A Structural Equation Modeling Approach to Disentangling Regional-Scale Landscape Dynamics in Ghana

Abstract

Land cover (LC) change is an integrative indicator of changes in ecosystems due to anthropogenic or natural forcings. There is a significant interest in the investigation of spatio-temporal patterns of LC transitions, and the causes and consequences thereof. While the advent of satellite remote sensing techniques have enhanced our ability to track and measure LC changes across the globe, significant gaps remain in disentangling specific factors that influence, or in certain cases, are influenced by, LC change. This study aims to investigate the relative influence of regional-scale bioclimatology and local-scale anthropogenic factors in driving LC and environmental change in Ghana. This analysis builds upon previous research in the region that has highlighted multiple drivers of LC change in the region, especially via drivers such as deforestation, urbanization, and agricultural expansion. It used regional-scale remotely sensed, demographic, and environmental data for Ghana across 20 years and developed path models on causal factors influencing LC transitions in Ghana. A two-step process is utilized wherein causal linkages from an exploratory factor analysis (EFA) are constrained with literature-based theoretical constructs to implement a regional-scale partial least squares path model (PLSPM). The PLSPM reveals complex interrelationships among drivers of LC change that vary across the geography of Ghana. The model suggests strong effects of local urban expansion on deforestation and vegetation losses in urban and peri-urban areas. Losses of vegetation are in turn related to increases in local heating patterns indicative of urban heat island effects. Direct effects of heat islands are however masked by strong latitudinal gradients in climatological factors. The models confirm that decreases in vegetation cover results in increased land surface albedo that is indirectly related to urban and population expansion. These empirically-estimated causal linkages provide insights into complex spatio-temporal variations in potential drivers of LC change. We expect these models and spatial data products to form the basis for detailed investigations into the mechanistic underpinnings of land cover dynamics across Ghana. These analyses are aimed at building a template for methods that can be utilized to holistically design spatially-disaggregated strategies for sustainable development across Ghana.

SERVIR West Africa Land Use and Land Cover Task Force: Building a Collaborative Network to Support Capacity Development in the Harmonization of Land Cover and Land Use Mapping and Monitoring in West Africa

“…Similarly, in its second Research and Action Plan (WRAP 2.0), WASCAL is supporting high-resolution LULC mapping through two projects, namely "greenhouse gas (GHG) emissions and mitigation options under climate and land use change in West Africa concerted regional modeling and assessment (CONCERT WEST AFRICA)" and "land surface processes as a determinant of climate change in Africascenarios, high-resolution modeling and development of a stakeholder data portal (LANDSURF)" [11]. The SERVIR Applied Science Teams have recently supported activities related to future land use scenario development and integration of time series earth observation data for land use planning [12,13]. The diversity of land cover mapping projects in the absence of a harmonized classification system necessitated the establishment of the West Africa Land Cover Task Force (WALC-TF) to moderate land cover mapping and monitoring initiatives in West Africa and ensure the harmonization of disparate legends in the sub-region.…”

Data and Values: Axiological Interpretations of Building Sprawl Landscape Risk in the Rural Territory of Noto (Italy)

“…The processes of landscape reworking are changing the faces of cities and territories day by day, creating landscapes in which it is increasingly difficult to trace the traditional codes or statutes of places that seem to be characterized by disorder, perhaps apparent in [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30].…”