Multi-criteria evaluation is an important aspect of decision support operations, which appear in process models. Process models in the Earth sciences describe the evolution of geo(bio)physical surface properties in time, independently from remote sensing observations. Examples of such process models on various time scales are, for instance, numerical weather prediction models (NWPs), vegetation growth models, hydrological models, oceanographic models and climate models.
Observation models and process models can supplement each other to enhance the quality of the interpretation of remote sensing data and to fill gaps in time that occur when observations are not possible owing to clouds or some other cause. Interactions are possible between observation models and process models with EO data and existing geographic information (GIS and ground measurements, supplemented with decision-support systems (DSSs)).
The process model provides information to the decision-support system, which supports management actions aimed at controlling/mitigating the process, based on an multi-criteria evaluation. A good example of this is a water management system, in which one might decide to allocate water for irrigation if the observed vegetation appears to suffer from drought stress.