Current Research in Geoscience Original Research Paper Contribution of Remote Sensing in the Estimation of the Populations Living in Areas with Risk of Gully Erosion in Kinshasa (D.R. Congo). Case of Selembao Township 1Kayembe wa Kayembe Matthieu, 1Ngoy Ndombe Alain, 2,3 Makanzu Imwangana Fils, 4Mpinda T. Martin, 5Misilu Mia Nsokimieno Eric and 6Eléonore Wolff 1Department of Geography, University of Lubumbashi, D.R. Congo 2Department of Geosciences, University of Kinshasa, D.R. Congo 3Center of Geological and Mining Survey, Kinshasa, D.R. Congo 4Department of Natural Resources Management and Renewables, Faculty of Agricultural Sciences, University of Lubumbashi, Congo 5China University of Geosciences, China 6IGEAT, Université Libre de Bruxelles, Belgium Article history Abstract: This paper proposes a methodology combining very high spatial Received: 01-04-2016 resolution satellite image, GIS and field surveys to estimate the number Revised: 02-06-2016 of people living in areas at (high) risk of landslides or gully erosion in Accepted: 06-06-2016 Selembao (Kinshasa). It also gives their socio-economic characteristics. Results show that 185,000 out of the 314,699 inhabitants estimated in Corresponding Author: Kayembe wa Kayembe Selembao (58.3% of the population) live in areas at high risk of gully Matthieu erosion. There are in the spontaneous neighborhoods built on steep areas Department of Geography, (slope >10%). The study of the socio-economic characteristics shows that University of Lubumbashi, these inhabitants belong to the modest socio-economic category (self- D.R. Congo made bricklayers, seller at the markets and street traders selling food Tel: +243 99 022 15 42; stuff). The level and nature of their income led them to have residential +243 84 10 20 526 integration strategic restricted to hazardous areas where land prices and Email: [email protected] rents are more attractive. Keywords: Remote Sensing, Gully Erosion, GIS, Estimation of Population, Hazardous Area, Kinshasa Introduction deficient census methods and the civil state offices not working properly (Kayembe wa Kayembe et al ., 2009). The knowledge of the size of the population is a These projections of the Congolese INS do not pressing need in several areas, including transport, health make it possible to obtain the right number of people (public), education, housing (residential), economic living in areas at risk of landslides and gully erosion in planning, taxation (capitation), etc. (Romaniuk, 1967). Kinshasa. However, these areas involve a large The United Nations recommend us to make a census population. In 2004, for example, over 50% of the once every 10 years. But given its cost, there are few Kinshasa population (3,441,506 inhabitants/7,017,000) African countries that meet this requirement. Some lived in townships considered to be at (high) risk of countries organize it at irregular time intervals. gully erosion or landslide, especially Makala, Lemba, Since its independence (in 1960) until today, the KimbansekeNgaliemaSelembao, Mont Ngafula and DRC has organized general population censuses in Kisenso (DSRP, 2005). Yet all the territories of these 1970 and 1984 only. National population data result townships are not located on the areas at (high) risk of from simple projections from the Institut National de gully erosion or landslide. Indeed, for the la Statistique/National Statistics Institute (INS). It is municipalities of Makala, Lemba, Selembao and true that regional censuses were often organized. But Kimbasenke, the risk areas are in the southern part, the figures on the population of townships are not always while Ngaliema and Kisenso are completely on reliable because of the quality of the census takers, hazardous areas. © 2016 Kayembe wa Kayembe Matthieu, Ngoy Ndombe Alain, Makanzu Imwangana Fils, Mpinda T. Martin, Misilu Mia Nsokimieno Eric and Eléonore Wolff. This open access article is distributed under a Creative Commons Attribution (CC-BY) 3.0 license. Kayembe wa Kayembe Matthieu et al . / Current Research in Geoscience 2016, 6 (1): 71.79 DOI: 10.3844/ajgsp.2016.71.79 Every year, all these towns are facing real Apart from Cité Verte , which is well equipped with environmental problems related to the gully erosion roads and a sewer system, other neighborhoods are built phenomenon. It increases quickly in number. There were on a land not laid out and therefore not equipped. Gully 195 gullies in 1970 over the entire city against 334 is much more developed in the central and southern areas identified ravines on World view 1 image in 2010 on the of the concerned township (Fig. 1). entire city (Makanzu Imwangana et al ., 2014). It also Due to the high rate of average annual growth (5% increases in size of gullies. For example, the gully of between 1984 and 2004), the need for housing is strong Mataba successively reached 14.4 hectares in 2007, there. Then, for the development of housing, heads of 16.8 hectares in 2009 and 43.9 hectares in 2010 circuses and steep valleys of Bumbu and Lubudi rivers (Kayembe wa Kayembe, 2012). Moreover, there is a are not discarded. The ongoing urbanization in this spatial deployment: All areas of the south-east and west township tends to filling interstitial spaces constituted of of Kinshasa are affected by this phenomenon. no aedificandi areas. This gully erosion phenomenon causes significant material losses (houses, roads, school buildings, clinics, Materials and Methods …are destroyed) and human ones (death during the collapse of houses) (Wouters and Wolff, 2010). Indeed, We chose a methodology which combines very high the ravines have destroyed 965 residential houses spatial resolution satellite image with the zonal between 1999 and 2010, 5 schools (completely or approach, a GIS and field survey to estimate the partially), 5 health centers and 16 other health centers amount of people living in risk area in Selembao. It have been at risk to be destroyed in 2010. A hundred of has the advantage of being less expensive compared to roads/tracks have been cut (Makanzu Imwangana et al ., the census (Lu et al ., 2002) and aerial photography 2015). Transportation, electricity and water (Yagoub, 2006). However, it requires the knowledge infrastructure have been destroyed as well as main of the size of the households as the counting of sewers for water runoff. The ravines have caused the housing units on aerial photography (Baudot, 1993 ; silting of rivers and homes at the foot of the hill and Hsu, 1971; Lo, 1985; Watkins and Morrow, 1985). killed about 150 people between 1970 and 2010. In Sub-Saharan Africa, this methodology was used Hazardous areas of Kinshasa were specified by by Yossi et al . (2002) and the POPSATER (2011) to Van Caillie (1997). According to this author, they are estimate the population of Yaounde (Cameroon) in 2000 characterized by slopes likely (from 12%) to trigger and of Lubumbashi (D.R Congo) in 2009. the gully erosion or landslide in this city. Now these The zonal approach is a subdivision of the region slopes are not visibly observable by census takers to morphologically homogeneous classes (or types of determine the number of people living in areas at risk. district) according to certain criteria, while the approach Hence the first objective of this paper is to define a based on the pixel consists of a satellite image methodology combining very high spatial resolution processing. satellite image, GIS and field surveys to estimate the number of people living in these areas at risk of Determination of the Morphological Classes and landslides or gully erosion. Typology of the District Study Area We indeed have used a false color composite Selembao township is located in the southern hilly image colors GeoEye-1 (spatial resolution: 2 m) to area, except for two districts (MwanaTunu and Nkulu) define morphologically homogeneous areas. Five in the north which are located in the plain. It is classes of morphological zones (Table 1 and Fig. 2) characterized by an almost spontaneous urbanization, were determined through visual interpretation based except for some southern districts ( Cité Verte and on the following parameters: Built-up density, Habitat ). In fact, it is a post-independence township. vegetation density and roads structuration. Each It was created, like other townships after a recent morphological class was coded with a succession of extension according to Flouriot et al . (1975) typology, three numbers from 1 to 3 for each parameter of from the watchword of political leaders inviting their homogeneity. 3 is used for high density, 1 for low activists (New and old urban city dwellers) to take a housing and vegetation density. Unlike the first two building plot in a context whereby these leaders parameters, only two digits are assigned to the road: 1 wanted to constitute their electorate, ahead of the first and 2 to express structured road (1) or unstructured democratic elections which were to take place in 1960 (2). For example, the class 311 means high built-up (De Saint Moulin, 2010). density, low density of vegetation, structured road. 72 Kayembe wa Kayembe Matthieu et al . / Current Research in Geoscience 2016, 6 (1): 71.79 DOI: 10.3844/ajgsp.2016.71.79 Table 1. Morphological classes codes and types of neighborhoods Morphological classes codes Types of neighborhoods 311 Old neighborhoods densely built on the top of the hill 211 Rich neighborhoods 332 Spontaneous settlements on steep slopes 112 Self-built neighborhoods on ongoing urbanization 222 Quarters in the process of densification (Source: Data collected on the field work, 2010) Fig. 1. Study area location (Source: Topographic contours lines are derived from DEM produced in 2010 by Philippe Trefois in Geomorphology and Remote Sensing Service of the Royal Museum for Central Africa) The choice of these parameters used to create which increases in areas with a high density of morphological classes lies in the fact that their vegetation. The latter correspond to areas affected by combination allows interpreting the structure of the gully erosion as the vegetation is used as a means to Selembao Township.