Geographical information systems as a tool to explore land characteristics and land use : with reference to Costa Rica

An adequate inventory of land characteristics and land use is increasingly necessary to support agricultural land use planning, especially in view of the conflicting demands on scarce land resources. Fortunately new tools like GIS are being developed and adapted to support these inventories. Although GIS may be a useful tool for the storage and management of spatial data, its development is often "technology driven" and not directly focused on the applications. This thesis presents approaches to use GIS in the inventory and analysis of land characteristics and land use. The approaches are explored and illustrated for the perhumid tropical lowlands in the northeast of Costa Rica. More detailed studies are focused on the Neguev settlement located in these lowlands.In Chapter 2, a procedure is formulated to develop and select database structures for soil survey data. The procedure is based on a five step approach in which i) a data model is developed for the soil survey data, ii) alternative database structures are created, iii) possible queries are analyzed, iv) the efficiency of the database structures is evaluated on the basis of quantitative indicators, and v) the most appropriate database structure is selected. Applications are not always based on queries only. Therefore, the structure of the soil survey database is tested on the basis of a practical application: possible modelling approaches to deal with biocide leaching on the basis of the soil survey data. Biocide leaching is one of the main environmental problems in the Northern Atlantic Zone. A best possible assessment of the severity of the problem, from different perspectives, is needed for the various stakeholders. For the Atlantic Zone, one of the few readily available data sets comprises the soil survey data. To deal efficiently with the different approaches of users, the proposed soil information system needs to provide data at different levels of detail. Therefore, a rule base is developed for each of the hierarchical levels (mapping units, pedons, and soil horizons). The rule base includes decision rules for the generalization of data at a specific hierarchical level. Although aside from soil survey data, additional measurements may be necessary for many applications, soil survey data are useful to screen for potential risk areas and to select sites where additional measurements are most effective.Typically, the analysis of land use at a regional scale should be focused on its changes over time, but this is rarely done in a systematic way. In Chapter 3, the use of GIS to quantitatively describe land use dynamics is explored. Three different indicators for land use dynamics have been developed. The indicators include a singletime approach based on qualitative knowledge of the colonization history, Markov chains with soil type as a probability modifier, and Markov chains with a geographical analysis to stratify for polygon size, shape and neighbouring land covers.Often, users of GIS require very specific, disciplinary operations on geo-information that are not supported by GIS. These operations can be made available to the GIS through links with external models. In Chapter 4, structures and examples are given to link GIS with models dealing with the sustainability of agricultural production. A general structure for the GIS-model interface is presented and identifies six consecutive steps: i) geometry operations, ii) attribute operations, iii) data export from the GIS to the external model, iv) model run, v) data import from the model into the GIS, and, vi) visualisation or spatial analysis of the model results with the GIS. This structure is illustrated for a case study where a GIS is linked with a LP model for the analysis of alternative land use scenarios. The structure can be operationalized, using the abilities of many commercial software packages to develop user oriented applications.To explore the possibilities to reduce soil nutrient depletion in a settlement area, a GIS was linked with a model estimating soil nutrient depletion for land use systems and a LP model. The distribution of land use over different land units can be optimized with the LP model to minimize soil nutrient depletion in the settlement. This technique explores the geographical distribution of land utilization types to create a more sustainable basis for agriculture in the area. In contrast with traditional land use planning where land utilization types are matched with land units on the basis of maximizing present agricultural production, this approach focuses on long-term effects of land use and sustainability.To explore the trade offs between sustainability and economic objectives, different models and tools were integrated for the analysis of different land use scenarios for the Neguev settlement. Crop growth simulation and expert systems were used to describe alternative land use systems. A GIS was used for data storage, and the analysis and presentation of results. The optimization of land use was carried out by a LP model. Using a series of relevant land use scenarios, effects are studied of: (i) restrictions on biocide use; (ii) nutrient depletion as a negative contribution to farm income, and (iii) changes in capital availability. For the integration of models and tools, a modular approach is proposed, which is based on separate software packages and appropriate database structures. The methodology is particularly appropriate for interdisciplinary research, integrating socio-economic and agro-ecological data.In Chapter 5, the use of GIS databases and data needs for the analysis of land use and its sustainability is studied. Externally, land use can be affected by incentives and regulations. Data needs are studied and discussed for the analysis of regional production possibilities of maize, an analysis of sustainability indicators, and the possible contamination of ground and surface water with the commonly used nematicide Ethoprop. The different cases vary in their complexity and the level of detail required for the results. Data requirements change correspondingly. General inventories may already indicate which type of data collection is useful. Studies with a low level of detail must precede more detailed studies, while complex detailed studies could benefit from a change of scale, associated with a more generalized representation of data.Future challenges to incorporate the use of GIS in both disciplinary and interdisciplinary methodologies are recognized. This will require an integrated development of both GIS technology and applications. The ultimate challenge remains applying the proposed techniques to support the increasing demand for agricultural products and at the same time safeguarding the sustainability of the production and natural resources.