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A master's thesis from Aalborg University
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Stimulating sustainable development goals' implementation and conservation action - Predicting future land use and land cover change in the Virunga national park

Translated title

Stimulering og implementering af verdensmålene for bæredygtig udvikling - Forudsigelse af den fremtidige arealanvendelse i Virunga National Parken

Author

Term

4. term

Publication year

2019

Submitted on

Pages

72

Abstract

FN’s 2030-dagsorden og verdensmålene (SDG’er) sætter fælles mål for bæredygtig og inkluderende udvikling, der skal beskytte naturen og sikre, at ingen lades i stikken. Alligevel ændrer befolkningstilvækst, urbanisering, skovrydning og hurtig økonomisk udvikling landskabet markant. Disse ændringer i landdække (fx skov, landbrug, by og åbent land) presser økosystemer og ressourcer. Denne afhandling undersøger Virunga Nationalpark og dens opland i Nord-Kivu i Den Demokratiske Republik Congo. Området er præget af langvarige konflikter og fattigdom. Samtidig er parken afgørende for millioner af menneskers levebrød, men trues af ukontrolleret landbrugsekspansion, udvinding af naturressourcer og skovrydning. Oplandet (det omkringliggende vandsystem, der forsyner parken) har derfor oplevet store ændringer i landdækket, som undergraver både parkens økologiske integritet og de økosystemtjenester, som befolkningen er afhængig af. Formålet er at vurdere og kvantificere fremtidige ændringer i landdækket frem mod 2030 for at give et datagrundlag til beslutninger, der understøtter SDG’erne. Studiet: (1) fremstillede landdækkekort for 2010, 2015 og 2019 ud fra satellitbilleder; (2) sammenlignede kortene for at måle ændringer; (3) opbyggede undermodeller og udvalgte forklarende variabler; (4) brugte maskinlæringsalgoritmer (computermodeller, der lærer af data) til at beregne overgangspotentialer, dvs. sandsynligheden for at én arealklasse skifter til en anden; (5) anvendte Markovkædeanalyse, en statistisk metode til at kvantificere, hvor meget ændring der forventes; og (6) forudsagde landdækket i 2030. Modellen kunne med succes simulere fremtidige ændringer i landdække og arealanvendelse. Resultaterne peger på, at landbrugsekspansion og byudvikling frem mod 2030 vil reducere Virungas skov- og åbne arealer betydeligt. Tilgængelighed – dvs. landskabets topografi og nærhed til eksisterende menneskelige aktiviteter – er en hoveddriver for ændringer i skovdække. Afhandlingen diskuterer, hvordan disse fremskrivninger kan understøtte politik og forvaltning, der sigter mod at opfylde SDG’erne i 2030.

The UN 2030 Agenda and the Sustainable Development Goals (SDGs) set shared targets for sustainable, inclusive development that protects nature and leaves no one behind. Yet population growth, urbanization, deforestation, and rapid economic development are reshaping the land. These land cover changes (for example, shifts among forest, farmland, urban areas, and open land) put pressure on ecosystems and resources. This thesis focuses on Virunga National Park and its catchment in North Kivu, Democratic Republic of the Congo. The area has experienced prolonged conflict and poverty. The park supports the livelihoods of millions, but conservation is threatened by uncontrolled agricultural expansion, natural resource extraction, and deforestation. The wider catchment (the surrounding watershed that feeds the park) has undergone major land cover change, undermining both the park’s ecological integrity and the ecosystem services people rely on. The goal is to assess and quantify future land cover change to 2030, providing evidence for data-driven decisions aligned with the SDGs. The study: (1) produced land cover maps for 2010, 2015, and 2019 from satellite imagery; (2) compared the maps to measure change; (3) built sub-models and selected explanatory variables; (4) used machine learning algorithms—computer models that learn from data—to estimate transition potentials, meaning the likelihood that one land type will change into another; (5) applied Markov chain analysis, a statistical method, to quantify how much change is expected; and (6) predicted land cover for 2030. The model successfully simulated future land cover and land use dynamics. It indicates that agricultural expansion and urban development will significantly reduce Virunga’s forest and open land by 2030. Accessibility—landscape topography and proximity to existing human activities—emerged as a primary driver of forest change. The thesis discusses how these projections can support policies and management aimed at achieving the SDGs by 2030.

[This abstract was generated with the help of AI]