Landscapeecological risk assessment of Xi river Basin based on land-use change

Leting, 吕乐婷 Lü; Jie, 张杰 Zhang; Caizhi, 孙才志 Sun; Xiaorui, 王晓蕊 Wang; Defeng, 郑德凤 Zheng

doi:10.5846/stxb201708111440

Cited by 9 publications

(10 citation statements)

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“…Referring to relevant research [51], the vulnerability assignments of various landscapes in the study area were determined as follows: 5 for sandy land, 4 for wetland, 3 for grassland, 2 for forest, and 1 for construction land. Forest secondary classification landscape assignment: 5 for larch, 4 for sycamore pine and birch, 3 for spruce, 2 for mixed birch forest, and 1 for mixed forest of fallen clouds.…”

Section: Expert Consultation Methods and Normalized Treatmentmentioning

confidence: 99%

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Kang,

Yang,

Qing

et al. 2024

Forests

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Examining the Saihanba Mechanical Forest Farm, this study utilized Landsat remote sensing data from 1987, 1997, 2001, 2013, and 2020 to interpret land use from the Support Vector Machine (SVM) method, and to decipher evolving land use patterns over the last four decades. Grounded in landscape ecology theory, an innovative evaluation index for landscape ecological risk was introduced, leading to the delineation of 382 ecological risk evaluation units. Employing landscape pattern indices and a method of spatial autocorrelation, we analyzed the spatial and temporal distribution characteristics and spatial correlation patterns of landscape ecological risk across five distinct periods. Geostatistical approaches were used to explore the driving factors of landscape risk. The results indicate that since 1987, there have been significant changes in land use types, especially in forest landscapes, their proportion increasing from 23.19% to 74.55%. In 1987, the proportion of high-risk areas was 72.30%, but in 2020, high-risk areas had significantly decreased and clustered in specific locations. The landscape ecological risks in each period of the study area showed a positive spatial correlation and tended to gather in space. After comprehensive exploration using a geographic detector, we found that landscape type, temperature, and vegetation coverage are the main risk factors. Among them, landscape type has the greatest impact on the landscape and works together with slope, aspect, and precipitation. In forest farm management, only the adaptation and adjustment of single factors are often paid attention to, while the compound effects of multiple factors are ignored. The results of this study bring important reference value to the operation and development of forest farms.

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Section: Expert Consultation Methods and Normalized Treatmentmentioning

confidence: 99%

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Kang,

Yang,

Qing

et al. 2024

Forests

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“…Based on the results of previous studies [15,16] and combining them with the actual situation of the study area, the size of each landscape index on the ecological environment was analyzed comprehensively. Fragmentation, separation, and dominance were assigned weights of a = 0.5, b = 0.3, and c = 0.2, respectively [17][18][19] .…”

Section: Methodsmentioning

confidence: 99%

Landscape Ecological Risk Assessment during 2000–2020 Based on Land Use and Land Cover Changes in Lanzhou City

2023

AJEE

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A landscape ecological risk model was constructed to evaluate the landscape ecological risk pertaining to Lanzhou City based on the land use and land cover (LULC) changes obtained using remote sensing data for the years 2000 covering the duration 2010 show that during 2010-2020, the LULC types in Lanzhou City mainly comprised of cropland, grassland, and construction land. In terms of LULC changes in Lanzhou City the trend shows a decrease in cropland and increase in construction land with an increase in the fragmentation and separation of cropland, grassland, and shrubland, which is pronounced for cropland and shrubland. The spatial distribution pattern of ecological risk shows very high and very low levels of risk in the main urban area in the south and in the northwest of the city, respectively. From 2010 to 2020, the ecological risk level of the landscape shows a gradual increase with evidence for significant changes. The results of the study provide a scientific basis for the optimization of the landscape pattern, rational utilization and development of land resources in Lanzhou City, and lay a solid foundation for the formulation of ecological risk control measures.

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“…These variations then influence the ecosystems' resistance to external shocks 35 . Drawing on existing research 36,37 and considering the characteristics of winter city areas, In this study, the Landscape Disturbance Index, Vulnerability Index and Loss Index were selected to construct a model to assess the risk of loss of ecological service functions.…”

Section: Eri Evaluation Modelmentioning

confidence: 99%

Spatial-Temporal Variation and Correlation Analysis of Ecosystem Service Values and Ecological Risks in Winter Cities: Evidence from Shenyang, China

Li,

Xie

2024

Preprint

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Ecosystems in winter cities are complex and fragile, experiencing significant changes due to climate variations and human construction activities. Assessing the ecological status and risk faced by these areas commonly involves using Ecosystem Service Value (ESV) and Ecological Risk Index (ERI). However, limited research has combined these two measures to reveal sptial-temporal trends in urban ecosystem conditions. This study utilizes land use data from 2000, 2010, and 2020 to construct ESV and ERI measurement models using the improved unit area value factor method and landscape pattern index method, respectively. By evaluating the regional and temporal differentiation features of ESV and ERI, in addition to their spatial association, the study identifies priority areas for urban ecological restoration and recommends rationalization solutions. The findings indicate: Between 2000 and 2020, Shenyang's total ESV decreased by 1.31%, from 273.97×108 CNY to 270.38×108 CNY. The ESV per unit area dropped from 21304.50 CNY/hm2 to 21025.33 CNY/hm2. The ecological risk to the study area has increased. The area of ERI high-value, higher-value, and medium-value zones remained relatively stable, while the area of low-value zones decreased by 12.78%, and the area of lower-value zones increased by 13.21%. There is a spatial correlation between ESV and ERI in winter cities. The H-H area is distributed in the northeastern hilly region, which exhibits strong ESV supply capacity while facing severe ecological risks, identifying it as a priority region to pursue ecological rehabilitation. These results offer theoretical justification for urban management and planning, guaranteeing the ecological security and sustainability of winter cities.

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Landscapeecological risk assessment of Xi river Basin based on land-use change

Cited by 9 publications

References 0 publications

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Landscape Ecological Risk Assessment of Saihanba under the Change in Forest Landscape Pattern

Landscape Ecological Risk Assessment during 2000–2020 Based on Land Use and Land Cover Changes in Lanzhou City

Spatial-Temporal Variation and Correlation Analysis of Ecosystem Service Values and Ecological Risks in Winter Cities: Evidence from Shenyang, China

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