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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.

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Presentation on theme: "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."— Presentation transcript:

1 Lieselot Vandenhoute, Lector Aardrijkskunde, Katho departement RENO Sint-Jozefstraat 1, B-8820 Torhout, Belgium Tel.: ++32 (0) Fax.: ++32 (0) Lieselot Vandenhoute, Lector Aardrijkskunde, Katho departement RENO Sint-Jozefstraat 1, B-8820 Torhout, Belgium Tel.: ++32 (0) Fax.: ++32 (0) Lieselot Vandenhoute, Lector Aardrijkskunde, Katho departement RENO Sint-Jozefstraat 1, B-8820 Torhout, Belgium Tel.: ++32 (0) Fax.: ++32 (0) Lieselot Vandenhoute, Lector Aardrijkskunde, Katho departement RENO Sint-Jozefstraat 1, B-8820 Torhout, Belgium Tel.: ++32 (0) Fax.: ++32 (0) Remote Sensing in Geography Education, illustrated by a vegetation dynamics study (Kikwit region, Democratic Republic of the Congo)

2 Step 1 Step 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 CONGO GABON CAMEROON CENTRAL AFRICAN REPUBLIC SUDAN UGAND A TANZANI A RWA BUR Congo. Bumba. Gbadolite Lualaba Lake Tanganyika km N

3 The increasing population growth shown in this graph is thought to have an enormous impact on the natural vegetation. Source: to Lahmeyer, J., Congo (Kinshasa). Historical demographical data of the whole country. Population Statistics, 06/09/2002.http://www.library.uu.nl/wesp/populstat/Africa/congokic.htm

4 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

5 Step 2 Step 2: Collecting Satellite Imagery N meter

6 0 N False Colour Composite of a SPOT scene taken on the 2 nd of July Spatial resolution: ± 20 x 20 m. Geometric accuracy: RMSE 59,500 m.

7 False Colour Composite of an ASTER scene of the 21 nd of July 2001 Western part of the study area. Resampled spatial resolution: ± 20x20 m. Geometric accuracy: RMSE 88,530 m meter N

8 Palmerais Forêt claire Forêt galerie Digitised vegetation categories on the Corona mosaic meter N Step 3 Step 3: Image Classification

9 meter N 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 NDVI-classification of the SPOT scene.

10 N 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

11 Multitemporal Colour Composite N meter

12 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, …


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