Lab 4: Normalizing Geodatabases

• Introduction: 
• In this week's lab we learned how to create our own geodatabases on ArcCatalog and how to normalize data entry for feature classes to make recording attribute data in the field with GPS devices much easier plus more accurate and efficient. Collecting attribute data along with GPS points can give a much more in depth view of how smaller scale components such as dark pavement on a road or a specific building have on a wider area being studied. This can be pertinent to ones research in providing a detailed description of an exact location in a collection of points.
• Study Area: 
• The area where the points of data collection will be taken is the lower campus of U-W Eau Claire, Wisconsin, U.S. A campus aerial photo with zones is also added to the Geodatabase for visual ground references. On Tuesday, February 23rd of 2016 at around 5:30 pm the atmospheric conditions were  foggy and cloudy with light rain and a temperature readings around 45 degrees Fahrenheit.
• Methods:
• In ArcCatalog a new geodatabase was created to take microclimate recordings of UWEC's lower campus. A point feature class was added with fields including temperature, humidity, wind direction, speed and several others. These fields were then normalized to fit the data they would soon contain. Normalizing fields helps with data entry errors which can throw off an entire study. Some fields get normalized by an acceptable range of numbers while others can be created to have a selection of text to choose from. It is important to have recognizable field names for ease of data entry and to have the data type pertain to the specific field. This way data entry errors can be cut down. For example if a temperature field is being created and the it is known that the temperatures in the area being record won't reach or exceed certain numbers, a range can be set. Therefore if a temperature outside of the range is incorrectly inputted then it will be rejected. This can be done in the geodatabases feature class properties window. (shown below in figure 1.) 

Figure 1. a view of the fields in the feature class in ArcCatalog

•  After normalizing the fields the geodatabase is opened up in ArcMap where it is paired with an aerial photo and deployed through ArcPad to the GPS device, in this case the Trimble Juno.
• Once the geodatabase was transported to the GPS we were able to pair into groups to collect sample readings around campus. After a couple readings were taken the GPS was connected to ArcMap once again where the new points and attribute table could be seen.
• Results/Discussion: 
• As this lab was in preparation for the next only two data points were recorded. While the readings show little variance on a large scale, It can be noticed that proximity to buildings and elevation play a role and truly have an affect on a surrounding area.  Being able to take multiple data points in an area and combining that information can show an overall glimpse of an area and can show variances in specific spots as well.
• Conclusions:
•  What makes data collection with mapping GPS different than just gathering a point is the fact that you truly pinpoint a specific location tied to the Geographic Coordinate System and have the data associated with that point linked together. Proper database setup and data normalization ease the process of data collection and can help prevent errors.
• My first try creating the geodatabase I realized I had actually created a polygon feature class instead of a point feature class and soon found out I wouldn't be able to record any data that way. I was then able to quickly remake a new geodatabase correctly and catch up before I fell behind. The second time creating the geodatabase I also included a notes field which was most helpful once in the field and something I won't forget in the future.