Transcript Dia 1

Remote Sensing in Geography Education, illustrated by a
vegetation dynamics study
(Kikwit region, Democratic Republic of the Congo)
Lieselot Vandenhoute, Lector Aardrijkskunde, Katho
departement RENO
Sint-Jozefstraat 1, B-8820 Torhout, Belgium
Tel.: ++32 (0)50 23 10 30 Fax.: ++32 (0)50 23 10 40
Email: [email protected]
Step 1: Situation of the study area
CENTRAL AFRICAN
REPUBLIC
SUDAN
. Gbadolite
CAMEROON
Congo
REP. OF
THE
GABON CONGO
. Mbandaka
. Bumba
. Kisangani
Goma .
Bukavu . RWA
Kindu .
BUR
. Ilebo
. KINSHASA
Lake
Tanganyika
Kikwit
. Matadi
. Kananga Kalemie .
.
ANGOLA
Kolwezi .
Atlantic
Ocean
. Lubmbashi
0
200
400 km
N
ZAMBIA
Geographical
situation of
the study
area in the
Democratic
Republic of
the Congo
Evolution of the population of the Democratic Republic of the Congo
60000
population ev olution
population (x 10³)
50000
40000
30000
20000
10000
19
00
19
05
19
10
19
15
19
20
19
25
19
30
19
35
19
40
19
45
19
50
19
55
19
60
19
65
19
70
19
75
19
80
19
85
19
90
19
95
20
00
0
y ear
Source: to Lahmeyer, J., 2002. Congo (Kinshasa). Historical demographical data of the whole
country. Population Statistics, http://www.library.uu.nl/wesp/populstat/Africa/congokic.htm.
06/09/2002.
The
increasing
population
growth
shown in this
graph is
thought to
have an
enormous
impact on the
natural
vegetation.
Savannah plateau
Dense forest
in river
valley
Foto from Prof. Dr. Rudi Goossens. Universiteit Gent, Faculteit Wetenschappen,
Opleiding Geografie. 1988.
This area was
chosen
because of its
dense
population in
comparison
with other
parts of the
country. The
increase of a
dense rural
population
should have a
clear impact on
the natural
vegetation.
Step 2: Collecting Satellite Imagery
0
N
12500 meter
False Colour
Composite of
a SPOT scene
taken on the
2nd of July
1987. Spatial
resolution: ±
20x20 m.
Geometric
accuracy:
RMSE 59,500
m.
N
0
12500 meter
False Colour
Composite of
an ASTER
scene of the
21nd of July
2001 Western
part of the
study area.
Resampled
spatial
resolution: ±
20x20 m.
Geometric
accuracy:
RMSE 88,530
m.
N
0
12500 meter
Step 3: Image Classification
Digitised
vegetation
categories
on the
Corona
mosaic.
Palmerais
Forêt claire
Forêt galerie
0
N
12500 meter
NDVI-classification of the
SPOT scene.
NDVI from –1 up to –0,60
NDVI from –0,59 up to –0,20
NDVI from –0,19 up to 0,00
NDVI from 0,01 up to 0,20
NDVI from 0,21 up to 0,40
NDVI from 0,41 up to 0,60
NDVI from 0,61 up to 0,80
NDVI from 0,81 up to 1,00
N
0
12500 meter
NDVI-classification of the
ASTER scene.
NDVI from –1 up to –0,60
NDVI from –0,59 up to –0,20
NDVI from –0,19 up to 0,00
NDVI from 0,01 up to 0,20
NDVI from 0,21 up to 0,40
NDVI from 0,41 up to 0,60
NDVI from 0,61 up to 0,80
NDVI from 0,81 up to 1,00
N
0
12500 meter
Multitemporal
Colour
Composite
N
0
12500 meter
Exercise 1:
Create a Satellite Images
mosaic.
Exercise 2:
Digitize all tree vegetation
on the Corona image.
Exercise 3:
Create a (false) colour composite selecting
the correct the spectral bands.
Students learn how to:
-Work with digital
images
-Interpret digital images
-Work with photo
editing software
-Reduce the inaccuracies
EXTRA
- Georeference
Students learn how to:
-Interpret a Corona image
-Work with Remote Sensing
software or GIS such as
ILWIS or ArcView, …
-Label the digitised objects
and work with attributes
Students learn how to:
- Create a (false) colour composite
- Select the correct spectral bands
- Stretch the spectral bands to become a
clear and readable
image
- Interpret a (false) colour composite
- Work with Remote Sensing software or
GIS such as ILWIS or ArcView, …
EXTRA:
- Remove noise
Exercise 4:
Create a NDVI image.
Exercise 5:
Create a multi temporal
colour composite.
Students learn how to:
- Create an NDVI image
- Combine different
spectral bands
- Visualise an NDVI
image
- Interpret an NDVI
image
- Work with Remote
Sensing software or GIS
such as ILWIS or
ArcView, …
Students learn how to:
-Work with the colour cube
- Interpret satellite images
- Interpret combined
satellite images
- Create binary images
- Work with Remote
Sensing software or GIS
such as ILWIS or ArcView,
…