The issue of spatial spread remains topical in any society, especially in cities. Today, cities are expanding at an exponential rate towards their peripheries under the influence of a set of factors including urban growth. African cities, and particularly Cameroonian cities, are characterized by their strong spatial growth. This situation is mainly due to the strong growth of the population but also the multiplication of human activities. It is in the light of this observation that we have oriented our research on the monitoring by remote sensing of the spatial spread of the city of Douala in the era of urbanization. The objectives are to analyze the spatial spread of the city of Douala, to identify the factors at the origin of the spatial spread, the consequences and the analytical tools. To achieve this objective, we started from the general hypothesis according to which the sprawl of the city of Douala is linked to demographic growth, the development of buildings, economic activities, etc. We have, of course, relied on documents to approach this study, but most of the work has been done in the field where direct observation, etc. were effective tools for the outcome of this research. Landsat’s images and shape files were also used etc. Results from our field investigations show that the city of Douala experienced strong spatial growth between 1975 and 2019. In 1975, we note that built-up areas represented 2.40% of the total area of the city of Douala. In contrast, forest represented 84.47% and crops 1.53% of the study area. In 2007, built-up areas represented 9.96% of the total area of the study area. On the other hand, the forest represented 79.09% of the studied area. In 2019, buildings made up 21.31% of the city of Douala, forests 58.69%, crops 8.56% and rivers 11.44%. The sprawl of the city of Douala is linked to various factors: the development of economic activities, the development of communication routes, the administrative center etc. The consequences among others are the development of precarious neighborhoods, the difficulties of access to basic urban services, the reduction of arable land, etc.

Keywords : Landsat’s Images, Spatial Dynamics, the City.