Club Meetings and Activities

Thursday, May 16, 2013,2:00 PM
Best Dam Bike Ride route planning meeting, SARUP 194. This is a great opportunity to get experience using the Esri Network Analyst tool and to make a difference at the same time.
See the Meetings page for details.

Club Officers

Hugh Christie, president
Angie Jackson, vice-president
Joe Larsen, secretary
Nelida Cortes, treasurer

Notices and Events


May 15-16, 2013
Wisconsin Land Information Association Spring Regional Meeting, Wausau, Wisc.

May 22-24, 2013
Free and Open-Source Software for Geospatial-North America (FOSS4G-NA), Minneapolis, Minn.

June 2-3, 2013
Milwaukee Data Initiative National Day of Civic Hacking,
Milwaukee, Wisc.

July 8-12, 2013
ESRI International User Conference, San Diego, Calif.

September 13, 2013
Deadline-NAICS Dynamic Map Competition

September 13, 2013
Deadline-NAICS Student Map and Poster Competition

Kern Park Solar Analysis

Client: Peter Trio

Need: To visualize the amount of sunlight falling on a hypothetical building site in Kern Park.

Description: In late January 2012, Peter asked the GIS Club to help him with an Architecture 420 project. He was designing a hypotetical school in Kern Park. He need to know the intensity and pattern of sunlight falling across the park throughout the year. Peter used the solar analysis that the club did for the UWM Food and Garden Club in his design for food gardens near the Sandburg residence halls. See details of his plans at his web site, ObjectiveArchitecture.com.

Results: The club used the ERSI Spatial Analyst Solar Analyst tool to determine the total solar energy during each month. We started with LIDAR data from the Milwaukee County Land Information Office. In this raster image, elevation is mapped to graytones. The lighter tones indicate greater elevation. Streets are symbolized by solid white lines. The Milwaukee River flows through the right side of the frame.

LIDAR


We then used the Solar Analyst to build a raster for each month, symbolizing the direct solar energy, in watts/square meter, accumlating during each month. This process combined the elevation of the terrain, trees, and buildings with the postion of the sun to model the path of shadows during each day in the month, thus translating

In the raster images that follow, lighter graytones indicate more solar energy. The images begin with January in the upper left, followed by February in the upper right, through December in the lower right.

 
Jan Feb
Mar Apr
May Jun
Jul Aug
Sep Oct
Nov Dec

From this, Peter could see how the sunlight, and solar energy, varied during the year as a guide to placing his structure.