Author
Listed:
- Rylle G. Anuber
- Jason Ben R. Paragamac
- Eugenio S. Guhao Jr.
- Joel B. Tan
- Rhoderick D. Malangsa
- Jannie Fleur V. Oraño
- Jude Ymarri P. Ansale
- Jorton A. Tagud
Abstract
This study addresses the persistent gap in localized and fine-scale agricultural suitability assessments in the Philippines by integrating Geographic Information System (GIS) and remote sensing techniques with a multi-criteria decision framework. While previous studies have explored spatial planning using limited biophysical parameters, this research introduces a novel integration of geomorphological, hydrological, climatic, and infrastructural variables—including slope, elevation, soil type, rainfall, topographic wetness index (TWI), land use/land cover (LULC), temperature, and proximity to roads and streams—using the Analytical Hierarchy Process (AHP) and Weighted Multi-Criteria Analysis (WMCA). Applied in Southern Leyte, the study reveals that 52.59% of the province's land is of very low suitability due to poor soil quality, extreme temperature variations, and limited water access, while only 2.04% is classified as very highly suitable. This fine-scale, evidence-based spatial model offers practical value: farmers can optimize crop selection and field layout; land use planners can align zoning strategies with biophysical constraints; and policymakers can prioritize irrigation and climate-adaptive interventions in vulnerable areas. The findings contribute not only to enhancing agricultural productivity and resource efficiency but also to advancing sustainable land management, mitigating climate risks, and supporting national targets under SDG 2 (Zero Hunger) and SDG 15 (Life on Land). By providing an empirically grounded, locally tailored decision support tool, this study helps bridge the gap between geospatial research and strategic agricultural development planning.
Suggested Citation
Rylle G. Anuber & Jason Ben R. Paragamac & Eugenio S. Guhao Jr. & Joel B. Tan & Rhoderick D. Malangsa & Jannie Fleur V. Oraño & Jude Ymarri P. Ansale & Jorton A. Tagud, .
"Analyzing Agricultural Suitability Using Geographic Information System (Gis) And Remote Sensing,"
International Journal of Agriculture and Environmental Research, Malwa International Journals Publication, vol. 11(4).
Handle:
RePEc:ags:ijaeri:371465
DOI: 10.22004/ag.econ.371465
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:ijaeri:371465. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: http://ijaer.in/ .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.