Land Cover Changes Utilising Landsat Satellite Imageries for the Kumasi Metropolis and Its Adjoining Municipalities in Ghana (1986–2022)

Frimpong, Bernard Fosu; Koranteng, Addo; Atta-Darkwa, Thomas; Fosu, Opoku; Zawiła-Niedźwiecki, Tomasz

doi:10.3390/s23052644

Cited by 6 publications

(4 citation statements)

References 65 publications

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“…For instance, [16] found that there were significant land use and land cover changes in the Kumasi Metropolis over a 30-year period, with negative effects on food crop production. Similarly, [17]observed an increase in residential land use in Kumasi and decreasing trends in forestlands and agricultural while [18]discovered an overall increase in built-up areas in the region.…”

Section: Discussionmentioning

confidence: 98%

Application of GIS and Remote Sensing to Identify Changes in Surface Water Bodies and Wetland Depletion in the Kumasi Metropolis, Ghana.

Amoako-Attah¹,

Henyo²,

Amoako-Mensah³

2023

Preprint

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This study aimed to use remote sensing and GIS to detect changes in surface water and wetlands in the Kumasi Metropolis over a period of 20 years (2002-2022). Landsat images were processed using the QGIS software, and the Maximum Likelihood Algorithm was used to perform supervised classification of land use land cover, while raster calculator aided in detecting wetlands by calculation for NDWI, MNDWI, and AWEI. The results showed that the majority of the landscape in the Kumasi metropolis was made up of built-up areas (79.4%), followed by agricultural lands (13.3%) and wetlands (7.3%). Over the 20-year period, built-up areas had gained 20.7% of the total landscape, while agricultural lands and wetlands had lost 16.7% and 4.0%, respectively. All water index methods recorded an increase in non-water cover and a loss of water cover over the period, with surface water decreasing by 5% and non-water land cover increasing by 5%. The study concludes that there have been significant changes in wetlands and surface water land use and land cover within the Kumasi Metropolis over the past 20 years, and recommends the enforcement of legislation on surface water protection in the area to protect wetlands

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Section: Discussionmentioning

confidence: 98%

Application of GIS and Remote Sensing to Identify Changes in Surface Water Bodies and Wetland Depletion in the Kumasi Metropolis, Ghana.

Amoako-Attah¹,

Henyo²,

Amoako-Mensah³

2023

Preprint

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“…Studies of land cover changes, including the coverage of forested areas, are currently carried out mainly using data acquired by remote sensing methods, among which satellite imagery, e.g., Landsat, is very common [41][42][43]. Their high information abundance makes it possible to perform their own land cover classification and a range of analyses based on widely accepted indicators derived from them, e.g., NDVI [41,42].…”

Section: Methodsmentioning

confidence: 99%

Changes in Forest Cover of Municipalities in Poland in 1990–2018

Kociuba,

Gawrysiak,

Kociuba

2024

Sustainability

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The study is part of the trend of searching for research methods to demonstrate changes in forest cover at the level of basic units of public administration with greater precision and accuracy. The purpose of the article is to present, for the first time, changes in forest cover of municipalities in Poland from 1990 to 2018 using CORINE Land Cover (CLC) data. The contributions of this study are threefold. Firstly, using GIS and CLC data (3.1. Forests), multivariate analyses of forest cover changes were carried out for 2481 municipalities for the CLC data collection years (1990, 2000, 2006, 2012, 2018), which showed the temporal and spatial dynamics of changes, with a predominance of deforestation in 1990–2000 and 2012–2018, and afforestation in 2000–2006 and 2006–2012. Secondly, the formal, legal and financial rationale for these changes was indicated. The increase in afforestation was a result of financial incentives under the National Program for Increasing Forest Cover and the EU’s Common Agricultural Policy (under Rural Development Programs—RDPs). Deforestation was related to a decrease in the supply of land for afforestation, the competitiveness of subsidies implemented under RDPs, and statutory liberalization of logging. Thirdly, the main discrepancies between the data obtained from CLC and from the public data collected by Statistics Poland (GUS) and the State Forests were indicated, which ranged from −32 kha to +310 kha, corresponding to percentage differences of 2.3% and 1.8%, respectively. This was mainly influenced by the differences in the complexity and updating of data collected for state and private forests, as well as delays in introducing changes to the land register by the public administration. This work contributes significantly to our understanding of the dynamics of forest cover changes in relation to the actual degree of forestation and deforestation, and the determinants of forest transformation in Polish municipalities, as well as demonstrating the new applicability of CLC data and their limitations related mainly to the generalization of forest cover area.

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“…(1) Machine learning is a technical tool used for solving research problems. For example, satellite images were used to identify land use changes [5], crime was assessed through street images [6], COVID-19 plan distribution states for urban security risk assessment were identified [7,8], and remote sensing images were used to detect forest carbon stocks to predict their carbon sink development [9]. (2) Machine learning provides innovative perspectives on extracting design elements to facilitate decisions.…”

Section: Introductionmentioning

confidence: 99%

The Development of an Experimental Framework to Explore the Generative Design Preference of a Machine Learning-Assisted Residential Site Plan Layout

Sun,

Yan,

et al. 2023

Land

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Generative design based on machine learning has become an important area of application for artificial intelligence. Regarding the generative design process for residential site plan layouts (hereafter referred to as “RSPLs”), the lack of experimental demonstration begs the question: what are the design preferences of machine learning? In this case, all design elements of the target object need to be extracted as much as possible to conduct experimental studies to produce scientific experimental results. Based on this, the Pix2pix model was used as the test case for Chinese residential areas in this study. An experimental framework of “extract-translate-machine-learning-evaluate” is proposed, combining different machine and manual computations, as well as quantitative and qualitative evaluation techniques, to jointly determine which design elements and their characteristic representations are machine learning design preferences in the field of RSPL. The results show that machine learning can assist in optimizing the design of two particular RSPL elements to conform to residential site layout plans: plaza paving and landscaped green space. In addition, two other major elements, public facilities and spatial structures, were also found to exhibit more significant design preferences, with the largest percentage increase in the number of changes required after machine learning. Finally, the experimental framework established in this study compensates for the lack of consideration that all design elements of a residential area simultaneously utilize the same methodological framework. This can also assist planners in developing solutions that better meet the expectations of residents and can clarify the potential and advantageous directions for the application of machine learning-assisted RSPL.

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Land Cover Changes Utilising Landsat Satellite Imageries for the Kumasi Metropolis and Its Adjoining Municipalities in Ghana (1986–2022)

Cited by 6 publications

References 65 publications

Application of GIS and Remote Sensing to Identify Changes in Surface Water Bodies and Wetland Depletion in the Kumasi Metropolis, Ghana.

Application of GIS and Remote Sensing to Identify Changes in Surface Water Bodies and Wetland Depletion in the Kumasi Metropolis, Ghana.

Changes in Forest Cover of Municipalities in Poland in 1990–2018

The Development of an Experimental Framework to Explore the Generative Design Preference of a Machine Learning-Assisted Residential Site Plan Layout

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