Transformation of A Sustainable City Using Object-Oriented Techniques for Urban Green Space Planning – A Case Study of Lusaka City
DOI:
https://doi.org/10.38027/ICCAUA2024EN0041Keywords:
Land resource planning, Urban green spaces, Remote Sensing, Object-based classification, Google Earth EngineAbstract
Effective land resource management and sustainable development, particularly in urban green spaces, rely on strategic
land planning and mapping techniques such as Remote Sensing. This study utilises object-based classification techniques,
employing Google Earth Engine and Quantum Geographic Information Systems (QGIS), to examine Lusaka City's green
space encroachment. Findings reveal a 59% increase in built-up areas towards the north-east direction and a 2% decline
in green spaces towards the south-east part of Lusaka. The implications are significant, highlighting the urgent need for
intervention to preserve the city's environmental balance. Immediate action is essential, requiring rigorous regulations,
community engagement, and stakeholder collaboration. Furthermore, the study underscores the critical role of remote
sensing in monitoring urban green spaces and identifying sustainability threats, emphasising the importance of prioritising
the protection and improvement of green spaces through comprehensive land use planning and land use land cover
mapping through the use of object-based classification techniques.
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Copyright (c) 2024 Dr. Penjani Hopkins Nyimbili, BEng. Otilia Muyabi, MSc. Masauso Sakala, Dr. Alick R. Mwanza, Dr. Ethel Tembo Mwanaumo, Prof. Dr. Erastus Misheng’u Mwanaumo , Prof. Dr. Wellington Didibhuku Thwala
This work is licensed under a Creative Commons Attribution 4.0 International License.