GIS raster datasets are geographic phenomena stored as grid cells or as images.  Each cell or pixel contains information that can be modified to generate new raster data.  ArcGIS 10 has many tools to manage and manipulate raster data information.  Intended for students who have taken the class on vector analysis or have explored GIS software in some detail, this class will give hands-on examples of various raster analysis tools.

To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=851

ArcGIS 10 has many different ways to access data sets, display them in a map, and analyze relationships over time and space. US Census data can be integrated with GIS boundary files to analyze the spatial relationships of poverty, ethnicity, environmental risk, and other parameters.  Hands-on examples will show how to find and download demographic data, how to combine the data with GIS files, and how to view the data in ArcMap. The class will work with historic US demographic data and explore the use of tables in ArcGIS. The session will assist any GIS user who wants to include tabular data in a spatial analysis.

To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=853

A Geographic Information System (GIS) combines software and digital geographic data to generate maps, tables and interactive analyses of spatial information.  Princeton faculty, students and staff use GIS technology to manage resources, explore spatial relationships, and visualize change. The class, intended for those with no previous GIS experience, describes the technology and includes simple exercises to introduce its capabilities.


To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=843

In this class students will learn how to collect geographic data from Google maps and Google Earth, add GPS data to GIS software, and learn how to georeference a scanned map. The exercise will also show how to extract points, lines, and areas from the georeferenced map.


To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=1158

ArcGIS 10 has a powerful set of software tools to visually explore and analyze spatial information.  Vector GIS data includes point, line and polygon features, which can be selected by proximity or by attributes features have in common.  Intended for students who have taken the previous class or have explored GIS software casually, this class will provide hands-on examples of the most common vector analytical tasks in GIS.

To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=839

GIS raster datasets are geographic phenomena stored as grid cells or as images.  Each cell or pixel contains information that can be modified to generate new raster data.  ArcGIS 10 has many tools to manage and manipulate raster data information.  Intended for students who have taken the class on vector analysis or have explored GIS software in some detail, this class will give hands-on examples of various raster analysis tools.


To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=851

Instructor: TBD

ArcGIS 10 has many different ways to access data sets, display them in a map, and analyze relationships over time and space. US Census data can be integrated with GIS boundary files to analyze the spatial relationships of poverty, ethnicity, environmental risk, and other parameters.  Hands-on examples will show how to find and download demographic data, how to combine the data with GIS files, and how to view the data in ArcMap. The class will work with historic US demographic data and explore the use of tables in ArcGIS. The session will assist any GIS user who wants to include tabular data in a spatial analysis.


To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=853

Maps can be extremely effective in communicating knowledge about an area.  ArcGIS ArcMap has a variety of tools and techniques to design maps.  Hands-on exercises will show how to use map-making tools within the software, and introduce common cartographic techniques.  The session will discuss how to design maps for a variety of presentation formats.

To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=854

Maps can be extremely effective in communicating knowledge about an area.  ArcGIS ArcMap has a variety of tools and techniques to design maps.  Hands-on exercises will show how to use map-making tools within the software, and introduce common cartographic techniques.  The session will discuss how to design maps for a variety of presentation formats.

To register please view the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=854

GIS users often want to run a process multiple times, changing the inputs, parameters or summaries generated.  ArcGIS has many ways to help users automate processes. The exercises show users how to use graphic tools in ModelBuilder, and how to modify Python scripts to perform repetitive tasks and build simple models.

To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=1159

Global Positioning System (GPS) receivers collect spatial information for use in GIS and elsewhere.  The accuracy, precision and overall capabilities of GPS receivers differ dramatically. The basic concepts of GPS will be introduced, and a variety of GPS receivers will be used to collect locations on campus.  The data collected will then be uploaded and displayed in ArcGIS, Google Earth, and other applications.


To register please visit the following link:

https://wass.princeton.edu/pages/viewcalendar.page.php?cal_id=1479

The Princeton Institute for Computational Science and Engineering (PICSciE) is pleased to announce its first conference highlighting research computing at Princeton to be held on May 8-9, 2012 at the Princeton Center for Theoretical Science. This conference will provide a perfect opportunity to engage Princeton's high performance computing community in developing a common vision on how to further strengthen its resources and services.

The two-day event will bring together computational scientists and researchers from across campus working on topics ranging from astrophysics to neuroscience. There will be poster sessions and an open discussion forum during the conference.