Embedding sustainable land-use optimization within system dynamics: bidirectional feedback between spatial and non-spatial drivers

Azuara-García, Guadalupe; Palacios, Efrén; Montesinos-Barrios, Pilar

doi:10.1016/j.envsoft.2022.105463

Cited by 5 publications

(4 citation statements)

References 25 publications

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“…services produced by the land uses facilitates comprehensive analysis, which is meaningful and novel in supporting land-use planning (Loiseau et al, 2018). Although many tools and models developed to evaluate environmental impacts and services and could support land-use planning (Polasky et al, 2008;Kennedy et al, 2016;Azuara-García et al, 2022), LCA stands out to perform multi-criteria assessment throughout the life cycle of the products and services provided by land uses (Loiseau et al, 2012). This work generating optimal land-use allocation for multiple products based on their spatial explicit life cycle impacts is needed, as mentioned by Miret et al (2016) and Beaussier et al (2019).…”

Section: Tablementioning

confidence: 99%

Coupling optimization with territorial LCA to support agricultural land-use planning

Ding

Steubing

Achten

2023

Journal of Environmental Management

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Section: Tablementioning

confidence: 99%

Coupling optimization with territorial LCA to support agricultural land-use planning

Ding

Steubing

Achten

2023

Journal of Environmental Management

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“…The main differences primarily manifest in the methods used to simulate and predict future land use processes. Currently, commonly used prediction methods include Markov chain analysis, the system dynamics (SD) model, multi-objective optimization (MOP), and gray multi-objective optimization (GMOP) [22][23][24][25]. The methods selected by different studies are based on the characteristics and actual conditions of the study area.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Variation and Prediction Analysis of Land Use/Land Cover and Ecosystem Service Changes in Gannan, China

Luo,

et al. 2024

Sustainability

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For the preservation of ecosystems, including the enhancement of ecological strategies, examining the temporal and geographical variance in ecosystem services (ESs) and land use/land cover change (LUCC) is crucial. Gannan is situated on the upper Yellow River, which is a notable water conservation region with excellent ecological quality, but in the background of the local traditional production mode and rapid economic development, natural disasters, grassland degradation, and other ecological problems occur frequently. The integrated valuing of ecosystem services and tradeoffs (InVEST) model and the patch-generating land use simulation (PLUS) model are combined in this work to assess the spatiotemporal variance in ESs in Gannan. We set up three scenarios in modeling future land use—ecological protection (EP), natural development (ND), and economic development (ED) in 2050—and analyzed and evaluated the drivers of the variation in ESs. In order to reveal the LUCC in Gannan between 1990 and 2020, we predicted the LUCC and ESs spatial distribution characteristics in 2050, explored the correlation between its driving factors, and comprehensively analyzed and propose optimization measures and protection strategies. Through several simulation experiments, the findings indicate the following: (1) the largest percentage of land expansion for construction in Gannan between 1990 and 2020 is 74.53%, and the most noticeable percentage of shrinkage in the sand area is 20.67%; (2) from 1990 to 2020, Gannan’s water yield, carbon storage, soil retention, and habitat quality all changed, by 60 × 108 m3, 0.04 × 108 t, −10.66 × 108 t, and −0.02, respectively; (3) ESs are influenced by a variety of natural and societal variables: the southern and southwestern regions of Gannan are home to the majority of ESs hot spot areas, while the northern region is home to the majority of cold spot areas. This study contributes to the analysis of the developmental traits of Gannan ecosystems and can serve as a model for the preservation of terrestrial ecosystems with comparable environmental traits.

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“…Exploring the mechanism of urban land expansion in the metropolitan fringe area is an important way to observe the phenomenon of unbalanced development of this region. The research methods of urban land expansion mechanism mainly include multiple linear regression (MLR) [21,22], system dynamics (SD) [23,24], analytic hierarchy process (AHP) [25], structural equation modeling (SEM) [26], logistic regression [27,28], and so on. Logistic regression allows the regression problem for the dependent variable to be treated as a discontinuous variable, which does not require a linear relationship between the dependent and independent variables.…”

Section: Introductionmentioning

confidence: 99%

Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China

Deng,

Huang,

Chen

2023

Land

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With the development of the regional economy, the metropolitan area has gradually shifted from the rapid development stage of concentrating on the central city to the stage of coordinated and integrated regional development. This trend has brought new development opportunities to the metropolitan fringe area; however, due to the differences in resource endowment and the complex relationship between different levels of government, the metropolitan fringe area inevitably has contradictions and imbalances in economic and social development. There has been extensive research on land use and urban governance in the metropolitan area, but less attention has been paid to the metropolitan fringe area, and it is difficult to quantitatively characterize the complex interactions between various forces in this area. This paper summarizes the spatial pattern and spatiotemporal characteristics of construction land use in the fringe area of Shenzhen metropolitan area based on the 30 m resolution land cover dataset from 2000 to 2020, and analyzes the driving factors affecting the changes of construction land use through logistic regression. The results show that the overall land use in the study area is shifting from cropland and forest land to urban and rural construction land. With different stages of development, the rate of land change varies greatly from one period to another. Three factors, population density, lighting index and distance to highway, have a significant correlation with the changes in built-up land across the region, while the boundary effects of administrative boundaries show some variation in the impact of urban land expansion at different economic levels. Finally, we put forward that reducing the negative impact of administrative divisions on the integration of resources in different cities is important for realizing the synergistic development of the Shenzhen metropolitan area.

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Embedding sustainable land-use optimization within system dynamics: bidirectional feedback between spatial and non-spatial drivers

Cited by 5 publications

References 25 publications

Coupling optimization with territorial LCA to support agricultural land-use planning

Coupling optimization with territorial LCA to support agricultural land-use planning

Spatiotemporal Variation and Prediction Analysis of Land Use/Land Cover and Ecosystem Service Changes in Gannan, China

Study on the Characteristics and Influencing Factors of Land Use Changes in the Metropolitan Fringe Area: The Case of Shenzhen Metropolitan Area in China

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