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by: Sarah Massar

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# GPHY384 notes, lectures 4&5 GPHY 384

Marketplace > Montana State University > Earth Sciences > GPHY 384 > GPHY384 notes lectures 4 5
Sarah Massar
MSU
GPA 3.9

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Topology is in here along with some decimal degree math and review.
COURSE
PROF.
Stuart Challenger
TYPE
Class Notes
PAGES
4
WORDS
CONCEPTS
GIS
KARMA
25 ?

## Popular in Earth Sciences

This 4 page Class Notes was uploaded by Sarah Massar on Sunday January 31, 2016. The Class Notes belongs to GPHY 384 at Montana State University taught by Stuart Challenger in Fall 2015. Since its upload, it has received 25 views. For similar materials see Advanced GIS and Spatial Analysis in Earth Sciences at Montana State University.

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Date Created: 01/31/16
GPHY384 Lecture 4&5-Topology 1/26&28 Lecture 4 1/26 REVIEW: +Standard Cartographic Elements- what every map needs to have on it 1. Figure/Ground (main image/background)- the figure is the “thing” being quantified and the ground is the supporting information 2. Title 3. Neat Line- the border, goes around everything, helps one to focus 4. North Arrow 5. Scale Bar- use graphic 6. Credits- Author, Date, Sources Optional Elements: 1. Legend a. Could use standard symbology and labels instead 2. Graphics 3. Logos +Applied Design Principles- What a well-designed map needs to have 1. Readability- easy to read and decipher what is being mapped 2. Hierarchy- most important map elements are where the eye is drawn a. Top left is highest level, bottom right has the lowest level 3. Balance- if the map was hung on a string, would it hang straight? Or does one end appear “heavier/more crowded” than the other? 4. Contrast- text pops out of background a. Add a halo around text 5. Repetition- if have a duplicate image make sure they are the same orientation and scale 6. Alignment- keep everything in straight lines 7. Proximity- “like” things on the map should be grouped a. North arrow, scale bar, and credits should all be in the same area, normally the bottom right TOPOLOGY: +Data Models- ways to represent Geography -Raster- geography represented as cell matrix’s that store numerical values -Vector- geography represented a points, lines, and polygons -Various types of vector data models 1. Spaghetti data structure- looks like spaghetti 2. Arc/Node data structure -Nodes- points -Ties- min and max coordinates for the data set 3. Topological data structure 4. Object oriented data structures +Topology- 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 -Can edit multiple geoclasses in one step -edited in database -There are 2 ways to conceptualize Topological data 1. ArcInfo Planar- shared geometry (pt., lines, and polygons) -all three classes stored in data set via table relationships -gives direction i.e.-stream flow, traffic flow -Relationship defined by: -Connectivity- arcs connected at nodes -Area Definition- polygons defined by arcs -Contiguity- arcs store left/right polygons -some advantages would be being able to calculate the fastest route home by taking into account speed limits, location of stop signs/lights, and average size of traffic flow -has arc (line) and node (point) attributes 2. ArcGIS object based- coincident (in the same space in the same plane) geometry -since the 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 Evolution of ESRI data models Common Approximate Interchange Vintage Software Data base Complexity Storage File formats Georelational .e00 - Arc Info Coverage Directories and Early 80’s ArcInfo Coverage - Topological files .zip - Arc Info Grid .gzip ArcView Shapefile Early 90’s (currently Simple Files .zip 3x) Personal Geodatabase - Microsoft Toplological Access Personal Early 00’s ArcGIS Geodatabase Object - Directory w/ .zip Oriented files .mdb Enterprise (SDE) - RDBMSh -ESRI has updated their data models over time and now if one has an older model they cannot open the newly published data -Data from clearinghouses only requires shapefiles Lecture 5 1/28/16 REVIEW: -If one wants to view or move data, they need to know how it is saved -.pgr- shows projection is defined -.dbf- attributes -.sid- compound raster data, lots of imagery, zoomed in -“Converge” complexity data comes up as files in Internet Explorer, can only view in the ArcGIS application -Shapefile- what most of our data is stored in -will come up as a folder in Internet Explorer -3 Color Models 1. RGB- red, green, blue 2. HSV- hue (color), saturation (amount of color 1-100%), value (amount of white or black mixed in 1-100%) 3. CMYK- cyan, magenta, yellow, black -reflected light, what is printed +Qualitative- categorical, what is it? +Quantitative- how much +Geovisualization- allows us to look beyond the static map -showing spatial and temporal spread of fires -Earth is a geoid, a flattened sphere -Rhumb line- line of constant compass direction -Standard line- where projected surface (plane, cylinder, cone) hits the globe -most accurate place to map -Graticule- graticular mesh of Earth’s surface with lines of latitude and longitude -Longitude- Meridians (N-S) –All are great circles (pass through the Earth’s center) - Latitudes- Parallels (E-W)- only the equator is a great circle -Coordinate Systems 1. Geographic – conceptualized with national data -non-projected so units are degrees (degrees, minutes, and seconds) -keeps direction constant, but area, shape, and distance are distorted 2. State Plane- Montana Library Clearinghouses -projection is Lambert conformal conic 3. Universal Transverse Mercator- Gallatin County Clearinghouse -projection is transverse Mercator -Converting Degrees, minutes, and seconds (DMS)  Decimal degrees (DD) +/- [D + M/60 + S/3600] DMS  Decimal minutes (DM) +/- [D, M + S/60]

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