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Geographic Information Systems
Intro Techniques Spatial Geostatistics Geocoding GIS software
Techniques
Data creation
Modern GIS technologies use digital information, for which various digitized
data creation methods are used. The most common method of data creation is
digitization, where a hardcopy map or survey plan is transferred into a digital
medium through the use of a computer-aided drafting (CAD) program, and
georeferencing capabilities.
Relating information from different sources
If you could relate information about the rainfall of your state to aerial
photographs of your county, you might be able to tell which wetlands dry up at
certain times of the year. A GIS, which can use information from many different
sources in many different forms, can help with such analyses. The primary
requirement for the source data consists of knowing the locations for the
variables. Location may be annotated by x, y, and z coordinates of longitude,
latitude, and elevation, or by other geocode systems like ZIP Codes or by
highway mile markers. Any variable that can be located spatially can be fed into
a GIS. Several computer databases that can be directly entered into a GIS are
being produced by government agencies and non-government organizations[citation
needed]. Different kinds of data in map form can be entered into a GIS.
A GIS can also convert existing digital information, which may not yet be in map
form, into forms it can recognize and use. For example, digital satellite images
generated through remote sensing can be analyzed to produce a map-like layer of
digital information about vegetative covers. Another fairly developed resource
for naming GIS objects is the Getty Thesaurus of Geographic Names (GTGN), which
is a structured vocabulary containing around 1,000,000 names and other
information about places[1].
Likewise, census or hydrologic tabular data can be converted to map-like form,
serving as layers of thematic information in a GIS.
Data representation
GIS data represents real world objects (roads, land use, elevation) with digital
data. Real world objects can be divided into two abstractions: discrete objects
(a house) and continuous fields (rain fall amount or elevation). There are two
broad methods used to store data in a GIS for both abstractions: Raster and
Vector.
Raster
Digital Elevation Model (DEM) + Map (image) + Vector dataRaster data type
consists of rows and columns of cells where in each cell is stored a single
value. Most often, raster data are images (raster images), but besides just
color, the value recorded for each cell may be a discrete value, such as land
use, a continuous value, such as rainfall, or a null value if no data is
available. While a raster cell stores a single value, it can be extended by
using raster bands to represent RGB (red, green, blue) colors, colormaps (a
mapping between a thematic code and RGB value), or an extended attribute table
with one row for each unique cell value. The resolution of the raster dataset is
its cell width in ground units. For example, in a LIDAR raster image, each cell
may be a pixel that represents an area of 3 meters by 3 meters. Usually cells
represent square areas of the ground, but other shapes can also be used.
Vector
Vector data type uses geometries such as points, lines (series of point
coordinates), or polygons, also called areas (shapes bounded by lines), to
represent objects. Examples include property boundaries for a housing
subdivision represented as polygons and well locations represented as points.
Vector features can be made to respect spatial integrity through the application
of topology rules such as 'polygons must not overlap'. Vector data can also be
used to represent continuously varying phenomena. Contour lines and triangulated
irregular networks (TIN) are used to represent elevation or other continuously
changing values. TINs record values at point locations, which are connected by
lines to form an irregular mesh of triangles. The face of the triangles
represent the terrain surface.
Advantages and disadvantages
There are advantages and disadvantages to using a raster or vector data model to
represent reality. Raster datasets record a value for all points in the area
covered which may require more storage space than representing data in a vector
format that can store data only where needed. Raster data also allows easy
implementation of overlay operations, which are more difficult with vector data.
Vector data can be displayed as vector graphics used on traditional maps,
whereas raster data will appear as an image that may have a blocky appearance
for object boundaries. Vector data can be a lot easier to register, scale, and
reproject. This can make it much simpler to combine vector layers from different
sources.
Non-spatial data
Additional non-spatial data can also be stored besides the spatial data
represented by the coordinates of a vector geometry or the position of a raster
cell. In vector data, the additional data are attributes of the object. For
example, a forest inventory polygon may also have an identifier value and
information about tree species. In raster data the cell value can store
attribute information, but it can also be used as an identifier that can relate
to records in another table.
Data capture
Data capture—entering information into the system—consumes much of the time of
GIS practitioners. There are a variety of methods used to enter data into a GIS
where it is stored in a digital format.
Existing data printed on paper or PET film maps can be digitized or scanned to
produce digital data. A digitizer produces vector data as an operator traces
points, lines, and polygon boundaries from a map. Scanning a map results in
raster data that could be further processed to produce vector data.
Survey data can be directly entered into a GIS from digital data collection
systems on survey instruments. Positions from a Global Positioning System (GPS),
another survey tool, can also be directly entered into a GIS.
Remotely sensed data also plays an important role in data collection and consist
of sensors attached to a platform. Sensors include cameras, digital scanners and
LIDAR, while platforms usually consist of aircraft and satellites.
The majority of digital data currently comes from photo interpretation of aerial
photographs. Soft copy workstations are used to digitize features directly from
stereo pairs of digital photographs. These systems allow data to be captured in
2 and 3 dimensions, with elevations measured directly from a stereo pair using
principles of photogrammetry. Currently, analog aerial photos are scanned before
being entered into a soft copy system, but as high quality digital cameras
become cheaper this step will be skipped.
Satellite remote sensing provides another important source of spatial data. Here
satellites use different sensor packages to passively measure the reflectance
from parts of the electromagnetic spectrum or radio waves that were sent out
from an active sensor such as radar. Remote sensing collects raster data that
can be further processed to identify objects and classes of interest, such as
land cover.
When data is captured, the user should consider if the data should be captured
with either a relative accuracy or absolute accuracy, since this could not only
influence how information will be interpreted but also the cost of data capture.
In addition to collecting and entering spatial data, attribute data is also
entered into a GIS. For vector data, this includes additional information about
the objects represented in the system.
After entering data into a GIS, the data usually requires editing, to remove
errors, or further processing. For vector data it must be made "topologically
correct" before it can be used for some advanced analysis. For example, in a
road network, lines must connect with nodes at an intersection. Errors such as
undershoots and overshoots must also be removed. For scanned maps, blemishes on
the source map may need to be removed from the resulting raster. For example, a
fleck of dirt might connect two lines that should not be connected.
Raster-to-vector translation
Data restructuring can be performed by a GIS to convert data into different
formats. For example, a GIS may be used to convert a satellite image map to a
vector structure by generating lines around all cells with the same
classification, while determining the cell spatial relationships, such as
adjacency or inclusion.
More advanced data processing can occur with image processing, a technique
developed in the late 1960s by NASA and the private sector to provide contrast
enhancement, false colour rendering and a variety of other techniques including
use of two dimensional Fourier transforms.
Since digital data are collected and stored in various ways, the two data
sources may not be entirely compatible. So a GIS must be able to convert
geographic data from one structure to another.
Projections, coordinate systems and registration
A property ownership map and a soils map might show data at different scales.
Map information in a GIS must be manipulated so that it registers, or fits, with
information gathered from other maps. Before the digital data can be analyzed,
they may have to undergo other manipulations—projection and coordinate
conversions, for example—that integrate them into a GIS.
The earth can be represented by various models, each of which may provide a
different set of coordinates (e.g., latitude, longitude, elevation) for any
given point on the earth's surface. The simplest model is to assume the earth is
a perfect sphere. As more measurements of the earth have accumulated, the models
of the earth have become more sophisticated and more accurate. In fact, there
are models that apply to different areas of the earth to provide increased
accuracy (e.g., North American Datum, 1927 - NAD27 - works well in North
America, but not in Europe). See Datum for more information.
Projection is a fundamental component of map making. A projection is a
mathematical means of transferring information from a model of the Earth, which
represents a three-dimensional curved surface, to a two-dimensional medium—paper
or a computer screen. Different projections are used for different types of maps
because each projection particularly suits certain uses. For example, a
projection that accurately represents the shapes of the continents will distort
their relative sizes. See Map projection for more information.
Since much of the information in a GIS comes from existing maps, a GIS uses the
processing power of the computer to transform digital information, gathered from
sources with different projections and/or different coordinate systems, to a
common projection and coordinate system.