Int. J. Fores. Env. | Volume 06, Issue 01, 235-244 | https://doi.org/10.18801/ijfee.060122.25
Article type: Research article | Received: 11.08.22; Revised: 01.11.22; First published online: 25 December 2022.
Article type: Research article | Received: 11.08.22; Revised: 01.11.22; First published online: 25 December 2022.
Change detection of the Upper Orashi forest wetland of Nigeria, using geospatial analysis
Iwebuke Edo¹, Evidence Chinedu Enoguanbhor 2&3 and Eike Albrecht ¹
¹ Faculty 5, Business, Law and Social Sciences, Department of Civil Law and Public Law with Reference to the Law of Europe and the Environment, Brandenburg University of Technology Cottbus-Senftenberg (BTU), 03046 Cottbus, Germany.
² Institute of Geography (Applied Geoinformation Science Lab), Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
3 Integrative Research Institute on Transformations of Human-Environmental Systems, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
✉ Corresponding author: [email protected] (Edo, I).
¹ Faculty 5, Business, Law and Social Sciences, Department of Civil Law and Public Law with Reference to the Law of Europe and the Environment, Brandenburg University of Technology Cottbus-Senftenberg (BTU), 03046 Cottbus, Germany.
² Institute of Geography (Applied Geoinformation Science Lab), Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
3 Integrative Research Institute on Transformations of Human-Environmental Systems, Humboldt University of Berlin, Unter den Linden 6, 10099 Berlin, Germany
✉ Corresponding author: [email protected] (Edo, I).
Abstract
Wetland is an essential ecosystem that provides numerous goods and services such as tourism and recreation, water purification, and groundwater recharge. It also acts as a carbon sink, which means that it is an essential asset in reducing the level of greenhouse gases in the environment. Despite the value, wetlands are disappearing at a fast rate, however, the need to ascertain the state of Upper Orsahi forest reserve wetland with respect to wetlands change. To ascertain the net and transition change detection in the wetland area of the Upper Orashi Forest Wetland, land cover classification change was performed using Geographic Information Systems and Remote Sensing methods, particularly the supervised classification of land cover data for 2002, 2013, and 2019. The land cover was classified into three classes: wetland, thick vegetation and light vegetation. The result shows a significant degradation of the Upper Orashi forest reserve wetlands within the study period. The data from the questionnaire is to know which sector and activities in the area result in wetland loss. The result shows that industrial sector is the major driver of wetland loss in the area, while the activities include; building of industries, installation of oil and gas facilities, and agriculture. This means that the available laws used to manage Nigeria's wetlands are ineffective. However, there is an urgent need to enact a new regulation for effective/sustainable management of wetlands in the country.
Key Words: Wetlands, Environment, Niger delta, Vegetation, Class and laws.
Wetland is an essential ecosystem that provides numerous goods and services such as tourism and recreation, water purification, and groundwater recharge. It also acts as a carbon sink, which means that it is an essential asset in reducing the level of greenhouse gases in the environment. Despite the value, wetlands are disappearing at a fast rate, however, the need to ascertain the state of Upper Orsahi forest reserve wetland with respect to wetlands change. To ascertain the net and transition change detection in the wetland area of the Upper Orashi Forest Wetland, land cover classification change was performed using Geographic Information Systems and Remote Sensing methods, particularly the supervised classification of land cover data for 2002, 2013, and 2019. The land cover was classified into three classes: wetland, thick vegetation and light vegetation. The result shows a significant degradation of the Upper Orashi forest reserve wetlands within the study period. The data from the questionnaire is to know which sector and activities in the area result in wetland loss. The result shows that industrial sector is the major driver of wetland loss in the area, while the activities include; building of industries, installation of oil and gas facilities, and agriculture. This means that the available laws used to manage Nigeria's wetlands are ineffective. However, there is an urgent need to enact a new regulation for effective/sustainable management of wetlands in the country.
Key Words: Wetlands, Environment, Niger delta, Vegetation, Class and laws.
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MLA
Edo, I. et al. "Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis". International Journal of Forestry, Ecology and Environment 06(01) (2022): 235-244.
APA
Edo, I., Enoguanbhor, E. C. and Albrecht, E. (2022). Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment, 06(01), 235-244.
Chicago
Edo, I., Enoguanbhor, E. C. and Albrecht, E. "Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis". International Journal of Forestry, Ecology and Environment 06(01) (2022): 235-244.
Harvard
Edo, I., Enoguanbhor, E. C. and Albrecht, E. 2022.Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment, 06(01), pp. 235-244.
Vancouver
Edo, I, Enoguanbhor, EC and Albrecht, E.Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment. 2022 December 06(01): 235-244.
Edo, I. et al. "Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis". International Journal of Forestry, Ecology and Environment 06(01) (2022): 235-244.
APA
Edo, I., Enoguanbhor, E. C. and Albrecht, E. (2022). Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment, 06(01), 235-244.
Chicago
Edo, I., Enoguanbhor, E. C. and Albrecht, E. "Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis". International Journal of Forestry, Ecology and Environment 06(01) (2022): 235-244.
Harvard
Edo, I., Enoguanbhor, E. C. and Albrecht, E. 2022.Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment, 06(01), pp. 235-244.
Vancouver
Edo, I, Enoguanbhor, EC and Albrecht, E.Change detection of the Upper Orashi Forest Wetland of Nigeria, using Geospatial Analysis. International Journal of Forestry, Ecology and Environment. 2022 December 06(01): 235-244.
References:
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[21]. Kwan, C. Gribben, D., Ayhan, B., Li, J., Bernabe, S. and Plaza, A. (2020). An Accurate Vegetation and Non-Vegetation Differentiation Approach Based on Land Cover Classification. Remote Sensing, 12(23), 3880. https://doi.org/10.3390/rs12233880
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[24]. Milton, G. R., Prentice, R. C. and Finlayson, C. M. (2018). Wetlands of the World. In: Finlayson, C., Milton, G., Prentice, R., Davidson, N. (eds). The Wetland Book. Dordrecht. https://doi.org/10.1007/978-94-007-4001-3_182
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[26]. Naeem, S. Chazdon, R., Duffy, J. E., Prager, C. and Worm, B. (2016). Biodiversity and human well-being: an essential link for sustainable development. Proceedings of the Royal Society B: Biological Sciences, 283(1844), 2016-2091. https://doi.org/10.1098/rspb.2016.2091
[27]. Nwogwugwu, N., Alao, O. and Egwuonwu, C. (2012). Militancy and insecurity in the Niger Delta: Impact on the inflow of foreign direct investment to Nigeria. Kuwait Chapter of Arabian Journal of Business and Management Review, 2(1), p. 23 – 37.
[28]. Onamuti, O. Y., Okogbue, E. C. and Orimoloye, I. R. (2017). Remote sensing appraisal of Lake Chad shrinkage connotes severe impacts on green economics and socio-economics of the catchment area. Royal Society Open Science, 4(11), 171120. https://doi.org/10.1098/rsos.171120
[29]. Orimoloye, I. R., Kalumba, A. M., Sonwabo P. Mazinyo, S. P. and Nel, W. (2018). Geospatial analysis of wetland dynamics: Wetland depletion and biodiversity conservation of Isimangaliso Wetland, South Africa. Journal of King Saud University Science, pp. 1 - 8.
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[33]. Rebecca, B. (2014). Improving the employer brand image of Company X amongst students in Finland, Helsinki: Haaga Helia University of applied science.
[34]. Rebelo, L. and Mathew, M. (2019). Earth observation data offers hope for Africa's wetlands for Africa's wetlands, s.l.: the conversation.
[35]. Robert, E. S. (2022). Technical Aspects of Wetlands, Wetlands as Bird Habitat, s.l.: United States Geological Survey Water Supply Paper 2425.
[36]. Satish, S. N., Shruthi, G. C. and Kiran, B. M. (2017). Applications of GIS & RS for Wetland Management in Mudigere Taluk, Chikkamagalur District, Karnataka. International Journal of Emerging Research in Management Technology, 6(9), 54 -60. https://doi.org/10.23956/ijermt.v6i9.85
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[38]. Tso, B. and Mather, P. M. (2009). Classification methods for remotely sensed data. Boca Raton: CRC Press.
[39]. Uluocha, N. O. and Okeke, I. C. (2004). Implications of wetlands degradation for water resources management: lessons from Nigeria. Geological Journal, 61(2), 51–154. https://doi.org/10.1007/s10708-004-2868-3
[40]. United Nations Environmental Programme (UNEP) (2012). The GEF's Strategic Programme for West Africa (SPWA) – Sub-component Biodiversity: Niger Delta Biodiversity Project, Lagos: Prodoc.
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[42]. Waldron, A. Miller, D., Redding, D. et al. (2017). Reductions in global biodiversity loss predicted from conservation spending. Nature, 551, 364 -367. https://doi.org/10.1038/nature24295
[43]. Weihua, X. et al. (2019). Hidden Loss of Wetlands in China. Cellpress, 29(18), 3065-3071. https://doi.org/10.1016/j.cub.2019.07.053
[2]. Armand, L. et al. (2020). Wetland Mapping with Landsat 8 OLI, Sentinel-1, ALOS-1 PALSAR, and LiDAR Data in Southern New Brunswick, Canada. Remote Sensing MDPI.
[3]. Campbell, J. B. and Wynne, R. H. (2011). Introduction to Remote Sensing. 5th ed. New York: The Guilford Press.
[4]. Cane, P. and Kritzer, H. M. (2012). The Oxford Handbook of Empirical Legal Research. Oxford: Oxford University Press. https://doi.org/10.1111/j.1740-1461.2011.01248.x
[5]. Davidson, N. C. (2014). How much wetland has the world lost? Long-term and recent trends in global wetland area. Marine and Freshwater Research, 65(10), 934-941. https://doi.org/10.1071/MF14173
[6]. Verschuren, D., Johnson, T. C., Kling, H. J., Edgington, D. N., Leavitt, P. R., Brown, E. T., . . . Hecky, R. E. (2002). History and timing of human impact on Lake Victoria, East Africa. Proceedings of the Royal Society of London. Series B: Biological Sciences, 269(1488), 289-294. https://doi.org/10.1098/rspb.2001.1850
[7]. Edo, I. and Albrecht, E. (2021). Threats to Niger-Delta Wetlands: A Case Study of Apoi Creek Forest. Open Journal of Ecology, 11, 136-147. https://doi.org/10.4236/oje.2021.112012
[8]. Elias, E. C. (2016). Spaces of Insurgency: Petro-Violence and the Geography of Conflict in Nigeria's Niger Delta, Berkeley: University of California.
[9]. Enoguanbhor, E. C. Gollnow, F., Nielsen, J. O., Lakes, T., Walker, B. B. (2019). Land Cover Change in the Abuja City-Region, Nigeria: Integrating GIS and Remotely Sensed Data to Support Land Use Planning. Sustainability, 11(5), 1313. https://doi.org/10.3390/su11051313
[10]. Enoguanbhor, E. C., Gollnow, F., Walker, B. B. et al. (2020). Simulating Urban Land Expansion in the Context of Land Use Planning in the Abuja City-Region, Nigeria. GeoJournal, 87, 1479-1497. https://doi.org/10.1007/s10708-020-10317-x
[11]. European Commission (2007). Life and Europe's wetlands: restoring a vital ecosystem, Luxembug: Office for official publications of the European Communities.
[12]. Fengqin, Y. et al. (2017). Monitoring spatiotemporal changes of marshes in the Sanjiang Plain China. Ecological Engineering, 104, 184-194. https://doi.org/10.1016/j.ecoleng.2017.04.032
[13]. Galloway, A. (2005). Non-Probability Sampling. In K. Kempf-Leonard (Ed.), Encyclopedia of Social Measurement (pp. 859-864). New York: Elsevier. https://doi.org/10.1016/B0-12-369398-5/00382-0
[14]. Hemba, S. I. E. T. and Orimoloye, I. R. (2017). Analysis of the Physical Growth and Expansion of Makurdi Town Using Remote Sensing and GIS Techniques. Imperial journal of interdisciplinary research, 3(7), .1 -7.
[15]. Hilton-Taylor, C. (2000). IUCN Red List of Threatened Species. IUCN, Gland, Switzerland and Cambridge, United Kingdom: IUCN.
[16]. Hirsch, D. l. et al. (2011). Acknowledging Conservation Trade-Offs and Embracing Complexity. Conservation Biology, 25(2), 259-264. https://doi.org/10.1111/j.1523-1739.2010.01608.x
[17]. Ilker, E., Sulaiman, A. M. and Rukayya, S. A. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11
[18]. Izah, S. C. (2018). Ecosystem of the Niger Delta region of Nigeria: Potentials and Threats. Biodiversity International Journal, 2(4), pp. 338-345. https://doi.org/10.15406/bij.2018.02.00084
[19]. Jiang, L., Liu, Y., Wu, S. and Yang, C. (2021). Analyzing ecological environment change and associated driving factors in China based on NDVI time series data. Ecological Indicators, 129, 107933. https://doi.org/10.1016/j.ecolind.2021.107933
[20]. Song, K, Wang, Z., Du, J. et al. (2014). Wetland Degradation: Its Driving Forces and Environmental Impacts in the Sanjiang Plain, China. Environmental Management, 54, 255–271. https://doi.org/10.1007/s00267-014-0278-y
[21]. Kwan, C. Gribben, D., Ayhan, B., Li, J., Bernabe, S. and Plaza, A. (2020). An Accurate Vegetation and Non-Vegetation Differentiation Approach Based on Land Cover Classification. Remote Sensing, 12(23), 3880. https://doi.org/10.3390/rs12233880
[22]. Liu, X. T. and Ma, X. H. (2002). Natural environmental changes and ecological protection in the Sanjiang Plain in China. Beijing: Science press.
[23]. Lu, D., Weng, Q., Moran, E. L. G. and Hetrick, S. (2011). Remote Sensing Image Classification. In: Weng, Q. (Ed.), Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications. Boca Raton: Tailor & Francis Group. https://doi.org/10.1080/01431161.2010.547884
[24]. Milton, G. R., Prentice, R. C. and Finlayson, C. M. (2018). Wetlands of the World. In: Finlayson, C., Milton, G., Prentice, R., Davidson, N. (eds). The Wetland Book. Dordrecht. https://doi.org/10.1007/978-94-007-4001-3_182
[25]. Mitsch, W. J., Bernal, B. and Hernandez, M. E. (2015). Ecosystem services of wetlands. International Journal of Biodiversity Science, Ecosystem Services & Management, 11, 1-4. https://doi.org/10.1080/21513732.2015.1006250
[26]. Naeem, S. Chazdon, R., Duffy, J. E., Prager, C. and Worm, B. (2016). Biodiversity and human well-being: an essential link for sustainable development. Proceedings of the Royal Society B: Biological Sciences, 283(1844), 2016-2091. https://doi.org/10.1098/rspb.2016.2091
[27]. Nwogwugwu, N., Alao, O. and Egwuonwu, C. (2012). Militancy and insecurity in the Niger Delta: Impact on the inflow of foreign direct investment to Nigeria. Kuwait Chapter of Arabian Journal of Business and Management Review, 2(1), p. 23 – 37.
[28]. Onamuti, O. Y., Okogbue, E. C. and Orimoloye, I. R. (2017). Remote sensing appraisal of Lake Chad shrinkage connotes severe impacts on green economics and socio-economics of the catchment area. Royal Society Open Science, 4(11), 171120. https://doi.org/10.1098/rsos.171120
[29]. Orimoloye, I. R., Kalumba, A. M., Sonwabo P. Mazinyo, S. P. and Nel, W. (2018). Geospatial analysis of wetland dynamics: Wetland depletion and biodiversity conservation of Isimangaliso Wetland, South Africa. Journal of King Saud University Science, pp. 1 - 8.
[30]. Ramsar (2008). Ramsar Sites Information Service. [Online] Available at: https://rsis.ramsar.org/ris/1759 [Accessed 07 09 2021].
[31]. Ramsar Convention on Wetlands (2018). Global wetland outlook: state of the world's wetlands and their services to people, Gland, Switzerland: Ramsar Convention Secretariat.
[32]. Ramsar, (2007). Information Sheet on Ramsar Wetlands. [Online] Available at: https://rsis.ramsar.org/RISapp/files/RISrep/NG1759RIS.pdf [Accessed 07. 09.2021].
[33]. Rebecca, B. (2014). Improving the employer brand image of Company X amongst students in Finland, Helsinki: Haaga Helia University of applied science.
[34]. Rebelo, L. and Mathew, M. (2019). Earth observation data offers hope for Africa's wetlands for Africa's wetlands, s.l.: the conversation.
[35]. Robert, E. S. (2022). Technical Aspects of Wetlands, Wetlands as Bird Habitat, s.l.: United States Geological Survey Water Supply Paper 2425.
[36]. Satish, S. N., Shruthi, G. C. and Kiran, B. M. (2017). Applications of GIS & RS for Wetland Management in Mudigere Taluk, Chikkamagalur District, Karnataka. International Journal of Emerging Research in Management Technology, 6(9), 54 -60. https://doi.org/10.23956/ijermt.v6i9.85
[37]. Thomas, W. E. and David, O. M. (2017). Research Methods for Cyber Security, Cambridge, MA: Syngress, an imprint of Elsevie. pp404.
[38]. Tso, B. and Mather, P. M. (2009). Classification methods for remotely sensed data. Boca Raton: CRC Press.
[39]. Uluocha, N. O. and Okeke, I. C. (2004). Implications of wetlands degradation for water resources management: lessons from Nigeria. Geological Journal, 61(2), 51–154. https://doi.org/10.1007/s10708-004-2868-3
[40]. United Nations Environmental Programme (UNEP) (2012). The GEF's Strategic Programme for West Africa (SPWA) – Sub-component Biodiversity: Niger Delta Biodiversity Project, Lagos: Prodoc.
[41]. United States Geological Surveys (2019). USGS science for a changing world. s.l.: s.n.
[42]. Waldron, A. Miller, D., Redding, D. et al. (2017). Reductions in global biodiversity loss predicted from conservation spending. Nature, 551, 364 -367. https://doi.org/10.1038/nature24295
[43]. Weihua, X. et al. (2019). Hidden Loss of Wetlands in China. Cellpress, 29(18), 3065-3071. https://doi.org/10.1016/j.cub.2019.07.053
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