Computerised land evaluation systems

The Automated Land Evaluation System-ALES (Rossiter and Van Wambeke, 1997) is a computer program that allows land evaluators to build their own expert systems to evaluate land according to the FAO framework for land evaluation (FAO, 1976). ALES is a framework within which evaluators can input their own knowledge for use in local projects or regional scale land evaluation, taking into account local conditions and objectives. The administrative entities evaluated by ALES are map units, which may be defined either broadly, such as in reconnaissance surveys and general feasibility studies, or narrowly, such as in detailed resource surveys and farm-scale planning. Since each expert system is built by a different evaluator to satisfy local needs, there is no fixed list of land use requirements by which land uses are evaluated, and no fixed list of land characteristics from which land qualities are inferred. Instead, these lists are determined by the evaluator to suit local conditions and objectives (http://www.css.cornell.edu/landeval/ales/alesprog.htm; FAO, 2007b, p. 10).

Basically, the ALES has seven components:

1. “a framework for a knowledge base describing proposed land uses, in both physical and economic terms;

2. a framework for a database describing the land areas to be evaluated;

3. an inference mechanism to relate these two, thereby computing the physical and economic suitability of a set of map units for a set of proposed land uses;

4. an explanation facility that allows model builders to understand and fine-tune their models;

5. a consultation mode that allows a casual user to query the system about one land use at a time;

6. a report generator (on-screen, to a printer, or to disk files); and

7. an import/export module that allows data to be exchanged with external databases, geographic information systems, and spread sheets. This includes the ALIDRIS interface to the IDRISI geographic information system as well as an interface to xBase (dBase III+) - format database files, including Attribute Tables in PC- Arc/Info” (http://www.css.cornell.edu/landeval/ales/alesprog.htm).

ALES is not a GIS tool and does not display maps. It, however, can analyse geographic land characteristics if map units are appropriately defined, and it can directly reclassify IDRISI maps or Arc/Info Attribute Tables with the same mapping unit legend as the ALES database.

Another computerised land evaluation system is called MicroLEIS. The MicroLEIS system (De la Rosa et al., 2004) was developed to assist specific types of decision- makers faced with specific agro-ecological problems. It was designed using a knowledge-based approach which incorporates a set of information tools, as presented in Figure 3.3. Each of these tools is directly linked to another, and custom applications can be carried out on a wide range of problems related to land productivity and land degradation. They are grouped into the following main modules: i) basic data warehousing, ii) land evaluation modelling, and iii) model application software. The land attributes used in MicroLEIS DSS correspond to the following three main groups: soil/site, climate, and crop/management (De la Rosa et al., 2004).

Recently, the MicroLEIS system was used to assess soil quality in Argentina (De la Rosa et al., 2008), and to design soil-specific agro-ecological strategies for sustainable land use in Spain (De la Rosa et al., 2009).

Figure 3.3: Conceptual design and component integration of the MicroLEIS DSS system Source: De la Rosa et al. (2004)

A system called sustainable options for land use (SOLUS) provides a framework for sub-regional land use analysis by quantifying biophysical and economic sustainability characteristics. The SOLUS framework was developed for land use analysis at the field to regional scales (Bouman et al., 1998). Bouman et al. (1999, p. 57) describe SOLUS as consisting of technical coefficient generators which are used to quantify inputs and outputs of production systems, a linear programming model that selects production systems by optimizing regional economic surplus, and a geographic information system. Biophysical and economic factors are integrated and various types of

User applications

Agricultural soil use planning and management Basic data warehousing

MDBm Farming database CDBm

Climate database Soil databaseSDBm

Land evaluation modelling

Land suitability/Land vulnerability-related -Qualitative approaches -Expert systems -Parametric systems -Statistical methods -Neural networks -Hybrid approaches -Optimisation tools

Model application software

knowledge, ranging from empirical expert judgment to deterministic process models are synthesized in a systems-analytical manner. Economic sustainability indicators include economic surplus and labour employment, and biophysical ones include soil nutrient balances (N, P and K), biocide use and its environmental impact, greenhouse gas emission and nitrogen leaching loss and volatilization. Land use scenarios can be implemented by varying properties of production inputs (e.g., prices), imposing sustainability restrictions in the optimization, and incorporating alternative production systems based on different technologies.

Another system called the Intelligent System for Land Evaluation (ISLE) automates the land evaluation process and graphically illustrates the results on digital maps (Tsoumakas and Vlahavas, 2001). ISLE is designed as a framework for integrating the functionality of a geographical information system with an expert system and consists of the following main features:

1. The front end, that provides the interface to the expert system, encapsulates the mapping objects, and provides the user interface;

2. The digital map and the geographical database of the land subject to evaluation; 3. The expert system, which is responsible for land evaluation.

Land evaluation and site investigation (LESI), are also systems for land evaluation. They are undertaken to determine the most suitable use of land in terms of planning or development (Bell, 2004). In the LESI process, the environmental impacts may have to be assessed, including geological hazards, mineral resources and the impacts of mining, water supply and hydro-geological conditions, soil resources and the ground condition of the disposal of waste. An investigation in relation to land use planning and development obviously can take place at various scales, from specific site to regional investigation. A site investigation may form part of a feasibility study or be carried out to assess the suitability of a site and surroundings for a proposed engineering structure.

which is based on historical climatic data which is used to calculate potential crop production estimations. Using a statistical analysis of the results it is possible to identify the different potential yield levels which could be achieved by different crop production systems. The 75% quartile yield represents the annual potential yield level which can be expected to be exceeded 75% of the time. This yield level corresponds to the dependable yield, satisfying the yield requirements of farmers in the majority of years.

CYSLAMB is a tool for land use planning, which integrates knowledge about the heterogeneous livelihood strategies and the biophysical conditions at various spatial scales. Although the CYSLAMB model primarily reflects a farmer/farm-oriented approach, other levels within the stakeholder hierarchy are also considered indirectly through the management component of the model. By analysing the farmer’s access to resources (land, labour and capital) and the availability of technologies within the local setting, aspects influenced by other land management levels are considered. They include factors such as land tenure, marketing conditions and government support systems (Birch-Thomsen and Kristensen, 2005).

Further, information regards physical parameters or land characteristics, and a number of management-related variables reflecting the socio-economic conditions of the farmer are also included. Such as, date of ploughing and planting, number of planting opportunities used, date of weeding and percentage weed cover. The management variables can be adjusted to reflect differences in the farmers’ socio-economic conditions, such as the availability of household labour, sources of power, tools and fertilizer, income levels, non-agricultural incomes, and livestock-crop interactions. This facility makes CYSLAMB a flexible tool that can model crop production based on physical and socio-economic conditions at several levels, village to district and the national scale (FAO, 2007b). The application of CYSLAMB for determining the rain- fed arable production potential of climatically marginal land has been conducted by Mbatani (2000).

Thanks to the development of computer science, many computerised land evaluation systems have been generated. These systems effectively support land evaluation, giving

land evaluators opportunities to select and apply models in different situations. Using these computerised systems can lead to decreased costs, and more importantly, help time saving for the land evaluation procedure. Today, many computer programs are used widely as support tools for land evaluation. They can help to store, import, export, and analyse data during land evaluation, as well as to present the results of land evaluation. A Geographic Information System is a tool which can satisfy the above functions and it will now be described.