Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Collection and Processing
2.3. Methods
2.3.1. Land Use Dynamics
2.3.2. Land Use Transfer Matrix
2.3.3. Landscape Ecological Risk Assessment
2.3.4. Spatial Autocorrelation Analysis
- (1)
- Global spatial autocorrelation
- (2)
- Local spatial autocorrelation
3. Results
3.1. Land Use Change Processes from 2000 to 2020
3.1.1. Analysis of Land Use Dynamics Change
3.1.2. Analysis of Land Use Transfer Change
3.2. Analysis of Spatial and Temporal Changes in Ecological Risks
3.3. Analysis of the Spatial Pattern of Ecological Risks
3.3.1. Global Spatial Autocorrelation Analysis
3.3.2. Local Spatial Autocorrelation Analysis
4. Discussion
4.1. Tempo-Spatial Changes of the Land Use and Landscape Ecological Risk in YRBS
4.2. Ecological Protection and High-Quality Development of the YRBS
4.3. Limitation
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Index | Calculation Formula | Ecological Significance |
---|---|---|
Landscape loss degree index (Ri) | Ri indicates the degree of loss of natural properties of ecosystems represented by different landscape types when they are subjected to natural and anthropogenic disturbances [54]. | |
Landscape disturbance index (Ei) | Ei describes the extent to which ecosystems located in different landscape types are disturbed by human activities and characterizes differences related to maintenance of ecological stability of different landscape types [57]; a, b, and c represent weights of the corresponding landscape indices; according to results of previous studies, values of a = 0.5, b = 0.3, and c = 0.2 are assigned. | |
Landscape fragmentation index (Ci) | Describes the degree of fragmentation of a landscape type in the region at a given time; such that, the higher its value, the lower the stability within the landscape unit and the greater the heterogeneity and discontinuity among patches [58]; ni denotes the number of patches of landscape type i and Ai denotes the total area of landscape type i. | |
Landscape dominance index (Di) | The higher the value, the greater the influence of the landscape type on the overall landscape pattern [59]. Qi = number of samples in which patch i occurs/total number of samples; Mi = number of patch i/total number of patches; and Li = area of patch i/total area of samples. | |
landscape separateness index (Ni) | The greater the degree of separation between different patches in a landscape type, the more discrete the distribution of the landscape type in the region for a correspondingly higher degree of fragmentation [60]; A is the total area of the landscape; Ni is the distance index of landscape type i. | |
Landscape vulnerability index (Fi) | Based on the previous studies | The higher the value, the more vulnerable and unstable the landscape type is and the more likely it will suffer ecological losses and physical changes due to external disturbances [61]. Based on the previous studies, in this study [62], vulnerability indices of six landscape types were assigned as follows: unused land 6, water 5, cultivated land 4, grassland 3, woodland 2, and residential land 1, with the landscape vulnerability index Fi obtained after normalization. |
Ecological Risk | Risk Level | ||||
---|---|---|---|---|---|
Low | Low-Medium | Medium | Medium-High | High | |
rank | I | II | III | IV | V |
value | 0.0135 < ERI | 0.0135 ≤ ERI < 0.030 | 0.030 ≤ ERI < 0.060 | 0.060 ≤ ERI < 0.099 | ERI ≥ 0.099 |
Land Type | 2000–2010 | 2010–2020 | 2000–2020 | |||
---|---|---|---|---|---|---|
Area Change (km2) | Single Dynamics (%) | Area Change (km2) | Single Dynamics (%) | Area Change (km2) | Single Dynamics (%) | |
Cultivated Land | −1000.56 | −0.17 | −197.86 | −0.03 | −1198.41 | −0.11 |
Forest Land | 351.25 | 0.09 | −118.57 | −0.03 | 232.68 | 0.03 |
Grassland | −502.24 | −0.11 | −1232.16 | −0.28 | −1734.4 | −0.2 |
Shrubland | 159.93 | 3.14 | −28.45 | −0.41 | 131.48 | 1.36 |
Wetland | −54.8 | −2.03 | −10.77 | −0.51 | −65.56 | −1.28 |
Water Body | −40.31 | −0.69 | 30.08 | 0.56 | −10.23 | −0.09 |
Artificial Surface | 1072.16 | 3.11 | 1665.78 | 3.59 | 2737.94 | 4.21 |
Bare Ground | 14.47 | 0.09 | −103.61 | −0.64 | −89.13 | −0.29 |
Comprehensive Dynamics (%) | 0.108 | 0.114 | 0.111 |
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Zhu, Z.; Mei, Z.; Xu, X.; Feng, Y.; Ren, G. Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China. Int. J. Environ. Res. Public Health 2022, 19, 9547. https://doi.org/10.3390/ijerph19159547
Zhu Z, Mei Z, Xu X, Feng Y, Ren G. Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China. International Journal of Environmental Research and Public Health. 2022; 19(15):9547. https://doi.org/10.3390/ijerph19159547
Chicago/Turabian StyleZhu, Zhiyuan, Zhikun Mei, Xiyang Xu, Yongzhong Feng, and Guangxin Ren. 2022. "Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China" International Journal of Environmental Research and Public Health 19, no. 15: 9547. https://doi.org/10.3390/ijerph19159547
APA StyleZhu, Z., Mei, Z., Xu, X., Feng, Y., & Ren, G. (2022). Landscape Ecological Risk Assessment Based on Land Use Change in the Yellow River Basin of Shaanxi, China. International Journal of Environmental Research and Public Health, 19(15), 9547. https://doi.org/10.3390/ijerph19159547