nourishments are applied for sand nourishments (Roelse, 2002). 
(non-vegetated zones) and wetness index (dry zones). Altitudes 
1190 
  
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B4. Istanbul 2004 | Inte 
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as erosion, transport and sedimentation of sandy materials are In this study we focus on beach nourishments as their effects on | bet 
causing major changes along the north-western coast of the maintenance of the coastline are better known. | con: 
Ameland. | elev 
According to Dutch policy regulations, beach nourishments are zon 
170.000 194000 mg 2 carried out (1) if safety of the hinterland is at risk, (2) to | zone 
North Sca | 2 | safeguard dune objects, (3) to stimulate and manage beach zon« 
610.000 a | f | recreation, or (4) to reduce the loss of nature areas (Roelse, | Zero 
e pem qut. LS 2002). To calculate the required volume of sand, the expected | cons 
ons RT A erosion, the recurrence interval and the sand reserve have to be et. a 
so Wadden Sea AA determined. The sand reserve, i.e. the beach volume at time (t | 
is the most important variable and can be calculated from the | The 
dataset. Reference is made to the basal coastline, being the factc 
coastline position on | January 1990. The beach volume at com 
basal coastline is the standard for preservation of the coastline. inhe 
Beach nourishments are carried out when the beach volume at wetn 
actual coastline is below the volume at basal coastline. The attril 
actual beach volume can be calculated by multiplying the beach 
area, i.e. the area between the dune feet and the actual coastline, 
with the surface area. 
For beach management purposes, Rijkwaterstaat - the part of 
the Ministry of Public Works responsible for the maintenance 
of the coast - divide the beach area into compartments. Each 
compartment has two boundaries to its adjacent compartment 
(CL), a beach-sea boundary (BS) and a beach-dune boundary 
(BD). Rijskwaterstaat use these compartments to calculate sand 
volumes and treat them as crisp objects (Roelse, 2002). The 
interest of this application is to take into account the ‘fuzzy’ 
nature of objects, and their ‘dynamism’ in time. Hence, we 
propose to describe the boundaries between beach-sea and 
beach-dune as vague boundaries (Van de Vlag et al., 2004). 
Next, it is possible to calculate structural erosion per 
compartment, by plotting the beach volumes from before 1990 
against the beach volume with the basal coastline. A negative 
Figure 1: A landsat image (1999) from the north-western part of trendline indicates erosion, whereas a positive trendline | 
the Isle of Ameland. The white box shows the study indicates sedimentation. | 
area. The bottom part of the study area contains 
mainly dunes, the middle part is beach, the upper part Two constraints apply when deciding upon nourishment; first | 
is sea. constraint (Ci) is that a coast compartment shows structural | 
erosion, the second constraint (C5) is that the volume for beach 
The dataset for the Ameland case study consists of multi- nourishment should exceed 0.2 Mm*. Constraint Ca is a soft | ; 
temporal digital elevation models and satellite imagery. Each constraint, as nourishment may be carried out, depending on | Figure 
digital elevation model of Ameland is derived from the local and regional policies. | 
JARKUS data from the DONAR database (Eleveld, 1999). The | The s 
DONAR database contains annual beach and foredune profiles 2.3 Ontological Approach | be ES 
derived from stereometric analysis of aerial photographs for the aH 
dry part of the coastal transect. The underwater part of the The ontological approach chosen in this paper is to handle the | 
profile is measured with echosoundings from ships with underlying data management problem as an integration of both | 
automatic position-finding systems. The transects are 200 to data and semantics, within a common reasoning framework | C vc 
250 m apart and elevation is measured at S mintervals alonga (Jeansoulin and Wilson, 2002). The ontological approach | 
cross-shore line. From the point data, we interpolated the clarifies the structure of knowledge, and leads to coheren 
profiles towards a 30 m x 30 m grid. Satellite images are knowledge base. An ontology exists of objects, their attributes | where 
derived from LandsatS-TM and Landsat7-ETM+ satellites. and relationships (that may be time dependent), evens | Cat ti 
Landsat images contain pixels corresponding to 30 m x 30 m processes and states. Ontologies may enable knowledge shame | 
ground surface. and reuse for different domains or time intervals. For the | mi, 
> Ameland application, ontologies will be used as a common 
The beach objects are structured in compartments within a reasoning framework with different, yearly, time intervals. Y | where 
higher conceptual level, based on perceivable regions on the the Ameland case study, the spatio-temporal problem a wd 
beach. Compartments are the regions between two transects. defined as: T). How to localize and quantify beach areas pe | object 
require nourishment, and 2) How to assist the decision maker 10 | n 
2.2 Beach Nourishment manage the process of nourishment in time. ii s 
To counteract beach erosion, sand nourishments have to be Identification of areas that require beach nourishment depend | je | 
carried out. Either beach nourishments or underwater UPON terrain altitude (height around zero), vegetation index | Rm 0 
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