TITLE:
Assessing and Mapping Land Suitability Units for Maize (Zea mays L) Production Using Integrated DEMATEL-ANP Model and GIS in the Foumbot Agricultural Basin (Cameroon Western Highlands)
AUTHORS:
Bertrand Kenzong, Dieudonné Bitondo, Primus Azinwi Tamfuh, Georges Simplice Kouedeu Kameni, Joseph Guepi Vounang, Roger Kogge Enang, Emile Temgoua, Dieudonné Bitom
KEYWORDS:
Decision Making Trial Evaluation Laboratory, Analytical Network Process, Geographic Information System, Land Evaluation, Maize, Weighted Overlay Analysis, Foumbot, Western Cameroon
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.10 No.6,
June
27,
2022
ABSTRACT: Land
suitability assessment (LSA) is an essential step in the process of determining environmental limits for sustainable crop
production. Up to date, studies on LSA for crop production in Cameroon
have been based on empirical methods which are limited as they consider similar
singnificance levels for all evaluation criteria and do not consider the interrelationships
of criteria in the best-fit models. In the present study a qualitative land
suitability evaluation by an integrated multi-criteria decision-making (MCDM)
approach and geographic information system (GIS) was tested to assess and map
suitable land units for maize (Zea mays L) production in Cameroon
Western highland. Eight environmental criteria identified as the most relevant
for maize production in the area of interest (AOI) saw their thematic maps
prepared using ArcGIS 10.8. The relationship between criteria was considered by
the DEMATEL method. The criteria were weighted using the ANP method. Thereafter,
the land suitability map was obtained using the weighted overlay analysis (WOA)
in ArcGIS. The results obtained indicated that slope has the highest specific
weight and consequently the greatest influence on land suitability for maize
production in the locality. The land suitability map generated showed that
Foumbot’s agricultural land suitability for maize production varies from very
high to marginally suitable (99% of the surface area). Specifically, 11% (8056
ha) is very highly suitable, 29% (21,119 ha) is highly suitable, 38% (27,405 ha)
are moderately suitable and 20% (14,422 ha)
are marginally suitable. The remaining 1% that falls under non suitable class represents
606 ha and is located on the steep slopes around the Mount Mbappit. The kappa
analysis reveals a total overall accuracy of 78.67% and a kappa value of 0.7256
with an asymptotic error of 0.058 which is good. Then the model used in this
research is highly recommended for
future land evaluation works in Cameroon and similar ecosystems around the
world.