Intro. To GIS Lecture 5 Downloading and Exploring Datasets March 4 th , 2013

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Intro. To GIS Lecture 5 Downloading and Exploring Datasets March 4 th , 2013. Reminders. Please turn in last weeks homework Midterm review in 2 weeks (March 13 th ) Review Session: next Wed (March 6 th ). REVIEW:Heads-up digitizing. Also known as on-screen digitizing - PowerPoint PPT Presentation


Introduction to Geographic Information Systems

Intro. To GISLecture 5

Downloading and Exploring Datasets

March 4th, 2013RemindersPlease turn in last weeks homework

Midterm review in 2 weeks (March 13th)

Review Session: next Wed (March 6th)

REVIEW:Heads-up digitizingAlso known as on-screen digitizing

Scanned maps or aerial photographs used to trace features and record locationsPaper maps require a large format scannerImages must be georeferencedCan still be very time-consumingREVIEW: GeoreferencingWhen images with unknown coordinates are fed into GIS2D georeferencing: resize (rescale), rotate, and translate to fitControl pointsTransformations:PolynomialFirst order (affine)splineHistoric Map

REVIEW: New ShapefileCreate New ShapefilePoint, polyline, polygonCoordinate SystemEmpty attribute table

REVIEW: New AttributesBefore you start to edit, add fields:Consider the information you need to store about the features you will be digitizing (i.e. type, name)Name: no spaces, charactersChoose the correct field typeFor text, edit length (max = 254)

REVIEW: The Editor ToolbarOptions greyed out depending on feature typeTools for creating or modifying featuresUse to open the attribute windowAllows you to edit attributes for selected featureAttributes can also be input into table directly

REVIEW: GeocodingConverting street addresses to XY coordinates

Reference Layer(Indexed Network)

Attribute Table

ResultsREVIEW: ApplicationsMapping restaurants in downtown BostonMapping customers' addresses for your business/education Mapping households with high power consumption (e.g. nstar)REVIEW: InterpolationMeadowlark St.From:700To:799750 Meadowlark725 Meadowlark} OffsetREVIEW: Address LocatorChoose locator typeSpecify street dataChoose the right fieldsFrom addressTo addressPrefix (i.e. East, West)Street NameStreet Type (Rd./St./Ave.)Suffix

REVIEW: Rematching

Fixing the unmatched addressesREVIEW: Remote Sensing 03_16_FigureREVIEW: Remote Sensing Platforms

Unmanned Airborne Vehicles14REVIEW: Earth Observing (EO)/Infrared (IR) Remote Sensing SystemsSpace borneCORONAIKONOS / Geoeye (high spatial res.)Quickbird / WorldView (high spatial res.)Landsat/ SPOT (medium spatial res.)MODIS/VIIRS/AVHRR (low spatial res.)Airborne (UAV)AVIRISPredatorGlobal Hawk

REVIEW: Concept of Resolution SpatialSpectralTemporalRadiometric

REVIEW: Spectral Resolution Electromagnetic Spectrum

Pan band

REVIEW: Spectral Resolution Reflectance (%)Electromagnetic Spectrum REVIEW: Spectral Resolution Panchromatic (one single band, e.g. CORONA, old aerial photographs, IKONOS/Quickbird Pan band)Multispectral (several bands, e.g. Landsat, MODIS)Hyperspectral (many bands, e.g. AVIRIS)

Courtesy of Guam Coastal AtlasREVIEW: Trade-off between Spatial and Spectral ResolutionIn order to maintain a reasonable level of energy (or signal) reaching the camera (or imaging system), the relation between the pixel size (or pixel area) and spectral bandpass (channel width) must be considered:Pixel areaSpectral bandpassEnergyREVIEW: Airborne Remote SensingCollected by cameras mounted on planesMultiple passes over a short time periodOrthorectified once images are joinedPerspective view

Orthophoto Vs. Aerial photo/remotely sensed photoBonus question: due on Wed (March 6th)What is the difference between an aerial photo and an orthophoto?

03_23_FigureVery similar23REVIEW: LiDARLight Detection and Ranging laser elevations!

Downloading DatasetsDownloading DatasetsIf somebody asked you to make a map, where would you go to find the data?

Data often available online in digital formats

GIS files may exist with the attributes you need

Do some research to find out who has your dataDownloading DatasetsStarting your web searchTopic: environment, government, business, healthGeography: neighborhood, city, state, country, worldTime frame: one vs. many years; historical data?Sources:Government agencies (local, state, federal, intl.)Non-profit organizationsPrivate corporations?

Data SourcesMunicipal GIS departmentsParcel boundaries, zoning, wards + precinctsStreet centerlines, sidewalks, building footprintsInfrastructureWater supply, sewers, storm drainsElectric, gas, broadbandMunicipal facilities police, fire, DPW, schoolsCities & towns may charge a fee for a copy of data

Data SourcesState AgenciesMassGIS is a repository for many agenciesPolitical boundaries, roads, other infrastructureHydrography, Wetlands, Open SpaceOrthophotos, DEM, Shaded Relief

GIS data for some other states is much harder to find!

Data SourcesFederal AgenciesThe National Atlas, U.S. Census TIGERUSGS: Natl. Hydro. Dataset, DEMs, OrthophotosNASA: Earth Observing System ClearinghouseNOAA: Coastal Data, Weather, FisheriesNWS: National Wetlands InventoryNRCS: Soil Data Mart (NATSGO, STATSGO, SSURGO)FEMA: Floodplains & Disaster Locations

Data SourcesInternational:United Nations Food & Agriculture OrganizationThe Nature ConservancyOpenStreetMapGeofabrik extracts: areas: the DataCheck the metadataItem Description in ArcCatalogDetails about source, attributes, date, methods

Make a map, play with symbology and labelsGet a sense of the range of values for attributesFigure out which attributes will be useful to youData Structures/Models in GISVector??????Raster??????TopologyHow does the machine know about relative positions of various features like point, line polygon?

Through TopologyVector Data and TopologyTopologyThe arrangement for how point, line, and polygon features share geometryOr knowledge about relative spatial positioning

Two types of vector models exist in a GISGeo-relational Vector ModelArc Coverage (has topology) >>> format: binayShape files (no topology) >>>> format: *.shp, *.shx, *dbf, etc.Object-based Vector ModelIncludes classes and geodatabases >>> format: *.mdbTopologyConcepts AdjacencyEnclosureConnectivityTerms to be definedNodeArcPolygon

OK.No matter what if we have topology or not we can ask questions from a GIS database (spatial or non-spatial) to do some quick analysis. QueryA query is a question posed to a database (attribute data)

Examples: Mouse click on a map symbol (e.g. road) may meanWhat is the name of road pointed to by mouse cursor ?Typing a keyword in a search engine (e.g. google, yahoo) meansWhich documents on web contain given keywords?SELECT FROM Senator S WHERE S.gender = F meansWhich senators are female?Non-spatial DataOr Attributes

RecordField (Attribute)--- It could be either numeric or text)The Shape Field/Object ID tells about the type of vector feature (point/polygon/line) It is where the coordinates are also stored (you do not see them here)Organizing Attribute DataFlat Files Hierarchical Relational (databases)Object-oriented (database)

Organizing Attribute DataFlat Files Spreadsheets (e.g. excel spreadsheet)

HierarchicalOrganizing Attribute Data

Relational (What is commonly used in GIS)Various tables (databases) are linked through unique identifiers

Organizing Attribute Data

Query: Making SelectionsUsually interested in some subset of the data

Selections can be made in two primary ways:Select by Attribute specify matching criteriaSelect by Location based on spatial proximityQuery: Select by AttributesOr Structured Query Language (SQL)

Enter criteria for one or more fieldsNumeric values =,,Nominal values = text

Change criteria or narrow results based on additional criteria

Select by Attribute TipsBe careful with case sensitivity and spacesUse parentheses to carefully construct a queryUse Boolean Operators (AND, OR, NOT, LIKE)AND means both criteria, OR means eitherNOT allows you to exclude some criteriaLIKE lets you be more flexible, use wildcard characters (_ for one character, % for many)Verify your expression to make sure it worksSpatial Query: Select by LocationUse vectors to select data from other vectorsSame selection methods as Select by AttributeChoose Target & SourceMany options for the spatial selection method

Spatial Query: Select by LocationSpatial selection methodsTarget intersects sourcewithin a distance ofcontain, completely containwithin, completely withinClementini (not boundary)are identical to; touch the boundary of; share a line; crossed by the outline of

Select by Location TipsMake sure Target and Source are correct

Combine with Select by AttributesCheck Use Selected Features under Source

Option to apply a search distance when not using the within a distance of methodJoining and Relating TablesMany datasets are available in tabular formatExcel (.xls, .xlsx), comma-spaced values (.csv), text

Tables can be imported to ArcMap and linked points, lines, or polygons using a common ID

Joining TablesTables downloaded as text or CSV may need to be opened and saved as Excel files first

First row of table should contain short headers with no special characters (or spaces, ideally)

Table must have an ID that matches geography

One-to-one relationshipsA one-to-one relationship means that each record in one table has only one matching record in another table

Many-to-one relationshipsMany-to-one means multiple records in the table match to one record in another table

Joining TablesUsually you will choose to Keep All RecordsAlways Validate JoinMaybe a mismatched IDSometimes missing records in the join tableJoined fields will display in the target layer table

Relating TablesRelates are used when tables have a one-to-many or many-to-many relationshipAttributes are not appended to the table, but select