A novel integrated computational approach for agroecological similarity

Loading...
Thumbnail Image

Date Issued

Date Online

2025-05-09

Language

en

Review Status

Peer Review

Access Rights

Open Access Open Access

Usage Rights

CC-BY-4.0

Share

Citation

Tonle, F.B.; Tonnang, H.E.; Ndadji, M.M.; Tchendji, M.T.; Nzeukou, A.; Niassy, S. (2025) A novel integrated computational approach for agroecological similarity. Environmental Modelling & Software 191: 106494. ISSN: 1364-8152

Permanent link to cite or share this item

External link to download this item

Abstract/Description

Assessing agroecological similarity is crucial for shaping sustainable agricultural practices and resource allocation, especially in regions undergoing rapid environmental changes. Current evaluation methods face challenges such as managing large datasets, adjusting for temporal variations across locations, and the need for accessible, comprehensive analytical tools. Addressing these challenges, this paper presents the Agroecology Fourier-based Similarity Assessment (AFSA), an innovative computational approach that applies principles of the Fourier transform to systematically evaluate similarities among agroecological sites. To enhance usability, AFSA is complemented by webafsa, a user-friendly web application designed for researchers and policymakers, emphasizing ease of use and broad applicability. The implementation of AFSA and webafsa aims to improve land suitability assessments, enhance decision-making for resource allocation, and support better adaptation strategies for sustainable agriculture. By offering both a sophisticated computational methodology and an accessible decision-support tool, this study paves the way for more informed and environmentally considerate agricultural practices.

Author ORCID identifiers

Contributes to SDGs

SDG 2 - Zero hunger
SDG 13 - Climate action
Investors/sponsors
CGIAR Action Areas