GEO 481/506  Mid-term exam review items Oct 2009

* Definition of GIS

process-oriented

Problem-solving oriented                

* DIKI: data, info, knowledge, intelligence  

* GIScience vs. GISystems

* Examples of typical GIS operations 

* Small vs. large map scales

* UTM and State Plane coordinate systems

* Identify the UTM zone for given longitudes

* Map projections vs. coordinate systems     

*3 Fundamental components of GIS data

                   spatial location, attributes, and topology

* Types of attribute data

                   nominal, ordinal, interval, and ratio

* The two views

                   objects vs. field

* The two data models and how they work

                   vector vs. raster

                   advantages and disadvantages of each

*Data structures

       raster data structure – run length and Quadtree

                   vector data structure – specifically topological data structure

       - the four tables and the relationships they represent

* Database models              

       Relational and object-oriented

*Response of earth features to EM energy

                   reflection, transmission, absorption, emission

                   reflection+transmission+absorption=100%

*Define four types of resolution

                   spectral, spatial, radiometric, and temporal

* How do we calculate distance between a satellite and a GPS receiver, and why do we   

need at least 3 satellites?

* How does differential GPS work?

* DEM

                    details of the 1:24,000 DEM and 1:250,000 DEM data

* The storage of TIN data

                    edges, nodes, and elevation

* TIGER

                    Census units – census tracts, block groups, and blocks

                    The coordinate system used by TIGER – geographical

                 Content of spatial TIGER data, linear street and polygon census unit

* The nature of DLG, LULC, HUC, and Soils (SSURGO and STATSGO) data

                 content, map scale, and coordinate system if covered in the class

* Two pairs of terms – accuracy/precision, and error/uncertainty

* Inherent and operational errors – define and give example of each

* Data quality and data quality assessment

                  metadata

                  5 components of data quality

* Define garbage-in/garbage-out (output accuracy)