Spatially Explicit Evaluation and Driving Factor Identification of Land Use Conflict in Yangtze River Economic Belt

Cui, Jiaxing; Kong, Xuesong; Chen, Jing; Sun, Jianwei; Zhu, Yongchun

doi:10.3390/land10010043

Cited by 37 publications

(17 citation statements)

References 81 publications

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“…Previous studies had shown that SEFs were important driving factors of LUPs. Previous results on the effects of SEFs on the changes of LUPs were not always coincident due to the difference of spatial range in various study areas [28][29][30][31]. However, SEFs generally had both positive and negative effects on LUPs, which was less studied in previous research.…”

Section: Introductionmentioning

confidence: 79%

The Interaction Relationship between Land Use Patterns and Socioeconomic Factors Based on Wavelet Analysis: A Case Study of the Black Soil Region of Northeast China

Wang

2021

Land

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Analyzing the interaction between land use patterns (LUPs) and socioeconomic factors (SEFs) could provide a basis for regional land spatial planning and management decisions in the future. In this study, population, gross domestic product (GDP) and land use intensity were selected to explain the relationship between SEFs and LUPs. The study designed a new method of sample line acquisition for wavelet analysis, and identified the interaction grid scales of LUP changes with SEFs in 1991, 2005 and 2019 by using cross wavelet transform analysis (XWT). Wavelet transform coherent analysis (WTC) was used to reveal the interaction direction and impact strength between LUPs and SEFs. The results showed that: (1) There were two ranges of 2978–5008 m and 24,400–29,738 m in which the grid scales showing interaction between LUPs and SEFs (population, GDP and land use intensity) from 1991 to 2019 were overlapping. (2) The interaction direction between LUPs and SEFs from 1991 to 2019 was almost negative on all sample lines, while the interaction directions of the middle sample line of population and GDP from 1991 to 2019, the end sample line of GDP in 2019, and the start sample line of land use intensity in 1991 were positive. (3) Dry land, grassland and construction land were most affected by SEFs, followed by paddy fields, forest land and other land, and the least affected were water areas during 1991 to 2019. The impact of population and GDP on LUPs was reduced, while the impact of land use intensity on LUPs was increased from 1991 to 2019. Overall, population, GDP and land use intensity were the important SEFs in the changes of LUPs, and were important factors for social progress and economic development.

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Section: Introductionmentioning

confidence: 79%

The Interaction Relationship between Land Use Patterns and Socioeconomic Factors Based on Wavelet Analysis: A Case Study of the Black Soil Region of Northeast China

Wang

2021

Land

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“…This novel application of participatory mapping captured spatial data across multiple catchments with varying land use and environmental characteristics by stakeholders from four key land and water management stakeholder groups. The heat maps of perceived conflict illustrated the complex combination of local and landscape-scale issues present in the catchments and identified the three main aspects of land use conflict-trade-offs between ecological, agricultural, and construction interests [66]. We were able to quantify how perceived conflicts differed between catchments and groups of stakeholders and used modelling of land cover types to predict conflict in the study catchments.…”

Section: Discussionmentioning

confidence: 99%

Catchment-Scale Participatory Mapping Identifies Stakeholder Perceptions of Land and Water Management Conflicts

Stosch

Oliver

2022

Land

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Competing socioecological demands and pressures on land and water resources have the potential to increase land use conflict. Understanding ecosystem service provisioning and trade-offs, competing land uses, and conflict between stakeholder groups in catchments is therefore critical to inform catchment management and the sustainable use of natural resources. We developed a novel stakeholder engagement methodology that incorporates participatory conflict mapping in three catchments with a short questionnaire to identify the perceptions of 43 participants from four key land and water management stakeholder groups: environmental regulators, water industry practitioners, the farm advisor community, and academics. The participatory mapping exercise produced heat maps of perceived conflict and land use competition, providing spatial detail of the complex combination of land use issues faced by catchment managers. Distinct, localised hotspots were identified in areas under pressure from flooding, abstraction, and urbanisation; as well as more dispersed issues of relevance at the landscape scale, such as from farming, forestry, energy production, and tourism. Subsequent regression modelling linked perceived conflict to land cover maps and identified coastal, urban, and grassland areas as the most likely land cover types associated with conflict in the study catchments. Our approach to participatory conflict mapping provides a novel platform for catchment management and can facilitate increased cooperation among different catchment stakeholders. In turn, land and water management conflicts can be recognised and their underlying drivers and likely solutions identified in an effort to better manage competing demands on catchment resources.

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“…The second is the types of land use conflicts [55]. Many scholars mainly classify land use conflicts from different research perspectives, including conflict areas [56,57], conflict processes [58,59], conflict consequences [60][61][62], etc. The third is the identification of land use conflict [63].…”

Section: Deepening Understanding Of Space Conflictmentioning

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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Spatially Explicit Evaluation and Driving Factor Identification of Land Use Conflict in Yangtze River Economic Belt

Cited by 37 publications

References 81 publications

The Interaction Relationship between Land Use Patterns and Socioeconomic Factors Based on Wavelet Analysis: A Case Study of the Black Soil Region of Northeast China

The Interaction Relationship between Land Use Patterns and Socioeconomic Factors Based on Wavelet Analysis: A Case Study of the Black Soil Region of Northeast China

Catchment-Scale Participatory Mapping Identifies Stakeholder Perceptions of Land and Water Management Conflicts

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

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