- Titel
- Optimising mine planning by integrating geospatial modelling into system dynamics
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:105-qucosa2-972964
- Datum der Einreichung
- 03.02.2025
- Datum der Verteidigung
- 18.03.2025
- Abstract (EN)
- In an era of mineral-driven energy transition, the largely untapped mineral reserves in Africa are gaining global attention. Kenya, presently featuring Africa's most modern mining law, has set a high target to increase the mining sector's contribution to the GDP from barely 1% currently to 10% by 2030. Despite regulatory reforms and advances in Earth observation and geospatial technologies, gaps in mining sector governance have persisted with the lack of spatially enabled decision support models for strategic mine planning at regional scales involving multiple projects, interconnected sectors, and diverse stakeholders, including local communities. Motivated by the urgent need to address the gaps using an applied case study of Taita Taveta, a mineral-rich region in Kenya, this thesis developed a system dynamics model that integrates spatial metrics and simulates scenarios from 1969 to 2029, with the aim of informing long-term strategy, policy, and planning in the mining sector. Branded the Taita-Taveta Integrated Mine Planning Model (TIMPM), this scalable prototype incorporated 40 variables into 7 model sectors representing 75 mining areas, protected areas, and spatial planning parameters. The model projected Taita Taveta population to exceed 427000 by 2029 with an annual water demand of 31 million cubic metres. From GIS analysis, 16% of the mapped mines were located within a kilometre of the water bodies, with most human-induced degradation taking place 3-35 m from the Voi River. TIMPM's flexible structure supports multi-stakeholder participation and spatio-temporal simulations of divergent mining and land-use scenarios with policies for long-term sustainability, transparency, and accountability in mining sector governance. The findings reinforce the superiority of machine learning in geospatial analysis for precise parameterisation of decision support models. The outlook projects a growing need for a participatory, geodata-driven systems approach to developing integrated decision support systems for sustainable mineral resource governance.
- Freie Schlagwörter (EN)
- causal loop diagram, decision support model, dynamic modelling and simulation, GIS analysis, mining-environment-society nexus, multicriteria spatial decision support systems, procedural rationality, STELLA, stocks and flows, supervised satellite image classification, system dynamics model, systems thinking, Taita Taveta Integrated Mine Planning Model (TIMPM)
- Klassifikation (DDC)
- 624
- Klassifikation (RVK)
- QT 000
- QP 360
- Normschlagwörter (GND)
- Kenia
- Bergbau
- Bergbaubetrieb
- Nachhaltigkeit
- Planung
- Produktionsplanung
- Bergwerk
- Fernerkundung
- Geoinformationssystem
- Umweltschutz
- Umweltveränderung
- Landschaftsentwicklung
- Satellitenfernerkundung
- Modellierung
- Bildanalyse
- Geoinformatik
- Geoinformation
- Datenanalyse
- Projektplanung
- GutachterIn
- Prof. Dr. Carsten Drebenstedt
- Prof. Dr.-Ing. Jörg Benndorf
- Prof. Dr. Washington Yotto Ochieng
- BetreuerIn Hochschule / Universität
- Prof. Dr. Carsten Drebenstedt
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Bergakademie Freiberg, Freiberg
- Version / Begutachtungsstatus
- publizierte Version / Verlagsversion
- URN Qucosa
- urn:nbn:de:bsz:105-qucosa2-972964
- Veröffentlichungsdatum Qucosa
- 04.06.2025
- Dokumenttyp
- Dissertation
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
CC BY-NC-SA 4.0