geographical information systems/science (gis) · geographical information systems/science (gis)...

Introduction to:

Geographical Information Systems/Science (GIS)

Didac Pascual, 2019

[email protected]

Lunds universitet / Fakultet / Institution / Enhet / Dokument / Datum

Geographic Information System

or

Geographic Information Science

Definition…


Geographic Information System

or

Geographic Information Science

What is GIS?

Definition…

‘’Is a system designed to capture, store, manipulate,

analyse, manage, and present spatial or geographic data.’’


Learning outcome

Part 1 GIS

What is GIS?

How is reality represented an a GIS?

How can GIS provide new knowledge?

SQL and logic operations

Examples of common visualisations using GIS

Examples of common analyses using GIS

Part 2 Remote Sensing

Introduction to remote sensing

How does it work? Reflectance in different wave lengths

Some examples

Vegetation –spectral signal of vegetation

FCC and vegetation indices


1. We produce maps

• What is a map then?

Is this a map?


1. We produce maps...


How about this one?




Or this?


Why isn’t a photograph considered to be a map?

A map is a symbolic representation of selected characteristics of a place,

usually drawn on a flat surface.

What is a map?





Maps are interpreted and generalized.

What is a map?





Maps are interpreted and generalized.

Maps have scales that are homogenous –

scales in photographs varies

What is a map?


How do we transform earth properties to map?

models about the properties to map




Object model (vector)

Space is empty except when

occupied by objects with well

defined borders




Object model (vector)



defined borders

Based on:

-points,

-lines,

-polygons

-bodies

Field model (raster)

No space is empty.

Based on:

- pixels


Vector model

• We generalise reality

• We apply a spatial reference (coordinate system)


Vector model

• We generalise reality

• We apply a spatial reference (coordinate system) Object model (vector)



defined borders


Vector model

• Point 0-dim scale independent


Vector model

• Point 0-dim scale independant

• Line 1-dim length represent scale


Vector model



• Polygon 2-dim proportional to actual shape


Vector model



• Polygon 2-dim proportional to actual shape

• Body 3-dim proportional to actual shape (z often enhanced)


Vector vs. Raster

Model = continuous surface Model = Well defined objects

Datatype:

Points

lines

Polygons

Bodies (3D)

Datatype:

Pixels


Vector vs. Raster

Model = continuous surface Model = Well defined objects

Datatype:

Points

Lines

Polygons

Bodies (3D)

Datatype:

Pixels


What do these maps have in common?

How do they differ?

B A

C D


1. A rectangular matrix in 2D

2. Each cell/pixel is considered to be homogenuous

3. Each cell/pixel has a value –often reprented as a color/shade in the GIS

4. Digital aerial photos/satellite images are stored as rasters

The raster structure


Spatial resolution

• Cell size

• High resolution = raster containing cells with small cell sizes (more details)

• Low resolution = larger cells


Spatial resolution of raster data

“The higher the resolution, the more details will be possible to

detect. Therefore, one should always use the highest spatial

resolution as possible when performing analyses.”

TRUE or FALSE?


Spatial resolution of raster data

“The higher the resolution, the more details will be possible to

detect. Therefore, one should always use the highest spatial

resolution as possible when performing analyses.”

TRUE or FALSE?

Depends on the aim of your study!


Problems with raster


Problem med raster


Each property compose a layer

The layers are put

on top of one

another

Note! There could

only be one data

type within one

layer


In the program:

Choose what layers to show

Choose the order of the layers Map window

Table of Contents


Does it matter which model we use?

• Households in Brösarp

• Major road network of Skåne

• Elevation of Scania

• Soils of Sweden

• Landuse (crop field, urban/cities, forest, lake ....)

• Temperature variations within Skåne or within Sweden

• Precipitation in Skåne

• Precipitation in Europe

• Nice walking path around the Bertilstorp forests

How do you think the below properties could be obtained?

How do you think they should be represented in a GIS?


What is a GIS?

1. Geometrical objects as vector

(points,lines, polygons) or

raster (pixels) to represent

properties defined in space


What is a GIS?

1. Geometrical objects as vector

(points,lines, polygons) or

raster (pixles) to represent

properties defined in space.

2. Each object is connected to an

attribute table, providing more

information about the object.


Each object in the map has an id number.

The id-number has a row in the table

LINK

ID

NAME

Tax. value

12

A. Nilsson

150 000

13

P. Jonasson

210 000

14

K. Hallén

97 000

15

J. Fransson

1 120 000

How are the map and table linked?


How do we use table information in GIS?

Select specific information to show on the map using the attribute

table

Ex. Find all cities with a population above 5000 citizens

Perform computations based several properties (columns)

Visualisation of attribute data (tematic maps)

Analyses of relationships between attribute data and

spatial/geographic locations


SQL = Structural Query Language

The syntax:

•Select (columns)

•From (which table)

•Where (criteria)

”*” = all

Select * Select all columns


How do we use the information from tables in a GIS?

Perform computations based several properties: from table or/and

geographic location

Ex. 1

Leakage of nutrients to a river comes

from crop fields

How many crop fields do the river pass?

What is the area of those crop fields?

What is the leakage?


How do we use the information in a GIS?

Ex. 2

Planning for school capacity: How many children are expected to

start school next year

How many children of a certain age live within a radius of 2 km from the

school?


Spatial relationships

Spread of the Russian flu along the rail road network (Russion flu 1889-1890).

Development per week

Blue dots = new discoveries of the flu


* Nov. 1 1889

** Nov. 7



Rumsliga samband:

Spridning av influenza utmed järnvängsnät (ryska influensan 1889-1890).

Veckovis tidsserie

Blå ploppar = upptäcka fall av influensa



Rumsliga samband:

Spridning av influenza utmed järnvängsnät (ryska influensan 1889-1890).

Veckovis tidsserie

Blå ploppar = upptäcka fall av influensa

* Fall av influenza

31 januari 1890



Rumsliga samband:

Spridning av influenza utmed järnvängsnät

Number of

infected

people is also

easily

illustrated in a

GIS



Models and simulations

How are air polutions spread?

• Wind direction/speed

• Vertical temperature profile

• Property/amount of pollution


Net work analyses

• Shortest route from A to B

• Fastest route from A to B ( type of road,

speed limits, etc

• Accelerations/Slow downs

• Road work

• Traffic (specific hours)


What is remote sensing?

= Any data collected from a distance

Images from: Air Images: www.aerialphotography.com/ NASA //www.NASA.gov

Aircraft

Satellites Active sensors

P

l

a

t

f

o

r

m

s

I

n

s

t

r

u

m

e

n

t

s

Psssive scanners Camera /film or digital


Why?

• Reach uninhabited areas -large parts of earth surface is hardly ever visited: water/ice (weather prediction)

• Cover large areas general overview for spatial patterns

• Provides up-to-date information overview spatial distribution/quick changes


How?

• Reveal information from light sources/wavelength regions invisible to our eyes


When?

• To produce maps

• Weather prediction

• Detection/distribution of gases

• Crop forecasting

• Mineral detection

• Forest monitoring

• Land use change detection

• Climate and environmental changes

• ...


Glacier retreat…


Deforestation…


The electromagnetic spectrum

• Visible part is small

• Photographs use

mainly VIS

• Near infrared to

some extent


Human:

blue, green, red

Bee:

Blue, green

Insects:

blue, green, red,

ultra violet

Snakes:

green, red, infrared...

Sensibility of wavelengths... In remote sensing we

use the ”invisible”

wavelengths.

How can we view

reflectance from the

invisible wavelength

bands?


Reflectance

White

Black

Blue

High reflectance in all

visible wavelengths

Low reflectance in all

visible wavelengths

High reflectance in blue

and low reflectance in all

other visible

wavelengths

Reminder: All objects reflect electromagnetic

waves differently different colors.

It is the reflected light that we sense as colors.

blue green red

blue green red

blue green red


Image identification How do we identify surface characteristics from satellite data?


Image identification by: color, shape, size

Farmland in Illinois, USA Landsat image

Detection of surface properties


Example by texture

Ikonos: 1 m resolution

3 1

2

What is this?

What do the different

textures represent?


Identification by texture

Oil palm plantation

1.Individual palm trees. Regular

pattern.

2.Tree canopies merge together.

Shrubs and abandoned trees. tall

undergrowth between the trees.

3.Open field with short grass +

individual shrub

Ikonos: 1 m resolution

3 1

2


Identification by relative size

Trees, shrubs or?


http://wiki.landscapetoolbox.org/lib/exe/fetch.php/remote_sensing_methods:ii_size_f2.png?cache=


Identification by size


http://wiki.landscapetoolbox.org/lib/exe/fetch.php/remote_sensing_methods:ii_size_f2.png?cache=


Identification of tree species using

shadows



Image identifications

• Color-tone

• Size

• Shape

• Texture

• Shadows

• Pattern

• Neighborhood/association



Computorised image classification

methods

Color/reflectance

= pixel based.

Identifies pixel by

reflectance value in

certain wavelengths

Object based

–identify

objects by

Shape + size

+ pattern



Empirical example!

How FIELD studies, REMOTE SENSING and GIS are used together.


Empirical example!


Permafrost distribution


Empirical example!


* Research question: How much organic Carbon is there in the soil in the e.g. Aktru

Valley (Russian Altai)?

(adapted from Brown et al., 1997).


• 1. Field studies:


• Remote sensing:

LANDSAT 8: passive sensor for acquisition of satellite imagery of the Earth.


• Analysis of remote sensing products in a GIS:

Land Cover Classification:

- Land cover classes?

- Areal extent?

- Location of sampling sites?

- Data statistics?


• Analysis of remote sensing products in a GIS:

Land Cover Classification:

- Land cover classes?

- Areal extent?

- Location of sampling sites?

- Data statistics?

Upscaling of field data!


• Results:

Soil Organic Carbon (kg C m⁻²)

SOC storage:

Vegetated: 3.5 ± 0.8

Unvegetated: 8.5 ± 0.8


All studies put together…



All studies put together…

(from Hugelius et al 2014)



THANKS FOR YOUR ATTENTION!

QUESTIONS?

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