Currently, in many of the highly productive lowla nd areas of E and SE Asia a trend to further intensification and diversification of (agricultura l) land use can be observed. Growing economies and urbanization also increase the claims on land and water by non-a gricultural uses. As a result, decisions related to the management and planning of scarce resources become increasingl y complex. Technological innovations at the field/f arm level are needed but not sufficient - changes in resource use at regional scale will also be essential. To suppo rt decision- making in such situations, we advocate a multi-scal e modelling approach embedded in a solid participat ory process. To this end, the Integrated Resource Management and Land use Analysis (IRMLA) Project is developing an analytical framework and methods for resource use analysis and planning, for four sites in Asia. In th e envisaged multi-scale approach, integration of results from f ield, farm, district and provincial level analysis is based on Interactive multiple goal linear programming (), Fa rm Household Modelling (FHM), production ecological concepts and participatory techniques. The novel approach co mprises the following steps: (i) Inventory/quantifi cation of current land use systems, resource availability, ma nagement practices and policy views, (ii) Analysis of alternative, innovative land use systems/technologies, (iii) Exp loration of the opportunities and limitations to ch ange resource use at regional scale under alternative future scen arios, (iv) Modelling decision behavior of farmers and identification of feasible policy interventions, an d (v) Synthesis of results from farm to regional le vel for negotiation of the most promising options by a stakeholder plat form. In the current paper, the operationalization of a dual-scale approach is illustrated by the outputs (development scenarios, promising policy measures and innovativ e production systems) from various component models for the case study Ilocos Norte, Philippines. A procedure is di scussed for the integration of results from the different model components at two different decision making levels (farm and province).