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Tytuł artykułu

Forest loss and land cover land use change. Dynamics in the peri-urban rural districts of Greater Kumasi - Ghana

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Warianty tytułu
PL
Wylesianie i zmiany w pokryciu terenu. Dynamika zmian użytkowania gruntów w podmiejskich okręgach wiejskich Wielkiego Kumasi w Ghanie
Języki publikacji
EN
Abstrakty
EN
The study evaluated the space-time fluctuations of the land cover land use changes (LULCC) in the peri-urban rural districts of Greater Kumasi in Ghana from 1990 to 2020. Several satellite images derived from medium to high-level spatial resolution (Landsat, Disaster Monitoring Constellation (DMC) and Sentinel) in decadal intervals of 1990-2000; 2000-2010 and 2010-2020 were analyzed. The multi-temporal satellite images were preprocessed (georeferenced, radiometrically, and geometrically corrected). The Land use land cover (LULC) maps were derived using the Maximum Likelihood Classifier (MLC) technique and the maps were validated. Comparisons were undertaken in post-classification for the LULCC detection analysis. Closed Forest, Open Forest, Agriculture, Built-up and Water were the five LULC categories defined. Accuracy assessments of the LULC maps were very satisfactory. The results displayed a disturbing forest loss trend. There was forest degradation in protected forests and deforestation in forests outside designated areas from 1990 to 2020. The land use class of Agriculture reduced over the period 1990-2020. For agrarian communities in the study area, this is cause for concern however, it still represented a sizeable land use. Built up category was the largest gainer from 2.27% in 1990 to 18.60% in 2020. Overall, from 1990 to 2020, 62933.20 ha (33.37%) of the study area had undergone an extensive LULCC. Temporal investigation shows that these variations occurred mainly between 1990 and 2000. There was a strong reafforestation in 2000-2010 and forest loss in 2010-2020. Closed forests were preserved, and Open forests were lost in the 30 years of study. This study adds to the endeavors of salvaging what is left of the natural environment and an effort to ascertain the proximate causes of LULCC in the area of study.
PL
W niniejszym artykule zbadano fluktuacje przestrzenno-czasowe zmian pokrycia terenu i użytkowania gruntów (LULCC) w wiejskich okolicach okręgu miejskiego Wielkie Kumasi w Ghanie w latach 1990-2020. Analizie poddano kilka obrazów satelitarnych o średniej i dużej rozdzielczości przestrzennej (Landsat, Disaster Monitoring Constellation - DMC i Sentinel) w interwałach dekadalnych 1990-2000, 2000-2010 i 2010-2020. Wieloczasowe obrazy satelitarne zostały poddane wstępnemu przetwarzaniu (korekcja radiometryczna i geometryczna). Mapy użytkowania terenu (LULC) zostały wygenerowane przy użyciu klasyfikatora największego prawdopodobieństwa (MLC), a następnie poddane ocenie dokładności. Porównania zostały wykonane poprzez analizę wykrywania zmian LULCC po przeprowadzonej klasyfikacji. Zdefiniowano pięć kategorii LULC: Lasy o zwartej strukturze, Lasy o luźnej strukturze, Tereny rolne, Tereny zabudowane i Woda. Ocena dokładności map LULC była bardzo zadowalająca. Wyniki pokazały niepokojącą tendencję ubytku powierzchni leśnych. Zaobserwowano w badanym okresie od 1990 do 2020 r. degradację lasów chronionych oraz wylesianie w lasach poza wyznaczonymi obszarami. Klasa użytkowania Terenów rolnych również zmniejszyła się w okresie 1990-2020. Dla społeczności rolniczych w obszarze badawczym jest to powód do zmartwienia, choć nadal tereny te zajmują istotną część analizowanego obszaru. Z kolei kategoria Terenów zabudowanych odnotowała największy wzrost z 2,27% w 1990 roku do 18,60% w 2020 roku, a obszar badawczy o powierzchni 62933,20 ha (33,37%) przeszedł znaczną zmianę LULCC. Badania wieloczasowe pokazują, że te zmiany wystąpiły głównie między rokiem 1990 a 2000. W latach 2000-2010 obserwowano silne nasadzenia leśne, natomiast w latach 2010-2020 nastąpiła utrata lasów. Lasy o zwartej strukturze zostały zachowane, a Lasy o luźnej strukturze doznały znaczącego zmniejszenia pola powierzchni w analizowanym okresie. Niniejsze badanie przyczynia się do wysiłków mających na celu ocalenie tego, co pozostało z naturalnego środowiska oraz określenie bezpośrednich przyczyn LULCC w obszarze badawczym.
Rocznik
Tom
Strony
5--17
Opis fizyczny
Bibliogr. 48 poz., rys., tab.
Twórcy
  • Kumasi Technical University Institute of Research, Innovation and Development, Kumasi, Ghana
  • Kwame Nkrumah University of Science and Technology Department of Geomatic Engineering, Kumasi, Ghana
  • Brandenburg University of Technology Department of Hydrology, Cottbus, Germany
  • Kumasi Technical University Faculty of Engineering and Technology Department of Civil Engineering, Kumasi, Ghana
  • Coordination Centre for Environmental Projects, Warszawa, Poland
Bibliografia
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  • Abugre, S., Sackey, E.K. 2022. Diagnosis of perception of drivers of deforestation using the partial least squares path modeling approach. Trees, Forests and People, 8: 100246.
  • Acheampong, E.O., Macgregor, C.J., Sloan, S. and Sayer, J. 2019. Deforestation is driven by agricultural expansion in Ghana's forest reserves. Scientific African, 5: e00146.
  • Antwi-Agyei, P., Kpenekuu, F., Hogarh, J.N., Obiri-Danso, K., Abaidoo, R.C., Jeppesen, E. & Andersen, M.N. 2019. Land use and land cover changes in the owabi reservoir catchment, Ghana: implications for livelihoods and management. Geosciences, 9(7): 286.
  • Asante, K.T. 2021. Political Economy of the Oil Palm Value Chain in Ghana.
  • Ayesu, S., Barnes, V.R., & Agbenyega, O. 2021. Threats of Changes in Land-Use and Drivers on Owabi and Barekese Watershed Forests in Ghana. International Journal of Applied Geospatial Research (IJAGR), 12(3): 1-18.
  • Baffour-Ata, F., Antwi-Agyei, P. & Nkiaka, E. 2021. Climate variability, land cover changes and livelihoods of communities on the fringes of Bobiri Forest Reserve, Ghana. Forests, 12(3): 278.
  • Bawa, S.A., Antwi-Agyei, P. & Domfeh, M.K. 2022. Impact of the ban on illegal mining activities on raw water quality: A case-study of Konongo Water Treatment Plant, Ashanti Region of Ghana. Journal of Sustainable Mining, 21(2): 80.
  • Behera, D.K. 2012. Economic growth and sectoral linkages: Empirical evidence from Odisha. Journal of Regional Development and Planning, 1(2): 91-102.
  • Brobbey, L.K., Agyei, F.K. & Osei-Tutu, P. 2020. Drivers of cocoa encroachment into protected forests: The case of three forest reserves in Ghana. International Forestry Review, 22(4): 425-437.
  • Cillis, G., Statuto, D. & Picuno, P. 2021. Historical gis as a tool for monitoring, preserving and planning forest landscape: A case study in a mediterranean region. Land, 10(8): 851.
  • Clerici, N., Cote-Navarro, F., Escobedo, F.J., Rubiano, K. & Villegas, J.C. 2019. Spatio-temporal and cumulative effects of land use-land cover and climate change on two ecosystem services in the Colombian Andes. Science of the Total Environment, 685: 1181-1192.
  • Fearnside, P.M. 1993. Deforestation in Brazilian Amazonia: The effect of population and land tenure. Ambio-Journal of Human Environment Research and Management, 22(8): 537-545.
  • Forestry Commission. 2014. National REDD+ R-PP implementation mid-term progress report and request for additional funding. Accra, Ghana.
  • Frimpong, B.F. & Molkenthin, F. 2021. Tracking urban expansion using random forests for the classification of landsat imagery (1986-2015) and predicting urban/built-up areas for 2025: A study of the kumasi metropolis, Ghana. Land, 10(1): 44.
  • Ghana Statistical Service (GSS). 2021. 2021 Population and Housing census National analytical report. Accra, Ghana: 1-430.
  • Gomes, L.C., Bianchi, F.J.J.A., Cardoso, I.M., Schulte, R.P.O., Arts, B.J.M. & Fernandes Filho, E.I. 2020. Land use and land cover scenarios: An interdisciplinary approach integrating local conditions and the global shared socio-economic pathways. Land Use Policy, 97: 104723.
  • Govender, T., Dube, T. & Shoko, C. 2022. Remote sensing of land use-land cover change and climate variability on hydrological processes in Sub-Saharan Africa: Key scientific strides and challenges. Geocarto International: 1-25.
  • Hemati, M., Hasanlou, M., Mahdianpari, M. & Mohammadimanesh, F. 2021. A systematic review of landsat data for change detection applications: 50 years of monitoring the earth. Remote sensing, 13(15): 2869.
  • Hua, A.K. 2017. Application of Ca-Markov model and land use/land cover changes in Malacca River Watershed, Malaysia. Applied Ecology and Environmental Research, 15(4): 605-622.
  • Ishiyama, N., Miura, K., Inoue, T., Sueyoshi, M. & Nakamura, F. 2021. Geology-dependent impacts of forest conversion on stream fish diversity. Conservation Biology, 35(3): 884-896.
  • Jarzebski, M.P., Ahmed, A., Karanja, A., Boafo, Y.A., Balde, B.S., Chinangwa, L., Degefa, S., Dompreh, E.B., Saito, O. & Gasparatos, A. 2020. Linking industrial crop production and food security in sub-Saharan Africa: Local, national and continental perspectives. In Sustainability Challenges in Sub-Saharan Africa I. Springer, Singapore: 81-136.
  • Khamaru, L., Chakraborty, J., Samanta, S., Banerjee, D. & Dutta, S.B. 2022. Assessment and monitoring of urbanisation on Himalayan lacustrine environment. A case study in Mirik municipality area. GeoJournal, 87 (Suppl 4): 703-722.
  • Koranteng, A., Adu-Poku, I., Donkor, E. & Zawiła-Niedźwiecki, T. 2020. Geospatial assessment of land use and land cover dynamics in the mid-zone of Ghana. Folia Forestalia Polonica, Series A - Forestry, Vol. 62(4): 288-305.
  • Le Boulzec, H. 2022. The raw materials conundrum of the energy transition: an energy and building sectors approach (Doctoral dissertation, Université Grenoble Alpes, 2020).
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  • Liu, M., Wei, H., Dong, X., Wang, X.C., Zhao, B. & Zhang, Y. 2022. Integrating Land Use, Ecosystem Service, and Human Well-Being: A Systematic Review. Sustainability, 14(11): 6926.
  • Liu, W., Zhan, J., Zhao, F., Yan, H., Zhang, F. & Wei, X. 2019. Impacts of urbanization-induced land-use changes on ecosystem services: A case study of the Pearl River Delta Metropolitan Region, China. Ecological Indicators, 98: 228-238.
  • Mahmud, A. & Achide, A.S. 2012. Analysis of land use/land cover changes to monitor urban sprawl in Keffi-Nigeria. Environmental Research Journal, 6(2): 130-135.
  • Makwinja, R., Kaunda, E., Mengistou, S. & Alamirew, T., 2021. Impact of land use/land cover dynamics on ecosystem service value - A case from Lake Malombe, Southern Malawi. Environmental Monitoring and Assessment, 193(8): 1-23.
  • Mekuria, W., Gebregziabher, G. & Lefore, N. 2020. Exclosures for landscape restoration in Ethiopia: Business model scenarios and suitability, Vol. 175. IWMI.
  • Mhangara, P. 2011. Land use/cover change modelling and land degradation assessment in the Keiskamma catchment using remote sensing and GIS (Doctoral dissertation).
  • Mohan Rajan, S.N., Loganathan, A. & Manoharan, P. 2020. Survey on Land Use/Land Cover (LU/LC) change analysis in remote sensing and GIS environment: Techniques and Challenges. Environmental Science and Pollution Research, 27(24): 29900-29926.
  • Nti, T. 2020. Illegal Mining and Sustainability Performance: Evidence from Ashanti Region, Ghana. International Journal of Scientific Research and Management (IJSRM), 8(3).
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  • Ogidi, O.I. & Akpan, U.M. 2022. Aquatic Biodiversity Loss: Impacts of Pollution and Anthropogenic Activities and Strategies for Conservation. In Biodiversity in Africa: Potentials, Threats and Conservation. Springer, Singapore: 421-448.
  • Panuju, D.R., Paull, D.J. & Griffin, A.L. 2020. Change detection techniques based on multispectral images for investigating land cover dynamics. Remote Sensing, 12(11): 1781.
  • Parsa, M., Dirgahayu, D., Harini, S. & Kushardono, D. 2020. Optimization of a Rice Field Classification Model Based on The Threshold Index of Multi-Temporal Landsat Images. International Journal of Remote Sensing and Earth Sciences, 17(1): 75-84.
  • Siqueira-Gay, J., Soares-Filho, B., Sanchez, L.E., Oviedo, A., & Sonter, L.J. 2020. Proposed legislation to mine Brazil's Indigenous lands will threaten Amazon forests and their valuable ecosystem services. One Earth, 3(3): 356-362.
  • Snedecor, G.W. & Cochran, W.G. 1989. Statistical Methods, Eighth Edition, Iowa State University Press.
  • Souza Jr, C.M., Z. Shimbo, J., Rosa, M.R., Parente, L.L., A. Alencar, A., Rudorff, B.F., Hasenack, H., Matsumoto, M., G. Ferreira, L., Souza-Filho, P.W. & de Oliveira, S.W. 2020. Reconstructing three decades of land use and land cover changes in brazilian biomes with landsat archive and earth engine. Remote Sensing, 12(17): 2735.
  • Takyi, S.A., Amponsah, O., Yeboah, A.S., & Mantey, E. 2021. Locational analysis of slums and the effects of slum dweller’s activities on the social, economic and ecological facets of the city: Insights from Kumasi in Ghana. GeoJournal, 86(6): 2467-2481.
  • Tariq, A., Yan, J., Gagnon, A.S., Riaz Khan, M. & Mumtaz, F. 2022. Mapping of cropland, cropping patterns and crop types by combining optical remote sensing images with decision tree classifier and random forest. Geo-spatial Information Science: 1-19.
  • Tong, X.Y., Xia, G.S., Lu, Q., Shen, H., Li, S., You, S. & Zhang, L. 2020. Land-cover classification with high-resolution remote sensing images using transferable deep models. Remote Sensing of Environment, 237: 111322.
  • Verma, P., Raghubanshi, A., Srivastava, P.K. & Raghubanshi, A.S. 2020. Appraisal of kappa-based metrics and disagreement indices of accuracy assessment for parametric and nonparametric techniques used in LULC classification and change detection. Modeling Earth Systems and Environment, 6(2): 1045-1059.
  • Yuan, Q., Shen, H., Li, T., Li, Z., Li, S., Jiang, Y., Xu, H., Tan, W., Yang, Q., Wang, J. & Gao, J. 2020. Deep learning in environmental remote sensing: Achievements and challenges. Remote Sensing of Environment, 241: 111716.
  • Zurmotai, N.H. 2020. GIS, Remote Sensing and GPS: Their activity, Integration and Fieldwork. IJAR, 6(9): 328-332.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f2690994-2061-417d-aaeb-bf8731a464b4
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