Simulation of Land Use Pattern Evolution from a Multi-Scenario Perspective: A Case Study of Suzhou City in Anhui Province, China

Zhang, Rongtian; Jun, Lu

doi:10.3390/ijerph18030921

Cited by 11 publications

(5 citation statements)

References 32 publications

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“…The Markov transfer matrix was initially applied to describe of the state and state transition over a certain period and gradually extended to the field of land management, known as the land-use transfer matrix (LUTM) [56]. It has been widely employed in mass literatures to gain in-depth insight of the evolution process of land-use change [58,59]. It is helpful to comprehensively explain the mutual conversions among different land-use types [60,61].…”

Section: Land-use Transfer Matrixmentioning

confidence: 99%

Spatio-Temporal Variation and Driving Forces of Land-Use Change from 1980 to 2020 in Loess Plateau of Northern Shaanxi, China

Zhou

2021

Land

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Land-use cover is undergoing intense change under global climate change and rapid urbanization, especially in the Loess Plateau, where ecological restoration policies like Green for Grain Project (GFGP) have been vigorously implemented since the 1980s. The main objective of this study was to distinguish the difference of spatio-temporal variation of land-use change in the two study periods of 1980–2000 and 2000–2020 at the county scales. Geographically and temporally weighted regression (GTWR) was employed to handle both the spatial and temporal heterogeneity of the driving forces for land use change. The results showed that the quantity of construction land, woodland and grassland experienced continuous growth, but arable land declined substantially. The results of GTWR model showed that the dominant influencing factors of land-use change had temporal and spatial differences in the Loess Plateau. Specifically, the implementation of GFGP and precipitation accelerated the changes in arable land, grassland and woodland. For construction land, its growth was mainly promoted by gross domestic product (GDP) and population, both of which had more obvious positive effects in the last 20 years. The findings provide a scientific basis to put forward countermeasures emphasizing sustainable land use in the Loess Plateau.

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Section: Land-use Transfer Matrixmentioning

confidence: 99%

Spatio-Temporal Variation and Driving Forces of Land-Use Change from 1980 to 2020 in Loess Plateau of Northern Shaanxi, China

Zhou

2021

Land

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“…Baokang is a famous mountainous county with more than 3100 hilltops, so it is more suitable for forestry and fruit farming since the singular topography promotes the development of NGP. The central and eastern parts of Hubei Province are abundant in rainfall and heat, which help the growth of crops [72]. Jianghan Plain, which has a large number of agricultural exports, has fertile soil and an extensive water network.…”

Section: Mechanism Of Factors Affecting Ngpmentioning

confidence: 99%

Spatio-Temporal Evolution and Driving Factors of “Non-Grain Production” in Hubei Province Based on a Non-Grain Index

Wang

Song

2023

Sustainability

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Non-grain production (NGP) on cultivated land has become a common phenomenon due to the prosperity of the rural economy and the optimisation of the agricultural structure. However, the excessive use of cultivating land for NGP has threatened food production and the sustainable use of cultivated land. To halt this trend and to ensure food security, the authors of this paper applied a novel non-grain index to measure NGP, which could reflect multiple NGP activities; designated Hubei Province as its object of research; and revealed NGP’s spatio-temporal patterns of the past 30 years. We then assessed the characteristics of NGP based on spatial autocorrelation analysis, the Theil index, and geographically weighted regression. The results showed that the value of the non-grain index grew from 0.497 to 1.113 as NGP increased significantly in Hubei Province. The number of high-NGP counties increased, spatial agglomeration became obvious, and the eastern and western sides of Hubei Province witnessed an observable growth in NGP. As a result, the NGP in the eastern and western regions overtook production in the central region. Despite a series of historical subsidy policies and agricultural modernisation initiatives that promoted the planting of grain crops, the policy of “grain on valuable cultivated land” could be better implemented. We conclude by making some suggestions for reducing NGP and protecting cultivated land.

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“…In order to simulate land use change, many scholars have developed many models, such as the CLUE-S model [39,67,68], FLUS model [42,43,69] and PLUS model [70,71]. Recent studies have shown that most spatial models still have a high degree of uncertainty, which indicates no single model or method can fully describe the different processes of land use on all spatiotemporal scales [72][73][74]. In this study, a Markov model can describe the direction of land use change by considering the impact of relevant factors on land use demand, predict the future land demand of land use types, and allocate the predicted land demand to geospatial through FLUS model, so as to realize land use spatial prediction.…”

Section: Deficiencies and Future Directionmentioning

confidence: 99%

Conflict Identification and Zoning Optimization of “Production-Living-Ecological” Space

Xiao

Zhao

2022

IJERPH

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With the acceleration of economic and social development and the increasing competition between multi-functional spaces, the coordination and stability of land space have been seriously affected. In order to simulate the conflict pattern of “production, living ecological” space and analyze its evolution characteristics, taking Qianjiang City as the research area and based on the current data of land use, the FLUS (Future Land Use Simulation) model and spatial conflict measurement model are used to calculate the change trend of “production, living ecological” spatial conflict in Qianjiang City in the past and in the future. The research results are of great significance for the scientific use of land space and the optimization of regional development patterns. The results show that: (1) From 2000 to 2020, the level of spatial conflict in Qianjiang City showed an upward trend, the proportion of medium and above conflict units gradually increased, and the conflict level in the study area gradually became dominated by strong conflict. (2) Due to the process of urbanization and the continuous growth of population and GDP (Gross Domestic Product), the construction land in Qianjiang City shows a rapid increase trend under three scenarios, and the cultivated land area shows a downward trend. (3) In 2035, under the three scenarios, the spatial conflict in Qianjiang City will be strengthened, mainly at the level of medium and above. (4) According to the change degree of conflict transformation, 15 change types are divided into five functional zones: ecological protection zone, ecological conservation zone, modern agriculture zone, urban–rural development coordination zone and urban optimization zone.

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Simulation of Land Use Pattern Evolution from a Multi-Scenario Perspective: A Case Study of Suzhou City in Anhui Province, China

Cited by 11 publications

References 32 publications

Spatio-Temporal Variation and Driving Forces of Land-Use Change from 1980 to 2020 in Loess Plateau of Northern Shaanxi, China

Spatio-Temporal Variation and Driving Forces of Land-Use Change from 1980 to 2020 in Loess Plateau of Northern Shaanxi, China

Spatio-Temporal Evolution and Driving Factors of “Non-Grain Production” in Hubei Province Based on a Non-Grain Index

Conflict Identification and Zoning Optimization of “Production-Living-Ecological” Space

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