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GEOS2161 Final Exam Weeks 1 to 11

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unsupervised classification Digital information extraction technique in which the computer assigns pixels to categories with no instructions from the operator. Unsupervised classification advantages and disadvantages advantages: - no extensive prior knowledge of the area is required - opportunity for human error is minimised - unique classes are recognised as distinct units disadvantages: - analyst has little control of the classes and their specific identities - spectral properties may change over time - requires the analyst to match spectral classes generated to the land use categories of interest Supervised classification - Digital-information extraction technique in which the operator provides training-site information that the computer uses to assign pixels to categories. - analyst uses knowledge of the area to guide the classification Classification Method: minimum distance to means classifies each pixel of unknown land cover class to the category whose mean brightness value lies closest Classification Method: maximum likelihood classifies each pixel of unknown land cover class to a land cover category on the basis of probability. Assumes training data are normally distributed11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11 about:blank 2/20 drones - 'third generation source of remote sensing' - agriculture, emergency services, atmospheric sciences Big Data refers to spatial data sets exceeding the capacity of current computing systems Thematic maps - a map of a theme or topic (rainfall stations, land use, geology) Dot maps - used to represent discrete phenomenon or themes that vary smoothly over space - example: livestock farms, population distribution in a region Choropleth maps - shows regions or ranges which have the same characteristics represented with colours example: population density Proportional symbol map A map that uses symbol in proportion to the value of the phenomenon it is representing.11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11 about:blank 3/20 Dasymetric maps Usually used to show population distribution using boundaries that divide the area into zones. Isopleth maps maps that have lines that connect points of equal intervals, often used for temperature, dew point etc (isotherms/isobars/etc.) three methods of division 1. equal interval 2. equal count or percentile 3. natural breaks Equal interval method Divides attribute values into equal size ranges. Often used to depict population on a choropleth map density, crime rates, etc. Equal Count or Percentile Method data is divided percentiles, and are generally unequal Natural Breaks Method data is divided into classes based on natural breaks observed in data histogram11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11 about:blank 4/20 small scale map has a SMALL RF (e.g. 1:1,000,000) that shows a LARGE area large scale map has - a LARGE RF (e.g. 1:100) that shows a SMALL area Map elements (9) Title Orientation Author Date Scale Legend Index Grid Source Remote sensing definition The use of remote sensors to read an object using electromagnetic energy without making physical contact remote sensing process 1) Energy Source (electromagnetic energy) 2) transmission path 3) target 4) Sensor11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11

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11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11




GEOS2161 Final Exam Weeks 1 to 11 | 117 Questions And
Answers updated graded A

unsupervised classification
Digital information extraction technique in which the computer assigns pixels to categories with no
instructions from the operator.




Unsupervised classification advantages and disadvantages

advantages:
- no extensive prior knowledge of the area is required
- opportunity for human error is minimised
- unique classes are recognised as distinct units

disadvantages:
- analyst has little control of the classes and their specific identities
- spectral properties may change over time
- requires the analyst to match spectral classes generated to the land use categories of interest
Supervised classification

- Digital-information extraction technique in which the operator provides training-site information that
the computer uses to assign pixels to categories.
- analyst uses knowledge of the area to guide the classification




Classification Method: minimum distance to means

classifies each pixel of unknown land cover class to the category whose mean brightness value lies
closest

Classification Method: maximum likelihood
classifies each pixel of unknown land cover class to a land cover category on the basis of probability.
Assumes training data are normally distributed




about:blank 1/20

,11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11




drones

- 'third generation source of remote sensing'
- agriculture, emergency services, atmospheric sciences

Big Data
refers to spatial data sets exceeding the capacity of current computing systems

Thematic maps
- a map of a theme or topic (rainfall stations, land use, geology)




Dot maps
- used to represent discrete phenomenon or themes that vary smoothly over space
- example: livestock farms, population distribution in a region




Choropleth maps
- shows regions or ranges which have the same characteristics represented with colours example:
population density




Proportional symbol map

A map that uses symbol in proportion to the value of the phenomenon it is representing.




about:blank 2/20

, 11/13/23, 1:55 AM GEOS2161 Final Exam Weeks 1 to 11




Dasymetric maps

Usually used to show population distribution using boundaries that divide the area into zones.




Isopleth maps

maps that have lines that connect points of equal intervals, often used for temperature, dew point etc
(isotherms/isobars/etc.)




three methods of division

1. equal interval
2. equal count or percentile
3. natural breaks

Equal interval method
Divides attribute values into equal size ranges. Often used to depict population on a choropleth map
density, crime rates, etc.




Equal Count or Percentile Method
data is divided percentiles, and are generally unequal

Natural Breaks Method
data is divided into classes based on natural breaks observed in data histogram




about:blank 3/20

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