Ecological vulnerability analysis (EVA) is vital for ecological protection,restoration,and management of wetland-type national parks.In this study,we assessed the ecological vulnerability of Beidagang National Park ba...Ecological vulnerability analysis (EVA) is vital for ecological protection,restoration,and management of wetland-type national parks.In this study,we assessed the ecological vulnerability of Beidagang National Park based upon remote sensing (RS) and geographic information system (GIS) technologies.To quantify the ecological vulnerability,10 indices were collected by the 'exposuresensitivity- adaptive capacity' model and spatial principal component analysis (SPCA) was then applied to calculate the ecological vulnerability degree (EVD).Based on the numerical values,EVD of the study area was classified into five levels: moderate,light,medium,strong,and extreme.Results showed that the average EVD value was approximately 0.39,indicating overall good ecological vulnerability in Beidagang National Park.To be specific,80.42% of the whole area was assigned to a moderate level of EVD with the highest being the tourism developed areas and the lowest being the reservoirs and offshore areas.Ecological vulnerability of the region was determined to be affected by the natural environment and anthropogenic disturbance jointly.The primary factors included tourism disturbance,traffic interference,exotic species invasion,land use/land cover,and soil salinization.We expected to provide some insights of the sustainable development of Beidagang National Park and would like to extend the results to other wetland-type national parks in the future.展开更多
科学地规划游客的数量与时段已经成为当前国家公园迫切需要解决的问题。基于2000—2018年MODIS 250 m NDVI数据、土地覆盖/利用数据、90 m高程(DEM)数据、地理信息数据和气象资料等,分析研究了武夷山国家公园不同景区活动类型(保护区、...科学地规划游客的数量与时段已经成为当前国家公园迫切需要解决的问题。基于2000—2018年MODIS 250 m NDVI数据、土地覆盖/利用数据、90 m高程(DEM)数据、地理信息数据和气象资料等,分析研究了武夷山国家公园不同景区活动类型(保护区、景区和过渡区)森林植被的生长季、NDVI年际变化趋势和脆弱性。结果表明:(1)相对于保护区植被生长季10月份结束,景区植被生长季结束期提前,最早提前到9月份。(2)2000—2018年气候变化和景区活动均带来植被指数的增加,但景区活动影响大于气候变化影响。(3)景区活动加重森林植被的脆弱性,其脆弱性程度呈景区>过渡区>保护区。(4)景区活动对森林植被呈负作用,但正在发生的气候变暖和景区有效管理可在一定程度上补偿这一负作用。研究结果可为武夷山国家公园制定旅游时间和游客数量提供决策依据。展开更多
Climate change is the main factor affecting the country’s vulnerability,meanwhile,it is also a complicated and nonlinear dynamic system.In order to solve this complex problem,this paper first uses the analytic hierar...Climate change is the main factor affecting the country’s vulnerability,meanwhile,it is also a complicated and nonlinear dynamic system.In order to solve this complex problem,this paper first uses the analytic hierarchy process(AHP)and natural breakpoint method(NBM)to implement an AHP-NBM comprehensive evaluation model to assess the national vulnerability.By using ArcGIS,national vulnerability scores are classified and the country’s vulnerability is divided into three levels:fragile,vulnerable,and stable.Then,a BP neural network prediction model which is based on multivariate linear regression is used to predict the critical point of vulnerability.The function of the critical point of vulnerability and time is established through multiple linear regression analysis to obtain the regression equation.And the proportion of each factor in the equation is established by using the partial least-squares regression to select the main factors affecting the country’s vulnerability,and using the neural network algorithm to perform the fitting.Lastly,the BP neural network prediction model is optimized by genetic algorithm to get the chaotic time series BP neural network prediction model.In order to verify the practicability of the model,Cambodia is selected to be an example to analyze the critical point of the national vulnerability index.展开更多
基金the National Natural Science Foundation of China(Grant No.41771098)Shandong Natural Science Foundation(Nos.ZR2014DQ028 and ZR2015DM004).
文摘Ecological vulnerability analysis (EVA) is vital for ecological protection,restoration,and management of wetland-type national parks.In this study,we assessed the ecological vulnerability of Beidagang National Park based upon remote sensing (RS) and geographic information system (GIS) technologies.To quantify the ecological vulnerability,10 indices were collected by the 'exposuresensitivity- adaptive capacity' model and spatial principal component analysis (SPCA) was then applied to calculate the ecological vulnerability degree (EVD).Based on the numerical values,EVD of the study area was classified into five levels: moderate,light,medium,strong,and extreme.Results showed that the average EVD value was approximately 0.39,indicating overall good ecological vulnerability in Beidagang National Park.To be specific,80.42% of the whole area was assigned to a moderate level of EVD with the highest being the tourism developed areas and the lowest being the reservoirs and offshore areas.Ecological vulnerability of the region was determined to be affected by the natural environment and anthropogenic disturbance jointly.The primary factors included tourism disturbance,traffic interference,exotic species invasion,land use/land cover,and soil salinization.We expected to provide some insights of the sustainable development of Beidagang National Park and would like to extend the results to other wetland-type national parks in the future.
文摘科学地规划游客的数量与时段已经成为当前国家公园迫切需要解决的问题。基于2000—2018年MODIS 250 m NDVI数据、土地覆盖/利用数据、90 m高程(DEM)数据、地理信息数据和气象资料等,分析研究了武夷山国家公园不同景区活动类型(保护区、景区和过渡区)森林植被的生长季、NDVI年际变化趋势和脆弱性。结果表明:(1)相对于保护区植被生长季10月份结束,景区植被生长季结束期提前,最早提前到9月份。(2)2000—2018年气候变化和景区活动均带来植被指数的增加,但景区活动影响大于气候变化影响。(3)景区活动加重森林植被的脆弱性,其脆弱性程度呈景区>过渡区>保护区。(4)景区活动对森林植被呈负作用,但正在发生的气候变暖和景区有效管理可在一定程度上补偿这一负作用。研究结果可为武夷山国家公园制定旅游时间和游客数量提供决策依据。
文摘Climate change is the main factor affecting the country’s vulnerability,meanwhile,it is also a complicated and nonlinear dynamic system.In order to solve this complex problem,this paper first uses the analytic hierarchy process(AHP)and natural breakpoint method(NBM)to implement an AHP-NBM comprehensive evaluation model to assess the national vulnerability.By using ArcGIS,national vulnerability scores are classified and the country’s vulnerability is divided into three levels:fragile,vulnerable,and stable.Then,a BP neural network prediction model which is based on multivariate linear regression is used to predict the critical point of vulnerability.The function of the critical point of vulnerability and time is established through multiple linear regression analysis to obtain the regression equation.And the proportion of each factor in the equation is established by using the partial least-squares regression to select the main factors affecting the country’s vulnerability,and using the neural network algorithm to perform the fitting.Lastly,the BP neural network prediction model is optimized by genetic algorithm to get the chaotic time series BP neural network prediction model.In order to verify the practicability of the model,Cambodia is selected to be an example to analyze the critical point of the national vulnerability index.
