The geologist try to understand relationship between soil erosion observed and natural landscape structure. Erosion can
effectively appears in the vicinity of linear or planar structures of soil (lines, faults or materials change). Once eroded
areas are mapped, an inventory of relief linear shapes is done. The crossing geomorphological analysis with other
environmental parameters allows to predict the becoming eroded areas. Lineaments detection is usually made by photointerpretation.
DEM (Digital Elevation Model) visual analysis is another alternative but not sufficient, so it uses the
derived models from DEM called hillshade images. The DEM is lighted up by a virtual source with a direction and
height incidence. A good study require a complete lightings visual interpretation which is very slow and subjective. This
paper propose an automatic process that help geologist to detect and analyse the geomorphological structures present in
the landscape by using image analysis methods. This study focus on lines and catchments basins structures. First a new
watershed and catchments basins segmentation method is developed it defines an attractive structure between pixels
(based on path of steepest slope). After these lines are automatically extracted by Hough transform and their preferential
direction is analysed by a technique called directions rose. Some results are given on DEM and Hillshade images for a
particular areas of the main New Caledonia island where soil erosion is a serious problem mainly due to tropical weather
(violent rains) and human activities (mining, bush fire) on the weathered rocks (laterites) in mountain.
The management of small Pacific coastal territories has become a crucial issue; these are insular units that often display a
high level of biodiversity in a context of changing climate and
sea-level rise. In order to preserve and protect
populations, infrastructure and living resources, there is a need to understand inland processes that may influence the
behaviour of coastal systems and, more particularly, active erosion zones. Cartography of stripped surfaces by remote
sensing has become routine and we propose here the first step of a method that aims to monitor erosion features using an
automated process. Managing catastrophic erosion and/or landslides needs high frequency image acquisition so as to
optimize hazard prevention.
On the basis of a single remote sensing map, we propose a generic method for automatically assigning expert-designed
labels to erosion areas. Our automated process follows three steps: first, we use classical algorithms to detect stripped
zones; second, we assign a label to each extracted zone using domain knowledge. Finally, as a post-processing phase,
detected and labelled erosion areas are checked by experts. This method has been validated in an erosion-sensitive area
of south-eastern New Caledonia.
The image segmentation is the process which permits the image to be partitioned in zones of interest corresponding to scene objects. We propose two algorithms based on the mathematical pretopology and the structuring functions for detecting crests lines in a grey level image at a very high definition. The first algorithm is based on a method of grouping by relaxing propagation on the definition of a pretopological structure on the set to be classified. The second algorithm consists of grouping by extraction of a new pretopology from the one defined initially. It directly detects the crests lines, whereas the first makes it in an indirect way. These methods were tested on a SPOT panchromatic image on the region of Oran. From the results, we could conclude that these methods can be very well be embedded to a process of detection of roads, iron-shod ways, and water courses.
We aim in this paper to propose a new process for the extreme lines detection based on the pretopological model. We set a new algorithm to analyze images of lines (images of the third type), it partly uses the principle of functioning of clustering algorithms proposed by H. Emptoz in his thesis, but has a different `philosophy' to interpret the results.
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