Land Suitability

 

Methodology

In order to support PODB with a technical tool able to explore the potentiality of Pakistan territory concerning olive production, an information system able to deal with spatial data (Geographic Information System - GIS) was set up by the project. A GIS is a tool for organizing, storing, analyzing, displaying and reporting spatial information. It is made up of data, software tools, hardware and expertise that support a decision process.

The main objective of the information system was to produce thematic maps able to disclose the relevant information to choose areas productive for olive and to define a methodology and a set of data that can be used in the future to produce new useful information for olive policy planning. To get this result, an evaluation model based on a set of specific criteria was defined.

Data availability and the wide extension of Pakistan territory just permitted a national evaluation at a reconnaissance level of detail. For this reason, a more accurate analysis was attempted for Mardan district. This local assessment was mainly intended as a pilot project to define a methodology suited for future detailed studies.

 

QGIS: data visualization (Mardan district) - Click to enlarge.

 

Evaluation Model

Land suitability analysis involves the application of criteria to the landscape to assess where land is suitable for development of a specific crop. The suitability is the attitude of a given type of land to support a defined use.

In developing the land suitability assessment for olive growing in Pakistan a number of challenges were faced. The determination of the evaluation model and the selection of the criteria had to take into consideration that in many of the newly producing countries the cultivation of olives was sometimes proved to be possible in not strictly definable “Mediterranean climates”, thus making difficult to directly apply models specifically set for those climates. Another factor of uncertainty is represented by the lack of field information acquired from experimental field or mother blocks. When available, field data were not entirely trustable because no or limited records were taken or made available. Finally, limited available sources of environmental data represented an important driving factor in defining an effective methodology.

Considering all the constraints, the overall objective of the study and the specific context of Pakistan, the selected model is based on a limiting factor analysis where a set of constraint thresholds defines valid range of environmental conditions. This approach, that can be called minimum requirements selection, divides land in “suitable” (where all the criteria are satisfied) or “unsuitable” (where at least one criteria is not satisfied).

Minimum environmental as well as agronomical requirements for olives were taken into consideration, to ensure a viable production without any specific extra support by the growers (e.g. irrigation systems). Therefore selecting only areas in which an adequate oil production would be obtained solely through ordinary orchard husbandry (mainly pruning and fertilization). Nevertheless, through the information system is always possible to explore the environmental conditions that have excluded specific areas.

During the elaboration of the model, a specific attention was given not to include, among the suitable areas, zones characterized by difficult morphology or at risk of erosion.

According to the general environmental requirements for olives already discussed, the main thematic groups of data useful to identify suitable areas can be summarized as follow:

  • Morphology

  • Climate

  • Soil

Once defined a meaningful set of selecting criteria inside each of these thematic groups, the challenge was to get data in order to operate the analysis. As no complete set of digital data, at the appropriated level of detail, were made available to the project, for some of the criteria a certain degree of approximation was taken into account by using lesser detail set of data (national broad scale maps) or, when no data was available, indirect indexes. A slightly different evaluation model was used for the two analyses at national level and for Mardan district.

It is important to point out that many data already exist for all Pakistan (i.e., land cover, a complete network of meteorological stations, detailed topographic maps) but they were not accessible to the project considering the time and budget constraints or legal restrictions concerning their use. These dataset may be used in future improvement of this analysis. Thus, most of the data used were freely downloaded from Internet, i.e. the digital elevation model and its derived products, and satellite images and their derived products.

 

Software Platform

To realize the all above mentioned operations, a modular, spatially oriented and comprehensive information system based on free software was set up. The choice of free software was dictated by three main reasons:

  1. use of free software saved consistent economic resources that were used to acquire data;

  2. many tools included in free GIS software are more advanced than most of the common commercial software;

  3. free software can be acquired by any local institution and organization that will carry on these analysis in further studies.

The selected software platform is made up of: a server relational database management system (PostgreSQL*) and its spatial extension (PostGIS*), were all tabular and vector data where stored and processed; the desktop GIS QGIS*, used to visualize and explore data and to compose the final maps; GIS GRASS*, used to store, manage and analyze raster data (the main software tool used throughout the project); GIS Kosmos*, used to digitize data from paper maps and satellite images; GDAL*, to reproject the raster layers; OpenOffice*, used mainly as spreadsheet. All these software were strictly integrated into one single modular platform. The system is ready to be linked to Internet using free software such as Mapserver* and KaMap*, where data and results of the project could be disseminated in the future to other organizations and to the general public.

 

GRASS: example of model builder tool to define unfavorable aspect values - Click to enlarge.

 

 

(*) Open Source and Free Software list:

PostgreSQL - Click here to visit the Web SitePostGIS - Click here to visit the Web SiteQuantum GIS - Click here to visit the Web SiteGRASS GIS - Click here to visit the Web SiteGIS Kosmos - Click here to visit the Web SiteGDAL - Click here to visit the Web SiteMapServer - Click here to visit the Web Site

ka-Map - Click here to visit the Web SiteOpenOffice - Click here to visit the Web Site

 

 

 Copyright 2009 – All Right Resereved

 

Summary
Suitability Analysis
Olive Trees: Environmental Requirements
Methodology
  Evaluation Model
  Software Platform
National Assessment
Mardan District Assessment


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