GIS4043: Journey to Find Data

This was a mammoth task in hunting for Data! I have survived week 7 and week 8 as this was an extended Lab for the Mid-Term interrogation.

Our task was to find data for an assigned county in Florida (mine is Charlotte county) and create a map (up to three maps) that depict five vector layers, two environmental layers, and two raster layers. This seems like a lot a data to me. The specific learning objectives are:

• Review and record metadata for data coming from multiple sources
• Select GIS data that meets the needs of a defined project (scale, attributes, geographic extent, time    sensitive, software being used or required format)
• Download data from online sources
• Practice data management of GIS data coming from multiple sources
• Detect and correct data errors for use in a GIS
• Intelligently select a geographic projection to be used in a defined project
• Detect and correct geographic projection issues
• Reproject data from Albers to UTM
• Utilize select by location and clip tools in ArcGIS to isolate a study area
• View selected records and create a new map layer from selected feature
• Create easy to interpret maps presenting multiple downloaded data layers using ArcGIS

I acquired most of my data from FGDL and one file from LABINS. The files I selected were:

o   cities_feb04 (cities & towns)

o   countyshore_areas_jul11 (County boundary)

o   fdot_localnames_jan15 (major roads)

o   fnaiip_jun10 (Environmental 1: Invasive Plants)

o   gc_parks_aug14 (Public Land: Parks)

o   nhd24waterbody_dec12 (Surface Water)

o   rarimpwaters_2013 (Environmental 2: Strategic Habitat)

o   ned08 (Raster1: DEM)

o   q2417nw.jp2  (Raster2: DOQQ) Acquired from LABINS

The above data search took a very long time-- good thing we had two weeks to conclude this task. Sorting through FGDL to find data such as Parks, Roads, Surface Water, etc. was a challenge by itself. Initially, I placed all the Data Frames on one map; however, as I viewed the requirement to not exceed 3 maps, I was concerned that 3 data frames plus an inset map would actually be 4 maps. I learned a great lesson here: Data Frames are not maps-- by themselves. I was still somewhat confused because we call an Inset Map a Map-- presumably the Inset Map is in reference to another, perhaps more detailed Map? That sounds like two maps to me. But alas, these are data frames that make up "the map." So, I divided my data frames into two maps: 

Map 1:  I sized the county clip to 1: 400,000.  This was much better than the original size I had to use when all the data frames were on one sheet (one map). Surface water was a problem as there was so much of it. I used a lighter blue. Transparency and turned off the OUTLINE. This presented a much better image.

MAP 2: For the second map, DEM and DOQQ, I was not satisfied that the aerial photo was so small against the county DEM; I needed to use an inset (map). In order to better see the detail in the aerial, I used a 1: 100000 scale and used the county clip behind it with a very light green to help highlight and pop-out features. By enlarging the DEM to a scale of 1:400000, like the first map, you can better see and appreciate the elevation change over the county.  I also added a text box explaining a little about the Orthoimage; how it is presented and what it shows. Finally, I changed the DOQQ Legend to say Vegetation- Soils – Water, instead of, Red- Green- Blue.