Driving forces analysis of reservoir wetland evolution in Beijing during 1984–2010

The reservoir wetland, which is the largest artificial wetland in Beijing, constitutes one of the important urban ecological infrastructures. Considering two elements of natural environment and socio-economy, this paper established the driving factor indexing system of Beijing reservoir wetland evolution. Natural environment driving factors include precipitation, temperature, entry water and groundwater depth; social economic driving factors include resident population, urbanization rate and per capita GDP. Using multi-temporal Landsat TM images from 1984 to 2010 in Beijing, the spatial extent and the distribution of Beijing reservoir wetlands were extracted, and the change of the wetland area about the three decade years were analyzed. Logistic regression model was used to explore for each of the three periods： from 1984 to 1998, from 1998 to 2004 and from 2004 to 2010. The results showed that the leading driving factors and their influences on reservoir wetland evolution were different for each period. During 1984-1998, two natural environment indices： average annual precipitation and entry water index were the major factors driving the increase in wetland area with the contribution rate of Logistic regression being 5.78 and 3.50, respectively, and caused the wetland growth from total area of 104.93 km 2 to 219.96 km 2 . From 1998 to 2004, as the impact of human activities intensified the main driving factors were the number of residents, groundwater depth and urbanization rate with the contribution rate of Logistic regression 9.41, 9.18, and 7.77, respectively, and caused the wetland shrinkage rapidly from the total area of 219.96 km 2 to 95.71 km 2 . During 2004-2010, reservoir wetland evolution was impacted by both natural and socio-economic factors, and the dominant driving factors were urbanization rate and precipitation with the contribution rate of 6.62 and 4.22, respectively, and caused the wetland total area growth slightly to 109.73 km 2 .     

1984-2008年北京湿地景观格局驱动机制(英文)

The landscape pattern of Beijing wetlands has undergone a significant change as a result of natural and artificial elements.Supported by remote sensing and GIS technology,using multi-temporal TM images from 1984 to 2008 in Beijing,this paper analyzed the dynamic characteristics of wetlands landscape pattern through selected typical indices including patch area,patch average area,fractal dimension index,diversity,dominance,contagion indices and the spatial centroids of each wetlands type were calculated.Finally,the paper explored the evolution mode and driving factors of wetland landscape pattern.The results were obtained as follows:the total wetland area increased during the period 1984-1996,then decline from 1996 to 2004.The wetland area in 1994 accounted for only 47.37% of that in 2004.The proportion of artificial wetland area was larger than that of natural wetland.The proportion of reservoir wetland was 33.50% to 53.73% and had the maximum average area.pond and paddy field wetland type with the least average area accounted for 16.46% to 45.09% of the total wetland area.The driving forces of the natural river wetland were mainly natural elements;its fractal dimension index was greater than the others.The Shannon diversity index of wetland landscape increased from 1.11 in 1992 to 1.34 in 2004,indicating that the difference between proportions of each wetland type decreased and areas of each wetland type were evenly distributed.The contagion index went down from 65.59 to 58.41,indicating that the connectivity degraded.Miyun Reservoir had the largest area and its area change had a great impact on the location of the centroid.Wetland resources degenerated gradually from the joint effects of natural and artificial factors.During the period 2006-2008,the precipitation increased and the drought condition was relieved.The government implemented series of positive policies to save water resources,and the wetland area increased.     

向海自然保护区鹤类生境优化水位的模拟

The probaility of crane living in reedy wetlands can reach 100%, at the same time,the area of reed ,the water level and adjacent water area are main factors which control the crane‘‘‘‘‘‘‘‘s habitat selection.We all know that all these factors are spatially heterogeneous.For the Xianghai wetland safety and to protect the Xianghai wetland habitat of crane,this paper has mainly identified a solution to these problems.The wetland in formation is extracted from the TM images,which reflect the whole wetland landscape and are very important for both quantitative analysis of remote sensing observation of the earth system and positioning analysis in GIS database that is automatically extracted from DEM.The DEM for Xianghai characteristics of topography is created.On the basis of the GRID SUBMODULE,applying the GIS spatial overlay analysis,the relationship between the water level and the reed area below the water level and the rating distribution maps of reed area above water level is established ,When the water level reaches the altitude of 165 n ,the reed area,981.2 ha is maximum,i.e., the water level of 165 m is the optimal.     

乌梁素海湿地环境演变

The environment evolution of Wuliangsuhai wetland since 1986 is analyzed based on the remote sensing principle. The total water area of Wuliangsuhai lake has been increased during the past 17 years. The open water area had an increasing trend before 1987, and the trend was decreasing up to 1996, then the trend has increased again since 2000; the variation of the water area with dense aquatic weed is basically contradictory to the variation of open water area. The natural reed area had been decreased before 1987, and then it has been increased. The areas of shallow water and swamp have been slightly increased, in fact, the variations are quite steady. The artificial reed area has been increased since the reed plantation was started in 1988. The relationships of the water environment, the climate, hydrology and different types of areas are discussed, and then the technological measures for sustainable development and utilization of Wuliangsuhai lake water environment are proposed.     

Lake Area Changes and the main causes in the hinterland of Badain Jaran Desert during 1973–2010,China

Lake area information in the Badain Jaran Desert in 1973, 1990, 2000, and 2010 was obtained by visual interpretation and water index analysis of remote sensing images, based on the spatial and temporal characteristics of lake area changes during 37 years. Results indicated that the nttmber of lakes declined from 94 to 82 and the total surface area was reduced by 3.69 km2 during 1973-2010. The desert lake area reduced by different degrees in different periods, but this occurred most rapidly during 1973-1990. According to the statistics of lake area changes, lake area decreases mainly occurred in the lakes with areas less than 0.2 km2, while the areas of lakes greater than 0.9 km2 only fluctuated. The changes of lake areas were probably due to changes in the quantity of underground water supplies rather than the effects of local climate change or human factors.     

Attribution analysis for water yield service based on the geographical detector method: A case study of the Hengduan Mountain region

Ecosystem services, which include water yield services, have been incorporated into decision processes of regional land use planning and sustainable development. Spatial pattern characteristics and identification of factors that influence water yield are the basis for decision making. However, there are limited studies on the driving mechanisms that affect the spatial heterogeneity of ecosystem services. In this study, we used the Hengduan Mountain region in southwest China, with obvious spatial heterogeneity, as the research site. The water yield module in the In VEST software was used to simulate the spatial distribution of water yield. Also, quantitative attribution analysis was conducted for various geomorphological and climatic zones in the Hengduan Mountain region by using the geographical detector method. Influencing factors, such as climate, topography, soil, vegetation type, and land use type and pattern, were taken into consideration for this analysis. Four key findings were obtained. First, water yield spatial heterogeneity is influenced most by climate-related factors, where precipitation and evapotranspiration are the dominant factors. Second, the relative importance of each impact factor to the water yield heterogeneity differs significantly by geomorphological and climatic zones. In flat areas, the influence of evapotranspiration is higher than that of precipitation. As relief increases, the importance of precipitation increases and eventually, it becomes the most influential factor. Evapotranspiration is the most influential factor in a plateau climate zone, while in the mid-subtropical zone, precipitation is the main controlling factor. Third, land use type is also an important driving force in flat areas. Thus, more attention should be paid to urbanization and land use planning, which involves land use changes, to mitigate the impact on water yield spatial pattern. The fourth finding was that a risk detector showed that Primarosol and Anthropogenic soil areas, shrub areas, and areas with slope 5° and 25°–35° should be recognized as water yield important zones, while the corresponding elevation values are different among different geomorphological and climatic zones. Therefore, the spatial heterogeneity and influencing factors in different zones should be fully con-sidered while planning the maintenance and protection of water yield services in the Hengduan Mountain region.     

基于模型的中国东北地区土地利用时空格局变化研究（英文）

Spatially explicit modeling techniques recently emerged as an alternative to monitor land use changes. This study adopted the well-known CLUE-S(Conversion of Land Use and its Effects at Small regional extent) model to analyze the spatio-temporal land use changes in a hot-spot in Northeast China(NEC). In total,13 driving factors were selected to statistically analyze the spatial relationships between biophysical and socioeconomic factors and individual land use types. These relationships were then used to simulate land use dynamic changes during 1980–2010 at a 1 km spatial resolution,and to capture the overall land use change patterns. The obtained results indicate that increases in cropland area in NEC were mainly distributed in the Sanjiang Plain and the Songnen Plain during 1980–2000,with a small reduction between 2000 and 2010. An opposite pattern was identified for changes in forest areas. Forest decreases were mainly distributed in the Khingan Mountains and the Changbai Mountains between 1980 and 2000,with a slight increase during 2000–2010. The urban areas have expanded to occupy surrounding croplands and grasslands,particularly after the year 2000. More attention is needed on the newly gained croplands,which have largely replaced wetlands in the Sanjiang Plain over the last decade. Land use change patterns identified here should be considered in future policy making so as to strengthen local eco-environmental security.     

Lake Area Changes and the main causes in the hinterland of Badain Jaran Desert during 1973–2010, China

Lake area information in the Badain Jaran Desert in 1973, 1990, 2000, and 2010 was obtained by visual interpretation and water index analysis of remote sensing images, based on the spatial and temporal characteristics of lake area changes during 37 years. Results indicated that the number of lakes declined from 94 to 82 and the total surface area was reduced by 3.69 km² during 1973–2010. The desert lake area reduced by different degrees in different periods, but this occurred most rapidly during 1973–1990. According to the statistics of lake area changes, lake area decreases mainly occurred in the lakes with areas less than 0.2 km², while the areas of lakes greater than 0.9 km² only fluctuated. The changes of lake areas were probably due to changes in the quantity of underground water supplies rather than the effects of local climate change or human factors.     

中国边境地区城镇化时空格局及其驱动力

Border area is not only an important gateway for inland opening-up,but also an important part of completing the building of a moderately prosperous society and optimizing national urban spatial pattern in China.Due to the location,natural resources endowment,and traffic accessibility,the urbanization speed is relatively slow in border areas.Therefore,it is a special area that needs to pay close attention to,especially under the background of the Belt and Road Initiative and China's regional coordinated development program.Based on the county-level data from 2000 to 2015,this paper tries to analyze the spatio-temporal pattern of urbanization in 134 border counties,and applies geographical detector method to study the driving forces of urbanization in border areas.Conclusions are as follows:(1)From 2000 to 2015,urbanization rate in border areas has been lower than the national average,and the gap has been widening.Some border counties in southern Xinjiang,Tibet,northeast of Inner Mongolia,and Yunnan,are even facing the problem of population loss.(2)In the same period,urbanization rate in the northwestern and southwestern border is low,while their urbanization rate grows relatively faster comparing with other border counties;urbanization rate in Tibet border is the lowest and grows relatively slowly;urbanization rate in the northeastern and northern border is slightly higher,but it grows slowly or even stagnates.(3)Transportation and industry are the important driving forces of urbanization in border areas,while the driving forces of market is relatively weak.And there are obvious mutual reinforcements among the driving forces,while the effort and explanatory power of resource force increases obviously after interaction.(4)Urbanization rate in the northwestern and southwestern border areas grows relatively fast,with industrial force and transportation force,market force and administrative force as the main driving forces respectively.Tibet border area has the lowest urbanization rate and growth rate,as the driving force of urbanization with strong contribution has not yet formed in Tibet.In the northeastern and northern border areas,the contribution of transportation force to urbanization is greater than other forces,and its interaction with market and industry has obvious effects.     

Hydrochemical characteristics of salt marsh wetlands in western Songnen Plain

According to classification system of wetland in Ramsar Convention, salt marsh belongs to inland salt lake formed by regional hydrogeologic and climatic conditions[1]. In western Songnen Plain, the most distinct characteristic of water environment in salt marsh wetlands is that many water bodies have high salt contents and pH values, so salt marsh wetlands are categorized as a special natural synthesis[2]. 1 Natural environment in western Songnen PlainThe Songnen Plain lies to the east of …     

基于Logistic回归模型的北京市水库湿地演变驱动力分析

水库湿地作为北京市面积最大的人工湿地,是北京市重要的生态基础设施。从自然环境和社会经济因素两个方面,构建北京市水库湿地演变的驱动因子指标体系,其中自然驱动因子包括年均降水量、气温、入境水量和地下水埋深;社会经济驱动因子包括常住人口数、城市化率和人均GDP。应用长时间序列(1984-2010 年) 的TM遥感影像,提取北京市近30 年来水库湿地的空间分布信息,根据湿地面积增长和消退的演变规律,利用Logistic 回归模型定量分析不同时间段下水库湿地演变的驱动机制。结果表明:不同时期内水库湿地变化的驱动因子及其影响力存在一定的差异。在1984-1998 年间,北京市水库湿地增长变化的主导驱动因子是年均降水量和入境水量,Logistic 回归的贡献率分别为5.778 和3.504,主要受自然环境因素的影响;在1998-2004 年期间,水库湿地急剧减少的驱动因子主要为常住人口、地下水埋深和城市化率,影响贡献率分别为9.41、9.18 和7.77,人为活动的影响开始加剧;在2004-2010 年间,影响水库湿地发生变化的主导因子是城市化率和年均降水量,贡献率分别为6.62 和4.22,受自然和社会经济因素的交叉影响。     

WETLAND RESOURCES INVESTIGATION IN URBAN PARKS BASED ON QUICKBIRD REMOTE SENSING IMAGE IN JINAN, CHINA

1INTRODUCTIONThe definition of wetlands included in RamsarConvention is deliberately broad,encompassing"areas of marshes,fen,peatland or water,whethernatural or artificial,permanent or temporary,withwater that is flowing or static,fresh,brackish orsalty,i…     

1999～2007年天津湿地景观格局及水鸟生境变化

天津市湿地是亚洲东部候鸟南北迁徙的重要驿站,有大量属国家一、二级保护的鸟类。近几十年来,受人类活动和自然因素变化影响,天津市湿地景观结构发生巨大变化,对湿地鸟类栖息地环境和鸟类迁徙、繁殖产生了不利影响。在遥感和地理信息系统技术的支持下,以天津市1999年、2003年和2007年3期TM影像为数据源,采用目视解译分类方法,并结合其他非遥感以及高清晰影像作为辅助资料,获得了天津市湿地基本信息;在此基础上,将天津市湿地分成2大类12小类;利用ArcMap软件,分析了3个时期湿地面积的变化;利用Frag-stats3.0软件和Excel软件,得到天津市湿地景观格局的动态变化。研究结果表明,天津市湿地总面积从1999年的312088.73hm2增加到2007年的328133.61hm2,面积增加了4.89%;湿地面积增加的主要原因是人工湿地盐田面积大幅增加,人工湿地8年间共增加了24043hm2,其中,盐田面积增加了25699.57hm2,但天然湿地面积减少了7.38%。天津市湿地景观的破碎化程度在一直加剧,斑块类型更加多样化,湿地景观中没有明显的优势类型,且各斑块类型在景观中均匀分布。湿地类型转化的基本规律表现为天然湿地向人工湿地、人工湿地向农林用地、农用地向建设用地转换,人类的开发活动已经转向一些人为干扰较少的潮间带、滩涂区以及河流河口水域、浅海水域、湖泊和沼泽等地区。将各种驱动因素加以组合,归纳为2大类和20个变量指标,建立湿地景观变化驱动因素指标体系。分析表明,人口和经济因素对湿地景观格局变化有显著影响。随着经济发展水平的提高,天津市产业结构并未得到改善,尤其是第二产业仍然占较大比重;城市人口急剧增长,快速城市化导致的城市实体扩张占用大量农田和湿地;在农业因子中,粮食产量的提高与通过占用湿地来扩大种植面积有直接关系。1999～2007年间,天津湿地水鸟生境发生了明显变化,深积水区面积和斑块数量逐年增加;无隐蔽物的湿地面积和人工建筑物的面积大幅增加,重干扰区的面积增加;水鸟的水生动物性食物增多,谷物草籽等植物性食物减少。人类活动已对天津湿地水鸟生存环境构成严重威胁。总体上,天津湿地水鸟生境质量在下降。     

Impact of economic development on wetlands in Hangzhou Bay Industrial Belt

Based on Landsat TM images in 2005 and urban planning data of 2005–2020 in Hangzhou Bay Industrial Belt, this paper studied the potential risk of the planned urban construction land extension to the wetlands by employing a GIS spatial analysis method. The results show that: (1) The wetland resources are widely distributed and diverse, with a proximal distribution to present urban construction lands spatially. (2) From 2005 to 2020, the urban construction lands will expand vastly and rapidly, and will take over large areas of wetlands that are mostly the ponds and the aquiculture water areas in the reclamation areas of Hangzhou Bay south coast. Moreover, this change will be spatially uneven obviously, e.g., the most serious recessions of the wetlands are concentrated in Ningbo city, Hangzhou city and Cixi city. (3) Overall, the potential risk to wetlands is very high, and will keep increasing with the trend of urbanization. (4) The quantity and spatial pattern of the planning urban construction land have substantial impacts on the wetland loss. Therefore, some policies and regulations are suggested to coordinate the relationship between urban economic development and wetland resource protection such as adjusting the construction land planning, compensating for wetland occupation as well as constructing wetland parks.     

北京湿地景观格局演变特征与驱动机制分析

在遥感和GIS技术的支持下,应用1984-2008 年多时相长时间序列的TM遥感数据,选取斑块总面积、平均面积、分维度、多样性、优势度和聚集度等具有典型生态意义的景观格局指数,对北京湿地20 多年的湿地景观格局演变特征进行分析,探索其演变机制。结果表明：北京湿地总面积在总体上呈先增加后急剧减少再小幅回升的趋势,1994 年的湿地总面积仅为2004 年的47.37%。北京湿地以人工湿地为主,其变化主导着湿地总面积的变化趋势。水库湖泊湿地类型面积占到33.50%~53.73%,其平均面积高于其他湿地类型。坑塘稻田类型的平均面积最小,其面积比例为16.46%~45.09%。河流湿地由于受到自然驱动因子作用较大,其分维度指数高于人工湿地类型;1992-2004 年湿地景观多样性指数由1.11 上升到1.34,表明此阶段各类型所占面积比例分布趋于均匀,而聚集度指数从65.59 下降到58.41,表明景观连通性降低,破碎化程度加重。研究不同湿地类型空间质心变化表明：密云水库面积最大,导致水库湖泊类型质心位于密云县内;1984-1998 年充足的降水使河流湿地质心整体向东北方向偏移了10.43 km,1999-2006 年,连续干旱和大量不合理的开采利用,河流湿地质心向西南部偏移了10.75 km;由于受“退稻还旱”政策影响,使得北部地区的水稻种植面积减小,坑塘稻田湿地质心2006 年以后向南偏移;市区北部兴建的奥林匹克森林公园,使2008年公园湿地质心向海淀区北部偏移。     

环杭州湾城市规划及产业发展对湿地保护的影响

根据浙江省环杭州湾产业带2005 年TM 影像和2005-2020 年城市规划数据, 利用GIS 空间分析方法, 分析了规划期间建设用地扩展对湿地的侵占威胁, 并对湿地退缩的潜在风险 进行分析。结果表明： ① 环杭州湾产业带湿地资源丰富, 类型多样, 分布广泛, 现状建设用地在空间上与湿地交错分布, 关系十分密切。② 未来15 年, 城市建设用地扩展规模大、速 度快, 将侵占大面积湿地, 主要是分布在杭州湾南岸湿地围垦区的坑塘、养殖水面类湿地;宁波、杭州、慈溪是湿地退缩最严重的区域。③ 由于现状建设用地与湿地空间分布紧密相关, 湿地被建设用地侵占的潜在风险整体上较大, 且随着建设用地的扩展, 对湿地的侵占有加剧的趋势。④ 建设用地增长幅度及其规划布局对湿地减少有重要影响, 应通过调整建设用地规划、湿地占用补偿、城市湿地公园建设等措施, 加强湿地保护。     

黄河兰州城区段湿地现状及保护建议

调查了黄河兰州城区段湿地类型和分布,结果表明:黄河兰州城区段湿地总面积1729.68hm2。5000m2以上的河岸湿地共计47块,总面积517.17hm2,其中几乎无人为干扰的湿地105.99hm2,仅占河岸湿地面积的20.50%;人为破坏程度非常严重、湿地功能几乎完全丧失的近裸露湿地252.43hm2,占河岸湿地面积的48.81%。黄河兰州城区段湿地存在乱侵乱占、遭受污染、河岸湿地植被破坏和湿地功能日趋退化等问题,提出了湿地保护与恢复建议。     

东北屯人工湿地污水处理系统的设计与应用

从人工湿地规划设计的角度出发,依据地表水环境质量标准,以现有废弃渠道、坑塘为基础,通过开挖回填、调坡整治、基础压实等措施,建立了衡水市故城县郑口镇东北屯人工湿地污水处理系统。该系统包括前池、沉淀池、垂直流湿地、生态塘湿地、表面流湿地和蓄水池。探讨了人工湿地渗滤处理系统的主要设计参数;采用Freundlich公式、Kikuth公式和有关经验公式,分析了渗滤系统对污水生化需氧量、总氮、总磷的处理效果;研究了处理系统中垂直流、生态塘渗流和表面流的污染物去除率;针对水质、水量和环境温度3个主要因素进行了敏感性分析,给出了渗滤系统敏感性分析结果,并与湿地去污实验结果进行了比较,变化趋势基本一致。研究结果表明:①人工湿地规划设计应进行敏感性分析,以便更好地制定系统的控制运行预案;②湿地出水口高度应能够调节,以便控制湿地床体的"饱和"状态,充分发挥湿地渗滤、微生物的作用;③北方人工湿地的去污效果,受季节性影响较大,应采取塑料大棚或秸秆覆盖进行保温,在冬季,塑料大棚能够使湿地温度维持在13.3℃以上,日照时间基本不减少,湿地植物可正常生长;④当进水的生化需氧量浓度超过75mg/L时,应减小进水负荷,控制污染物总量在湿地高效处理范围内;⑤当日污水处理量超过3000m3/d时,应提高集污渠、前池、沉淀池的临时蓄存水位。     

广州南沙地区湿地生态系统的服务功能与保护

南沙地区是广州城市空间“南拓”发展战略的重点开发区域。南沙地区湿地资源丰富，其开发建设必须正确处理湿地开发与保护的关系，实现社会经济与生态环境可持续发展。在南沙地区湿地资源现状调查的基础上，分析了南沙地区湿地生态系统的服务功能，依据功能的重要程度与湿地资源的稀缺性，指出了南沙开发中应加强生态敏感区、红树林生境、水生动物繁殖区与鱼类洄游通道、自然林植被区、历史文化遗迹与自然景观分布区等重要湿地的保护，并提出了相应保护措施。