Farmers' knowledge and GIS

Corazon M. Lawas
Henk A. Luning


Indigenous knowledge has become an important and a valuable input in the planning and decision making related to the sustainable management of natural resources. This article presents a method of collecting genuine information from indigenous farmers and using a computer system to store important spatial and geographic information. The retrieval and quantification of such indigenous information by means of a GIS maximizes the usefulness of the data. The GIS also makes it possible to create, analyze and process scenarios, using the information stored in the computer. Moreover, it approaches the rationality and validity of the farmers' knowledge by relating their conception of elevation to the intensity of their cropping practices.

Introduction
It is generally recognized that indigenous knowledge plays an important role in the sustainable management of natural resources. This recognition is directly related to the growing realization that scientific knowledge has not contributed to the development of communities and societies, but rather has led to the depletion of their social and natural resources (Murdoch and Clark, 1994; Norgaard, 1992; FAO, 1990; Ulluwishewa, 1993).

The collection of information from diverse indigenous sources is often a laborious, time-consuming and costly process. Proper storage and management must be ensured, if the information is to be made available and accessible for quick analysis and manipulation to all those who need it, e.g., planners and decision makers involved in the management of land resources.

The GIS, or geographic information system, is capable of performing these functions and is widely used in the management of information for planning and decision making purposes. There are important spatial aspects to indigenous knowledge. However, up until now the possible application of GIS in IK management has been underexplored. The present article focuses on the implementation of farmers' knowledge (FK) by means of a GIS, demonstrating that such a system can facilitate the management of indigenous information and enhance its usefulness.

Indigenous knowledge in sustainable development
There is general agreement that the concepts 'indigenous knowledge' (IK), 'traditional knowledge', 'local knowledge', 'community knowledge' and 'rural peoples' knowledge' are all terms for knowledge belonging to grassroots people. While certain distinctions can be made, these terms often refer to the same thing (see, for example, Mathias, 1994; Warren, 1992; Reijntjes et al., 1992; Howes and Chambers, 1979; Roach, 1994). The term 'farmers' knowledge' (FK) will be used here, because it refers specifically to the type of knowledge that the farmers have in the area of research. In our view, the term 'indigenous knowledge' denotes a type of knowledge that has evolved within the community and has been passed on from one generation to another. In the area of research farmers' knowledge, which they have been putting into practice for decades, encompasses not only IK, but also scientific and other knowledge gained from foreigners. Some of the farmers' knowledge has resulted from experimentation and the observation of their environment. Since many people use IK as a more or less standard term for grassroots peoples' knowledge, it will be adopted in our discussion of sustainable development. The concept 'farmers' knowledge', meanwhile, will be used when we are talking about the research itself.

Sustainable development involves producing goods for the needs of the present generation, while at the same time conserving resources in order to ensure continuous production in the future (FAO, 1993). Many authors, such as Mathias (1994), Labatut and Akhtar (1992) and Warren (1992), have stressed the value of indigenous knowledge for development. But indigenous knowledge has its limitations (Bebbington, 1993; Bonds, 1991, Reijntjes et al., 1992; Leach and Mearns, 1988), and is not in itself capable of addressing all the issues related to sustainable development (Murdoch and Clark, 1994). Sustainable development may well be better served by a system which incorporates both indigenous and scientific knowledge systems (Icamina, 1993). Organizations like the IUCN (1980) and the WCDE (1987) also stress that the sustainable management of natural resources can only be achieved by developing a science based on the priorities of local people, and creating a technological base that includes both traditional and modern approaches to problem-solving (Johnson 1992, as quoted by Labatut and Akhtar 1992).

Incorporating indigenous and scientific knowledge means integrating information collected from farmers with scientific information and technology. This means that we must find a way to process indigenous information in the same way as scientific information. This is the subject of the present article. Geographic information technology**1 is used to address the problems associated with the storage, analysis and processing of indigenous information. It is also employed in the integration of the two types of information, which is a major theme of the current research. As we have seen, such a process is useful in planning and decision making for the sustainable management of resources.

Geographic information technology
GIS is seen as an essential instrument in the effective use of geographic information, whether for planning, decision making or forecasting. It has three components:

Thus a GIS can be defined as a collection of instruments for the collection, storage, retrieval, display and analysis of spatially referenced data (Aronoff, 1989; Bonham-Carter, 1995; Huxhold and Levinsohn, 1995).

A GIS has four major features:

Before making use of a GIS, one must first decide how the real situation is to be represented (modelled). A GIS uses two approaches in conceptualizing a real-world situation, namely, field-based and object-based. The field-based approach conceptualizes 'reality' as a non-empty space composed of a tiling of area units in which thematic data are recorded for each unit. The object-based concept views 'reality' as an empty space filled with individual terrain objects (Ehlers et al., 1989; Goodchild, 1992, as cited by Kufoniyi, 1995). In a geometric representation, two different methods are commonly employed. The first is 'tessellation', in which geographic space is partitioned into regular cells; each cell is characterized by the area it covers and one or more values which describe non-spatial properties of the cells. The second is 'vector', in which a terrain object is predefined and its location measured (Peuquet, 1990; Kufoniyi, 1995).
A GIS requires a spatial database representing the terrain situation as seen by an application. Such a database is usually the result of four levels of data abstraction (Peuquet, 1990): Research
This article is based in part on the current research project of Corazon M. Lawas entitled 'Integrating established knowledge and the knowledge of resource users for purposes of land resource management'. The primary aim of the project is to contribute to the existing body of knowledge on how land can be appropriately managed, while acknowledging the importance of the knowledge of resource users, and integrating it with established--scientific--knowledge. The present article is an output of one of the project's specific objectives: to identify and analyze user knowledge and to find a procedure for quantifying and storing that knowledge in a system which allows quick analysis and processing. It also presents a method of collecting genuine information from indigenous farmers.

The project was set up among the Kankana-ey farmers in the municipality of Buguias, Benguet province, Northern Luzon, the Philippines. These farmers have their own dialect known as 'kankana-ey', which distinguishes them from other groups in the province. The project started in October 1993 and is expected to be completed early in 1997.

For the collection of primary data, a number of different data acquisition techniques were used, such as rapid rural appraisal (RRA), village immersion, the farmer-based interview schedule, field visits and observations, and the use of a checklist of questions, analog maps and aerial photographs. Such integrated techniques of data retrieval have proved efficient in obtaining genuine information from the farmers. Each technique was selected for a particular purpose. For example, aerial photographs enabled farmers to identify their own fields and to explain the previous use of specific areas of land. This made them more interested and cooperative during the visits and interviews. Although village immersion was essential in obtaining the support of the farmers during the conduct of RRA, farmers were often suspicious and reluctant to talk. Since they are always busy in their own fields, the farmer-based interview schedule was adopted to encourage them to cooperate.

The types of secondary information collected included data obtained by remote sensing, analog maps, aerial photographs, and published and unpublished reports and documents. For this particular paper, topographic and land management unit maps were used to articulate farmers' knowledge in a spatial and graphical form.

The concepts elaborated above were adopted in the present research. Here, 'reality' incorporates farmers' own field utilization system (FUS), including the techniques and practices they employ in utilizing and managing their fields. Specifically, FUS covers their knowledge of cropping methods, cropping patterns, the cropping calendar, cropping intensity and cultivation techniques such as land preparation, planting and irrigation. The relationship between FUS and the farmers' perception of such natural factors as climate, elevation, etc. was also examined. This reality was modelled using the field- based approach, in which area units were predefined as land management units (LMUs), and attribute data attached to each unit. Thus geometric data were represented using a 'tessellation' data model. The thematic or attribute data of the area units (LMUs) were organized according to a relational data structure. Here data are stored as a collection of values, in the form of simple records referred to as 'tuples.' Each tuple represents a fact (a set of permanently related values); they are grouped together in two-dimensional tables, also known as relations. Each table represents the various relationships between all the attributes it contains (Aronoff, 1989; Bonham-Carter, 1994). Our implementation was based on the so-called dual-architecture or geo-relational database concept which is part of GIS implementation.

The GIS software used was the Integrated Land and Water Information System (ILWIS), developed by the International Institute for Aerospace Survey and Earth Sciences (ITC) in Enschedé (the Netherlands). ILWIS integrates image processing and spatial analysis capabilities, tabular databases, and conventional GIS characteristics (ITC, 1993). It supports both vector and tessellation data structures, as well as a tabular attribute data structure. The use of ILWIS meant that our attribute data, organized in DBaseIV (a relational database management system), had to be exported to its database management tool 'Tabcalc' (Gorte et al., 1990), which is similar to a relational database. ILWIS is continuously updated to meet the changing requirements of the users.

Results
First the data model was translated into a data structure, which was then mapped onto the basic structure of the chosen GIS, i.e., ILWIS. To take an example, the farmers' knowledge of elevation and cropping intensity was selected, and using ILWIS we were able to present this knowledge in digital form.
The farmers recognize three classifications of elevation:

The farmers were asked to identify the areas belonging to each of these categories of elevation zones. Then the equivalent elevation in meters was identified, using the topographic map of the area. This facilitated the transformation of the farmers' knowledge of elevation into a digital form.
With respect to cropping intensity, the farmers' practice can be classified as follows: The farmers in the research area grow mainly potatoes, carrots and leafy vegetables such as cabbage, Chinese cabbage and lettuce. This classification of the farmers' cropping intensity was attached to each land management unit (LMU), and cropping intensity was treated as an attribute of the LMUs.

Using ILWIS, digital maps were created for each factors (elevation and cropping intensity). The two maps were then laid over one another, in order to assess the relationship between the two variables {[a href="#table1"]}(see table 1){[/a]}. This resulted in the relationship units R1, R2, etc. In principle, there should have been nine such units, but because cropping intensity 'one to two times a year' does not exist in elevation zones dagdag and nalamag, there were only seven units.

{[a href="#table1"]}Table 1 {[/a]}shows the differences between the relationship units in terms of surface area (in hectares). The results indicate a general correlation between elevation and cropping intensity, which is broadly in accordance with the farmers' statement that their practices vary according to elevation. There are, however, exceptions, as in the case of fields located close to the creeks in the upland areas, which makes possible the same cropping intensity as in lower elevation zones (e.g. R2, R4, and R5). The relationship units R2, R4 and R5 stand for a cropping intensity of two to four times a year, normally practised in dagdag and nalamag areas. During our interviews with the farmers, and our visits and observations in the three elevation zones, we found that two major reasons for such differences in cropping intensity are the availability of water and distance; the latter is particularly important when it comes to bringing in farm inputs like chicken dung, and getting produce to market. The results also show that it is possible to quantify farmers' knowledge by applying geographic information technology.

Conclusion
Farmers' knowledge can be quantified and systematically organized by means of a GIS. This approach maximizes the utility of indigenous information for development, since it can be shared by a number of users. These users include natural resource managers, project or development planners, and decision makers or people with a particular interest in indigenous knowledge functions. Moreover, there is a greater likelihood that information stored in a GIS environment will actually be shared, since it can be easily accessed and analyzed. Moreover, comparisons can be made and scenarios created on the basis of the information stored in the system.

Although only two variables (FK on elevation and cropping intensity) are dealt with here, by way of illustration, the same approach can be used to correlate all the variables of the FUS mentioned above. It can also be adopted in the same type of application elsewhere.

In planning and decision making exercises directed towards the sustainable management of natural resources, it is essential that the various types of information relating to a particular area of concern are available. As indigenous information is acknowledged to be a valuable input in those exercises, it must be available and accessible at all times. GIS technology makes this possible. It can provide spatial and non-spatial information which facilitates both planning and decision making aimed at the sustainable management of natural resources. Another benefit of GIS is the fact that it can narrow the information gap between professionals and resource users by making such indigenous information transparent and accessible. This is in effect an essential condition for achieving any development goal.

While the use of a GIS may initially be costly, it is important to consider the accessibility to data which it offers, and the many other advantages to be gained from indigenous information. Today more and more people are recognizing and promoting the importance of indigenous knowledge for purposes of sustainable development. Such knowledge is a valuable resource and requires proper management. What we need now is the means to properly store such information, so that it can be processed, analyzed and disseminated, thus maximizing its usefulness. As GIS software development continues, products are becoming increasingly affordable and thus accessible to more and more people.

Furthermore, the above results suggest that, like established- -scientific--knowledge, farmers' knowledge is valid and rational, which makes it a valuable input in the design of resource management activities. We are also justified in seeing these results as a corroboration of the view of Howes (1979) that 'localised indigenous knowledge may also provide the basis for the preliminary formulation of hypotheses which may then be referred "upwards" for refinement and specific testing.'


Corazon M. Lawas
Department of Land Resources and Urban Studies
International Institute for Aerospace Survey and Earth Sciences
P.O. Box 6
7500 AA Enschede
The Netherlands
Tel: +31-53-4874444
E-mail: lawas@itc.nl

Henk A. Luning
Faculty of Geographical Sciences
University of Utrecht
P.O. Box 80115
3508 TC Utrecht
The Netherlands


Acknowledgement

The authors would like to thank Dr O. Kufoniyi for commenting on this article.


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Endnote
**1 In this article geographic information technology is synonymous with geographic information system (GIS).


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