Keywords: Agent, GIS, Land Use and Land Cover, Model,
Abstract: AGENT-LUC, Anthropogenically Engineered Transformation of Land Use and Land Cover Model, is a national scale model, that allows for dynamics time-series simulation and analysis of the changes brought about in the land use by the action of humans within the boundaries of the natural terrestrial earth system. The model deals with the application of the concept of "agent" as the decision-maker in simulating the land use/ land cover changes. The agent decides on the next course of action based on the information available to him from both the worlds of micro and macro-information. The bio-physical characteristics of the land is considered along with its economic condition, given the social apparatus at a given point in time, in arriving at the choice of the land use. The entire process is carried out on a grid-by-grid basis, and is aggregated at the different scales to analyze and the results compared with the prevailing macro-condition. This kind of bottom-up approach with inter-scale aggregations help to develop more realistic scenario of the land use changes. The use of GIS platform and its tools has helped in analyzing the micro-information (spatial) within the boundaries of the available macro-level (non-spatial) data.
1. Introduction
Most of the global physical and biological models that have been developed for the understanding of the various parts of the global earth system, are dependent on the land use and land cover information, as these with their control on the albedo and water & nutrient cycling establish the boundary conditions to these models (Robinson, 1994). Land use/ land cover is continuously changing, both under the influence of humans and nature, resulting in various kinds of impacts on the ecosystem (Rajan, et. al., 1997a). These impacts at local, regional and global levels have the potential to significantly affect the sustainability of the world agricultural systems and the forest systems- the two major human life supporting systems. The most important factor in the modification of the land cover and its conversion is the human use component rather than the natural changes (Turner, et. al., 1993). Changes in the land cover cannot be understood without a better knowledge of the land use changes that drive them and their links to human causes. The linkages between the human and biophysical causes or drivers to land management and land cover are not sufficiently understood (Rajan et. a., 1997b). This arises from the complexity in dealing with the considerable variations in the land use drivers; land use and land cover at the various levels-local, national and regional.
At present, the global models and studies of land use changes capture the broad sectoral trend based on the changes in some of the macro variables, like population, quality of life and technology level. The statistical data shows a strong support in concluding that these variables may be the underlying drivers of environmental changes (Bilsborrow et. al., 1992). On the other hand, such statistical relationship do not hold good for long-term analysis if the trends are dominated more by policy options, like export oriented agricultural production of cassava, and not by the inherent needs of the population, as seen in Fig. 1 , for Thailand. Around 10% of the Cassava produced is consumed domestically, while the rest is mainly for export markets.
Land use can be looked upon as a multi-dimensional (
³4D) process, which consequently poses many difficulties for proper description and classification. In the context of global change, the formal characteristics of land use. i.e. its effect on cover structure, phenology and composition, is more relevant than the purpose of function of landuse (Veldkamp et. al., 1996). But, unless the function is properly understood, it is difficult to amalgamate the land use conditions into the processes that drive the changes in land use and land cover. Most of the changes are highly dependent on the biophysical constraints of the land units and the human understandings of these. The model should be able to simulate land use/land cover changes in response to both the biophysical constraints - existing and the changes within, and the socio-economic conditions prevailing at a given point of time. The socio-economic factors like the population, economic, conditions, educational levels etc. are the human drivers that have to be considered in such a model. It is recognized that changes in the scale of analysis, changes the results. As such, it is necessary to consider the feedback effects in such models, as these feedbacks also act as causes or drivers at different scales of analysis and interpretation should be taken into account.
Fig 1 Cassava Production and Population distribution in Thailand for the period 1961 to 1991.
Here, in this paper we describe a new concept that can be used to effectively model the macro-characteristics that describe the landuse along with the known macro-variables that also influence such changes. First, we describe the general concept and principles and issue of the new concept developed by us. Also, its applicability will be discussed within the framework of developing a land use/cover change model at the national level.
2. AGENT-LUC Model
2.1 Concepts and Principles
Land evaluation and suitability has long used the biophysical factors like climate and soil as its determining factors. (FAO, 1978) but the influence of human factors are not so well studies and described. Also, there exists considerable gap between the potential suitability of a given area to its actual productivity. Recent advances in modeling crop-yields based on their phenology have yielded better results, though the majority of them are point/location-specific.
In order to model land use/cover changes under the assumption that its function is influenced by the prevailing economic conditions at a given place and time, it is necessary to evaluate or estimate the scenario that closely resembles reality. The human ability to comprehend and anticipate (with a limited risk) needs to be considered in deriving land use/cover changes. The model proposed here deals with the development and application of a new concept, proposed by the authors, in simulating the land use/cover changes-the presence of an agent as the decision-maker. The agent decides on the next course of action based on the information available to him from both the worlds of macro information. The decision making process takes into consideration the prevailing bio-physical characteristics of the land, the economic condition, and the land use history along with the existing social apparatus in a given year, for arriving at the choice of the annual land use.
Concept of an agent
Here, the term agent refers to an individual or a group of individuals who exist in a given area (referred to as grid) and are capable of making decisions for themselves (or the given area). The agent also acts as an interface in helping to assimilate the broader macro-information into the decision-making process at the grid level, thereby creating an action in response to the natural and economic stimuli.
World of Micro and Macro Information
In this paper, the term 'micro' refers to the data used at the grid level in assessing the supportability of each grid. The crop-specific productivity is calculated at the grid-level, considering the local bio-physical characteristics. The bio-physical attributes considered here, are the climate (temperature, rain and radiation) and soil properties, along with water and nutrient stresses to agricultural productivity.
The 'world of macro' information refers to the data at the sub-national (regional or provincial) or national level. This data is mainly statistical in nature. It is used to compare and adjust the model simulations, to arrive at realistic cause-effect relationship within the model. The macro-data considered are total agricultural demand and supply in a given year, the GNP per capita changes, the contribution of the agricultural and non-agricultural sectors to GNP, and population distributions at the National and sub-national levels.
Additional Information Used
In addition to the above data, the experience of different researchers in arriving at qualitative conclusions on the land use practices in the difference regions of the study area are also considered in charting out the behavioral patterns of the agents.
