Field Exercise 5 - Microclimate Geodatabase: Working with Domains

INTRODUCTION

             The objective of field exercise five is to create a microclimate geodatabase with appropriate fields, attribute types, and domains for the purpose of deploying it onto a portable GPS device. The portable GPS device equipped with the geodatabase would then be used in the field to collect various climate measurements. Creating a deployable geodatabase with the proper specifications prior to data collection is done to speed up the collection process as well as to increase data integrity.

Geodatabases

            Understanding how a geodatabase operates and performs is essential when working with large sets of geospatial data. In a nutshell, a geodatabase is a repository for files that contain the same spatial data, and it has the unique ability to perform interoperable tasks. Interoperability is the ability of feature classes to work/communicate with one another and is one of the main strengths of a geodatabase. The old system of geospatial technology relied on shapefiles that contained separate spatial data and could not perform interoperable tasks. With a geodatabase, however, all files stored within create seamless feature classes that can be fit together like puzzle pieces.

Domains

            Geodatabases also contain fail safes in the form of attribute domains. An attributes domain can be set by the geodatabase creator, and is simply the legal set of values for that attribute. Using geodatabase domains is encouraged because it increases data integrity. There are two basic domain types: range domains and coded domains. A range domain specifies a valid range of values for a numeric attribute. When creating a range domain, you enter a minimum and maximum valid value. A range domain can be applied to short-integer, long-integer, float, double, and date attribute types. For a coded value domain the attribute being measured receives a coded value that corresponds to the actual attribute being measured (this can be for any attribute type). For instance the actual attribute might be a classification scheme for pipes; so water and sewage might be two two possibilities. A coded value domain assigns numbers to these classifications so water might equal a coded value of one and sewage might equal a coded value of two.

METHODOLOGY

Microclimate Geodatabase

This section covers the creation of the microclimate geodatabase.
Step 1: The first thing I had to was create the geodatabase and name it. The name I used was generic: Micro_Climate_myusername.gdb. Figure one below shows how to execute step one.


Figure 1: right click on the desired folder, click new, click file geodatabase. It will then ask the user to name the geodatabase

Step 2: The next thing I had to do before completing the microclimate geodatabase was set the parameters for the field domains. As stated above domains create a legal set of values that will be accepted for an attribute and can either be a range or coded value domain. The geodatabase will not allow a number to be entered that is outside of the legal range. The legal set of values I created were different for each domain created. I will go into further detail below in the fields, data types, and domains section. By right clicking on the geodatabase and scrolling down to properties, the domain properties window can be accessed.  Figure two below shows a list of my microclimate geodatabase domains.


Figure 2: shows where domain names and parameters were created. A detailed list of the domains will be provided in The fields, data types, and domains section below.  

Step 3: the next step was to create a point feature class that contained all the microclimate fields I felt were necessary to creating an accurate climate map of the UW Eau Claire campus. The fields I deemed necessary were as follows: Wind_Speed, Wind_Direction, Humidity, Dew_Point, Temp_Surface, Temp_2Meters, Wind_Chill, Ground_Cover, and Notes. All of these different fields were stored under different data types depending on what I would be measuring them with. In general, if the measurement being taken is a simple number a short integer data type will suffice. If the measurement being taken is a very long number that includes decimals, a long integer or float data type may be necessary. In order to record visual observations a text data type may be necessary. In figure one below a list of my field types and corresponding data types can be seen.

Figure 3: shows the list of microclimate fields and the corresponding data types they are stored in. 

 

DISCUSSION

The fields, data types, and domains

Wind_Speed - I chose wind speed as a micro climate field because it will show where there are wind tunnels as well as calm areas on campus. I will be measuring wind speed using the short integer data type. The domain I set up was a range domain to be measured in miles per hour with the minimum value set at zero and the maximum value set at 50. I chose these numbers because wind speed can never be less than zero mph and it is very unlikely that it would be higher than 50 mph.

Wind_Direction - I chose to measure wind direction because it will show how the campus buildings affect the air's behavior around campus. I chose to measure wind direction using the short integer data type. I used a range domain measured in azimuth with a minimum value of zero and a maximum value of 360. I chose these numbers because these are the degree parameters on a compass.

Humidity - I'm measuring humidity because I want to see how both elevation and proximity to the Chippewa River affect it. I will be measuring humidity using the short integer data type. I used a range domain measured in percent with a minimum value of zero and a maximum value of 100. I chose these numbers because there can't be negative humidity and there can't be humidity over 100 percent.

Dew_Point - I'm measuring dew point to see how saturated the air is with moisture. I expect it to be quite low because it is cold and dry outside at this time of year (early March). I will be measuring the dew point using the short integer data type. I used a range domain to be measured in degrees Fahrenheit with a minimum value of -30 and a maximum value of 60. I used these temperatures because it is unlikely that the temperature would be below 30 degrees Fahrenheit or above 60 degrees Fahrenheit in early March.

Temp_Surface - I'm measuring the surface temperature in order to see how it varies throughout campus. I'll be measuring the surface temperature using the short integer data type. I used the same range domain for the surface temperature as I did for the dew point. This is because the temperature minimum and maximum will be the same.

Temp_2Meters - I chose to measure the temperature of the air two meters above the ground just to see if it varies from the surface temperature. I chose to measure the temperature two meters above the ground using the short integer data type. I again used the same range domain for the temperature at two meters as I did for the dew_point and temp_surface fields because the temperature range stays the same.

Wind_Chill - I'm also measuring wind chill because it will show the effect the wind has on the temperature. I will be measuring the wind chill using the short integer data type. I used the same range domain for wind_chill, temp_2meters, temp_surface, and dew_point because the minimum and maximum temperature range for those measurements were all the same.

Ground_Cover - I will be measuring the ground cover to see if it has an effect on any of the other measurements. I will be measuring the ground cover using the text data type. I used as coded value domain for the ground cover field because I simply needed to input the type of ground I was standing on. The coded values were as follows: 1 = snow, 2 = concrete, 3 = blacktop, 4 = grass, 5 = gravel, 6 = sand, 7 = water, 8 = other.

Notes - the notes section is for me to record anything unusual or noteworthy I suppose. The notes will be recorded using the text data type. The notes don't necessarily need a domain because they will be different every time, but a coded value domain can be used to input often used observations.

 CONCLUSION          

            Attribute domains are supposed to increase the efficiency of data collection as well as data integrity, and the domains I created for my microclimate geodatabase did just that. When I was out in the field physically collecting the data I knew that the data I was entering could only be relevant data due to the domain fail safes I had set up prior to collection. I was also able to enter the data faster because all of the microclimate fields were present with readily available scroll down lists. Creating a deployable geodatabase prior to the data collection also allowed me to become familiar and comfortable with the different climate fields I would be working with. In other words I had a set plan I was able to follow which can be important as sometimes obstacles in the field can confuse or sidetrack a data collector. Creating a deployable geodatabase with set domains may have seemed like an arduous process, but in actuality it only took about twenty minutes to complete so it's well worth it to create a game plan before heading into the field.