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J-F. Pekel and P. DefournyDepartment of Environmental Sciences
and Land Use Planning - GEOMATICS
UCL Université Catholique de Louvain BELGIUM
Supported by the SSTC (Services fédéraux des affaires Scientifiques, Techniques et culturelles)
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Mapping of the African Great Lakes Mapping of the African Great Lakes
region from daily VEGETATION dataregion from daily VEGETATION data
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Main challenge for VGT time series data interpretation
How to use simultaneously :
• multispectral information
• temporal information
• full spatial resolution consistency
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Window: 4°N-14°S / 25°E-35°E
Area: 2.257.920Km²
Study area
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
• Clouds and large gaps
06 may 20000708091011121314091516
(Blue, Red, NIR)
Particularities of the study area
• TopographyTopography
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Particularities of the study area
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
• Inversion of seasonality
6 mars 2000 (R, PIR, MIR)6 mars 2000 (R, PIR, MIR)3 july 2000 (R, PIR, MIR)3 july 2000 (R, PIR, MIR)
Spatial consistency ?
Particularities of the study area
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
1st Strategy: Manual compositing
Compositing
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
2nd Strategy: Mean compositing
Annual
Compositing
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
2nd Strategy: Mean compositing
Feb-March-April July-August-September Annual
Compositing
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Annual
mean
Classification
(50 classes)
Mean reflectance per class
Seasonal mean
(Feb-March-April)
Seasonal mean
(July-August-September)
RNIR
MIR
RNIR
MIR
Classification methodology
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Mean reflectance
per class
Classification
(17 classes)
RNIR
MIR
RNIR
MIR
Classification
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Classe 1: forêt dense humide semprevirente et semi-décidue
Classe 2: forêt dense humide semi-décidue
Classe 3: forêt ombrophile secondaire
Labelling
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Labelling
1 Lacs et fleuves Perennial waterbodies2 Forêt galerie et formation marécageuse Gallery-forests and ,,,3 Forêt dense humide et forêt de basse montagne Dense moist forest and ,,,,4 Miombo (Forêt claire) Dense dry forest and Miombo woodland5 Mosaîque forêt claire - savane (Savane parc) Open forest-savannah mosaic6 Forêt de transition et forêt de montagne Mountain forest and ,,,,7 Miombo très clair (mosaîque forêt claire - savane) Very open forest-savannah mosaïc8 Mosaîque forêt dense - savane Dense forest- Savanna mosaic9 Savane herbeuse et complexe rural Grass-Savannah and rural complex
10 Savane herbeuse à arbustive Grassland and Shrub Savannah 11 Forêt secondaire (=forêt semi-décidue) Secondary forest12 Forêt de montagne Mountain forest13 Mosaîque forêt - savane et complexe rural Forest-Savannah-rural complex mosaic14 Formation buissonante et fourés Shrub savannah15 Forêt de bambou Bamboo forest16 Prairie flottante Swamp grasslands17 Plaine de lave : Forêt et brousaille sclérophyle Lava plain
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Landsat TM(Nir, MIR, Green)
Classification result of VEGETATION
data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Landsat TM(Nir, MIR, Green)
Classification result of VEGETATION data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Landsat TM(Ni r, MIR, Green)
Classification result of
VEGETATION data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Landsat TM(Nir, MIR, Green)
Classification result of VEGETATION
data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Landsat TM(Nir, MIR, Green)
Classification result of VEGETATION
data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Roads
Primary forest
Secondary forest
Validation: visual assesment
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
TREES map Classification result of VEGETATION data
Validation: visual comparison
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
TREES map
(2000)
Classification result of VEGETATION data
Validation: visual comparison
Landsat TM(Nir, MIR, Green)
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
Validation: visual comparison
TREES map
(2000)
Classification result of VEGETATION data
Landsat TM(Nir, MIR, Green)
Department of Environmental Sciences and Land Use Planning - UCL GLC 2000, 18 - 22 march 2002
• Automatic and operational methodology of mapping
• Use of all reflectance channels and not only the NDVI
• High local contrast between land cover types
• Mean compositing provides a large spatial consistency
• Methodology based on phenology
• Methodology most probably applicable to many areas and
various conditions
Conclusions