An integrated agro-economic and agro-ecological framework for land use planning and policy analysis

The growing concern about land resource management and the associated decline in land qualities, has led to the realisation that land use planning and policy problems cannot be addressed adequately through a single discipline. This awareness has resulted in renewed attention for integrated, interdisciplinary approaches. It is argued that such an integrated, interdisciplinary approach to problems of land use planning and policy analysis is specifically hampered by lack of an adequate methodology. Although the limitation is increasingly recognised in the various disciplines, relatively little attention has been paid to the question of how to integrate agro-ecological and socio-economic aspects of land use. The study reported here, contributes to development and operationalisation of a land use planning and policy analysis methodology that integrates agro-ecological and agro-economic information in such a way that land use policy options at sub-regional level can be formulated and evaluated with the aim of aiding policy makers.The study starts with a critical review of the current state of the formal tools of land use planning with particular emphasis on their strengths and weaknesses to integrating bio-physical and socio-economic analysis, stating a need for an alternative integrated methodology, with due recognition of the obstacles and challenges this involves. After a thorough literature search, conceptual and methodological challenges that stand in the way of integration are analysed and described. The basic structure of the framework to a methodology for integrating bio-physical and socio-economic analysis in land use planning and policy analysis is developed and outlined.The integrated framework derives its conceptual foundation largely from an adaptation of the theory of economic policy of agricultural sector analysis, the systems analytic approach, and the concepts of regional planning, to land use planning and policy analysis. The procedure of building the methodological framework is structured in a set of interrelated blocks (sub-frameworks). Each sub-framework of the methodology actually contains a number of steps, and requires a number of tools and/or methods for its operationalisation. The sub-frameworks of the methodology are further developed and operationaliesd for a case of Amol sub-region in Iran.After an identification of limitations of existing farm classification procedures, an alternative methodology is developed and outlined. The main purpose for farm classification methodology is to reduce aggregation errors, while integrating farm level with aggregate level of analysis. The methodology combines various clustering methods and proximity measures to group farms on the basis of operational parameters that reflect conditions necessary for exact aggregation. The methodology builds a step-by-step search procedure through a set of possible classifications to identify one that fits the purpose reasonably well. The methodology is illustrated for Amol Township. It allows generating and testing alternative classifications each with different resultant farm types.The study argues that land has a very strong socio-economic components that are not dealt with in the land unit concept and, therefore, a more integrated unit is defined. For this purpose the concept of "farm type land unit (FTLU)" is introduced. A FTLU is considered to be a farm type's share in a particular land unit or, alternatively, a land unit share in a particular farm type. The concept of FTLU is operationalised by establishing a (partial) link between geographic information system (GIS) and classification models. This link allows mapping of farm types and then linking them spatially with land units.An integrated approach to definition and description of land use systems, and quantification of their input and output coefficients is presented. The approach presented here considers land use systems as integral systems that include both bio-physical and socio-economic components. The concept ILUS is proposed for a specific form of describing a land use system. The term ILUS is defined as a unique combination of a farm type land unit (FTLU), a land use type (LUT), and a production technique. ILUSs are described in terms of operation sequences. Such a description then serves as a basis for the calculation of the required input-output coefficients. Each unique operation sequence within a ILUS can be interpreted as a specific (land use) activity. Each activity is defined and described quantitatively in terms of input and output coefficients which quantify the relation between inputs of production and the outputs, desired as well as undesired.Information on bio-physical and socio-economic components of land use systems is then confronted in an integrated land use planning and policy analysis (ILUPPA) model. The linear programming model. ILUPPA is a mathematical programming model in terms of solution technique, however, it is best described as a behavioural simulation model. It attempts to describe how farmers will react to certain classes of policy instruments that may influence their land allocation decisions. ILUPPA generates alternative land use policy options through the definition and description of various land use policy scenarios, corresponding to various policy instruments.Because the purpose of the model is to generate sustainable land use policy options, various land use scenarios corresponding to different policy instruments are defined. On the basis of these scenarios, the model generates a number of feasible land use policy alternatives with their associated ILUSs and corresponding input and output coefficients. A multi-criteria evaluation technique is applied to rank the set of alternative land use policy scenarios, and hence to assist policy makers in selecting the "best" or the most preferred land use alternative or to facilitate a movement towards a consensus. To take into account the multiple and conflicting views, various preferences or priorities are included in the evaluation.The rankings of the various policy scenarios, from different policy perspectives, are presented. Results show, that, for the specific situation of Amol sub-region and under the assumed policy views: non-price policy instruments are more effective in bringing about the desired changes and in achieving policy objectives;when more priority is given to environmental protection, the present situation, as reflected by the base scenario, is ranked most unfavourable; and the 'land consolidation' scenario is a good compromise among the different policy views.In conclusion, the proposed methodology proves to considerably reduce the aggregation errors when compared to the existing modelling approaches in land use planning and policy analysis and is therefore expected to make a significantly positive contribution to improved quality of agricultural planning and policy analysis. Some degree of aggregation is, of course, inevitable to facilitate modelling and to restrict the costs of the analysis to 'reasonable' levels. Implementation of the proposed methodology requires a large database and the gains in precision of the analysis must be balanced against the higher costs of developing and implementing the methodology