Assessment of past and future land use/cover change over Tordzie watershed in Ghana

Nyatuame, Mexoese; Agodzo, Sampson K.; Amekudzi, Leonard K.; Mensah-Brako, Bismark

doi:10.3389/fenvs.2023.1139264

Cited by 11 publications

(4 citation statements)

References 42 publications

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“…The validation module assesses the level of agreement and disagreement between the CA-Markov predicted LCLU map and the classified LCLU map. An overall agreement (Kno) exceeding 0.8 indicates a strong agreement between the CA-Markov predicted and the classified LCLU maps (Nyatuame et al, 2023;Mishra et al, 2018;Mondal et al, 2016). In this study, if the overall accuracy assessment of the LCLU classification was above 85%, and the CA-Markov predicted LCLU did not achieve an overall accuracy of 0.8, the LCLU maps were not reworked.…”

Section: Calibration and Validation Of The Ca-markov Modelmentioning

confidence: 78%

“…Finally, the CA-Markov model was executed with the 2013 LCLU map as the image from which 2023 LCLU was to be predicted, Markov transition areas file and the suitability image outputted from CA module as inputs. The reader can refer to Nyatuame et al, (2023), Mondal et al (2016), Memarian et al (2012) for on the calibration process for the CA-Markov.…”

Section: Calibration and Validation Of The Ca-markov Modelmentioning

confidence: 99%

“…Calibration and validation of the CA-Markov model are important stages in the forecasting process. The usefulness of the CA-Markov model is dependent on the results of the validation (Nyatuame et al, 2023;Mondal et al, 2016;Memarian et al, 2012).…”

Section: Calibration and Validation Of The Ca-markov Modelmentioning

confidence: 99%

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Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

Zimba,

Banda,

Mbewe

et al. 2024

Preprint

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This study aims to demonstrate the potential of assessing future land cover degradation status by combining the forecasting capabilities of the Cellular-Automata-Markov chain (CA-Markov) models in Idris Selva with the land cover degradation (LCD) model in the Trends.Earth module. The study focuses on the upper Zambezi Basin (UZB) in southern Africa, which is one of the regions with high rates of land degradation globally. Landsat satellite imagery is utilised to generate historical (1993–2023) land cover and land use (LCLU) maps for the UZB, while the European Space Agency Climate Change Initiative (ESA CCI) global LCLU maps are obtained from the Trends.Earth module. The CA-Markov chain model is employed to predict future LCLU changes between 2023 and 2043. The LCD model in the Trends.Earth module in QGIS 3.34 is then used to assess the historical and forecasted land cover degradation status. The findings reveal that land cover degradation maps produced from local LCLU classifications provide more detailed information compared to those produced from the ESA CCI global LCLU product. Between 2023 and 2043, the UZB is predicted to experience a net reduction of approximately 3.2 million hectares of forest cover, with an average annual reduction rate of -0.13%. In terms of land cover degradation, the UZB is forecasted to remain generally stable, with 87% and 96% of the total land cover area expected to be stable during the periods 2023–2033 and 2033–2043, respectively, relative to the base years 2023 and 2033. Reduction in forest cover due to the expansion of grassland, human settlements, and cropland is projected to drive land cover degradation, while improvements in forest cover are anticipated through the conversion of grassland and cropland into forested areas. By leveraging the predictive power of the CA-Markov model and the capabilities of the LCD model, as evidenced in this study, valuable information can be effectively obtained for monitoring land cover degradation. This information can then be used to implement targeted interventions that align with the objective of realising the United Nations' land degradation neutral world target by 2030.

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Section: Calibration and Validation Of The Ca-markov Modelmentioning

confidence: 78%

Section: Calibration and Validation Of The Ca-markov Modelmentioning

confidence: 99%

See 1 more Smart Citation

Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

Zimba,

Banda,

Mbewe

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…The relationship between the LULC type, LULC change, impacts, and controls of land cover change must be presented understandably without oversimplification of the issues or their interactions. This study has adopted and merged two frameworks, namely, the conceptual framework of LULC dynamics (Nyatuame et al, 2023;Suale et al, 2023). The frameworks (Fig.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

Analysis of Trends in Land Utilization and Land Cover Dynamics in the Kwahu West Municipality, Ghana

Aninakwah,

Adu- Boahen,

Edoh

et al. 2024

jag

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The connection between people and the environment has been blamed for changes. Planning for sustainable development requires awareness of land use and land cover (LULC), its severity, causes, and implications. The purpose of this study was to generate maps that illustrate the land use and land cover within the Kwahu West Municipality and detect changes to identify and analyse overall patterns in LULC changes in the area. This research employed remote sensing techniques to assess land use and land cover alterations (LULC). This study used Landsat 7 Enhanced Thematic Mapper (ETM+) images from 2001, Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images from 2015, and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) images from 2023 to detect and quantify LULC changes that occurred over a 22-year study period. Arc GIS 10.8 and ERDAS Envision 13 were used to pre-process the data. According to the study, built-up land and bare land rose in their respective areas and years by 10.675 km2 (or 2%), 18.421 km2 (or 5%), and 29.096 km (or 7%), respectively, between 2001 and 2015 and 2015 and 2023. The overall change from 2001 to 2023 was correspondingly 29.096 km. The results depicted a drastic change in the study area's forest vegetation, which can be attributed to a sharp rise in population, urbanisation, and other infrastructure projects. These changes have been determined to cause biodiversity loss and water contamination. It is recommended that the Municipality's Lands Commission initiate a public education campaign about creating local planning schemes for lands, especially in undeveloped and underdeveloped areas.

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Human-environment nexus: evaluating the anthropo-geomorphology and urban expansion of the Weija Gbawe Municipality, Ghana

Adu-Boahen,

Addai,

Hayford

et al. 2023

Discov Environ

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The study's overarching goal was to examine the dynamics of geomorphological interaction and their effects on the urban expansion of the Weija-Gbawe Municipality in Ghana's Greater Accra Region. The study deployed a quantitative research approach to achieve the objective. A descriptive research design was used in collecting and analyzing data from three hundred and fifty-one (351) participants with a closed-ended questionnaire. The study employed a cluster sampling technique to select the participants based on areas with high concentrations of built-ups and other areas with low concentrations. Using the important relative index (RII), the fundamental level is ranked by the index. SPSS version 26 was used to analyse the data, and the results are shown in a descriptive frequency distribution table. The findings revealed population growth in the Weija-Gbawe Municipality as the main human factor transforming the landscapes' geomorphology, as residents change the landscape for human occupation and industrial uses. Similarly, the topographical terrain, emphasizing slope and elevation were the predominant geomorphological characteristic modifying urban expansion in the Municipality, as settlements were mainly distributed on flat terrain, and the elevation and slope were significant constraints for expansion of the city. Furthermore, urban land utilization in the Weija Gbawe Municipality is distinguished by an industrialized economy and built-up facilities. The paper concludes that applying geographic information systems, remote sensing, and field surveys is essential for generating comprehensive knowledge of urban and anthropocene geomorphology; this is possible through the use of GIS and remote sensing in analyzing the land use land cover changes in the study area. The study suggests enacting, enforcing environmental by-laws, intensifying, and restructuring environmental education by various stakeholders, including the Environmental Protection Agency (EPA) and the Municipality's Physical Planning Agency (PPA). This could be done by bridging the weak linkage between land use/road planning and aborting applications received which were not in line with the planning standards and approving those that are accurate and standard.

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Assessment of past and future land use/cover change over Tordzie watershed in Ghana

Cited by 11 publications

References 42 publications

Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

Integrated use of the CA-Markov model and the Trends.Earth module to enhance the assessment of land cover degradation: Application in the Upper Zambezi Basin, southern Africa

Analysis of Trends in Land Utilization and Land Cover Dynamics in the Kwahu West Municipality, Ghana

Human-environment nexus: evaluating the anthropo-geomorphology and urban expansion of the Weija Gbawe Municipality, Ghana

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