Multi-objective land use optimization based on low-carbon development using NSGA-II. Abstract: Land use/land cover change (LUCC) caused by human beings is ...
Abstract—Land use/land cover change (LUCC) caused by human beings is the main source of the increases of CO² in the atmosphere. Land resource is not only ...
This paper presents a multi-objective land use optimization model based on low-carbon development. Carbon emission, economic benefit objectives, and constraint ...
Jan 1, 2024 · The method optimizes land use while predicting ESV for the Liangjiang New Area, China. •. The ecological spatial constraints are developed based ...
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NSGA-II is effective on achieving low carbon emission in spatial optimization. •. Optimum solutions provide valuable references for land use zoning plan.
This study applied the non-dominated sorting genetic algorithm II (NSGA-II) to optimize land-use allocation in the Taleghan watershed, northwest of Karaj, Iran.
It is solved with non-dominated sorting genetic algorithm-II (NSGA-II), in which each gene represents a specific type of land use category. The optimal ...
Jing, Multi-objective land use optimization based on low-carbon development using NSGA-II, Int. Conf. Geoinformatics, № 1–5; Johnson, Identifying ...
The multi-objective spatial optimization of urban land use based on low-carbon city planning ... It is solved with non-dominated sorting genetic algorithm-II ( ...
This study aims to examine the impact of land use variations on carbon emissions by incorporating the development of photovoltaics as a scenario.