A novel integrated computational approach for agroecological similarity

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 lo...

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Main Authors: Tonle, Franck B.N., Tonnang, Henri E.Z., Ndadji, Milliam M.Z., Tchendji, Maurice T., Nzeukou, Armand, Niassy, Saliou
Format: Journal Article
Language:Inglés
Published: Elsevier 2025
Subjects:
Online Access:https://hdl.handle.net/10568/174963
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author Tonle, Franck B.N.
Tonnang, Henri E.Z.
Ndadji, Milliam M.Z.
Tchendji, Maurice T.
Nzeukou, Armand
Niassy, Saliou
author_browse Ndadji, Milliam M.Z.
Niassy, Saliou
Nzeukou, Armand
Tchendji, Maurice T.
Tonle, Franck B.N.
Tonnang, Henri E.Z.
author_facet Tonle, Franck B.N.
Tonnang, Henri E.Z.
Ndadji, Milliam M.Z.
Tchendji, Maurice T.
Nzeukou, Armand
Niassy, Saliou
author_sort Tonle, Franck B.N.
collection Repository of Agricultural Research Outputs (CGSpace)
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.
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spelling CGSpace1749632025-11-13T10:39:09Z A novel integrated computational approach for agroecological similarity Tonle, Franck B.N. Tonnang, Henri E.Z. Ndadji, Milliam M.Z. Tchendji, Maurice T. Nzeukou, Armand Niassy, Saliou climate change agroecology modelling land suitability decision-support systems-decision support tools 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. 2025-06 2025-06-04T12:29:38Z 2025-06-04T12:29:38Z Journal Article https://hdl.handle.net/10568/174963 en Open Access application/pdf Elsevier 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
spellingShingle climate change
agroecology
modelling
land suitability
decision-support systems-decision support tools
Tonle, Franck B.N.
Tonnang, Henri E.Z.
Ndadji, Milliam M.Z.
Tchendji, Maurice T.
Nzeukou, Armand
Niassy, Saliou
A novel integrated computational approach for agroecological similarity
title A novel integrated computational approach for agroecological similarity
title_full A novel integrated computational approach for agroecological similarity
title_fullStr A novel integrated computational approach for agroecological similarity
title_full_unstemmed A novel integrated computational approach for agroecological similarity
title_short A novel integrated computational approach for agroecological similarity
title_sort novel integrated computational approach for agroecological similarity
topic climate change
agroecology
modelling
land suitability
decision-support systems-decision support tools
url https://hdl.handle.net/10568/174963
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