Assessing wetland changes in the venice lagoon by means of satellite remote sensing data

Not only does lagoon ecology represent a transitional zone between the sea and the continent but it also expresses the equilibrium belt between erosion and sedimentation processes. Within the framework of a coastal management scheme, a precise and timely mapping of morphological changes in this environment is important. This paper illustrates the possible contribution of multi-temporal satellite observations in the monitoring of the erosion/sedimentation processes of coastal zones, where landscape features are subjected to highly morphodynamical modifications. In particular, an improved mapping accuracy was obtained by the successive application of the Maximum Likelihood (MLH) classifier and the Linear Mixture Model (LMM) techniques to the satellite image classification procedure. In fact, by estimating the amount of shallow water and wetland within each satellite pixel, the LMM technique allows for an accurate mapping of the transitional zones in the lagoon environment, thus permitting an optimal separation between land and water. The study concerns the Venice lagoon (Italy) which has been sinking slowly since the beginning of this century. This has led to widespread loss of wetlands. In order to monitor the development of the land cover, four Landsat Thematic Mapper scenes were examined, during the period 1984 to 1993. The results obtained proved that the digital analysis method of multitemporal satellite imagery, applied over a selected test area, enables the evolution of an estuarine environment landscape, with its different sequences of erosion and periods of accretion, to be monitored. The significant influence of tidal stages is discussed in the data analysis.     

An Environmental Domain Classification of New Zealand and Its Use as a Tool for Biodiversity Management

Abstract:   Successful biodiversity management, including the selection and subsequent management of protected areas, depends in large measure on classifications showing land areas with similar ecosystem character. In contrast to widely used, qualitative land-classification techniques, we used a numerical classification of explicit spatial layers describing aspects of New Zealand's climate and landforms. We chose input variables for their strong functional links with major physiological processes of trees and high statistical correlations with geographic distributions of individual tree species as determined from previous studies. Higher-level divisions of the resulting classification were dominated by macroclimatic variation associated with change in both latitude and orographic protection provided by New Zealand's main mountain ranges, but variation in landform became more important at finer scales of classification. Classification units showed marked variation in the proportional extent of both indigenous vegetation cover and land set aside for conservation purposes. Indigenous ecosystem remnants of the highest priority for increased protection occurred in warm, lowland domains, particularly in drier environments, where both indigenous cover and protected areas are of minimal geographic extent. Such results underline the considerable potential of an environmental classification to provide a landscape context for systematic conservation management, particularly in environments where the natural ecosystem pattern has been severely modified by human activity.     

试论湖北省伏旱的环流特征

通过对湖北省几个典型伏旱年的同期环流特征的分析,揭示了与湖北严重伏旱灾害密切联系的几中大气环流系统,并进行了分型。指出,造成严重伏旱的主要天气系统有西太平洋副热高压,西风带环流和西太平洋台风,并根据伏旱期大气环流的不同型式,将造成湖北伏旱的环流特征主要归结为两类,一是副高势力强盛,西伸强烈,稳定控制长江中下游地区;中高纬度向环流占优势;台风活动较少,另一类是副高压势力较弱,主体位于太平洋面上空,西     

贵阳市乌当区耕地土壤重金属污染现状及其评价

在对乌当区10乡镇耕地土壤进行全面调查的基础上，对土壤重金属污染现状进行了监测与初步评价，结果表明：该区域10乡镇耕地土壤5种重金属元素(Cd、Pb、Cr、Hg、As)的含量变幅较大；全区耕地土壤重金属污染综合评价处于警戒水平，多因子综合污染指数为0．78．其中，金华、朱昌两镇的耕地土壤已受到了重金属轻度污染，多因子综合污染指数分别为1．13、1．22，羊昌、新堡、下坝、东风、水田等5乡镇的耕地土壤处于警戒状态，新场、百宜、偏坡等3乡镇的土壤处于安全状态；Cd、Cr是该区耕地土壤的主要污染元素。     

中国生态用地及生态系统服务价值变化研究

生态用地具有重要的生态系统服务功能,在维护生态平衡、保障国土生态安全、应对全球气候变化中具有特殊地位。论文在总结国内研究学者有关生态用地研究成果的基础上,从生态系统服务功能入手,界定了生态用地的概念,根据生态干扰度构建了生态用地分类体系,并将生态用地分类与土地利用分类进行衔接,对全国生态用地的生态系统服务价值进行了评估,分析其特征及规律。研究表明：1）广义的生态用地是指能发挥供给、调节、支持生态系统服务功能,以及对维持区域生态平衡和调节全球气候具有重要作用的土地类型;2）依据“生态干扰度”构建了生态用地分类体系,将生态用地分为3个一级地类、5个二级地类和31个三级地类;3）2012年全国生态用地的生态系统服务价值为280 483.80亿元,呈现“西高、中次、东低”空间格局。2009—2012年全国生态用地的生态系统服务价值整体呈下降趋势,变化幅度空间分布差异较大,呈现“中增、东西减”的格局特点;2009—2012年全国生态用地各项生态系统服务功能受到损失,呈下降趋势,生态系统稳定性不容乐观。     

基于决策树的城市黑臭水体遥感分级

水体黑臭程度遥感监测是了解城市水质现状和综合评价城市水环境治理效果的重要手段.以南京、常州、无锡和扬州为研究区,共采集171个样点,同步测量水质参数和光学参数,分析黑臭水体与一般水体的水色和光学特征,构建决策树模型进行重度黑臭水体、轻度黑臭水体和非黑臭水体（记为一般水体）识别.结果表明：①根据色度可将水体分为1~6类水体,其中,类型1~4为黑臭水体,分别为灰黑色、深灰色、灰色和浅灰色水体,类型5和类型6水体为一般水体,分别为绿色系和黄色系水体;②类型1水体的非色素颗粒物和有色可溶性有机物含量高,但色素颗粒物的吸收并不占主导,类型2和5水体的吸收以色素颗粒物吸收占主导,类型3、4和6水体的吸收以非色素颗粒物吸收占主导;③根据六类水体的反射光谱差异用黑臭水体差值指数（difference of black-odorous water index,DBWI）、三波段面积水体指数（green-red-nir area water index,G-R-NIR AWI）、绿光波段反射率和归一化黑臭水体指数（normalized difference black-odorous water index,NDBWI）构建的水体分类识别决策树,能够有效识别出重、轻度黑臭水体和一般水体;④将决策树模型应用于2019年4月9日扬州的PlanetScope影像上,并利用10个同步过境点进行验证,整体识别精度达到80.00%,K值达到0.67.通过水色分类后的城市水体分级模型方法,可推广应用于类似的水体,为黑臭水体监管提供技术方法.     

建设项目环境影响后评价

建设项目环境影响后评价是一个新生事物,它的发生和发展需要人员的关注和支持。《中华人民共和国环境影响评价法》是建设项目环境影响后评价的法律依据,建设项目环境影响后评价分为主动后评价和责成后评价,应当在建设项目正常运行阶段,运行负荷会达到设计符合的75%以上进行。建设项目环境影响后评价的主要程序分为准备阶段、评价阶段和报告编制阶段,各阶段均有后评价独特的工作内容和技术要求。据此以污水处理厂后评价为例,沿着评价程序的这一主线,详细介绍了建设项目环境影响后评价各阶段的主要工作内容和技术要求,为规范建设项目环境影响后评价提供思路。     

Classification of different sustainable flood retention basin types

Using a revised version of a previously published expert classification system, a database of potential Sustainable Flood Retention Basins has been developed for Scotland. The research shows that the majority of small and former (often old) drinking water reservoirs are kept full and their spillways are continuously in operation. Utilising some of the available capacity to contribute to flood control could significantly reduce the costs of complying with the European Union Flood Directive. Furthermore, the application of a previously developed classification model for Baden in Germany for the Scottish data set showed a lower diversity for basins in Scotland due to less developed infrastructure. The classification system appears to be robust and has the potential, with minor modifications, to be applied across Europe. The principle value of this approach is a clear and unambiguous categorisation, based on standard variables, which can help to promote communication and understanding between stakeholders.     

The method for leakage detection of urban natural gas pipeline based on the improved ITA and ALO

To solve the problems of the difficulty in early leakage monitoring and larger positioning error for urban hazardous chemicals pipelines, the optimized method based on the improved Inverse Transient Analysis (ITA) and Ant Lion Optimizer (ALO) was proposed. Firstly, based on the obtained experiment's results of leakage of natural gas in the non-metallic pipeline, the segment classification method was incorporated into the pressure gradient calculation. The modified method can adapt to the multi-node characteristics of urban pipe networks and help to obtain the preliminary positioning calculation results after optimization. Then the calculation results were embedded in the ITA calculation model. The input parameters of the gas pipeline such as boundary conditions, leakage rate and friction coefficient were used to establish the characteristic linear equations. Then the objective function of the least-squares criterion was defined, and the improved ITA model suitable for leakage detection of urban natural gas pipeline networks was constructed. Finally, the ALO was used to optimize the calculation process of the improved ITA model, and iteratively optimize the optimal friction coefficient and its corresponding minimum objective function (OF) value. As a result, a more precise location of the leakage source was calculated. The validation of the modified method is conducted by comparing the calculated values with the experiment's results. The results show that the method can accurately predict the location where the pipeline leakage occurs. The minimum error is 3.17%. Compared with the traditional ITA, this method not only accelerates the convergence speed of the objective function, but also improves the accuracy of location calculation.