Stimulating implementation of sustainable development goals and conservation action:Predicting future land use/cover change in Virunga national park, Congo
| Autor: | Mads Christensen, Jamal Jokar Arsanjani |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
virunga national park Geography Planning and Development 0211 other engineering and technologies TJ807-830 Sustainable development goals Virunga national park 02 engineering and technology Land cover Management Monitoring Policy and Law TD194-195 01 natural sciences Renewable energy sources remote sensing Deforestation Urban planning Urbanization Machine learning GE1-350 Environmental degradation Land cover modelling 0105 earth and related environmental sciences Sustainable development Environmental effects of industries and plants Land use Renewable Energy Sustainability and the Environment business.industry land cover modelling Environmental resource management 021107 urban & regional planning Remote sensing sustainable development goals Natural resource Environmental sciences machine learning Geography business |
| Zdroj: | Christensen, M & Arsanjani, J J 2020, ' Stimulating implementation of sustainable development goals and conservation action : Predicting future land use/cover change in Virunga national park, Congo ', Sustainability (Switzerland), vol. 12, no. 4, 1570 . https://doi.org/10.3390/su12041570 Sustainability, Vol 12, Iss 4, p 1570 (2020) Sustainability Volume 12 Issue 4 |
| Popis: | The United Nations 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDG&rsquo s) presents a roadmap and a concerted platform of action towards achieving sustainable and inclusive development, leaving no one behind, while preventing environmental degradation and loss of natural resources. However, population growth, increased urbanisation, deforestation, and rapid economic development has decidedly modified the surface of the earth, resulting in dramatic land cover changes, which continue to cause significant degradation of environmental attributes. In order to reshape policies and management frameworks conforming to the objectives of the SDG&rsquo s, it is paramount to understand the driving mechanisms of land use changes and determine future patterns of change. This study aims to assess and quantify future land cover changes in Virunga National Park in the Democratic Republic of the Congo by simulating a future landscape for the SDG target year of 2030 in order to provide evidence to support data-driven decision-making processes conforming to the requirements of the SDG&rsquo s. The study follows six sequential steps: (a) creation of three land cover maps from 2010, 2015 and 2019 derived from satellite images (b) land change analysis by cross-tabulation of land cover maps (c) submodel creation and identification of explanatory variables and dataset creation for each variable (d) calculation of transition potentials of major transitions within the case study area using machine learning algorithms (e) change quantification and prediction using Markov chain analysis and (f) prediction of a 2030 land cover. The model was successfully able to simulate future land cover and land use changes and the dynamics conclude that agricultural expansion and urban development is expected to significantly reduce Virunga&rsquo s forest and open land areas in the next 11 years. Accessibility in terms of landscape topography and proximity to existing human activities are concluded to be primary drivers of these changes. Drawing on these conclusions, the discussion provides recommendations and reflections on how the predicted future land cover changes can be used to support and underpin policy frameworks towards achieving the SDG&rsquo s and the 2030 Agenda for Sustainable Development. |
| Databáze: | OpenAIRE |
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