**4. Methodology**

464 Remote Sensing – Applications

densely inhabited, commonly called the "ville basse" (low city). After independence in 1960, the city has spread into the complex hills surrounding the city and low peaks around 600 m

Two SPOT images dating respectively from March 31, 1995 and July 1, 2005 were used. They are recorded in panchromatic and multispectral modes. Their radiometric quality is variable. The 1995 images have a cloud cover of 7% in multispectral and 5% in panchromatic, while the 2005 images have 6% of cloud cover in multispectral mode and 10% in panchromatic mode. The presence of these clouds is evidence of the difficulty of obtaining cloud-free images for areas located in the sub-equatorial climate. To make the different images comparable, a radiometric correction was performed. Unfortunately, due to the low correlation between the red and the green bands, it did not yield good results and

Other data were collected, digitized and georeferenced, if necessary, to analyse urban growth of the city. This entailed using the old cards to map the growth of Kinshasa over the

In addition, to map the dynamics of the habitat of the Atlas of Kinshasa (Flouriot, 1975), the map "District Urban Leopoldville 1/60 000" presents the urban area in 1920. Plan Leopoldville (map 1/15 500 published by the bookseller Congo Leopoldville) gives the limit of the city in 1954. The map "Plan of Commons of Kinshasa and its Environs" to 1/20 000 published in 1959 by the Geographic Institute of Zaire is the drawing of municipal boundaries of the urbanized area in 1959. The map "City of Kinshasa-health zones" (Card 1/20 000 published in 1969 and revised in 1997 from the bottom of the base map of Kinshasa), provisional edition, published by the Geographical Institute of Zaire has the delineation of municipal boundaries of the urbanized area in 1969. All these documents are completely overwhelmed by the current

The population data used suffers from both a paucity of quality and reliability in a country where the offices of the civil state are characterized by operating failure and where the general census of the population is not regularly organized. With the exception of the 1984 population numbers from the 1984 census, the others are mere projections of the National

Coverage maps scale 1 / 10 000 by the Geographical Institute of the Belgian Congo (IGCB) dating from 1958 covering the city of Kinshasa have been scanned. The contours at a contour interval of 5 metres were digitized by students from MA1 geography at the university, corrected and interpolated by Mathieu De Maeyer (IGEAT / ULB) by the spline technique to

Some roads (in the north of the city and the far east, after the airport) were digitized from the SPOT panchromatic band (of 10 April 2000) and a plan of the city of Kinshasa (1 / 10 000) of March 1970 created by the Geographical Institute of the Congo. The roads in the west and south were measured and corrected by DGPS Pathfinder software. The railway was also digitized from the map of the city of Kinshasa. The roads of the southern part were digitized

above sea level. This area is mainly occupied by slums, called the "high".

long-term, population data and the relief and major roads.

situation (Delbart et al., 2002; Fox et al., 1997) and require updating.

produce a digital terrain model and derive the slope.

using only the SPOT panchromatic band of the 10 April 2000.

**3. Data** 

was abandoned.

Institute of Statistics.

Two approaches for change detection exist. "Image-image" comparison methods imply a radiometric normalization; this standardization is difficult to implement on data from different seasons and radiometric quality is also variable (Singh, 1986; Alphan, 2003; Coppin et al., 2004; Yuan et al., 2005). In addition, they do not identify the nature of change. Comparison methods compare the post-classification classifications of land produced independently at different dates (Gupta et al., 1985). The other group of methods is less sensitive to differences in season and they identify the nature of change but are susceptible to misclassification. To detect changes, classifications are compared in pairs. From this comparison, a map where the changes can be located and a change matrix that summarizes the amount and the nature of these changes are derived.

#### **4.1 Geometric correction and cutting recovery images**

To detect changes, it is essential that the SPOT images are properly stowed from the geometrical point of view.

This is why the latest panchromatic image has been corrected from an image of higher resolution. This is a panchromatic IKONOS image from 2002 of a resolution of 1 m corrected itself with control points measured in absolute mode with a Garmin GP60 GPS. Root mean square errors of 9.46 m on the hilly part and 4.14 m on the plain were obtained.

Then all the other images SPOT (panchromatic and multispectral mode) were corrected on the panchromatic SPOT image, corrected with a polynomial function of first order and the nearest neighbour method. All are projected onto the ellipsoid WGS 84 UTM coordinates, zone 33 south.

Geometric corrections lead to RMS errors smaller than the size of a pixel with 29 to 35 control points (Table 1), which is acceptable according to Moller-Jensen (1990) and is suitable for a detect changes study.


Table 1. RMS errors after geometric correction

Not all SPOT images have the same spatial extension. In addition, their size being 60 km on each side, is wider than the extension of the city of Kinshasa. The images of 1995 and 2005 were cut to the same extension.

The Mapping of the Urban Growth of Kinshasa (DRC)

**4.2.5 Validation** 

 The overall accuracy, The overall Kappa, The Kappa class.

Table 2. Classification accuracy

Zone 2 Island Mimosa

parameter 0.1 (0.5 for compactness and 0.5 for smoothing).

the city. This result will therefore not be used subsequently.

**Confusions errors in 1995**  Zone 1 Canoes to the east of Industrial Limete

**Confusions errors in 2005** 

**Errors of omission in 2005** 

(abundance of vegetation)

Zone 2 Field burned to the east of the city

Zone 5 Sand bank to the west

regions according to their proximity to areas of statistical training.

Through High Resolution Remote Sensing Between 1995 and 2005 467

limits the size of the resulting segments. The segmentation was performed on the image of 2005 spectral bands of green, red and near infrared respectively, giving them a weight of 2, 1 and 1. The scale parameter was chosen by trial and ,error and set at 20 with the shape

The algorithm for supervised classification of the nearest neighbour was used. It ranks the

The classifications are evaluated by comparing 34 areas of validation within the matrix of

The overall accuracy is good (> 80%) obtained for the different classifications (Table 2). The Kappa coefficient is only acceptable for the classification of 1995 (85%) and 2005 (92%). The classification of 2000 has a poor Kappa (64%) caused by the fog that covers the southwest of

Years Overall accuracy (%) Kappa Coefficient (%)

Extensive field visits conducted in late January 2009 to the end March 2009 in the extension zones of Kinshasa to understand the factors of urbanization has revealed the existence of different confusions and omissions in the class "building". For example, here are some for

1995 93 85 2005 96 92

the image of 1995 and 2005. They are located in Figure 1 and identified in Table 3.

Zone 3 Fields and sand pit in the southwest in the commune of Mont Ngafula

Zone 4 Island Mimosa with large rocks and a mining company in building materials

Zone 3 Residences in the area of the general staff of the Congolese armed forces

Table 3. Confusion and omission errors for the class built-up in 1995 and 2005

Zone 1 Sand pit area behind the camp CETA and fields of vegetable crops

confusion. Indices are calculated to assess the quality of results (Richards, 1993):

#### **4.2 Land use classification**

Given the uneven quality of SPOT images and the strong texture of the buildings, they were classified by a supervised method and object-oriented software using eCognition.
