Figure 7: Geographic map of Gabon
Figure 7: Geographic map of Gabon
The Republic of Gabon covers 267,667 km² and has a population of 1,3 million (information 1991). Its capital is Libreville (352,000 inhabitants - information 1987). The major sources of income are the exploitation of forests and oil fields on the coastal shelf.
Besides the natural resources of the tropical forests, large coastal areas of Gabon are covered by mangrove forests, an ecosystem of particular importance for the diversity of marine and land fauna and flora. Together with the tropical forests, which are normally exploited by clear-cuttings, mangrove forests play an important role in the stability of the global climate. Pressure on this ecosystem has recently increased through the growth in shrimp farming, which uses the coastal zones for their cultivation and for which the mangrove forest has to be destroyed.
In order to ensure a sustainable development of the mangroves by reducing the effect of "wild cutting", a permanent mangrove forest surveillance system could be envisaged. Such a system would also provide the opportunity to regularly update the cartographic maps of the country (or at least the sensitive coastal regions).
The next ERS-SAR image (image 22) was acquired on July 28, 1994 over an area to the south of Libreville.
The river estuary (upper left) appearing in black is that of the river Ogooué. The white area along the river can clearly be identified as mangrove forest. The black spots in the lower part correspond to lakes, one of which is lake Azingo. The grey area, covering almost the whole image, is tropical forest.
Image 22: ERS-SAR scene acquired on July 28, 1994 region in
the south of Libreville, Gabon
A further subset (image 23) shows more details of the mangrove forest, the boundaries of which can easily be detected and mapped. The hydrological network can also be seen and mapped in detail. For this cartographic approach, a scale of 1:50,000 is sufficient. In order to test the consistency of the detectability of mangrove forests, a second image was interpreted, acquired on August 14, 1994. This subset (image 24) showing the border region between Gabon and Equatorial Guinea shows the same results.
Image 23: Subset - ERS-SAR for mangrove mapping (processed
with an 8 x 8 pixels moving average filter)
The mangrove forest is easy to detect and map as a white area. In this case, the forest around the estuary of the rivers Noya and Temponi is more oriented towards the land surface. The grey areas in the estuary correspond to a coverage of reed which might, in some cases, hinder ship traffic. Image 25 gives an overview of the northern coast of Gabon. One can see the estuary/mangrove area already shown in image 24. In the southern part, another mangrove forest is visible which is close to the capital of Gabon, Libreville, which borders the ocean and appears as a white area. The black line above Libreville is the airport. Light grey areas, covering the majority of the land surface, correspond to tropical forests.
Image 24: ERS-SAR subset (filtered) at the border between
Equatorial Guinea and Gabon
Image 25: Overview scene acquired on August 14, 1994
(Libreville in the lower part)
Looking in more detail into the urban area of Libreville (image 26), one can clearly differentiate the airport to the upper left as well as a number of roads within the city.
However, the image also shows the limitations of ERS-SAR data for urban applications.The boundary of the urbanization can be identified but inside the city it is difficult to distinguish different subgroups. One can see a few towers (white crosses) and a zone with denser housing, but the data does not fully meet the needs of town planners. Oil terminals, visible in image 27, however, indicate the usefulness for regional planning. The distance of these terminals from housing areas might be important in the event of further development of this infrastructure, as well as for the planning of access roads. The white square visible in the southernmost part of the land surface probably corresponds to a lighthouse or a surveillance tower constructed for the guidance of ships entering the harbour area (white line left of the point). The images below have not been filtered in order to preserve the contours in urban areas, which tend to disappear during the average filtering process.
Image 26: Libreville
Image 27: Oil terminal south of Libreville
A further example over Gabon once again clearly indicates the usefulness of ERS-SAR data for regional cartography. Images 28 and 29 are from east of the estuary shown in image 22. In the very upper left of the image a bridge is visible as a white line crossing the river. When looking in detail at image 22 one can see that this is the only bridge that crosses the river for the next 20 km. A road runs parallel to the mountain chain to the south. On image 29 this road is visible as red line.
Image 28: ERS subset
Image 29: Simple cartographic interpretation of road network
The visible interpretation of these two images over Gabon provides a clear demonstration of the usefulness of ERS-SAR data for cartographic purposes on regional or national levels. The SAR sensor could equally demonstrate its unique capabilities for the detection of mangrove forests in coastal zones and river estuaries. Specifically this unambigious identification of mangrove forests, which cannot be achieved with any optical sensor, should be further exploited in an operational system for mangrove management. The example of Libreville shows the limits of the SAR for local (urban) planning. The current and expected future maximum resolution of this type of sensor means that it can only be used to identify trends for urban developments.
SP-1199