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All People > DWright-esristaff > Dawn Wright's Blog > 2014 > August
2014

A unique new class at Stanford University ! is BIO 128: Geographic Impacts of Climate Change: Mapping the Stories. The capstone of the course is a terrific story map which they have just released, http://stanford.maps.arcgis.com/apps/StorytellingTextLegend/index.html?appid=dafe2393fd2e4acc8b0a4e6e71d0b6d5. The map has been sent to CA Governor Jerry Brown at his request, and was originally inspired by requests from the Executive Office in Washington, D.C. and a global scientific consensus statement on climate change (http://consensusforaction.stanford.edu).

Jack Dangermond will be keynoting at the Second International Conference on CyberGIS and Geodesign (CyberGIS'14) at Esri headquarters, Redlands, CA. The conference (Aug 19-21) will provide a forum for sharing cutting-edge research, education and training experiences ranging from new theories, methods, and applications of cyberGIS and geodesign to related industrial relations and partnerships, and international collaborations. CyberGIS'14 will include an international research symposium that will bring together foremost thinkers, researchers and educators to discuss leading research and education activities in cyberGIS and geodesign as well as related areas.

 

Possible topics include:

·         Python and building geoprocessing tools

·         Big data / Hadoop

·         AGOL content overview/highlights

·         AGOL analysis

·         GeoPortal Server

·         A features/licensing discussion about AGOL for Orgs and Portal for ArcGIS related to academic site licenses.

 

For more information see,http://cybergis.illinois.edu/events/cybergis14/http://cybergis.illinois.edu/events/cybergis14/


As was shown at this year's Esri User Conference, ArcMap now incorporates multidimensional data into GIS workflows to further the advancement of science (see Philip Mielke's excellent plenary presentation). This is a very important concept that we at Esri would like re-emphasize. With all the attention and focus on ArcGIS Pro, it is imperative that we do not forget that ArcGIS Pro will not do everything that Desktop can do, and that we continue to improve and enhance Desktop as well. ArcGIS for Desktop is still being enhanced and remains one of our most powerful GIS products (i.e., bigger than an app), providing much of the capability to fuel the ArcGIS platform. Our goal is to ensure a long term commitment to Desktop. ArcGIS Pro is just a complementary application to what our users already know about Desktop. While there are a number of enhancements to Desktop at 10.3, the multidimensional improvements are very important as we seek to advance science, and to position ArcGIS to always focus on advancing geographic information science in particular. Key messages from Philip's demo:

  • In addition to lightweight apps, enhancements abound in the more powerful and comprehensive ArcGIS desktop. Earlier in the morning plenary, the audience saw the new ArcGIS Pro app. But this demo represents a highlight of the powerful ArcMap with ArcGIS for Desktop.
  • Advancing science.
  • Users can consume scientific multidimensional datasets. Users can symbolize them with Vector Field Symbology.
  • The Python Adapter Function gives users the ability to use Python to model their data.
  • Users can animate Time-enabled data in ArcSceneTwo.

I would like to share an important article written by two of my colleagues, @Konstantin Krivoruchko and @Kevin Butler. This is a must read for those working with DEMs, especially those seeking an additional/alternative DEM-creation approach with considerable explanatory power.

 

To whet your appetite from the article:

"Raster based digital elevation models (DEM) are the basis of some of the most important GIS workflows: hydrologic modeling, site suitability, and cost path analysis. While there are several techniques for generating digital elevation models (DEMs), none of them can produce a true elevation surface. Locally varying measurement error and the inexactness of the interpolation methods contribute to the uncertainty of the model’s estimate of the true elevation value. Kriging models and geostatistical simulations available in the Geostatistical Analyst extension for ArcGIS 10.1 for Desktop to quantify the spatially varying uncertainty of a DEM derived from lidar data. ...

 

An alternative to deterministic algorithms, probablistic statistical interpolation methods such as kriging, have several advantages over deterministic methods. “Empirical Bayesian Kriging: Implemented in ArcGIS Geostatistical Analyst,” an article in the Fall 2012 issue of ArcUser magazine discusses these advantages in detail."

 

To read further and to contact the authors directly, please find the attached.

 

Happy kriging!