Modelling Land Suitability for Optimal Rice Cultivation in Ebonyi State, Nigeria: A Comparative Study of Empirical Bayesian Kriging and Inverse Distance Weighted Geostatistical Models

Simple item page
dc.contributor.authorOnyedikachi J, Okeke
dc.contributor.authorBaidoo, Dennis
dc.contributor.authorFrimpong, Justice A
dc.contributor.authorOlumide, Oni
dc.contributor.authorBamisaye, Cosmas K
dc.contributor.authorRekiya A, Idris
dc.date.accessioned2024-03-21T08:50:31Z
dc.date.available2024-03-21T08:50:31Z
dc.date.issued2023-11-30
dc.identifier.citationOnyedikachi J. O., Baidoo, D., Frimpong, J. A., Olumide, O., Bamisaye, C. K., & Idris, R. A. (2023). Modelling Land Suitability for Optimal Rice Cultivation in Ebonyi State, Nigeria: A Comparative Study of Empirical Bayesian Kriging and Inverse Distance Weighted Geostatistical Models. Paper presented at the Sustainable Agriculture, Environment, and Food Security session of the 2023 International Research Conference of Sri Lanka Technology Campus, Colombo, Sri Lanka, December 14-15, 2023.en_US
dc.identifier.isbn978-624-6045-02-9
dc.identifier.urihttp://repo.sltc.ac.lk/${dspace.ui}/handle/1/433
dc.language.isoenen_US
dc.publisherSri Lanka Technological Campusen_US
dc.subjectRice cultivation,en_US
dc.subjectAgricultural sustainability,en_US
dc.subjectFood security,en_US
dc.subjectGIS,en_US
dc.subjectLand suitability analysis,en_US
dc.subjectGeostatistics,en_US
dc.subjectEnvironmental factors,en_US
dc.subjectMultiple regression,en_US
dc.subjectANOVAen_US
dc.titleModelling Land Suitability for Optimal Rice Cultivation in Ebonyi State, Nigeria: A Comparative Study of Empirical Bayesian Kriging and Inverse Distance Weighted Geostatistical Modelsen_US
dc.typeArticleen_US

Files

Original bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
55.pdf
Size:
630.61 KB
Format:
Adobe Portable Document Format
Description:
Modelling Land Suitability for Optimal Rice Cultivation in Ebonyi State, Nigeria: A Comparative Study of Empirical Bayesian Kriging and Inverse Distance Weighted Geostatistical Models
Download

License bundle

Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

International Research Conference 2023