generalization and aggregation

GS-20 - Aggregation of Spatial Entities and Legislative Redistricting

The partitioning of space is an essential consideration for the efficient allocation of resources. In the United States and many other countries, this parcelization of sub-regions for political and legislative purposes results in what is referred to as districts. A district is an aggregation of smaller, spatially bound units, along with their statistical properties, into larger spatially-bound units. When a district has the primary purpose of representation, individuals who reside within that district make up a constituency. Redistricting is often required as populations of constituents shift over time or resources that service areas change. Administrative challenges with creating districts have been greatly aided by increasing utilization of GIS. However, with these advances in geospatial methods, political disputes with the way in which districts increasingly snare the process in legal battles often centered on the topic of gerrymandering. This chapter focuses on the redistricting process within the United States and how the aggregation of representative spatial entities presents a mix of political, technical and legal challenges.

AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
GS-20 - Aggregation of Spatial Entities and Legislative Redistricting

The partitioning of space is an essential consideration for the efficient allocation of resources. In the United States and many other countries, this parcelization of sub-regions for political and legislative purposes results in what is referred to as districts. A district is an aggregation of smaller, spatially bound units, along with their statistical properties, into larger spatially-bound units. When a district has the primary purpose of representation, individuals who reside within that district make up a constituency. Redistricting is often required as populations of constituents shift over time or resources that service areas change. Administrative challenges with creating districts have been greatly aided by increasing utilization of GIS. However, with these advances in geospatial methods, political disputes with the way in which districts increasingly snare the process in legal battles often centered on the topic of gerrymandering. This chapter focuses on the redistricting process within the United States and how the aggregation of representative spatial entities presents a mix of political, technical and legal challenges.

AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets
AM-62 - Approaches to point, line, and area generalization
  • Describe the basic forms of generalization used in applications in addition to cartography (e.g., selection, simplification)
  • Explain why areal generalization is more difficult than line simplification
  • Explain the logic of the Douglas-Poiker line simplification algorithm
  • Explain the pitfalls of using data generalized for small scale display in a large scale application
  • Design an experiment that allows one to evaluate the effect of traditional approaches of cartographic generalization on the quality of digital data sets created from analog originals
  • Evaluate various line simplification algorithms by their usefulness in different applications
  • Discuss the possible effects on topological integrity of generalizing data sets

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