Final Flashcards
What are the two spatial data models? [Spatial Data Models]
- Vector (points, lines, polygons; locations explicitly defined by set of coordinates)
- Raster (cells; location implicit by the size/area of the cell and the cell layout)
What is the basic building block for vector; and for raster? [Spatial Data Models]
Vector: point Raster: Cell
How is the resolution defined in a vector system; in a raster system? [Spatial Data Models]
Resolution is defined by map scale or minimum mapping unit for VECTOR.
Resolution is defined by cell size (area) in RASTER.
What does it mean to define a projection? [Spatial Referencing System]
To define a projection is to record (or register) the coordinate system information of a dataset – including any associated projection parameter, datum, and ellipsoid with the software.
What does it mean to reproject? [Spatial Referencing System]
To reproject is to permanently change the native coordinate system of a dataset, including its datum or ellipsoid, to another coordinate system.
What does on-the-fly projection mean? [Spatial Referencing System]
On-the-fly projection temporarily displays a dataset with its native coordinates stored in one coordinate system as if it were in another coordinate system.
What does georeferencing do? [Data Acquisition]
Georeferencing associates locations (coordinates) stored in unreferenced (such as an image) space with their corresponding coordinates in geographic or real-world space.
How does georeferencing work? [Data Acquisition]
By using control points which are locations that can be accurately identified on an unreferenced map and in real-world coordinates. Then uses a coordinate transformation which is a mathematical equation that estimates new coordinates based on control points and corresponding real-world coordinates.
What is root mean square error (RMSE) and how does it play into georeferencing? [Data Acquisition]
RMSE is a measure of “goodness of fit” of a transformation. This is the average deviation in distance of estimated control point coordinates from its true location. A low value generally suggests a better fit. Does not equal accurate registration always though.
What is address matching or geocoding? [Data Acquisition]
Geocoding is the process of assigning coordinates to an address based on a reference dataset, usually a streets dataset by assigning x/y by linearly interpolating between start and end ranges.
What are some problems with geocoding? [Data Acquisition]
Problems with geocoding include: errors in the street address, address does not correspond to a street address, or there is an outdated or incomplete street base map.
What is metadata? [Data Acquisition]
Metadata is data about data; describes what a user needs to know about a data set. Informs on any assumptions, limitations, approximations and simplifications.
What are some important elements to get from metadata? [Data Acquisition]
Scale (minimum mapping unit), method of capture, fields & associated values, and projection.
What is remote sensing? [Data Acquisition]
Remote sensing is the collection and interpretation of information about objects on the earth’s surface by measuring from remote platforms with specialized sensors the amount of electromagnetic energy the objects reflect.
What energy does remote sensing pick up? [Data Acquisition]
The energy that is reflected that sensors capture is both within and outside the visual spectrum and often includes near-infrared, mid-infrared, and thermal energy.
How are satellite imagery characterized? [Data Acquisition]
Multispectral satellite imagery is characterized by their resolution in the spectral (number and range of wavelengths captured), spatial (size of pixel), and temporal (time of return to same location).
How can objects be identified using remote sensing? [Data Acquisition]
Objects can be identified because different objects reflect energy differently at different wavelengths, objects can be identified using this unique spectral signature (thumbprint).
How is the health of vegetation measured using remote sensing? [Data Acquisition]
The combination of red (R) and near-infrared (NIR) energy is often used to measure the health of vegetation as chlorophyll reflects near-infrared wavelengths and absorbs red energy. (NIR-R)/(NIR+R). Healthy vegetation appears as RED. (If absorbing a lot of red that means its reflecting a lot of green)
What is image classification? [Data Acquisition]
Image classification is the digital process of identifying objects by grouping pixels with similar spectral signatures through two main methods: supervised and unsupervised.
What is supervised image classification? [Data Acquisition]
Supervised image classification requires an analyst to identify representative training sites for each class a priori and an algorithm then identifies all pixels with spectral signatures that are similar to training sites to generate a classified map.
What is unsupervised image classification? [Data Acquisition]
Unsupervised image classification requires an analyst to choose a total number of classes desired a priori and an algorithm identifies statistical clusters in data (mean, standard deviation) to generate a classified map; classes identified a posteriori
What is photointerpretation? [Data Acquisition]
Photointerpretation is the visual process of identifying objects (trees, buildings, roads) in imagery. Spatial data is created by manually digitizing recognizable objects of interest based on visual cues.
What is global positioning systems (GPS)? [Data Acquisition]
GPS is a system of radio-emitting and receiving satellites used to determine absolute positions on the earth made up of a constellation of satellites in orbit.
How does a GPS work? [Data Acquisition]
Each satellite transmits signals to receivers on earth who broadcast their location in orbit. Precise time is based on atomic clocks.
What does the receiver on earth do for GPS? [Data Acquisition]
The receiver on earth picks up each satellite signal it sees and statistically computes the range to the satellite – estimates the position based on trilateration.
How can accuracy be affected for GPS? [Data Acquisition]
Type of receiver: recreational grade vs survey grade
Alignment and geometry of satellites in sky
Signals bouncing off objects (multipath)
Signals blocked by objects and terrain
What is generalization? [Spatial Analysis, or Geoprocessing]
Generalization simplifies data while maintaining its geographic characteristics and integrity. Subsetting data through tabular or spatial queries and then export to a new data sheet you can either reclassify or dissolve boundaries.
A generalization tool is reclassification, what does it do and how? [Spatial Analysis, or Geoprocessing]
Reclassification works by grouping (aggregating) features or cells together based on criteria. Often used to assign new values, like ranks for a suitability model.
A generalization tool is dissolve, what does it do? [Spatial Analysis, or Geoprocessing]
Dissolve boundaries eliminates the boundaries between adjacent features with the same attribute. `
What does a vector overlay do? [Spatial Analysis, or Geoprocessing]
Combines spatial features AND attributes from two or more map layers – geometry of the features are changed and attributes merged together to form a new dataset.
What 3 types of overlays are there? [Spatial Analysis, or Geoprocessing]
Point in polygon (attach polygon attributes to points)
Line in polygon (attach polygon attributes to lines)
Polygon on polygon (attach polygon attributes to polygons)
Output layer usually takes geometry type of the lowest dimension: point in a polygon -> the point will be the output geometry type; line in polygon -> line will be the output geometry type
What is an intersect and how does it work? [Spatial Analysis, or Geoprocessing]
An intersect combines two or more polygon datasets and retains ONLY features and attributes from both the datasets that OVERLAP. Attributes and geometry are changed.
What is a union and how does it work? [Spatial Analysis, or Geoprocessing]
A union combines two or more polygon datasets and retains ALL features and attributes from both datasets that OVERLAP. Attributes and geometry are changed.
What is an identity and how does it work? [Spatial Analysis, or Geoprocessing]
An identity combines two or more polygon datasets, retaining features from ONE dataset merged with portions of the other datasets that overlap it. Attributes and geometry are changed.
