Evaluation of the Forest Quantity, Quality and Management through Gray Relational Analysis Method

Yıl 2022, Cilt: 10 Sayı: 2, 27 - 41, 05.09.2022

Gökhan Özkaya Ceren Erdin

https://doi.org/10.31195/ejejfs.1047538

Öz

Forests cover 30 per cent of the Earth’s land surface, almost four billion hectares. They are necessary to sustain human health, economic growth and the environment. Also, approximately 25 per cent of the global population depends on forests for food and work. The world population is expected to reach 9.6 billion by 2050. Therefore, there needs to be quick action at all levels to make sure that forests are managed in a way that is good for the environment and our way of life in the future. The Sustainable Forest Management Goals are included in the major headings of Sustainable Development Goals and the United Nations Strategic Plan for Forests 2017–2030. The data for the worldwide and six geographical areas were assessed using the Gray Relational Analysis (GRA) approach, which is one of the Multi-Criteria Decision Making methodologies. The major goal of the study is to use the GRA mathematical approach to assess data from 6 geographical areas, totalling 245 regions and nations, and 236 countries and regions worldwide. The second purpose is to contribute to the existing literature by expanding the geographical scope, number of indicators, and the time period covered by the study. The study also aims to provide information on new forest quality and management technologies, as well as the change of geographical areas over 30 years. South America consistently comes out on top in interregional comparisons. On the other hand, Oceania ranks last in the rankings. While the scores for 1990 increased markedly for all regions and worldwide in 2000, the performance values for the years 2000, 2010 and 2020 are fairly close to each other. The findings and methods of this study are aimed to be a useful resource for future researchers and policymakers.

Anahtar Kelimeler

monitoring and reporting, sustainable ecosystem, sustainable development goals, forest management, gray relational analysis, global forest goals

Destekleyen Kurum

Yildiz Technical University Scientific Research Projects Coordination Unit

Proje Numarası

SBA-2021-4323

Teşekkür

We are thankful to Yildiz Technical University Scientific Research Projects Coordination Unit for their support to our manuscript with the project ID: SBA-2021-4323.

Kaynakça

• Achard, F., Boschetti, L., Brown, S., Brady, M., DeFries, R., Grassi, G., . . . Pandey, D. (2014). A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals associated with deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation: GOFC-GOLD.
• Ananda, J., & Herath, G. (2009). A critical review of multi-criteria decision-making methods with special reference to forest management and planning. Ecological economics, 68(10), 2535-2548.
• Asner, G. P., Powell, G. V., Mascaro, J., Knapp, D. E., Clark, J. K., Jacobson, J., . . . Victoria, E. (2010). High-resolution forest carbon stocks and emissions in the Amazon. Proceedings of the National Academy of Sciences, 107(38), 16738-16742.
• Assembly, U. N. G. (2012). International Day of Forests.
• Baccini, A., Goetz, S., Walker, W., Laporte, N., Sun, M., Sulla-Menashe, D., . . . Friedl, M. (2012). Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature climate change, 2(3), 182.
• Barducci, A., Guzzi, D., Marcoionni, P., & Pippi, I. (2002). Infrared detection of active fires and burnt areas: theory and observations. Infrared physics & technology, 43(3-5), 119-125. doi: 10.1016/S1350-4495(02)0012-9
• Baynes, J., Herbohn, J., Smith, C., Fisher, R., & Bray, D. (2015). Key factors which influence the success of community forestry in developing countries. Global Environmental Change, 35, 226-238.
• Berry, J. K. (1993). Beyond mapping: concepts, algorithms, and issues in GIS: GIS World Books Fort Collins, Colorado, USA.
• Bolstad, P. (2005). GIS Fundamentals: a first text on Geographic Information Systems: Eider Press.
• Burrough, P. A., McDonnell, R., McDonnell, R. A., & Lloyd, C. D. (2015). Principles of geographical information systems: Oxford university press.
• Çağlayan, İ., Koç, M., & Demirel, T. Ranking of strategic plans with GRA on the basis of recreation and water production; the case of belgrade forest.
• Çağlayan, İ., Koç, M., & Demirel, T. (2017). Ranking of strategic plans with GRA on the basis of recreation and water production; the case of belgrade forest.
• Cashore, B., Gale, F., Meidinger, E., & Newsom, D. (2006). Confronting sustainability: Forest certification in developing and transitioning countries: Yale University Faculty of Environmental Studies Publication Series.
• Chan, J. W., & Tong, T. K. (2007). Multi-criteria material selections and end-of-life product strategy: Grey relational analysis approach. Materials & Design, 28(5), 1539-1546. Daşdemir, İ., & Güngör, E. (2010). Çok kriterli ve katılımcı yaklaşımla orman kaynaklarının işlevsel önceliklerinin belirlenmesi: Ulus Devlet Orman İşletmesi örneği. Bartın Orman Fakültesi Dergisi, 12(17), 11-25.
• De Jong, B. H. J. (2010). A sourcebook of methods and procedures for monitoring and reporting anthropogenic greenhouse gas emissions and removals caused by deforestation, gains and losses of carbon stocks in forests remaining forests, and forestation.
• FAO. (2010). Global forest resources assessment 2010.
• FAO. (2013). Voluntary guidelines on national forest monitoring—draft version for discussion of sections I and II.
• FAO. (2018). The State of the World’s Forests 2018 - Forest pathways to sustainable development. Rome.
• FAO. (2020). Global Forest Resources Assessment 2020: Main Reports.
• Feng, C.-M., & Wang, R.-T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6(3), 133-142.
• Gai, C., Weng, W., & Yuan, H. (2011). GIS-based forest fire risk assessment and mapping. Paper presented at the 2011 Fourth International Joint Conference on Computational Sciences and Optimization.
• GOFC-GOLD, A. (2010). A Sourcebook of Methods and Procedures for Monitoring and Reporting Anthropogenic Greenhouse Gas Emissions and Removals Caused by Deforestation, Gains and Losses of Carbon Stocks in Forests Remaining Forests, and Forestation. AB, Canada: GOFC-GOLD GOFC-GOLD Project Office. Natural Resources Canada Calgary.
• Gulliver, J., de Hoogh, K., Fecht, D., Vienneau, D., & Briggs, D. (2011). Comparative assessment of GIS-based methods and metrics for estimating long-term exposures to air pollution. Atmospheric Environment, 45(39), 7072-7080.
• Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S., Tyukavina, A., . . . Loveland, T. R. (2013). High-resolution global maps of 21st-century forest cover change. Science, 342(6160), 850-853. doi: 10.1126/science.1244693
• Henry, M., Réjou-Méchain, M., Jara, M. C., Wayson, C., Piotto, D., Westfall, J., . . . López, E. C. (2015). An overview of existing and promising technologies for national forest monitoring. Annals of Forest Science, 72(6), 779-788.
• Holmgren, P., & Thuresson, T. (1998). Satellite remote sensing for forestry planning—a review. Scandinavian Journal of Forest Research, 13(1-4), 90-110.
• Jordan, A. (2006). The environmental case for Europe: Britain's European environmental policy: CSERGE Working Paper EDM.
• Ju-Long, D. (1982). Control problems of grey systems. Systems & control letters, 1(5), 288-294.
• Kangas, J., & Kangas, A. (2005). Multiple criteria decision support in forest management—the approach, methods applied, and experiences gained. Forest ecology and management, 207(1-2), 133-143.
• Karaatlı, M., Ömürbek, N., Budak, İ., & Dağ, O. (2015). Çok kriterli karar verme yöntemleri ile yaşanabilir illerin sıralanması. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi(33), 215-228.
• Kleinn, C. (2003). New technologies and methodologies for national forest inventories. UNASYLVA-FAO-, 10-15. Lee, W.-S., & Lin, Y.-C. (2011). Evaluating and ranking energy performance of office buildings using Grey relational analysis. Energy, 36(5), 2551-2556.
• Lindquist, E. J., D'Annunzio, R., Gerrand, A., MacDicken, K., Achard, F., Beuchle, R., . . . San-Miguel-Ayanz, J. (2012). Global forest land-use change 1990-2005: Food and agriculture organization of the United Nations (FAO).
• Maniatis, D., & Mollicone, D. (2010). Options for sampling and stratification for national forest inventories to implement REDD+ under the UNFCCC. Carbon balance and management, 5(1), 9.
• Mitchard, E. T., Saatchi, S. S., Baccini, A., Asner, G. P., Goetz, S. J., Harris, N. L., & Brown, S. (2013). Uncertainty in the spatial distribution of tropical forest biomass: a comparison of pan-tropical maps. Carbon balance and management, 8(1), 10.
• Mitchell, R. B. (2002). International Environmental Agreements (IEA) Database Project.
• Nations, U. (2017). United Nations Strategic Plan for Forests, 2017-2030.
• Nilsson, H., Nordström, E.-M., & Öhman, K. (2016). Decision support for participatory forest planning using AHP and TOPSIS. Forests, 7(5), 100.
• Ok, K., Okan, T., & Yilmaz, E. (2011). A comparative study on activity selection with multi-criteria decision-making techniques in ecotourism planning. Scientific Research and Essays, 6(6), 1417-1427.
• Pimm, S. L., Alibhai, S., Bergl, R., Dehgan, A., Giri, C., Jewell, Z., . . . Loarie, S. (2015). Emerging technologies to conserve biodiversity. Trends in ecology & evolution, 30(11), 685-696.
• Rejou-Mechain, M., Muller-Landau, H. C., Detto, M., Thomas, S., Toan, T. L., Saatchi, S., . . . Butt, N. (2014). Local spatial structure of forest biomass and its consequences for remote sensing of carbon stocks. Biogeosciences Discussions, 11, 5711.
• Saatchi, S. S., Harris, N. L., Brown, S., Lefsky, M., Mitchard, E. T., Salas, W., . . . Hagen, S. (2011). Benchmark map of forest carbon stocks in tropical regions across three continents. Proceedings of the National Academy of Sciences, 108(24), 9899-9904.
• Selin, H., & VanDeveer, S. D. (2015). EU Environmental Policy Making and Implementation: Changing Processes and Mixed Outcomes.
• Stanujkic, M., Nikolic, D., & Stanujkic, D. Using MCDM Methods for Evaluating Harvesting Zone Scenarios In Forest Planning From Environmental Management Perspective.
• Tang, C.-W., & Young, H.-T. (2013). Using Grey relational analysis to determine wet chemical etching parameters in through-silicon-via etching application. Materials science in semiconductor processing, 16(2), 403-409.
• Wang, P., Zhu, Z., & Wang, Y. (2016). A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design. Information Sciences, 345, 27-45.
• Wang, Y., Zhou, L., Yang, G., Guo, R., Xia, C., & Liu, Y. (2020). Performance and Obstacle Tracking to Natural Forest Resource Protection Project: A Rangers’ Case of Qilian Mountain, China. International Journal of Environmental Research and Public Health, 17(16), 5672.
• Yamin, F., & Depledge, J. (2004). The international climate change regime: a guide to rules, institutions and procedures: Cambridge University Press.
• Zhai, L.-Y., Khoo, L.-P., & Zhong, Z.-W. (2009). Design concept evaluation in product development using rough sets and grey relation analysis. Expert systems with applications, 36(3), 7072-7079.
• Zuxing, C., & Dian, W. (2020). A prediction model of forest preliminary precision fertilization based on improved GRA-PSO-BP neural network. Mathematical Problems in Engineering, 2020.