new ways and answer advanced questions about it."

Turf provides you with functions like calculating buffers and areas. Other common functions include aggregation, measurement, transformation, data filtering, interpolation, joining features, and classification. The detailed explanations of these functions can be found on this page.

Turf seems like a cool tool to try out if you want to provide spatial analysis functions on your webGIS applications.

Saturday
Feb142015

Karin in the news! Google camera helps capture bay’s rising sea levels

Neat article about Google teaming up with the nonprofit San Francisco Baykeeper to use Google Street View technology to map tides and sea level rise around the Bay. Former kellylabber Karin Tuxen-Bettman is involved. 

http://www.sfgate.com/bayarea/article/Google-camera-helps-capture-bay-s-rising-sea-6080481.php#photo-7524438

Saturday
Feb142015

Landsat Seen as Stunning Return on Public Investment 

Undersanding the value of Landsat program to the U.S. economy has been the ambitious goal of the Landsat Advisory Group of the National Geospatial Advisory Committee. This team of commercial, state/local government, and NGO geospatial information experts recently updated a critical review of the value of Landsat information that has recently been released to the public.

They found that the economic value of just one year of Landsat data far exceeds the multi-year total cost of building, launching, and managing Landsat satellites and sensors.  This would be considered a stunning return on investment in any conventional business setting.

Full article by Jon Campbell, U.S. Geological Survey found here.