The multi-objective spatial optimization of urban land use based on low-carbon city planning

As the spatial carrier of carbon emission from land ecosystems and human activities, land use plays an important role in representing the spatial distribution of carbon emissions and carbon sinks. The intension of CO2 emission is closely attached to the fundamental unit of urban form—land use patter...

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Autores principales:	Gengzhe Wang, Qi Han, Bauke de vries
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Land use classification Land use optimization Spatial attribute Regression tree Genetic algorithm Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/14b5331d6dbc467aa194f783f50a89b8
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spelling	oai:doaj.org-article:14b5331d6dbc467aa194f783f50a89b82021-12-01T04:47:56ZThe multi-objective spatial optimization of urban land use based on low-carbon city planning1470-160X10.1016/j.ecolind.2021.107540https://doaj.org/article/14b5331d6dbc467aa194f783f50a89b82021-06-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S1470160X21002053https://doaj.org/toc/1470-160XAs the spatial carrier of carbon emission from land ecosystems and human activities, land use plays an important role in representing the spatial distribution of carbon emissions and carbon sinks. The intension of CO2 emission is closely attached to the fundamental unit of urban form—land use patterns. The exploration of the low-carbon oriented spatial optimization provides new scope for solving the high carbon emission in the urban area through spatial planning. In this paper, Eindhoven in the Netherlands was selected as the case study to implement spatial optimization. A set of parameters containing the spatial attributes of buildings and vegetation were introduced to classify the land use patterns into six categories through a combined random forest algorithm and regression tree approach. The results show the geographic features of vegetation are the crucial factors for the carbon emission. The multi-objective spatial optimization model integrated carbon emission, population, and constraint conditions. 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 solutions were incorporated with a regression model to analyze the impact of the variation in each land use category. Three categories were proved to be more influential on carbon emission performance. The optimized land use structure shows the potential to reduce the carbon emission and offer valuable consults to low carbon land use plan.Gengzhe WangQi HanBauke de vriesElsevierarticleLand use classificationLand use optimizationSpatial attributeRegression treeGenetic algorithmEcologyQH540-549.5ENEcological Indicators, Vol 125, Iss , Pp 107540- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Land use classification Land use optimization Spatial attribute Regression tree Genetic algorithm Ecology QH540-549.5
spellingShingle	Land use classification Land use optimization Spatial attribute Regression tree Genetic algorithm Ecology QH540-549.5 Gengzhe Wang Qi Han Bauke de vries The multi-objective spatial optimization of urban land use based on low-carbon city planning
description	As the spatial carrier of carbon emission from land ecosystems and human activities, land use plays an important role in representing the spatial distribution of carbon emissions and carbon sinks. The intension of CO2 emission is closely attached to the fundamental unit of urban form—land use patterns. The exploration of the low-carbon oriented spatial optimization provides new scope for solving the high carbon emission in the urban area through spatial planning. In this paper, Eindhoven in the Netherlands was selected as the case study to implement spatial optimization. A set of parameters containing the spatial attributes of buildings and vegetation were introduced to classify the land use patterns into six categories through a combined random forest algorithm and regression tree approach. The results show the geographic features of vegetation are the crucial factors for the carbon emission. The multi-objective spatial optimization model integrated carbon emission, population, and constraint conditions. 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 solutions were incorporated with a regression model to analyze the impact of the variation in each land use category. Three categories were proved to be more influential on carbon emission performance. The optimized land use structure shows the potential to reduce the carbon emission and offer valuable consults to low carbon land use plan.
format	article
author	Gengzhe Wang Qi Han Bauke de vries
author_facet	Gengzhe Wang Qi Han Bauke de vries
author_sort	Gengzhe Wang
title	The multi-objective spatial optimization of urban land use based on low-carbon city planning
title_short	The multi-objective spatial optimization of urban land use based on low-carbon city planning
title_full	The multi-objective spatial optimization of urban land use based on low-carbon city planning
title_fullStr	The multi-objective spatial optimization of urban land use based on low-carbon city planning
title_full_unstemmed	The multi-objective spatial optimization of urban land use based on low-carbon city planning
title_sort	multi-objective spatial optimization of urban land use based on low-carbon city planning
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/14b5331d6dbc467aa194f783f50a89b8
work_keys_str_mv	AT gengzhewang themultiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning AT qihan themultiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning AT baukedevries themultiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning AT gengzhewang multiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning AT qihan multiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning AT baukedevries multiobjectivespatialoptimizationofurbanlandusebasedonlowcarboncityplanning
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The multi-objective spatial optimization of urban land use based on low-carbon city planning

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