GIS-fuzzy logic approach for building indices: regional feasibility and natural potential of ranching in tropical wetland

Authors

  • Sandra Aparecida Santos Embrapa Pantanal
  • Helano Póvoa Lima Embrapa Informática Agropecuária
  • Humberto Perotto Baldivieso Cranfield University
  • Luíz Orcirio Oliveira Embrapa Pantanal
  • Walfrido Moraes Tomás Embrapa Pantanal

DOI:

https://doi.org/10.17700/jai.2014.5.2.140

Abstract

The regional feasibility of ranching (RFR) index was obtained in order to evaluate the productive potential of farms in the Pantanal. Five indicators were selected by expert and employed for the developing of the index. One of the five indicators corresponded to the natural potential for livestock ranching (NPLR) index which was generated by GIS-fuzzy logic. Fuzzy inference process, involving definitions of membership functions, fuzzy set operations and inference rules was implemented and validated with the participation of primary stakeholders. Different scenarios were simulated in a batch, next validated and adjusted with the participation of stakeholders. Both procedures were performed by the use of the Webfuzzy software. The NPLR and RFR index values, calculated for the pilot ranch, corresponded to the expectations of both expert and stakeholders. Fuzzy logic combined with landscape metric seems to be suitable for the definition of the productive natural potential of ranches to produce livestock in the Pantanal. The indices can assess the regional feasibility of ranching, contributing to decision-making of stakeholders.

Author Biography

Humberto Perotto Baldivieso, Cranfield University

Department of Environmental Science and Technology

Downloads

Published

2014-10-02

How to Cite

Santos, S. A., Lima, H. P., Baldivieso, H. P., Oliveira, L. O., & Tomás, W. M. (2014). GIS-fuzzy logic approach for building indices: regional feasibility and natural potential of ranching in tropical wetland. Journal of Agricultural Informatics, 5(2). https://doi.org/10.17700/jai.2014.5.2.140

Issue

Section

Journal of Agricultural Informatics