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Zhang Z, Yu H, He N, Jin G. Future land use simulation model-based landscape ecological risk prediction under the localized shared socioeconomic pathways in the Xiangjiang River Basin, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2024; 31:22774-22789. [PMID: 38413520 DOI: 10.1007/s11356-024-32621-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 02/20/2024] [Indexed: 02/29/2024]
Abstract
Landscape ecological risk (LER) is an effective index to identify regional ecological risk and measure regional ecological security. The localized shared socioeconomic pathways (LSSPs) can provide multi-scenario parameters of social and economic development for LER research. The research of LER under LSSPs is of scientific significance and practical value in curbing the breeding and spread of LER risk areas. In this study, land-cover raster files from 2010 to 2020 were used as the foundational data. Future land use simulation (FLUS), regression, and Markov chain models were used to predict the land cover patterns under the five LSSP scenarios in the Xiangjiang River Basin (XJRB) in 2030. Thus, an evaluation model was established, and the LER of the watershed was evaluated. We found that the rate of land cover change (LCC) in the XJRB between 2010 and 2020 had a higher intensity (increasing at an average of 18.89% per decade) than that projected under the LSSPs for 2020-2030 (averaging an increase of 8.58% per decade). Among the growth rates of all land use types in the XJRB, that of urban land was the highest (33.3%). From 2010 to 2030, the LER in the XJRB was classified as lower risk (33.73%), lowest risk (33.11%), and moderate risk (24.13%) for each decade. Finally, the LER exhibited significant heterogeneity among different scenarios. Specifically, the percentages of regions characterized by the highest (9.77%) and higher LER (9.75%) were notably higher than those in the remaining scenarios. The higher-level risk area under the localized SSP1 demonstrated a clear spatial reduction compared to those of the other four scenarios. In addition, in order to facilitate the differential management and control of LER by relevant departments, risk zoning was carried out at the county level according to the prediction results of LER. And we got three types of risk management regions for the XJRB under the LSSPs.
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Affiliation(s)
- Zhengyu Zhang
- School of Public Administration, China University of Geosciences, Wuhan, 430074, Hubei, China
| | - Han Yu
- School of Management, RMIT University, Melbourne, VIC, 3083, Australia
| | - Nianci He
- School of Economics and Management, China University of Geosciences, Wuhan, 430078, Hubei, China
| | - Gui Jin
- School of Economics and Management, China University of Geosciences, Wuhan, 430078, Hubei, China.
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Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone. LAND 2022. [DOI: 10.3390/land11070964] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.
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Chen D, Zhang F, Zhang M, Meng Q, Jim CY, Shi J, Tan ML, Ma X. Landscape and vegetation traits of urban green space can predict local surface temperature. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 825:154006. [PMID: 35192831 DOI: 10.1016/j.scitotenv.2022.154006] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 02/05/2022] [Accepted: 02/15/2022] [Indexed: 06/14/2023]
Abstract
Societal and technological advances have triggered demands to improve urban environmental quality. Urban green space (UGS) can provide effective cooling service and thermal comfort to alleviate warming impacts. We investigated the relative influence of a comprehensive spectrum of UGS landscape and vegetation factors on surface temperature in arid Urumqi city in northwest China. Built-up area range was extracted from Luojia 1-01 (LJ1-01) satellite data, and within this range, the landscape metric information and vegetation index information of UGS were obtained based on PlanetScope data, and a total of 439 sampling grids (1 km × 1 km) were generated. The urban surface temperature of built-up areas was extracted from Landsat8-TIRS images. The 12 landscape metrics and 14 vegetation indexes were assigned as independent variables, and surface temperature the dependent variable. Support Vector Machine (SVM), Gradient Boost Regression Tree (GBRT) and Random Forest (RF) were enlisted to establish numerical models to predict surface temperature. The results showed that: (1) It was feasible to predict local surface temperature using a combination of landscape metrics and vegetation indexes. Among the three models, RF demonstrated the best accuracy. (2) Collectively, all the factors play a role in the surface-temperature prediction. The most influential factor was Difference Vegetation Index (DVI), followed by Green Normalized Difference Vegetation Index (GNDVI), Class Area (CA) and AREA. This study developed remote sensing techniques to extract a basket of UGS factors to predict the surface temperature at local urban sites. The methods could be applied to other cities to evaluate the cooling impacts of green infrastructures. The findings could provide a scientific basis for ecological spatial planning of UGS to optimize cooling benefits in the arid region.
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Affiliation(s)
- Daosheng Chen
- Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
| | - Fei Zhang
- Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China.
| | - Mengru Zhang
- Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
| | - Qingyan Meng
- Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chi Yung Jim
- Department of Social Sciences, Education University of Hong Kong, Lo Ping Road, Tai Po, Hong Kong, China
| | - Jingchao Shi
- Departments of Earth Sciences, the University of Memphis, Memphis, TN 38152, USA
| | - Mou Leong Tan
- GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, Malaysia
| | - Xu Ma
- Key Laboratory of Wisdom City and Environment Modeling of Higher Education Institute, College of Resources and Environmental Science, Xinjiang University, Urumqi 830046, China; Key Laboratory of Oasis Ecology, Xinjiang University, Urumqi 830046, China
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Landscape Ecological Risk and Ecological Security Pattern Construction in World Natural Heritage Sites: A Case Study of Bayinbuluke, Xinjiang, China. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION 2022. [DOI: 10.3390/ijgi11060328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The evaluation of ecological risk and the construction of ecological security patterns are significant for the conservation of World Natural Heritage sites with high outstanding universal value. This paper constructed a landscape ecological risk evaluation framework for Bayinbuluke using the three aspects of the “nature–society–landscape pattern” and a cumulative resistance surface from the risk evaluation results. The ecological sources were identified based on Morphological Spatial Pattern Analysis (MSPA) and the landscape index. Finally, the Minimum Cumulative Resistance model (MCR) and gravity model were used to obtain both key ecological corridors and general ecological corridors. The results showed that: (1) the influencing factors of landscape ecological risk were, in order of strongest to weakest, landscape pattern factors, natural factors, and social factors; (2) the spatial differences in terms of landscape ecological risk within the study area could be identified. Low-risk areas were mainly concentrated in the core area, high-risk areas were mainly in the outer buffer zone, and the overall ecological risk level at Bayinbuluke was high; and (3) a total of four key corridors and ten general corridors could be constructed. This study provides a reference for decision-making on the ecological security and protection of heritage sites.
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Multi-Dimensional Urbanization Coordinated Evolution Process and Ecological Risk Response in the Yangtze River Delta. LAND 2022. [DOI: 10.3390/land11050723] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
The dislocated development of population, land, and economy will disturb the urban system, cause ecological risk problems, and ultimately affect regional habitat and quality development. Based on social statistics and nighttime lighting data from 2000 to 2018, we used mathematical statistics and spatial analysis methods to analyze the change process of urbanization’s coupling coordination degree and ecological risk response pattern in the Yangtze River Delta. Results show that: ① From 2000 to 2018, the coupling coordination degree of urbanization in the Yangtze River Delta increased, with high values in Suzhou-Wuxi-Changzhou, Shanghai, Nanjing and Hangzhou regions. ② The ecological risk in the Yangtze River Delta weakened, and the vulnerability and disturbance of landscape components together constitute the spatial differentiation pattern of regional ecological risk, which presented homogeneous aggregation and heterogeneous isolation. ③ The overall ecological stress of urbanization in the Yangtze River Delta decreased. ④ The population aggregation degree, socio-economic development level and built-up area expansion trend contributed to the spatiotemporal differentiation of urbanization’s ecological risks through the synergistic effects of factor concentration and diffusion, population quality cultivation and improvement, technological progress and dispersion, industrial structure adjustment and upgrading. This study can provide a reference for regional urbanization to deal with ecological risks reasonably and achieve high-quality development.
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Yang Y, Chen J, Lan Y, Zhou G, You H, Han X, Wang Y, Shi X. Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031595. [PMID: 35162617 PMCID: PMC8835525 DOI: 10.3390/ijerph19031595] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 01/26/2022] [Accepted: 01/28/2022] [Indexed: 12/10/2022]
Abstract
Due to ecological environmental fragility and soil erosion in Guangxi, studies of landscape patterns and associated ecological risks are needed to guide sustainable land development and ecologically sensitive land management. This study assesses dynamic spatial and temporal change patterns in land use and ecological risks based on 30 m land-use data, analyzes spatial correlations with ecological risks, and explores natural and socio-economic factor impacts on ecological risks. The results reveal: (1) A rapid and sizeable construction land increase in Guangxi from 2000 to 2018 associated mainly with loss of woodland and grassland. (2) Guangxi had the highest number of arable land patches from 2000 to 2018, and the distribution tended to be fragmented; moreover, the construction land gradually expanded outward from concentrated areas to form larger aggregates with increasing internal stability each year. (3) Guangxi ecological risk levels were low, low–medium, and medium, with significantly different spatial distributions observed for areas possessing different ecological risk levels. Regional ecological risk gradually decreased from the middle Guangxi regions to the surrounding areas and was positively correlated with spatial distribution. (4) Socio-economic factor impacts on ecological risk exceeded natural factor impacts. These results provide guidance toward achieving ecologically sensitive regional land-use management and ecological risk reduction and control, it can also provide a reference for ecological risk research in other similar regions in the world.
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Affiliation(s)
- Yanping Yang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
| | - Jianjun Chen
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
- Correspondence:
| | - Yanping Lan
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Guoqing Zhou
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Haotian You
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xiaowen Han
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Yu Wang
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
| | - Xue Shi
- College of Geomatics and Geoinformation, Guilin University of Technology, Guilin 541004, China; (Y.Y.); (Y.L.); (G.Z.); (H.Y.); (X.H.); (Y.W.); (X.S.)
- Guangxi Key Laboratory of Spatial Information and Geomatics, Guilin University of Technology, Guilin 541004, China
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Qiao F, Bai Y, Xie L, Yang X, Sun S. Spatio-Temporal Characteristics of Landscape Ecological Risks in the Ecological Functional Zone of the Upper Yellow River, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182412943. [PMID: 34948554 PMCID: PMC8700936 DOI: 10.3390/ijerph182412943] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 12/03/2021] [Accepted: 12/06/2021] [Indexed: 11/18/2022]
Abstract
The Ecological Functional Zone of the Upper Yellow River (EFZUYR) is a critical water-catching area in the Yellow River Basin, the ecological security of which affects the sound development of the ecosystem in the entire basin. Recently, significant land use changes have aggravated regional ecological risks and seriously affected the sustainable development of EFZUYR. In this context, this paper provides an in-depth study of the ecological risks caused by land use landscape changes. With the help of land use data and dynamic degree analysis, the land use transfer matrix, and the landscape pattern index, this paper quantifies the distribution trends of land use landscape patterns in EFZUYR from 1990 to 2018. In addition, this research explores the temporal and spatial dynamic distribution characteristics of landscape ecological risks in this functional zone. The research results show the following: (1) The transfer of land use in EFZUYR from 1990 to 2018 mainly occurred among cultivated land, grassland, and woodland, with the transferred area accounting for 87.16% of the total changed area. (2) The fragmentation degree of built-up areas is 0.1097, 0.1053, 0.0811 and 0.0762 in 1990, 2000, 2010 and 2018, respectively, with a decreasing trend. The dominance degree of grassland has been maintained at the highest level for a long time, with all values above 0.59. The separation degree and the interference degree of built-up areas were the highest and the values of the four periods were above 1.2 and 0.44, respectively. The loss degree of water was the highest, with a value above 0.67, while the value of other land use was mostly below 0.4. (3) The landscape ecological risk of EFZUYR presented a fluctuating rising, falling, and then rising trend. The spatial distribution characteristic of EFZUYR presented “high in the north and south, low in the middle.”, which has been maintained for a long time. The proportion of low-risk areas is as high as 70%, and the overall ecological risk of the region was low. However, the ecological risk of some areas, such as Linxia City and Magu County, increased. These findings can provide theoretical support for land use planning and achieving sustainable development of EFZUYR.
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Affiliation(s)
- Fuwei Qiao
- College of Economics, Northwest Normal University, Lanzhou 730070, China;
| | - Yongping Bai
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China;
| | - Lixia Xie
- College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China;
- Correspondence:
| | - Xuedi Yang
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730070, China;
| | - Shuaishuai Sun
- Northwest Branch of Shanghai Tongji Urban Planning & Design Institute Co., Xi’an 710000, China;
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Yan Y, Ju H, Zhang S, Chen G. The Construction of Ecological Security Patterns in Coastal Areas Based on Landscape Ecological Risk Assessment-A Case Study of Jiaodong Peninsula, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph182212249. [PMID: 34832002 PMCID: PMC8619657 DOI: 10.3390/ijerph182212249] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Revised: 11/18/2021] [Accepted: 11/19/2021] [Indexed: 11/24/2022]
Abstract
Increasing land utilization, population aggregation and strong land–sea interaction make coastal areas an ecologically fragile environment. The construction of an ecological security pattern is important for maintaining the function of the coastal ecosystem. This paper takes Jiaodong Peninsula in China, a hilly coastal area, as an example for evaluating landscape ecological risk within a comprehensive framework of “nature–neighborhood–landscape”, based on spatial principal component analysis, and it constructs the ecological security pattern based on the minimum cumulative resistance model (MCR). The results showed that the overall level of ecological risk in the study area was medium. The connectivity between the areas of low landscape ecological risk was relatively low, and the high risk areas were concentrated in the north of the Peninsula. A total of 11 key ecological corridors of three types (water, green space and road corridors) and 105 potential corridors were constructed. According to the ecological network pattern, landscape ecological optimization suggestions were proposed: key corridors in the north and south of Jiaodong Peninsula should be connected; urban development should consider current ecological sources and corridors to prevent landscape fragmentation; and the ecological roles of potential corridors should be strengthened. This paper can provide a theoretical and practical basis for ecological planning and urban master planning in coastal areas in the future.
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Affiliation(s)
- Yichen Yan
- School of Tourism and Geography Science, Qingdao University, Qingdao 266071, China;
- Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Hongrun Ju
- School of Tourism and Geography Science, Qingdao University, Qingdao 266071, China;
- Correspondence: (H.J.); (S.Z.)
| | - Shengrui Zhang
- Management College, Ocean University of China, Qingdao 266100, China
- Correspondence: (H.J.); (S.Z.)
| | - Guokun Chen
- Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093, China;
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Abstract
With rapid urbanization destroying the ecological environment, scholars have focused on ways to coordinate harmonious development using urban spatial layouts and landscape ecological security. To explore landscape ecological security (the landscape elements, spatial positions and connections that are of key significance to the health and safety of ecological processes) from the perspective of urban form evolution pattern will help to open a new perspective of urban management research, and become the basic work of urban space policy and the implementation of the beautiful China strategy. Based on urban growth and land use data from 356 cities in China, this study applied a geographically weighted regression (GWR) model to quantify the impact of China’s urban growth pattern on landscape ecological security at the spatial level. The research results show that: (1) To some extent, the infilling growth pattern has a certain effect on the enhancement of regional landscape ecological security; (2) In the three control variables (DEM, Population density and GDP), the following conclusions are drawn: regional landscape planning should reasonably allocate landscape resources according to the local topographic features to obtain a higher landscape ecological security; The increase of population density leads to the fragmentation and diversity of the landscape in some regions, which makes the landscape ecological security weak; more economically developed areas have stronger landscape ecological security. This paper highlights the importance of urban growth patterns to landscape ecological security. In addition, considering the different urban evolution trajectories in developed and developing countries, this study proposes targeted development recommendations, providing a reference for urban managers to formulate reasonable development policies and to realize sustainable development with the goal of landscape safety management and control.
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