Multicriteria land suitability assessment for cassava and bean production using integration of GIS and AHP

Abstract

Land valuation is essential for developing land use planning and achieving efficient land use, food security, and poverty reduction. This study aimed to assess land suitability for cassava and bean production using the multicriteria decision analysis AHP technique and GIS. Land suitability analysis considers factors affecting crop growth and development, particularly in producing beans and cassava. The Analytical Hierarchy Process (AHP) model was used to determine the importance of main and sub-criteria parameters. ArcGIS software was used to create crop suitability distribution maps for bean and cassava production. Each parameter was subjected to pair-wise comparison by employing the Analytical Hierarchy Process (AHP). The study found that the southern region displayed a vastly suitable level of 38% and 46% for beans and cassava, respectively. Farmers can use the comprehensive data to decide whether to plant beans and cassava on their lands, increasing revenue while preserving soil quality management. The GIS-AHP integration approach was suggested to determine optimal decisions based on chosen criteria.

Keywords:

• Suitability class
• ArcGIS
• modeling
• land suitability assessment
• analytical hierarchy process

REVIEWING EDITOR:

• Manuel Tejada, Academic Editor, Universidad de Sevilla, Spain

SUBJECTS:

• Earth sciences
• soil sciences
• agriculture and environmental sciences

Authors’ contributions

The authors confirm contribution to the paper as follows: study conception and design were contributed by EZN, HIG, BHJM, LRC, DMN, NA, and MFS; data collection was contributed by EZN, NA, BHJM, LRC, DMN, and HIG; analysis and interpretation of results were contributed by EZN, BHJM, LRC, DMN, and HIG; draft manuscript preparation was contributed by EZN, LRC, DMN, MFS, BHJM, and HIG. All authors reviewed the results and approved the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Researchers Supporting Project of King Saud University, Riyadh, Saudi Arabia [RSPD2024R751].

Notes on contributors

Emmanuely Z. Nungula

Emmanuely Nungula is an assistant lecturer based at Mzumbe University, Tanzania with a passionate research interest in GIS, soil fertility management, and land use planning.

Boniface J. Massawe

Boniface Massawe is a lecturer, pedologist, and land use planning specialist based at Sokoine University of Agriculture, Tanzania.

Luciana R. Chappa

Luciana R. Chappa is an agronomist and soil scientist from Mzumbe University, Tanzania.

Daniel M. Nhunda

Daniel Nhunda is an assistant lecturer specializing in soil fertility and plant nutrition from Sokoine University of Agriculture, Tanzania.

Mahmoud F. Seleiman

Mahmoud Seleiman is an agronomist from King Saud University, Saudi Arabia, whereas Nawab Ali is a Biosystems Engineer based at Michigan State University USA.

Nawab Ali

Mahmoud Seleiman is an agronomist from King Saud University, Saudi Arabia, whereas Nawab Ali is a Biosystems Engineer based at Michigan State University USA.

Harun I. Gitari

Jayne Mugwe and Harun Gitari are dedicated lecturers at Kenyatta University with expertise in Integrated Soil Fertility Management.