Lieselot Vandenhoute, Lector Aardrijkskunde, Katho departement RENO

Sint-Jozefstraat 1, B-8820 Torhout, BelgiumTel.: ++32 (0)50 23 10 30 Fax.: ++32 (0)50 23 10 40

Email: lieselot.vandenhoute@katho.be

Remote Sensing in Geography Education, Remote Sensing in Geography Education, illustrated by a vegetation dynamics studyillustrated by a vegetation dynamics study

(Kikwit region, Democratic Republic of the Congo)(Kikwit region, Democratic Republic of the Congo)

Step 1Step 1: Situation of the study area

Geographical situation of the study area in the Democratic Republic of the Congo

Kolwezi .. Lubmbashi

ANGOLA

ZAMBIA

Atlantic Ocean

. KINSHASA

. Kisangani

. Ilebo

. Mbandaka

Kindu .

. Kananga. Kikwit. Matadi

Bukavu .Goma .

Kalemie .

REP. OF THE CONGOGABON

CAMEROON

CENTRAL AFRICAN REPUBLIC SUDAN

UG

AN

DA

TA

NZ

AN

IA

RWA

BUR

Congo . Bumba

. Gbadolite

Lual

aba

Lake Tanganyika

0 200 400 kmN

The increasing population growth shown in this graph is thought to have an enormous impact on the natural vegetation.

Evolution of the population of the Democratic Republic of the Congo

0

10000

20000

30000

40000

50000

60000

year

popu

lati

on

(x10

³)

population evolution

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.

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.

Savannah plateau

Dense forest in

river valley Foto from Prof. Dr. Rudi Goossens. Universiteit Gent, Faculteit

Wetenschappen, Opleiding Geografie. 1988.

Step 2Step 2: Collecting Satellite Imagery

N0 12500 meter

0 12500 meterN

False Colour Composite of a SPOT scene taken on the 2nd of July 1987. Spatial resolution: ± 20x20 m. Geometric accuracy: RMSE 59,500 m.

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.

0 12500 meterN

Palmerais

Forêt claire

Forêt galerie

Digitised vegetation categories on the Corona mosaic.

0 12500 meterN

Step 3Step 3: Image Classification

0 12500 meterN

NDVI from –1 up to –0,60NDVI from –0,59 up to –0,20NDVI from –0,19 up to 0,00NDVI from 0,01 up to 0,20NDVI from 0,21 up to 0,40NDVI from 0,41 up to 0,60NDVI from 0,61 up to 0,80NDVI from 0,81 up to 1,00

NDVI-classification of the SPOT scene.

N0 12500 meter

NDVI-classification of the ASTER scene.

NDVI from –1 up to –0,60NDVI from –0,59 up to –0,20NDVI from –0,19 up to 0,00NDVI from 0,01 up to 0,20NDVI from 0,21 up to 0,40NDVI from 0,41 up to 0,60NDVI from 0,61 up to 0,80NDVI from 0,81 up to 1,00

Multitemporal Colour Composite

N0 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, …