GPHY384 final exam notes
GPHY384 final exam notes GPHY 384
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This 6 page Study Guide was uploaded by Sarah Massar on Sunday May 1, 2016. The Study Guide belongs to GPHY 384 at Montana State University taught by Stuart Challenger in Fall 2015. Since its upload, it has received 44 views. For similar materials see Advanced GIS and Spatial Analysis in Earth Sciences at Montana State University.
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Date Created: 05/01/16
GPHY384 Final Notes -Look at all the diagrams we have done -Review midterm and all in-class exercises -Specific things to know because Stuart mentioned them in the review: RASTER +Raster- uses cells that represent categories -always a number -Use an associated table to find what values mean +Extended Raster-When one joins the raster and associated tables to get more data -Two types of Rasters 1. Categorical Raster- an array of equally sized cells arranged in rows and columns, and composed of single or multiple bands. Each cell contains an attribute value and location coordinates. +Zone-group of cells with same value +Region- zone of cells that are continuous -stored in Integrated Grid 2. Continuous- elevation -whole or decimal numbers -no associated value attribute table -Stored in Floating Point grid +NoData- is a value -cell will not participate in the drawing SPATAIL OVERLAY- superimposing layers of geographic data that cover the same area to study the relationships between them Methods: (review in-class exercise) -Union- all input features are included as an output feature -Intersect- only input features that overlap are included in the output -Identity- only all of the features from one input set and all overlapped features are included WEIGHTED OVERLAY-use map algebra equation to rank variables in an equation according to importance Variable Weight: Farmland .2 (20%) Slope .2 (20%) Distance to City .2 (20%) Floodplain .4 (40%) Equation: (“Farmland”*0.2)+(“Slope”*0.2)+(“City”*0.2)+(“Floodplain”*0.4) UNCERTAINTY -There are several stages in our projects where we can begin to expect uncertainty -Real World Observations/Conception Measurements/compilation Analysis -Examples of error: -accuracy/inaccuracy -ambiguity -when an attribute may be appropriately assigned two or more different values -the shoreline: a point may be dry land at one point in the day and underwater at a different time -Direct measurement- crop yield -Indirect measurement- fertility of the soil -vagueness -used to describe indefinite boundaries that are constantly changing -the area of land that acts as a habitat for animals -fuzziness -boundary is blurred -line between soil types OBJECT ORIENTED DATABASE- A data management structure that stores data as objects (instances of a class) instead of as rows and tables as in a relational database -every objects identity is managed in the system -features have natural behaviors (road only crosses a stream at a bridge) -Properties of object oriented databases: +Inheritance- the new specialized classes share properties with the superclass, just with added unique properties -transportation is a superclass, with roads and railroads being specialized subclasses with all the same properties with a few unique ones +Methods- an action an object can perform -objects in same specialized class can perform the same methods +Polymorphism- each object will have a unique response to the same method +Encapsulation- data packaged together with its structure and behavior FRAMEWORKS +NSDI Framework- National Spatial Data Infrastructure -a means to assemble geographic data nationwide to serve a variety of uses -asking locals for GIS information to make it accurate -creates cheap, standardized datasets for everyone to use -comprised of different layers: -Geodetic control -Cadastral -Orthoimagery -Elevation -Hydrography -Administrative units -Transportation +MSDI Framework- Montana State Data Infrastructure -datasets for Montana, has a few more than the NSDI SQL: -if SQL for an elevation dataset and want all elevation value higher than 2,000: -Select*From Attributes Where ELEV>2000 -Other stuff you might want to remember: RMSE- -RMSE-Root Mean Square Error -equation used to find error between two datasets 2 2 2 2 - √(e1+ e 2 e +3e ) n e=error n n= number of measurements -Use RMSE to find the appropriate scale: -ex. if RMSE 27 meters: (1/x) = (1/50”)/(27 m) (1/x) = (.0005 m)/(27 m) .0005x = 27 1:54,000 TOPOLOGY- +Topology- a set of rules or behaviors which defines spatial relationships between vector geographic features -it integrates feature data so points, lines, and polygons are all in the same table -detects error well -great for managing spatial relationships -Integrated feature management – relationship stored in database -Can edit multiple geoclasses in one step -edited in database -What the rules of Topology dictate: -Connectivity- arcs connected at nodes -Area Definition- polygons defined by arcs -Contiguity- arcs store left/right polygons -Since points, lines, and polygons are in the same space, certain relationship rules have to be followed -Polygon Rules: -Must not overlap -Line Rules: -Must not overlap -Point Rules: -Must be within a polygon -Must be at the end of a line -Topology ensures that buffers don’t overlap -Use topology if the rules would be helpful in managing the data CONVERTING- Degrees, minutes, and seconds (DMS) Decimal degrees (DD) +/- [D + M/60 + S/3600] DMS Decimal minutes (DM) +/- [D, M + S/60] MAP ALGEBRA- Map Algebra Functions in raster: 1. Local (per-cell)- intersects with only 1 cell location - Take exact same cell location from all the stacked layers - Nothing around the cell is taken into consideration - Ex. resampling, weighted overlay 2. Focal (neighborhood)- take cells touching target cell into consideration - Ex. slope - For slope, take the max difference between cells on either side to determine value of target cell - Default neighborhood is 3x3 +Block- neighborhood that is generalized so all cells become the same -start out different and then change to computed target cell value 3. Zone- all cells with the same value that can be contiguous or non-contiguous - Does calculation by zone +Region- a contiguous zone with the same values 4. Global- acts on whole raster -output is calculated using all the cells in the grid DATA MODELING- 1 NF- eliminates duplicate fields -joins tables 2 NF- reduces redundancies -breaks things up into separate tables 3 NF- removing from a table those columns that do not depend on the table's primary key. SPATIAL ANALYSIS: +Model- abstract of reality +Analysis- separating of something into parts to study it -breaking down +Synthesis- combining separate parts into a complex whole -putting together -most of what we do in ArcMap +Distance -Euclidean-a straight line, Pythagoreans theorem -Network-linear networks like roads or rivers -Cost Surface- cost weighted difference, add in elevation and how much it would be to cover the distance not only horizontally, but vertically as well +Transformations- moving the coordinates of something on the map -Neighborhood functions -Buffers -in vector represented as Euclidean distance -in raster it is Euclidean or cost -Adjacency-what is next to it -raster represents well -vector used right and left polygons for this function -Proximity-what’s close -raster represents well -vector uses distance methods to show this
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