Alkema, Dinand 
  
Indicators 
A correct conceptual model can summarise a geomorphologic system. Once the link between the anthropic system and 
geomorphology is established, key-parameters can be identified that have a dual function: 1) they summarise the output 
of a specific part of the geomorphologic process; 2) they describe the interaction of a specific part of a geomorphologic 
process and human concerns. Key parameters that have such a dual function are called indicators. Lorenz, (1999): 
“Indicators describe the system or process such that they have significance beyond their face value; they aim to 
communicate information of the system or process; the dominant criterion behind an indicator’s specification is 
scientific knowledge and judgement”. Whenever geomorphologic processes with a certain intensity interact with human 
concerns, they are called hazards. Indicators are thus important parameters that on one hand give information on the 
hazard (like magnitude, frequency, spatial distribution, etc.) and on the other have additional importance because we 
can translate them into impact or risk if we know the sensitivity (or vulnerability) and value of the various elements of 
the anthropic system to these parameters. 
Identification of critical elements 
A development will interact with a geomorphologic system and this may lead to a change in the parameters of the 
indicators compared to the initial situation. Consequently, changes in indicators will result in change of impact and risk. 
The critical part is to identify a priori which elements within the geomorphologic system will be affected by a 
development. Cendrero (1991): geomorphologic risk and impact assessment must be based on the following four steps: 
identification and definition of the existing geomorphologic systems and land-units; 
determination of their descriptive parameters; 
evaluation of those morphologic features which are relevant for the individuation of hazards; 
identification of those morphologic features that represent assets. 
Model selection 
The critical elements of a geomorphologic system and their descriptive key-parameters (indicators) are identified that 
can be used to assess impact and risk. The next step is to quantify the interaction between a development and a 
geomorphologic element. Tools are required that allow to forecast the change in indicators due to the development. 
Fortunately in the last decades a lot of researches have been dedicated to get a better understanding of the characteristics 
of geomorphologic systems. Deterministic models would seem the more obvious choice as tools because of the physical 
explanation they give to the underlying deterministic cause-effects relations. Still some problems might not be suitable 
for such an approach, either because the interaction between different systems are not yet understood or are too 
complex, or because the studies require different spatial and temporal scales, or because the required data are not 
available or are insufficient. In some of these cases predictions can be made using statistical techniques like prediction 
models. (e.g. Chung and Fabbri 1996). 
Input data 
Once the objectives are defined and the tools are selected, a clear overview will arise of what input data are needed. 
In most cases the budget and timeframe put serious constraints on collecting new data so only old data can be used. 
These have to be put together into an integrated database. The fact that the data are retrieved from various sources will 
inevitably result in problems of scaling and unknown data quality. Another problem is that most data have been 
collected for a different purpose and have been elaborated for other goals. 
It is therefore important to get data that are as good as possible to make sure that overall data quality is maximised. 
The ideal conceptual model already indicates which data may be required. There are different types of data that could 
be integrated into a database to allow easy querying and data retrieval: 
fieldwork and field data; 
thematic maps: topographic maps, geologic maps, geomorphologic maps, land-use maps, ....; 
remotely sensed images: Aerophotos (black/white, colour, infra-red, multi-spectral) and Satellite images; 
temporal data: precipitation, river discharge, groundwater fluctuations, .....; 
historic events data: Occurrence of past events, magnitude, duration, spatial extend; 
geophysical and geo-technical data, .... 
Spatial data and temporal data 
Most spatial data have an inherent temporal component. Remote sensing images are snapshots of the area at a specific 
time and some thematic maps are valid only during a limited period due to the development and dynamics of the 
processes in the area. This put constraints on the elaboration because one should not use data retrieved from different 
time-periods in one analysis. When one can assume that one or more data-layers are not an accurate representation for 
  
56 International Archives of Photogrammetry and Remote Sensing. Vol. XXXIII, Part B7. Amsterdam 2000. 
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