Software Development for Geographic Ans Spacial Information

Credits
3
Types
  • MEI: Elective
  • MIRI: Elective
  • MDS: Elective
Requirements
This subject has not requirements , but it has got previous capacities
Department
MAT
Web
https://mat-web.upc.edu/fib/dsige/
Geographic Information Systems (GIS) allow for the storage, analysis, and visualization of spatial information about the real world. Due to the enormous amount of data that geographic software must be able to manage, it is essential to have algorithmic techniques and efficient data structures specially designed for this type of information. In this course, a selection of fundamental topics for the development of algorithms for geographic information systems will be presented. The selected contents will be introduced in the context of real applications, followed by the presentation of advanced computer techniques that provide efficient solutions to these geographic problems.

Teachers

Person in charge

Others

Weekly hours

Theory
4
Problems
0
Laboratory
0
Guided learning
0
Autonomous learning
7.1111

Competences

Technical Competences of each Specialization

Especifics

  • CTE7 - Capability to understand and to apply advanced knowledge of high performance computing and numerical or computational methods to engineering problems.
  • CTE11 - Capability to conceptualize, design, develop and evaluate human-computer interaction of products, systems, applications and informatic services.
  • CTE12 - Capability to create and exploit virtual environments, and to the create, manageme and distribute of multimedia content.

    • Generic Technical Competences

    Generic

  • CG4 - Capacity for mathematical modeling, calculation and simulation in technology and engineering companies centers, particularly in research, development and innovation tasks in all areas related to Informatics Engineering.
  • CG6 - Capacity for general management, technical management and research projects management, development and innovation in companies and technology centers in the area of Computer Science.
  • CG8 - Capability to apply the acquired knowledge and to solve problems in new or unfamiliar environments inside broad and multidisciplinary contexts, being able to integrate this knowledge.

    • Transversal Competences

    Information literacy

  • CTR4 - Capability to manage the acquisition, structuring, analysis and visualization of data and information in the area of informatics engineering, and critically assess the results of this effort.

    • Reasoning

  • CTR6 - Capacity for critical, logical and mathematical reasoning. Capability to solve problems in their area of study. Capacity for abstraction: the capability to create and use models that reflect real situations. Capability to design and implement simple experiments, and analyze and interpret their results. Capacity for analysis, synthesis and evaluation.

    • Basic

  • CB6 - Ability to apply the acquired knowledge and capacity for solving problems in new or unknown environments within broader (or multidisciplinary) contexts related to their area of study.
  • CB9 - Possession of the learning skills that enable the students to continue studying in a way that will be mainly self-directed or autonomous.

    • Objectives

    1. Learn what geographic information systems (GIS) are.
      Related competences: CTR4, CTE11, CG6, CG8, CB9,
    2. Analyze concrete problems that a GIS must be able to solve.
      Related competences: CTE11, CTR6, CTE12, CTE7, CG4, CG8,
    3. Study some of the algorithms behind GIS.
      Related competences: CTR6, CTE11, CG4, CB6,
    4. Learn different ways to represent and process geographic and spatial data.
      Related competences: CB9, CTE7, CG4,

    Contents

    1. Introduction to geographic information systems, spatial information, and geometric algorithms.
      Main principles of spatial information and geographic information systems. Examples of GIS applications. Introduction to geometric algorithms. Relation between the implementation of a GIS and geometric algorithms.
    2. Map representation, combination and overlay of geographic subdivisions.
      Introduction to map overlay. Unification of coordinate systems. Data structures for representing maps and geographic subdivisions. Algorithms for calculating overlaps of subdivisions. Algorithms and data structures for locating points in geographic subdivisions.
    3. Digital terrain models, vector and raster terrains
      Models for representing terrains. Raster and TIN (triangulated irregular network) models. Basic algorithms for rasters and TINs. Traversal and location in TINs. Conversion between different terrain models.
    4. Algorithms for terrain analysis: visibility and hydrology problems
      Applications of terrain analysis in visibility and hydrography. Calculation of viewsheds and watersheds in rasters and TINs. Removal of local minima and other artifacts.
    5. Voronoi diagrams applied to facility location and pattern analysis problems
      Definition of Voronoi diagram. Applications to GIS. Algorithms for constructing the Voronoi diagram.
    6. Basic algorithms for digital cartography: map generalization and labeling
      Introduction to maps and cartography. Principles of map design. Cartographic symbolization and generalization. Line simplification, Douglas-Peucker algorithm. Map labeling.
    7. Extra topics to be chosen by the students.
      The specific topics will be defined by the students and the instructors during the first half of the course.

    Activities

    Activity Evaluation act


    Introduction

    Introducción a los sistemas de información geográfica, la información espacial y los algoritmos geométricos
    Objectives: 1
    Contents:
    Theory
    4h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Map representation, combination and overlay of geographic subdivisions


    Objectives: 2 3 4
    Contents:
    Theory
    4h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Digital terrain models


    Objectives: 2 3 4
    Contents:
    Theory
    5h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Voronoi diagrams


    Objectives: 2 3 4
    Contents:
    Theory
    4h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Algorithms for terrain analysis


    Objectives: 2 3
    Contents:
    Theory
    4h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Basic algorithms for digital cartography


    Objectives: 2 3
    Contents:
    Theory
    4h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    7h

    Extra topics to be defined during the course


    Objectives: 2 3
    Contents:
    Theory
    2h
    Problems
    0h
    Laboratory
    0h
    Guided learning
    0h
    Autonomous learning
    6h

    Teaching methodology

    The course will consist of presentations of the main theoretical topics, followed by a discussion of the more practical aspects associated with them, and the presentation of practical tools to address them.

    Evaluation methodology

    Evaluation will be based on a final project that will consist of theory and bibliography research tasks about a concrete GIS problem, and in class participation.

    Bibliography

    Basic

    Complementary

    Previous capacities

    - Basic knowledge of data structures
    - Basic knowledge of algorithmic technique