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GIS final
fuck this class
| Question | Answer |
|---|---|
| What is a map and what isn’t a map | A graphic statement that locates facts. Graphic - visual display marks that stand for something else. Statement - to put forth info, a formal embodiment of facts or assertions. Locating facts - tangible and intangible phenomena located in geographic space |
| Elements of a Map | Geographic framework -projection, scale, coordinates |
| Why do we say that maps lie, how do they lie | In order to convey complex 3D information we must choose distortions to preserve whatever it is we want to show |
| GIS definition | • A Geographic Information System • Set of computer tools designed to work with spatial data • Spatial data is information indicating the location of a feature on the Earth (hardware, software, data, people/workflows) |
| what’s special about spatial data | ? |
| types of information | content (visual) and context (metadata) information |
| types of data | WGS 1984 - earth centered Most common for international and web maps, Default datum for most GPS units NAD - NA centered NAD 1927 based on Clarke 1866 spheroid Origin = Meades Ranch in Kansas NAD 1983 based on GRS spheroid Origin = Center of Earth |
| knowledge and how easily they can be shared | ? |
| types of software and computer platforms available | ? |
| popular programing languages used within GIS | ? |
| information vs data | data is the facts from which information is derived |
| Cartography and Mapping do’s and don’ts | • Map purpose/audience? • What are the appropriate symbols, colors, layout…? • Use intuitive colors, bold/bright carefully and sparingly • Only include necessary layers, highlight most important • Legends • What coordinate system is most appropriate? |
| coordinate systems | Addresses location & precision. GCS Composed of an angular unit of measure, a prime meridian, and a datum. Choice depends on map's purpose & extent |
| projections | transforming the earth's 3D surface onto a flat plane and the resulting distortions in area, shape, distance, or direction. Starts with a GCS > applies math formulas to convert degrees of lat/long into planar x-y coordinates (measured in feet or meters) |
| UTM | Universal transverse mercator. |
| State Plane | Split into systems and zones |
| Do all GIS maps need projection? | ? |
| projection vs (GCS) geographic coordinate systems | ? |
| types of distortions | projections distort either area, shape, distance, or direction. |
| Main type of World projections and what they preserve and distort | Mercator preserves shapes & distorts area (conformal/local), equal area map preserves area & distorts shape, Orthomorphic maps preserve direction/angle, equidistant maps preserve distance. |
| developable surfaces | flat surface that will become the map produced by the projection • Area (tangent) touching the globe will be most accurate • Distortion is least at points/lines of contact and increases with distance. 3 types: cylindrical, conical, azmuthal/planar |
| Datum | Datum Defined by: 1. Chosen spheroid/ellipsoid + 2. Location of it’s center relative to the geoid center + 3. Very precise surveyed reference/ control points/benchmarks Named after it’s origin (on or inside Earth) Hundreds of Datums worldwide! |
| Ellipsoid | Best for horizontal measurements (x,y). Degree of flattening given by f = (a-b)/a b = semi minor axis a = semi-major axis Reported in software as 1/f Can be local or global |
| Geoid | Geoid incorporates rotation and rock density information (earth slightly pear shaped) and is best for vertical measures (z). |
| Prime Meridian | greenwich, england. meridians are longitudinal bands or meridians - Not a consistant unit 0= 69 mi 45= 49 mi 90= 0 mi |
| Equator | center, measure of latitude - Parallels Parallel (equally spaced) 1 o= ~111km Variation of <1mi |
| What is the best projection for XXX area of the world, at what scale? | ? |
| UTM system, State Plane System | ? |
| Clues that give away in which projection a map/GIs file is in/not in? | ? |
| What are other ways to geolocate things | ? |
| What do you need to be able to map things? | ? |
| Spatial Data models | ? |
| attribute tabular data | Stores attributes of map features, is associated with a data layer, has special fields for spatial information |
| data compression | ? |
| DEMs | ? |
| TINs | ? |
| How do real world features get represented in GIS? | ? |
| Scale, Extent, Resolution | scale - how much of the earth to show, at what size. composed of extent (how much) and resolution (at what size) |
| Raster vs Vector (pros and cons, important differences) | ? |
| Geodatabase vs shapefiles | geodatabases create overlap area as new thing, they're smarter. shapefiles are dumb but universal |
| DBMS | database management system (DBMS) |
| relational vs flat databases | ? |
| Why is MS Excel not a relational DBMS | ? |
| Attribute Data and Tables: Relational databases | ? |
| Basic Vector Spatial Analysis: Overlays, Spatial Selection(Query) and Classification | ? |
| Topology vs Spaghetti | Spaghetti vectory data geometry (overlapping borders). |
| Raster Queries | use reclassification to create boolean images, intersect (overlay?) them to create one image |
| Vector (Re)classification | ? |
| dissolving | summarize attributes is added to the output feature class as a single field with the following naming standard of statistic type + underscore + input field name |
| Overlay types | erase, identify, intersect, spatial join, symmetrical difference, union, update |
| Distance and Buffer operations | the result of this operation is buffer polygons at the specified distances for the input geometry array. An option is available to union buffers at each distance. |
| Cartographic Modeling | • Several thematic layers of the same area are produced, processed, and analyzed. • Can be applied using the overlay method. • Operations on map layers can be combined into algorithms, and eventually into simulation or optimization models map algebra |
| Pros and Cons of raster analysis | Pros •Fast processing •easily compressed •global, neighborhood, and local operations •Allows for 3D •Cons: •Not discrete geographic locations (locations always generalized in the cell) •Detail depends on resolution •differing formats |
| encoding and storage of rasters | Bit depth capacity of a cell determines range of values a file can store. • Reduced Resolution Description (pyramids) allow for more rapid rendering |
| how are attributes handled in rasters | value attribute tables (VAT) - Raster version of an “attribute table,” more like a legend |
| raster spatial resolutions | Cell size plays a role. Resolution determines detail. Higher resolution takes up more space |
| formats of raster | Multiband • Band = sub-raster (each assigned pseudo colors) Multispectral (>3 bands) • Band = a raster image within an image (sub-image, includes full spectral range). Remote sensing, satellite data. |
| other ways to call raster images | ? |
| raster operations (types by operators and by spatial scale) | Operators can be mathematical or Boolean. Operator space: •Neighborhood (Focal) - cells around/adjacent •Local - singular cell info only •Global - Use value for entire datasets •Zonal - only pre-designed zone dataset (often a vector) |
| How are DEMs produced | remote sensing |
| What can be derived from DEMs | ? |
| Processing of DEMs for Hydro Applications | ? |
| Flow direction/Flow accumulation (How do they work) | Flow direction creates a raster of flow direction from each cell to its steepest downslope neighbor (biggest jump from one cell to the next is direction of flow). Accumulation calcs weight of all cells flowing into each downslope cell in the output raster |
| How do you translate a problem/question into a GIS exercise and set of tasks? | ? |
| What are the important questions one has to ask oneself? | ? |
| Use what you have learned conceptually during labs and the final project, and from how others have used GIS to address various issues | ? |
| shapefile components | Must •Main file (feature geometry) .shp •Index file (index position) .shx •dBASE table (database).dbf •Projection (coordinate & projection system) .prj Adtl •.xml metadata •.sbn Spatial index optimizes spatial queries •.sbx speeds up loading times |
| map coordinates | graph-like grids placed on the earth to assist with locating phenomena |
| What is a map simplified | georeferenced data of some type in a model. |
| What does a GIS contain? | • Hardware AND software, including… • Computers and computer networks • GIS software • Data (plus storage space and input hardware) • Personnel + a body of knowledge/conventions about cartography |
| What does GIS software allow for? | Data entry, management, and analysis • Thematic mapping (display of data) • Map design (layout, scale bar, north arrow, etc.) |
| 2 types of coordinate systems | Geographic Coordinate Systems (non-projected) • WGS 1984 • NAD 1983 / NAD 1927 • Lat / Long Projected Systems • Albers • Mercator • UTM |
| latitude & longitude | Angular measures from center of Earth |
| CGS | uses a 3D spherical surface to define locations Not a datum Includes: • Angular Unit of Measure (e.g. lat,long) • Prime Meridian (e.g. Greenwich) • Datum (e.g. NAD 1927, NAD 1983)(based on spheroid) |
| What do you need to project a map? | 1. GCS including datum, origin, extent, x/y axis 2. Projection system |
| Why do projections vary? | Scale/extent What they preserve/distort Developable surface How surface contacts the earth & # of contact lines Source of ‘light’ Aspect, orientation or position of the plane/ developable surface with respect to the earth rotation axis GCS Author |
| How the surface contacts the earth & number of contact lines/ points | tangent (touching) secant (through) |
| Light source | At center of the earth, from infinity, from the other side of the globe, from within |
| Aspect/orientation | Normal: like you stuck the earth in a can (projection surface is equator). Transverse: like you stuck the earth in a can and then tipped it over (projection surface is a meridian). Transverse - somewhere between the two |
| Author distortions | • Skill/state of the knowledge at the time • Objectives • World View • Trade offs |
| Vector features | points, lines, polygons |
| Shapefiles | • Older file type • Spaghetti • Geometry needs updating after being edited. Can cause problems when measuring adjacency. • Universal, transportable • Represents a geographic record that is stored in a file with: ID & location-defining coordinates |
| Geodatabases | • More robust • topologic (shared border) data geometry • ‘Spatial folder’ (cylinder icon) know they belong together • coordinates & topologic relationships recorded • Updates geometry automatically • Less known, other software can't use it |
| Table info | each line is a record. each column is a field/attribute/item. Table sources: Dbase (.DBF) ASCII Text (.csv) Spreadsheet (.xls) Attribute or Standalone. Latter has tabular data not associated with spatial data, OID not FID |
| Field types | Short integer (3e10), long integer (2e9), float (1.2e38 including decimals), double (2.2e308 including decimals), or text (non numerical) |
| Tabular operations include: | Sort • Add fields • Query • Select • Calculate • Summarize • Aggregate • Join |
| Joining tables part 1 | Appends a source table to a destination table. • Destination table = the original attribute table (spatial) • Source table = the source of new information (often, a stand alone table) • Must have a exact match common ID |
| Joinging tables part 2 | • Cardinality (direction of a join): 1 to 1: Each record in the destination table goes to 1 record in the source table. Ex: 1 gov/state many to 1: Many in destination table to 1 in the source. Ex: cities/state |
| Illegal join | one to many is no can do. Can't have many in source and 1 in destination |
| Attribute Queries | Questions based on the fields/variables (columns) and the values/entries registered in their records (rows) in the table. Output= a subset of rows ► Type of operations: SQL language 2 types mathematical (=,>,<, etc) or Boolean (AND, OR, etc) |
| Spatial Queries | Only in GIS and Maps ► Questions based on the location of the features/objects (points, lines, polygons) in the map with respect each other. ► Output= a subset of rows, new field, or new feature. ► Type of operations: Selection, Spatial Join, Overlay |
| Spatial operations | Selection (pointer, select by location): output= subset of features (rows) ▪ Spatial joins (inside, distance): output= a new field in the attribute table ▪ Overlay (with/without att.data: clip, intersect, union, etc.) output= new feature |
| Spatial operation - selection | proximity/distance relationships (adjacent or within a distance), containment (one feature within another), intersection (one feature intersects or overlaps with another) |
| Spatial operation - spatial join | attributes of features in the source layer are appended to features in the destination table based on the location/spatial relationship. • May be performed on any two spatial data layers. • Create a new, permanent data layer (not temp like attribute) |
| Spatial operation - spatial join part 2 | This new layer…. • Contains the same geography and number of records of the destination table • Is the same feature type as the destination layer |
| Spatial join operations | CONTAINMENT: One feature inside another ► PROXIMITY: One feature closest distance to another ► SIMPLE (what _ is _ close to/in?) OR SUMMARIZED (how many _ in/close to each _) |
| select by location vs spatial join | Spatial joins are more permanent bc they create a new layer (geography + attribute table) containing new info (at least 1 new field/column) based on the spatial relationships of features contained in the map layers |
| Raster data | • Best for continuous data • Includes • Imagery • Remote sensing data (multiband) • Good for Thematic Mapping in a GIS • Variables can be quantitative or qualitative (e.g., precipitation, land cover map). |
| Raster cells | • Spatial unit is the cell • Raster is almost always rectangular • Cell is almost always a square • Size of cell is the resolution of the dataset • Most raster data has only one value for each cell (no real attributes) |
| Raster image classification | Unsupervised (let the data speak, use stats) vs Supervised (with training sites/calibration/sample polygons) |
| cartographic modeling tips | • Be sure extent, resolution, and coordinate system/projection are exactly the same — necessary for Map Algebra operations to work |
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