geospatial analysis with raasa.ut.ee/tbilisi/01_intro_to _spatial_analysis_gis.pdf · • this is...

Geospatial Analysis with R

http://aasa.ut.ee/tbilisi

Geospatial Analysis with R

• Lecturer: Anto Aasa, PhD, senior research fellow

• Mobility Lab

• Department of Geography

• University of Tartu


http://mobilitylab.ut.ee/eng/http://aasa.ut.ee/tbilisi

http://mobilitylab.ut.ee/eng/


EestiCapital: TallinnArea: 45000 km2

Population: 1.35 MCurrency: €

The aim & learning outcomes

• This is introductory course and it provides students with a diverse set of skills of spatial analysis in R environment.

• The aim for students is to understand and explore the benefits of using a non GUI approach for spatial analytics and statistics, based on the standard approaches in R & RStudio.

• Learning outcomes: After passing the course student– knows basic concepts, skills, and tools for working with the R scripting environment;– is familiar with set of practical R libraries for everyday scientific and professional GIS (Geographic

Information System) use;– is able to solve common data-related tasks using R in specific GIS projects and tasks;– is competent of using spatial and non-spatial data in order to answer a research questions;– knows how to conduct and automate different standard GIS related tasks that support clear documentation

of methods in the R scripting environment.

• These lessons assume no prior knowledge of the skills or tools. It is a hands-on teaching course, so the majority of this course will be independent work in front of a computer and working on exercises.


• All the materials are available via course webpage: http://aasa.ut.ee/tbilisi/

• Schedule: April - May, 2020

• The course consists of– lectures

– practical sessions

– additional reading

– independent tasks

– essay


http://aasa.ut.ee/tbilisi/

Practical sessions:

1. Introduction to R

2. Data wrangling

3. Simple thematic maps

4. Physical map of Georgia & spatial queries

5. Mobile Data Collection Methods

6. Interactive plots & maps

7. …


Passing the course:

• To pass the course, students must

– solve independent task after every practical session based on previous materials. Results must be formatted as pdf-files and R-script files. Independent work make up 70% of the grade.

– write short essay (30% of the grade). Topic and more detailed description will be available here on May 11th, 2020.

• Deadline for all the submissions is May 15th 2020.


Introduction to spatial data analysis&

Geographical Information System –GIS

Spring 2020

Anto AasaMobility Lab

Department of Geography


Contemporary society:

• Digital revolution

• Information society

• Digital society, Digital Citizen

• Digital divide

• Innovation

• Mobility growth– Physical

– Virtual


Mobile society

• Compaction of time-space

– Virtual availability

• Widening of time-space

– Physical possibilities


What is geography?

• Physical geography • Human geography


Human geography deals with the study of people and their communities, cultures, economies, and interactions with the environment by studying their relations with and across space and place.Physical geography deals with the study of processes and patterns in the natural environment like the atmosphere, hydrosphere, biosphere, and geosphere.

Geography is everywhere!!!

Spatial relations!!!

Geographic information science

data structures and computational techniques to capture, represent, process, and analyze geographic information.

geographic information systems (GIS) =>software tools.



Time distance from London (1914)

Time distance from London (2016)



Physical distance isnot always euclidean…

Direct regular connections from Baltic capitals(2014)


61 35 35

Flights from Wuhan


1995putty http://aasa.ut.ee/tbilisi

www.georgiatoday.ge

http://aasa.ut.ee/tbilisi2020

http://www.georgiatoday.ge/

Rapid changes

http://aasa.ut.ee/augsburg

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No of Cars in Estonia, (x 1000)

Innovation speed


http://www.connectorsupplier.com/3g-versus-lte-versus-true-4g-speeds-huff-060413/http://aasa.ut.ee/tbilisi

http://www.connectorsupplier.com/3g-versus-lte-versus-true-4g-speeds-huff-060413/

Data: http://www.internetworldstats.com/stats.htm

578.5

1016.8

1405.1

2300.0

384.6500.7

582.4727.0

139235.8 322.4

453.0

51.1139.9

318.6522.0

248.2 273.1310.3

327.0

41.9 77 113.6 175.020.2 23.9 26.9 29.00

500

1000

1500

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2008 2011 2014 2020

Internet users, %

Asia

Europe

Latin-America

Africa

North-America

Middle East

Oceania & Australia


http://www.internetworldstats.com/stats.htm

Data: http://www.internetworldstats.com/stats.htm

15.3

26.2

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Internet users, %

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Europe

North-America

Africa

Latin-America

Middle- East

Oceania & Australia


http://www.internetworldstats.com/stats.htm

Population living below national powerty line:

http://aasa.ut.ee/tbilisihttps://www.quora.com/Why-is-China-home-to-almost-none-of-the-poorest-10-of-humans

https://www.quora.com/Why-is-China-home-to-almost-none-of-the-poorest-10-of-humans

http://aasa.ut.ee/tbilisihttps://ourworldindata.org/grapher/life-expectancy?tab=map

https://ourworldindata.org/grapher/life-expectancy?tab=map

Life expectancy, 2008


Big changes?

Internet traffic in 2007 vs traffic routes in ca 1930


Technological ground

• Fast development of mobile devices

– Display

– Global Navigation Satellite System (GNSS)

• GPS– A-GPS

• Galileo

• Glonass

• …


5110


Qualitative growth of Internet

http://www.urenio.org/2011/11/17/semantic-web-for-smart-cities/http://aasa.ut.ee/tbilisi

http://www.urenio.org/2011/11/17/semantic-web-for-smart-cities/

GIS functions

• Mapping and visualization;

• administration of geographical information;

• data collecting and updating;

• geographical analysis.


GIS in governance

GIS asdatabases

DecisionSupport systems

Modelling & SimulationActivities

PublicParticipation and

InformationAccess


Geographic information system (GIS)

• Mutually related complex of software and data

– Watching geographical information,

– Administration of geographical information,

– Analysis of spatial relationships and patterns,

– Modelling of spatial processes.


GIS

• Hardware

• Software

• Database

– Geographical space

– Theme (attributes)

• Operations

• Human resource


History

• First person who placed different layers on top of each other?


Cholera deaths in London

John Snow 1854


History• 1963: first nation-wide GIS - Canada• 1966: first raster-GIS• 1972: first civil use remote sensing satellite Landsat 1 • 1978: first satellites of NAVSTAR (development of GPS technology)• 1979: first vector-GIS –ODYSSEY GIS• 1981: Esri ARC/INFO • 1986: MapInfo – first desktop GIS• 1994: beginning of standardization of spatial data and infrastructure

(OpenGIS consortium)• 1996: first Internet based GIS products• 1996: first Internet based map service MapQuest• 2000: over 1 million professional GIS users in world, over 5 million

„average“ GIS users• Today: everyone can „GIS“


Area of use

• Land survey, cartography• Logistics• Aviation• Real estate• Military forces• Trade• Local authority• Science• Infrastructure management• …• Spatial planning


Important factors for spatial analysis

• Location data

• Attribute data

• GIS


Spatial databases & GIS

• Location: spatial vs descriptive?

– 41°40′09″N 44°57′17″E

– Tbilisi airport

• Relation between objects

– Distances

– Patterns

– Relationships, causality


Location:

• Descriptive

• Spatial

• Network


• Everything, what happens in real world has geographical coordinates

– X

– Y

– Z

– time

• (also in virtual space)


Location

• Map and database must be in same projection and datum

– Datum – model of the earth

– Projection – curved surface to flat plane


• Earth is not ideal sphere but geoid (potato-shaped)

– Earth model: ellipsoid

• Map projection – method of representing the surface of Earthon a plane

– All map projections distort the surface in some fashion

• Error minimization


Representation of spatial data

• Real world is too complex

• Simplified models

– Maps

– Cartography

http://www.colorado.edu/geography/gcraft/notes/datum/datum_f.html

http://www.colorado.edu/geography/gcraft/notes/datum/datum_f.html

Modelling the real world

• Discrete objects

• Continuous fields

Visualization of invisible objects / phenomenas (Augmented, Mixed Reality)

Distortions

– area,

– direction,

– scale,

– distance.

http://blog.perrygeo.net/2005/12/11/tissot-indicatrix-examining-the-distortion-of-2d-maps/

http://blog.perrygeo.net/2005/12/11/tissot-indicatrix-examining-the-distortion-of-2d-maps/

Model accuracy

Augmented reality


Representation of geoinformation in GIS

• objects

– points,

– lines,

– polygons;

• raster;

• attributes.


VectorPoint

Line

Polygon

Shp-layer:


Raster

slope Elevation shading Population density

ortophoto Landuse concentration

Lat | Lon | Value26.466 |58.478 | 165 … | … | …


Vector layer

• Attributes table:

– Rows: map objects

– Columns: attributes

– Queries (SQL)


• Layer based model:

– One theme for every layer

– One data type for every layer (point, line, polygon, raster)

Elevation


Perception

• Use of color

– Traditions of visualising certain object types

• orientation

• Symbols

• Colors


Perception


http://www.rpdms.com/satillusion/index.html

http://www.rpdms.com/satillusion/index.html

• Map (data) scale

– the ratio of a distance on the map to the corresponding distance on the ground (e.g. 1:400 000)

• Generalization

– Simplifying of objects

Measurements accuracyModel accuracyAmount of data


Generalization


GIS output

• Table

• Graph

• Report

• Thematic map

• Something else?

What is the aim?


Internet maps

• Open Street Map

• Google Map

• Bing Map

• …


Creating GIS

• Reality model (description of the real world)

• Data model (database structure and technology)

• Representation model (rules for data representation)

– e.g. Roads on top of rivers


Management of spatial data

• Raster model

– Rectangular regular grid of pixels

• Vector model

– Points, lines, polygons (functions determining the shape and form ofobjects)


Processing of geographical data

• Processing of the initial data for achievement of goals

– Queries (response to relevant conditions)

– Spatial analysis (description of place, attribues and relationshipsbetween them)


Quality of spatial data

• Completeness (missing, redundant data)

• Consistence

• Location correctness

• Up-to-date

• Thematic correctness


geospatial analysis with raasa.ut.ee/tbilisi/01_intro_to _spatial_analysis_gis.pdf · • this is...

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