The wicked problem of land use planning

Navigating stochasticity at the convergence of maximum entropy and generalised additive modelling

Bibliographic Data

ID22111897
AuthorsNonso Izuchukwu Ewurum (0000-0001-6383-5783, University of Botswana, corresponding author), Nkiruka Evangeline Aso (Nnamdi Azikiwe University), Nkiruka Aso (Nnamdi Azikiwe University), Keone Kelobonye (0000-0002-6652-6262, University of Botswana), Njideka MaryClara Aguome (0000-0002-6668-9731, University of Botswana), Nnyaladzi Tema (0009-0004-3772-6654, University of Botswana), Stella Obiageli Onwubuya-Ezeala (0009-0008-7889-889X, Chukwuemeka Odumegwu Ojukwu University)
Year2026
Volume12
Issue1
Publication date2026-12-31
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueCogent Social Sciences (JOURNAL)
Journal identifiersISSN: 2331-1886 • E-ISSN: 2331-1886
PublisherInforma UK Limited (PUBLISHER • GB)
DOI10.1080/23311886.2026.2633467
OpenAlexW7131647443
LanguageEN
References cited24

Conventional parametric models inadequately capture spatial complexity in weak governance contexts owing to the presence of volatile stochastic drivers. This study applied Maximum Entropy–Generalised Additive Modelling integration to examine non-linear development probabilities in Enugu, Nigeria. MaxEnt was applied to 685 development sites and 10,000 background points to rank 12 spatial and institutional predictors and extract functional complexity measures. GAM integrated the results through adaptive LASSO weighting and basis dimension selection. The framework achieved superior discrimination (AUC = 0.871) over logistic regression (AUC = 0.782), naïve GAM (0.831), and MaxEnt-only (0.847). Road proximity showed extreme non-linearity (EDF = 6.85, p < 0.001), with probability sharply decreasing within 100 metres. Proximity to land use demonstrated multi-modal patterns (EDF = 5.12, p < 0.001), whereas slope displayed U-shaped correlations (EDF = 3.29, p < 0.001). Tenure security followed an S-curve (EDF = 1.58) with diminishing returns beyond moderate levels. The results show that adaptable non-parametric models are crucial for land use planning where spatial linkages are distorted by institutional fragility. The MaxEnt-GAM is a replicable framework for improving planning accuracy in similar systems

Additive model · Land use · Logistic regression · Principle of maximum entropy · Regression · Weighting · Economic and Technological Innovation · Land Use and Ecosystem Services · Soil and Land Suitability Analysis

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