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Land use/land cover change (LULCC) is an important driver of ecosystem changes in coastal areas. Despite being pervasive in coastal Ghana, LULCC has not been investigated to understand its effects on the potential for coastal landscapes to supply ecosystem services (ES). In this study, the impacts of LULCC on the potential supply of ES by coastal landscapes in Southwestern Ghana was assessed for the years 2008 and 2018 by using remote sensing and benefit transfer approaches. Based on available data, relevant provisioning and regulating ES were selected for the assessment while indicators to aid the quantification of the ES were obtained from literature. Supervised classification methods and maximum likelihood algorithms were used to prepare land use/land cover (LULC) maps and the derived LULC categories were assigned according to the descriptions of the Land Cover Classification System (LCCS). Potential supply of provisioning (food, fuelwood) and regulating (carbon storage) services was quantified and the spatial and temporal distributions of these ES illustrated using maps. The results show variations in food and fuelwood supply and carbon storage potentials over the study period and across different locations on the landscape. Potentials for fuelwood supply and carbon storage in mangrove forests indicated declining trends between 2008 and 2018. On the other hand, food-crop supply and carbon storage potential in rubber plantations depicted increasing patterns over the same period. Population, slope and elevation exhibited strong effects on LULC conversions to food crop and rubber plantations whereas these factors were less important determinants of mangrove forest conversions. The findings of the study have implications for identifying and addressing tradeoffs between land uses for agriculture, industrial development and conservation of critical coastal ES within the context of rapid land system transformations in the study region.

Tropical peatlands such as Ghana’s Greater Amanzule peatland are highly valuable ecosystems and under great pressure from anthropogenic land use activities. Accurate measurement of their occurrence and extent is required to facilitate sustainable management. A key challenge, however, is the high cloud cover in the tropics that limits optical remote sensing data acquisition. In this work we combine optical imagery with radar and elevation data to optimise land cover classification for the Greater Amanzule tropical peatland. Sentinel-2, Sentinel-1 and Shuttle Radar Topography Mission (SRTM) imagery were acquired and integrated to drive a machine learning land cover classification using a random forest classifier. Recursive feature elimination was used to optimize high-dimensional and correlated feature space and determine the optimal features for the classification. Six datasets were compared, comprising different combinations of optical, radar and elevation features. Results showed that the best overall accuracy (OA) was found for the integrated Sentinel-2, Sentinel-1 and SRTM dataset (S2+S1+DEM), significantly outperforming all the other classifications with an OA of 94%. Assessment of the sensitivity of land cover classes to image features indicated that elevation and the original Sentinel-1 bands contributed the most to separating tropical peatlands from other land cover types. The integration of more features and the removal of redundant features systematically increased classification accuracy. We estimate Ghana’s Greater Amanzule peatland covers 60,187 ha. Our proposed methodological framework contributes a robust workflow for accurate and detailed landscape-scale monitoring of tropical peatlands, while our findings provide timely information critical for the sustainable management of the Greater Amanzule peatland.

Cultural ecosystem services (CES) in Southwestern Ghana evoke a strong sense of attachment of local land users to the landscape. Hence, their supply is necessary for a balanced socio-ecological system. This study explored the potential supply of cultural ecosystem services (science/education, spiritual, tourism, health and recreation benefits) under different land use planning (LUP) scenarios in Southwestern Ghana. Future LUP scenarios were developed and articulated with a diverse group of land-use planning actors (LUPAs) such as regional land use planners, environmental experts, researchers, farmers and landowners. The scenarios covered business-as-usual, mangrove ecosystem restoration, market-driven growth, and the establishment of an “eco-corridor” as green network. A spatially explicit modeling platform, GISCAME, which combines Geographic Information System and Cellular Automaton modules and multicriteria evaluation was used to evaluate the developed scenarios. Outcomes of the study revealed that in the coastal landscape of Southwestern Ghana, values, perceptions and preferences of LUPAs underpin socio-ecological interactions aimed at maintaining and enhancing CES supply. In addition, it indicated that future supply of CES is characterized by an interplay between multiple and diverse perspectives about plausible land-use futures. Perceptions of, and preferences for, CES align with land-use visions related to afforestation, infrastructure development, agriculture expansion and tourism. In the study area and similar contexts where an array and diversity of individual and societal values exist, effective negotiation and facilitation are essential for harnessing and optimizing land-use planning for CES supply.