Pixel-based and object-oriented approaches in segregating cocoa from forest in the Juabeso-Bia landscape of Ghana

Ashiagbor, George; Forkuo, Eric Kwabena; Asante, Winston Adams; Acheampong, Emmanuel; Quaye‐Ballard, Jonathan Arthur; Boamah, Prince; Mohammed, Yakubu; Foli, Ernest G.

doi:10.1016/j.rsase.2020.100349

Cited by 13 publications

(19 citation statements)

References 51 publications

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“…The study communities, Gyesewobre and Driver-Krom, are two of the 55 forest-based communities in the study district that were randomly selected for the study (figure 2). Cocoa agroforestry, practised harmoniously with the surrounding primary/secondary forest is the major income activity for more than 60% of households in these communities (Ashiagbor et al 2020). The key forest resources extracted before and during the COVID-19 pandemic are shown in table 1.…”

Section: Study Areamentioning

confidence: 99%

Pandemic-induced shocks and shifts in forest-based livelihood strategies: learning from COVID-19 in the Bia West District of Ghana

Kuuwill

Kimengsi

Campion

2022

Environ. Res. Lett.

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The COVID-19 pandemic has reshaped societies and will continue to do so. Despite its salience, micro-scale evidence on how this pandemic reshapes the livelihood strategies of forest communities in sub-Saharan Africa (SSA) are lacking. To bridge this lacuna, this paper analyses the dynamics around forest-based livelihood strategies in the context of the COVID-19 pandemic in the Bia West District of Ghana. Key informant interviews (n=8) and a survey of forest-dependent households (n=100) were conducted to generate relevant data. The study identified fuelwood harvesting, medicinal plants extraction, fruit-gathering and beekeeping as the four livelihood activities that were predominantly practised in the study communities during the COVID-19 pandemic. The analysis established an increase in the number of households that diversified into fuelwood harvesting. Regarding medicinal plants collection as a livelihood strategy, less than 10% of households either diversified or intensified this practice with similar charges recorded in fruit-gathering and beekeeping. The logistic regression disclosed gender, household size, education and income, as the socioeconomic variables that significantly predict livelihood diversification and intensification during the COVID-19 pandemic. Additionally, the financial, social and physical asset base of households significantly shaped livelihood diversification. Diversification into fuelwood collection, and medicinal plants extraction and beekeeping were the strategies that showed a significant positive correlation correlated significantly with the well-being outcomes of forest-based households. While this paper provides fresh evidence to inform the vulnerability dimension of the sustainable livelihoods framework, it further calls for policy interventions to build pandemic-resilient livelihood strategies around forest communities.

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Section: Study Areamentioning

confidence: 99%

Pandemic-induced shocks and shifts in forest-based livelihood strategies: learning from COVID-19 in the Bia West District of Ghana

Kuuwill

Kimengsi

Campion

2022

Environ. Res. Lett.

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“…To inform decision making, there is a need for insights into the structural changes caused by monocrops and their associated socio-cultural contributions to landscape services. Multi-temporal landscape studies have often merged tree monocrops with other crops while others treat them as part of open forests [27]. These miscategorizations of tree monocrops mask the spatial and structural dynamics attributable to the increased farmer participation in landscapes.…”

Section: Introductionmentioning

confidence: 99%

“…These miscategorizations of tree monocrops mask the spatial and structural dynamics attributable to the increased farmer participation in landscapes. Attempts to separate these commodity monocrops have been few and sometimes focused on specific crops [7,10,27].…”

Section: Introductionmentioning

confidence: 99%

Effects of Monocropping on Land Cover Transitions in the Wet Evergreen Agro-Ecological Zone of Ghana

Loh

Asubonteng

Adanu

2022

Land

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The wet evergreen forest ecological zone of Ghana is undergoing notable structural changes, although most maps erroneously depict the area to be an intact forest. Several hectares of plantation agriculture such as rubber, oil palm, and cocoa are replacing the natural vegetation and habitats, thereby threatening indigenous biodiversity. This study aimed to assess the effects of tree monocrop proliferation on landscape transitions between 1986 and 2020 in the Wassa East District of Ghana. The ISODATA clustering technique was used to produce land cover category maps from Landsat images of 1986, 2002, and 2020. A post-classification change detection technique resulted in transition matrices which were used for the computation of land cover transition intensities over 34 years. The results showed that the landscape was dominated by forests in 1986. Still, the forest continuously declined by 34% (1% annually) in 2020 while all other land cover types increased in both periods with cocoa covering 23% oil palm covering 14%, and rubber covering 2% of the land area. These conversions in the land area are important, especially since the closed forests usually transition to monocrops through the intermediate process: food crop farming. This information is essential for decision making on land development and biodiversity conservation.

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“…Abu et al (2021) detected cocoa and its impact on protected areas in Côte d'Ivoire. With the same dataset processed with deep learning, it was possible to separate full sun cocoa and cocoa agroforestry (cocoa associated with forest trees) in the same region (Ashiagbor et al 2020). However, cocoa farms are difficult to map, especially in the regions where they share the landscape with other spectrally overlapping crops such as rubber and palm oil.…”

Section: Introductionmentioning

confidence: 99%

Modelling the spatial distribution of the classification error of remote sensing data in cocoa agroforestry systems

Tamga

Latifi²,

Ullmann³

et al. 2022

Agroforest Syst

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Cocoa growing is one of the main activities in humid West Africa, which is mainly grown in pure stands. It is the main driver of deforestation and encroachment in protected areas. Cocoa agroforestry systems which have been promoted to mitigate deforestation, needs to be accurately delineated to support a valid monitoring system. Therefore, the aim of this research is to model the spatial distribution of uncertainties in the classification cocoa agroforestry. The study was carried out in Côte d’Ivoire, close to the Taï National Park. The analysis followed three steps (i) image classification based on texture parameters and vegetation indices from Sentinel-1 and -2 data respectively, to train a random forest algorithm. A classified map with the associated probability maps was generated. (ii) Shannon entropy was calculated from the probability maps, to get the error maps at different thresholds (0.2, 0.3, 0.4 and 0.5). Then, (iii) the generated error maps were analysed using a Geographically Weighted Regression model to check for spatial autocorrelation. From the results, a producer accuracy (0.88) and a user’s accuracy (0.91) were obtained. A small threshold value overestimates the classification error, while a larger threshold will underestimate it. The optimal value was found to be between 0.3 and 0.4. There was no evidence of spatial autocorrelation except for a smaller threshold (0.2). The approach differentiated cocoa from other landcover and detected encroachment in forest. Even though some information was lost in the process, the method is effective for mapping cocoa plantations in Côte d’Ivoire.

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Pixel-based and object-oriented approaches in segregating cocoa from forest in the Juabeso-Bia landscape of Ghana

Cited by 13 publications

References 51 publications

Pandemic-induced shocks and shifts in forest-based livelihood strategies: learning from COVID-19 in the Bia West District of Ghana

Pandemic-induced shocks and shifts in forest-based livelihood strategies: learning from COVID-19 in the Bia West District of Ghana

Effects of Monocropping on Land Cover Transitions in the Wet Evergreen Agro-Ecological Zone of Ghana

Modelling the spatial distribution of the classification error of remote sensing data in cocoa agroforestry systems

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