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Using Fuzzy Set Approaches in a Raster GIS for Land Suitability Assessment at a Regional Scale: Case Study in Maros Region, Indonesia

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  • Nurmiaty Nurmiaty
  • Sumbangan Baja

Abstract

Recently, spatial data on land resources have become more available, detailed, and sophisticated. Accordingly, it requires a method that could deal with those complex and detailed data in an effective way. A fuzzy set method with the semantic import model (SIM) was utilized within a raster GIS (geographic information systems) to analyze the area of Maros Regency on a reconnaissance scale basis. In this study, land attribute values were converted into continuous values (ranging from 0 to 1.0), according to the class limit determined based on field experiences, results of experiments, or fixed conventional standards. The evaluation criteria were based on land attributes which are divided into two main components- soil profile and topography. Each of land attributes within each component was valued from 0 (minimum) to 1.0 (maximum) according to the suitability of maize. Those values were represented as membership values, also ranging from 0 to 1.0. The result from land suitability analysis in Maros Regency for maize cultivation indicates that around 25% of land areas have a land suitability index (LSI) value of above 0.70 (suitable and very suitable), about 11% fall between 0.50 and 0.70 (moderately suitable), and 63% under 0.5 (not suitable). The main limiting factor for maize cultivation in this region is topography, especially slope gradient (s).

Suggested Citation

  • Nurmiaty Nurmiaty & Sumbangan Baja, 2014. "Using Fuzzy Set Approaches in a Raster GIS for Land Suitability Assessment at a Regional Scale: Case Study in Maros Region, Indonesia," Modern Applied Science, Canadian Center of Science and Education, vol. 8(3), pages 115-115, June.
    • Handle: RePEc:ibn:masjnl:v:8:y:2014:i:3:p:115
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    References listed on IDEAS

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    1. Ali Keshavarzi & Fereydoon Sarmadian & Ahmad Heidari & Mahmoud Omid, 2010. "Land Suitability Evaluation Using Fuzzy Continuous Classification (A Case Study: Ziaran Region)," Modern Applied Science, Canadian Center of Science and Education, vol. 4(7), pages 1-72, July.
    2. Reshmidevi, T.V. & Eldho, T.I. & Jana, R., 2009. "A GIS-integrated fuzzy rule-based inference system for land suitability evaluation in agricultural watersheds," Agricultural Systems, Elsevier, vol. 101(1-2), pages 101-109, June.
    3. Ali Keshavarzi & Fereydoon Sarmadian & Reza Labbafi & Majid Vandechali, 2011. "Modeling of Soil Cation Exchange Capacity Based on Fuzzy Table Look-up Scheme and Artificial Neural Network Approach," Modern Applied Science, Canadian Center of Science and Education, vol. 5(1), pages 153-153, February.
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    Cited by:

    1. Sumbangan Baja & Samsu Arif & Risma Neswati, 2017. "Developing a User Friendly Decision Tool for Agricultural Land Use Allocation at a Regional Scale," Modern Applied Science, Canadian Center of Science and Education, vol. 11(5), pages 1-11, May.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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