ESRI GIS Software

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ESRI GIS Software
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Contents

• Data Types
• ESRI Data Model
• Shapefiles
• Raster Data
• Digital Orthophoto Quadrangle
• Digital Elevation Model
• Digital Raster Graphic
• ESRI GeoDatabase
• 2D Representations
• Registration
• Layering
• Accuracy
• Skewing Size Registration
• Spatial Analysis
• United States
• Inyo County
• City of Bishop

• 3D Representations
• Registration
• Overlaying
• Data Extraction
• Exporting to dbf
• Joins
• Attribute Joins
• Spatial Joins
• Join Types
• Examples
• 7.5-Minute Maps
• ESRI Limitations

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ESRI Data Model
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Shapefile Data

• A shapefile stores nontopological geometry and
  attribute information for the spatial features in
  a data set. The geometry for a feature is stored
  as a shape comprising a set of vector
  coordinates.
• Because shapefiles do not have the processing
  overhead of a topological data structure, they
  have advantages over other data sources such as
  faster drawing speed and edit ability. Shapefiles
  handle single features that overlap or that are
  noncontiguous. They also typically require less
  disk space and are easier to read and write.
• Shapefiles can support point, line, and area
  features. Area features are represented as closed
  loop, double-digitized polygons. Attributes are
  held in a dBASE format file. Each attribute
  record has a one-to-one relationship with the
  associated shape record.

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Raster Data

• Digital Orthophoto Quadrangle (DOQ)
• A Digital Orthophoto Quadrangle (DOQ) is a
  digital, uniform-scale image created from aerial
  photos. It is a photographic map in which ground
  features are displayed in their true ground
  position because relief displacements caused by
  the camera and terrain of an aerial photograph
  have been removed. It combines the image
  characteristics of a photograph with the
  geometric qualities of a map thus, it is
  possible to get direct measurements of distances,
  areas, angles, and positions from a DOQ.

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Example (DOQ)

• 7.5 Minute Quad-Triangle
• Format MrSID
• 1-Meter

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Raster Data

• Digital Elevation Model (DEM)
• A Digital Elevation Model (DEM) is a digital
  cartographic/geographic dataset of elevations in
  xyz coordinates. The terrain elevations for
  ground positions are sampled at regularly spaced
  horizontal intervals. DEMs are derived from
  hypsographic data (contour lines) and/or
  photogrammetric methods using USGS 7.5-minute,
  15-minute, 2-arc-second (30- by 60-minute), and
  1-degree (1250,000-scale) topographic quadrangle
  maps.

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Example (DEM)

• 7.5-Minute
• Contour Lines
• ESRI 3D Analyst

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Raster Data

• Digital Raster Graphic (DRG)
• A Digital Raster Graphic (DRG) is a digital image
  (scanned version) of a USGS topographic map. DRGs
  are produced from USGS 124,000-,
  124,000/125,000-, 163,360- (Alaska),
  1100,000-, and 1250,000-scale topographic map
  series. The image inside the map neatline is
  georeferenced to the surface of the Earth and fit
  to the Universal Transverse Mercator (UTM)
  projection. The horizontal positional accuracy
  and datum of the DRG matches the accuracy and
  datum of the source map.

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Example (DRG)

• 7.5-Minute
• Registration
• Data Accuracy

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ESRI GeoDatabase

• Data Modification
• Data Extraction
• Tables
• Relationships
• Feature Classes

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2D Representations
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Quarter Quadrants
NW
NE
SW
SE
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Rubberized Quadrants

• Rubberizing Images
• Image Registration
• Image Locations (x,y)
• Spatial Adjustment

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Layering (Indian Reservations Waters)
Indian Reservation
Lake
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Layering (Roads)
Indian Reservation
Lake
Roads
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Data Accuracy

• Images are available upto a accuracy of about
  1-meter.
• Common data characteristic are very important.
• Time of capture data.
• Data accuracy size
• Lens Skewing

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Accuracy (Zoom 2x)
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Accuracy (Zoom 4x)
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Accuracy (Zoom 6x)
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Accuracy (Zoom 8x)
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Multi-Layer Accuracy
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Modified Image Registration
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Spatial Analysis (Projection USA)
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Spatial Analysis (Projection Inyo County)
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Spatial Analysis (Projection City of Bishop)
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3D Representations
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DEM to TIN

• Most DEM data contains the min and maximum
  elevation.

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Layering DOQ to TIN
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Adding Land Waters
Indian Reservation
Lake
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Complete All Layers
Indian Reservation
Roads
Lake
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Data Extraction

• Shapefiles contain attributes for given data
  points, vectors, and polygons.
• Data can be extracted directly into dbf format.
• Spatial location is not directly exportable.

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(Spatial Attribute) Joins
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Joins

• Like joining two tables by matching attribute
  values in a field, a spatial join appends the
  attributes of one layer to another.
• You can then use the additional information to
  query your data in new ways. While you can also
  select features in one layer based on their
  location relative to another layer, a spatial
  join provides a more permanent association
  between the two layers because it creates a new
  layer containing both sets of attributes.
• Several tables or layers can be joined to a
  single table or layer and relationship class
  joins can be mixed with attribute joins.
• When a join table is removed, all data from
  tables that were joined after it are also
  removed, but data from previously joined tables
  remain. Symbology or labeling that is based on an
  appended column is returned to a default state
  when the join is removed.

From http//support.esri.com/articles
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Spatial Joins

• Join by location or spatial join uses spatial
  associations between the layers involved to
  append fields from one layer to another. Spatial
  joins are different from attribute and
  relationship class joins in that they are not
  dynamic and require the results to be saved to a
  new output layer.
• Associations One of three types of associations
  can be used to perform a spatial join. These
  associations are described as follows
• Match each feature to the closest feature or
  features - In this association, you can either
  append the attributes of the nearest feature or
  append an aggregate (i.e. min, max etc.) of the
  numeric attributes of the closest features.
• Match each feature to the feature that it is part
  of - In this case, the attributes of the feature
  for which the current feature makes up a portion
  are appended.
• Match each feature to the feature or features
  that it intersects - Like with the closest
  feature(s) association above, you can either
  append the attributes of a single intersecting
  feature or an aggregate of the numeric attributes
  of the intersecting features.

From http//support.esri.com/articles
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Spatial Joins (Development Programming)

• Complex Queries With VBA, however, it is
  possible to perform a join based on any
  association and with any combination of point,
  line or polygon feature layers.
• Joins as well as other types of complex queries
  must be implemented using VBA or some other ESRI
  compliant language.
• ESRI toolbox works primarily with Borland and
  Microsoft development products. Other languages
  can be used for development but are not well
  integrated due to the heavy usage of COM.

From http//support.esri.com/articles
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Spatial Joins (Noted Points)

• Noted Points It is recommended that both layers
  have the same coordinate system. If the layers
  have different coordinate systems, the following
  rules apply
• The spatial join will be calculated in the target
  layer's (the select layer in the table of
  contents) coordinate system.
• If the type of join performed involves adding a
  field to show the distance between joined
  features, the distance will be in a unit of
  measure associated with the target layer's
  coordinate system.
• If one of the layers has an unknown coordinate
  system and the other a defined coordinate system,
  an error message will appear. If both layers have
  an unknown coordinate system, the join will
  proceed and the resulting layer will have an
  unknown coordinate system.
• The coordinate system used to display data in
  ArcMap has no effect on how the data is joined.
  ArcMap allows data to be stored in one coordinate
  system and displayed in another. The analysis is
  always performed using the stored coordinate
  system.

From http//support.esri.com/articles
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Spatial Joins (ESRI)
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Spatial Join (Data Tables)
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Spatial Join (Data Tables)
Joined Data
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Single Multiple Spatial Joins
The Roads layer is not spatially joined to
County, and does not have a attribute which
can relate location between them.
The Waters layer does not contain a spatial
relationship with the Counties layer, therefore
any queries based on counties will not be
applicable.

• Multiple spatial joins are commonly needed to
  create relationships between many different
  layers.

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Multiple Spatial Joins (Cont.)

• By spatially joining the all the layers with the
  layer Counties we are able to create a spatial
  relationship between all the layers and the
  county they are located in.

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What can we do with these relationships?
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Queries Selections

• Now that we have relations between the different
  layers, in order to take advantage of them,
  queries can be used to extract and filter data to
  find relevant spatial information.

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Lakes Within One Mile of a Landmark (Visual
Results)
Landmarks that are within a mile from a body of
water.

• Layers which contain common relationship can be
  queried based upon these relationships as well as
  there own table attributes.

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Lakes Within One Mile of a Landmark (Data Results)

• Layers which contain common relationship can be
  queried based upon these relationships as well as
  there own table attributes.

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Lakes Within One Mile of a Landmark

• Layers which contain common relationship can be
  queried based upon these relationships as well as
  there own table attributes.

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Lakes Within One Mile of the Road
Roads that are within a mile from a body of water.

• The returned table contains a filtered subset of
  the original roads, which are in Bishop and
  within one at most one mile from a body of water.

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Lakes Within One Mile of the Road

• The returned table contains a filtered subset of
  the original roads, which were in Bishop with
  roads which are now only within one mile of lakes.

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Lakes Within One Mile of the Road

• The returned table contains a filtered subset of
  the original roads, which were in Bishop with
  roads which are now only within one mile of lakes.

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Why 7.5-Minute Maps?
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National Map Accuracy Standards 1941/47

• Established in 1941 by the US Bureau of the
  Budget (now OMB) for use with US Geological
  Survey maps (Maling, 1989, p. 146)
• Horizontal accuracy not more than 10 of tested,
  well defined points shall be more than the
  following distances from their true location
• 162,500 1/50th of an inch (.02)
• 124,000 1/40th of an inch (amended to
  1/50.02 in 1947)
• 112,000 1/30 of an inch (.033)
• Thus, on maps with a scale of 163,360 (11
  mile) 90
• of points should be within 105.6 feet (63360 X
  .02)/12) of their true location.

From http//www.utdallas.edu/briggs/poec5319/qua
lity.ppt
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National Map Accuracy Standards 1941/47 (Cont.)

• On USGS quads with a scale of 124,000
  (12,000ft) 90 of points should be within 40
  feet (24,000 X .02)/12 of their true location.
• On a map with a scale of 112,000 (11,000ft),
  90 of points should be within 33 feet (1,000 X
  .033), approx. 10 meters
• Gives rise to the loose, but often used,
  statement that the NMAS is 10 meters
• Inadequate for the computer age
• How many points? how select?
• How determine their true location
• What about attribute completeness?

From http//www.utdallas.edu/briggs/poec5319/qua
lity.ppt
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7.5-Minute Map
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15-Minute Map
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ESRI ArcGIS Limitations

• ArcView v.3.3
• Depreciated
• ArcInfo v.8.2
• Command Line Based
• Best feature set between all of the different
  ESRI products
• Large learning curve
• ArcGIS v.8.1
• No Spatial Adjustment Support (Rubberizing)
• Limited registeration support
• ArcGIS v.8.2
• Supported Spatial Adjustments (Rubberizing)
• Better intgeration to ArcSDE