Monitoring land-use and land-cover changes due to extensive urbanization in the Odaw River Basin of Accra, Ghana, 1991–2030

Ackom, Edward Kofi; Adjei, Kwaku Amaning; Odai, Samuel Nii

doi:10.1007/s40808-020-00746-5

Cited by 26 publications

(8 citation statements)

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“…Furthermore, in 2005 the dense forest has declined, and it covered an area of about 18.1 km 2 (2.65 percent) in 2005, and, in the year of 2015 it had improved an area of about 25.5 km 2 (3.73 percent). Therefore, the results show that fluctuated growth of scrubs between 1975 and 2015 (Ackom et al, 2020).…”

Section: Land Use Changes Dense Scrubmentioning

confidence: 87%

An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India

Krishnan

Ramasamy

2022

Geos. Ind.

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Anthropogenic activities are leads to changing a natural land cover, and consequences are severe to human and environments etc. The present study has examined the Muthupet mangrove forest and its surrounding land-use changes from 1975 to 2015 using the geospatial technology. An assessment of land use and land cover was done at Muthupet mangrove forest which is an occupied the three coastal district of Tamilnadu i.e. Thanjavur, Thiruvarur, and Nagappattinam. The remote sensing (MSS, TM, and OLI) data was adopted to explore the land use and land cover with help of visual image interpretation. The study had justified the results based upon the ground truth verification, and 203 sites were selected for explore the 10 land use categories. An Accuracy Assessment has done based on the KAPPA index for the year 2015 classified image and appraisal of land use change detection from 1975 to 2015 for all the categories. The study revealed that the land use and land cover condition from the 1975 to 2015, for example 1975 water bodies covered an area of about 156.1 km2, and 2015 it has comprised 89.8 km2. An appraisal of land use and land cover clearly is evidence in 2005 entire land use and land cover changed, and reasons for that an influence of the Tsunami. Consequently, Muthupet mangrove forest is one of the important to human and environments, and the present study has exposed that the changes of the mangrove forest, and its impact on to the coastal community. Keywords : Mangrove Fores; Remote sensing; LULC; Classification; Change detection Copyright (c) 2022 Geosfera Indonesia and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

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Section: Land Use Changes Dense Scrubmentioning

confidence: 87%

An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India

Krishnan

Ramasamy

2022

Geos. Ind.

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“…The river is about 30 km long and covers an estimated 270 km 2 . It is regarded as the most polluted catchment in the country ( Amoako and Frimpong Boamah, 2015 ; Ackom et al, 2020 ), serving as both a water source and a solid waste sink ( Ansa et al, 2017 ). The river originates from the country’s Eastern region and flows through about 70% of the greater Accra region, discharging into the Atlantic Ocean via the Korle Lagoon (see Figure 3 ).…”

Section: The Study Setting: the Odaw River Catchmentmentioning

confidence: 99%

Using an extended model of the reasoned action approach to explore individual behavioral intentions regarding litter and plastic pollution prevention in a developing country

Oduro-Appiah,

Afful,

Osei-Tutu

2024

Front. Psychol.

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Implementing litter and plastic pollution prevention strategies is essential for cities of developing countries, mainly due to the prevailing high incidence of littering and the urgent need to realize the adverse per capita environmental impact target of the sustainable development goals. In this article, we report the use of the prominent reasoned action approach—in its original state and an extended model with moral norms—for exploring the critical socio-cognitive determinants of individuals’ litter prevention intentions in Ghana. By analyzing the valid answers of 447 participants to a structured questionnaire on litter prevention, we found attitudes (β = 0.35, SE = 0.014, p < 0.001) and moral norms (β = 0.57, SE = 0.099, p < 0.001) as the most influencing determinants to individual intentions in the original and the extended models, respectively. The analysis suggests that individuals will stop littering their environments if environmentally friendly interventions are implemented to elicit self-responsibility and moral obligation. Campaigns that demonstrate the effects of littering on drain blockage, flooding, and disease outbreaks may improve individual litter prevention attitudes. Installing waste receptacles in public spaces and communicating persuasive messages may facilitate personal antilittering intentions. Apart from contributing to the implementation of a litter management strategy to reduce the flood risk and enhance the resilience of the Greater Accra region of Ghana, this research helps to close the literature gaps in litter prevention behavior in developing countries, as well as support the implementation of the sustainable development goals and the global plastic action partnership.

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“…In this regard, Ackom et al [61], Mohammady et al [62] suggest hybrid approaches to solve the issues which have become more powerful and diversified, due to the development of powerful and advanced classifiers. Other strategies can be incorporated such as those which possibility to infer proportions of vegetation cover, commonly known as vegetation indexes.…”

Section: Remote Sensing Data Processing Techniques For Lulcmentioning

confidence: 99%

Developments in Land Use and Land Cover Classification Techniques in Remote Sensing: A Review

Macarringue¹,

Bolfe²,

Pereira³

2022

JGIS

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Studies on land use and land cover changes (LULCC) have been a great concern due to their contribution to the policies formulation and strategic plans in different areas and at different scales. The LULCC when intense and on a global scale can be catastrophic if not detected and monitored affecting the key aspects of the ecosystem's functions. For decades, technological developments and tools of geographic information systems (GIS), remote sensing (RS) and machine learning (ML) since data acquisition, processing and results in diffusion have been investigated to access landscape conditions and hence, different land use and land cover classification systems have been performed at different levels. Providing coherent guidelines, based on literature review, to examine, evaluate and spread such conditions could be a rich contribution. Therefore, hundreds of relevant studies available in different databases (Science Direct, Scopus, Google Scholar) demonstrating advances achieved in local, regional and global land cover classification products at different spatial, spectral and temporal resolutions over the past decades were selected and investigated. This article aims to show the main tools, data, approaches applied for analysis, assessment, mapping and monitoring of LULCC and to investigate some associated challenges and limitations that may influence the performance of future works, through a progressive perspective. Based on this study, despite the advances archived in recent decades, issues related to multi-source, multi-temporal and multi-level analysis, robustness and quality, scalability need to be further studied as they constitute some of the main challenges for remote sensing.

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Monitoring land-use and land-cover changes due to extensive urbanization in the Odaw River Basin of Accra, Ghana, 1991–2030

Cited by 26 publications

References 50 publications

An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India

An Assessment of Land Use and Land Cover Changes in Muthupet Mangrove Forest, using Time Series Analysis 1975-2015, Tamilnadu, India

Using an extended model of the reasoned action approach to explore individual behavioral intentions regarding litter and plastic pollution prevention in a developing country

Developments in Land Use and Land Cover Classification Techniques in Remote Sensing: A Review

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