Evaluating the efficiency of future crop pattern modelling using the CLUE-S approach in an agricultural plain

Akin, Anıl; Erdoğan, Nurdan; Berberoğlu, Süha; Çilek, Ahmet; erdoğan, Akif; Dönmez, Cenk; Şatır, Onur

doi:10.1016/j.ecoinf.2022.101806

Cited by 4 publications

(3 citation statements)

References 47 publications

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“…The CA-Markov model can be used to predict long-term land variation and simulate spatial changes in complex systems, but it relies on historical data [134]. The CLUE-S model is a dynamic, multidimensional, spatially explicit and regional simulation approach [135]. The MAgPIE model is an open-source framework for modelling global landsystems, with a spatial resolution of 0.5°x0.5° [69].…”

Section: Common Wlfc Nexus Simulation and Optimization Modelsmentioning

confidence: 99%

Review of the Water–Land–Food–Carbon Nexus Focused on Regional Low-Carbon and High-Quality Agricultural Development

Deng,

Xu,

Zhang

et al. 2024

Water

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To overcome the multiple challenges of water scarcity, agricultural land conversion, food security, and carbon emissions, an optimal collaborative management scheme for food production is urgently needed, especially in high food-production and food-consumption countries such as China. The water–land–food–carbon (WLFC) nexus provides a new perspective, but its interactions are complex, dynamic, and spatially heterogeneous; the coupling mechanism is not fully understood; and the driving forces and regulation strategies remain uncertain. Therefore, in this study, the WLFC nexus centered on low-carbon and high-quality agricultural development was systematically reviewed. The main contributions are as follows: (1) A framework of the regional agricultural WLFC nexus was proposed based on bibliographic analysis. (2) The main internal and external factors influencing the WLFC nexus in agriculture were identified by reevaluating meta-analysis review studies. The results showed that changes in the amount and type of irrigation water, the amount and planting activities of agricultural land, and climate change (temperature, precipitation, and CO2 concentration) affected food (rice, wheat, and maize) yields and carbon emissions to varying degrees. Moreover, population, technological innovation, trade, and polices were important external factors impacting food production and carbon emissions. (3) The common methods and tools for assessing, simulating, and optimizing the WLFC nexus in agriculture were summarized from the perspectives of its status, physical links, and embodied links. Integrated indices, complex system thinking, and process-based and data-driven methods were applied in the studies of the WLFC nexus. (4) Strategies and programs for collaborative WLFC management in agriculture within 10 global river basins were compiled. These findings could help us better understand the WLFC nexus in agriculture and identify the optimal cooperative management scheme, thereby realizing low-carbon and high-quality agricultural development.

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Section: Common Wlfc Nexus Simulation and Optimization Modelsmentioning

confidence: 99%

Review of the Water–Land–Food–Carbon Nexus Focused on Regional Low-Carbon and High-Quality Agricultural Development

Deng,

Xu,

Zhang

et al. 2024

Water

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“…The regression results are tested by ROC values, which are between 0.5 and 1. When the ROC value is greater than 0.7, it indicates that the regression result has a greater capacity to explain each land use type [53]. According to previous studies and the land use change features of the LX region [33,54], ten driving factors, including DEM, slope, soil type, multi-year mean precipitation, NDVI, distance to water areas, distance to city center, distance to main roads, per capita GDP, and population density, were selected for logistic regression calculation (Figure S2).…”

Section: The Mcr-mop-dyna-clue Model Frameworkmentioning

confidence: 99%

Land Use Optimization Embedding in Ecological Suitability in the Embryonic Urban Agglomeration

Chen

Zhao

Shi

et al. 2023

Land

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Healthy and sustainable urban agglomerations development relies heavily on land use optimization. However, there is insufficient scientific basis and reliable quantitative analysis for land use pattern identification and optimal prediction in embryonic urban agglomeration. Therefore, taking the Lanzhou–Xining (LX) region, a typical primary developing urban agglomeration, as the study area, we first assessed the land ecological suitability (LES). Then, we embedded the LES evaluation results in the land optimization process and constructed the MCR-MOP- Dyna-CLUE model framework, simulating and optimizing land use patterns for the year 2035 under ecological optimization and business as usual scenarios, which aimed to explore a sustainable land use pattern for embryonic urban agglomerations. The results indicated that the ecological optimization scenario based on LES had a more rational land use pattern. It appropriately controlled the expansion rate of construction land and effectively alleviated the problems of construction land encroaching on farming land and ecological land. Meanwhile, the ecosystem services increased in value based on adequately addressing the need for food security and economic development. Compared to the business as usual scenario, the construction land under the ecological optimization scenario was 19,622.69 ha less, and the cultivated land was 32,103.29 ha more. Moreover, the ecological benefit and the economic benefit increased by 187,490.4595 million yuan and 151,808,605.1 million yuan from 2020 to 2035, respectively, under the ecological optimization scenario. Our research is of great value for making decisions on sustainable land use and land resource management in initial developing agglomerations.

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“…The CLUE-S model utilizes spatial iterative computation to determine the total probabilities of each land use type, primarily through the spatial allocation module for simulating the spatiotemporal patterns of land use [54]. The formula for spatial iteration is as follows:…”

Section: Spatial Iterative Computationmentioning

confidence: 99%

The Spatial Pattern Evolution of Rural Settlements and Multi-Scenario Simulations since the Initiation of the Reform and Opening up Policy in China

Sheng,

Lian

2023

Land

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Since the inception of China’s reform and opening-up policy, the rapidly advancing process of urbanization and the primacy accorded to urban development policies have imparted increasingly profound ramifications on rural domains. Nonetheless, antecedent research has predominantly fixated on urban sprawl, overlooking the spatial metamorphosis of rural settlements and the prospective developmental trajectories within the policy paradigm. Consequently, this inquiry endeavors to scrutinize the evolution of the spatial configuration of rural settlements in She County from the advent of reform and opening-up (1980–2020) utilizing remote sensing data. In tandem, through scenario delineation and the utilization of the CLUE-S model, it aspires to prognosticate the evolving trends in the spatial arrangements of rural settlements in She County by 2035. The empirical findings divulge that (1) The temporal progression of rural settlement spatial configurations in She County over the preceding four decades can be delineated into two discernible phases. From 1980 to 2000, alterations in the number, extent, and spatial morphological attributes of rural settlements remained circumscribed. While the count of rural settlements registered a diminution (by 3), the aggregate extent experienced a marginal augmentation (by 8.45%), concomitant with a gradual gravitation towards regular boundaries, manifesting a stochastic distribution throughout the investigation expanse. Conversely, from 2000 to 2020, the quantity and extent of rural settlements in She County underwent a precipitous augmentation (92 and 36.37%, respectively), characterized by irregular peripheries. (2) The CLUE-S model achieved an overall precision of 0.929, underscoring its applicability in emulating fluctuations in rural settlements. (3) Within the new-type urbanization scenario, the cumulative expanse of rural settlements witnessed a decline of 35.36% compared to the natural development scenario, marked by substantial conversions into grassland and urban land usage. Furthermore, orchestrated planning and directive measures have propelled the consolidation of rural settlements in She County, engendering a more equitable and standardized layout. Under the aegis of the ecological conservation scenario, the total rural settlement area recorded a 0.38% reduction vis-à-vis the natural development scenario, primarily entailing competitive coexistence with arable land, grassland, and urban land usage in spatial terms.

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Evaluating the efficiency of future crop pattern modelling using the CLUE-S approach in an agricultural plain

Cited by 4 publications

References 47 publications

Review of the Water–Land–Food–Carbon Nexus Focused on Regional Low-Carbon and High-Quality Agricultural Development

Review of the Water–Land–Food–Carbon Nexus Focused on Regional Low-Carbon and High-Quality Agricultural Development

Land Use Optimization Embedding in Ecological Suitability in the Embryonic Urban Agglomeration

The Spatial Pattern Evolution of Rural Settlements and Multi-Scenario Simulations since the Initiation of the Reform and Opening up Policy in China

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