利用卫星遥感评估广西壮族自治区SO_2减排成效

基于2005—2012年OMI卫星遥感PBL SO2柱浓度数据分析了广西壮族自治区SO2污染的时空格局和变化特征,并结合燃煤火电厂SO2排放模型估算与工业经济增长数据,在时间、空间尺度上分析了自治区内不同区域的SO2污染对火电厂烟气脱硫政策的响应以及所呈现出的减排成效。结果表明,广西因火电厂脱硫政策驱动的SO2污染改善具有显著的空间异质性,自治区内高污染区的SO2浓度在2011—2012年出现了显著下降,而低污染区的SO2浓度则在8年中持续增长;排放模型估算结果显示,烟气脱硫驱动的火电厂SO2减排贡献将在2008年后持续下降,而遥感观测结果显示,广西全区SO2半年浓度均值总体呈现波动上升趋势,2005—2012年浓度增加了8.6%、年均增长约0.9%;综合工业经济增长数据发现,近年来其他工业源的增量排放已给广西SO2减排带了新挑战,而这一变化仍未得到相关决策部门关注,存在明显缺陷的SO2统计排放量数据尚未得到修正。针对上述污染变化新特征,政府相关部门应引起足够重视,尽快更新完善污染源信息并启动针对其他污染源的限排措施,以确保环境持续改善。     

Soil erosion and non-point source pollution impacts assessment with the aid of multi-temporal remote sensing images

Soil erosion associated with non-point source pollution is viewed as a process of land degradation in many terrestrial environments. Careful monitoring and assessment of land use variations with different temporal and spatial scales would reveal a fluctuating interface, punctuated by changes in rainfall and runoff, movement of people, perturbation from environmental disasters, and shifts in agricultural activities and cropping patterns. The use of multi-temporal remote sensing images in support of environmental modeling analysis in a geographic information system (GIS) environment leading to identification of a variety of long-term interactions between land, resources, and the built environment has been a highly promising approach in recent years. This paper started with a series of supervised land use classifications, using SPOT satellite imagery as a means, in the Kao-Ping River Basin, South Taiwan. Then, it was designed to differentiate the variations of eight land use patterns in the past decade, including orchard, farmland, sugarcane field, forest, grassland, barren, community, and water body. Final accuracy was confirmed based on interpretation of available aerial photographs and global positioning system (GPS) measurements. Finally, a numerical simulation model (General Watershed Loading Function, GWLF) was used to relate soil erosion to non-point source pollution impacts in the coupled land and river water systems. Research findings indicate that while the decadal increase in orchards poses a significant threat to water quality, the continual decrease in forested land exhibits a potential impact on water quality management. Non-point source pollution, contributing to part of the downstream water quality deterioration of the Kao-Ping River system in the last decade, has resulted in an irreversible impact on land integrity from a long-term perspective.     

基于EMD-HHT可定位长输天然气管道第三方破坏事件监测技术

为适应目前管道安全监测需要,满足对扰动信号分类监测的实际需求,提出1种基于希尔伯变换和经验模态分解(EMD-HHT)的信号特征提取技术,利用基于φ-OTDR分布式光纤传感系统采集振动信号,通过EMD+HHT区分算法对管道沿线振动事件进行分解并提取6个典型特征向量,各特征事件数据经过EMD后选取IMF3为最终提取特征向量的原始数据,BP神经元网络可有效识别机械破坏、敲击破坏、车辆经过、人工挖掘、动力干扰5种事件。研究结果表明：在长输管道信号识别中,BP神经网络对5类事件平均识别率高达98.6%,该技术分类识别5类事件扰动信号,能够达到较高准确性,并且误报率平均在1.3%,能较好满足现场安全实时监测需求。研究结果对长输油气管道附近第三方破坏扰动信号分类监测具有一定参考意义。     

地表水环境遥感监测关键技术与系统

本文主要是围绕地表水环境遥感检测展开讨论,全面介绍了水环境检测的关键技术和系统,建立改进双峰法的水体分布遥感提取方法,并以具体地区为例进行分析,采用不同方法建立解析方法,从根本上提升反演方法的区域和积极适用性,希望能够对相关人员起到参考性价值。     

玛纳斯河流域荒漠草地沙化遥感监测研究

以1989—2016年玛纳斯河流域TM/OLI遥感影像为数据源,利用混合像元分解技术,计算玛纳斯河流域草地总覆盖度和裸沙面积。在此基础上通过监测年与基期年的比较,计算草地覆盖度相对基期年的减少率和裸沙面积相对基期年的增加率两个监测指标,依据《天然草地退化、沙化、盐渍化的分级指标》(GB 19377—2003),对计算出的两个指标分别进行沙化等级评定和赋值,将两种评定结果相综合来监测草地沙化。结果表明,玛纳斯河流域近30年来荒漠草地沙漠化总体呈现先增加后降低的趋势。分析表明,玛纳斯河流域草地沙化是人为和自然因素双重作用的结果。     

Hyperspectral Characteristics of Canopy Components and Structure for Phenological Assessment of an Invasive Weed

Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and postflowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.     

Mapping the Spatial Variability of Plant Diversity in a Tropical Forest: Comparison of Spatial Interpolation Methods

Knowledge of the spatial distribution of plant species is essential to conservation and forest managers in order to identify high priority areas such as vulnerable species and habitats, and designate areas for reserves, refuges and other protected areas. A reliable map of the diversity of plant species over the landscape is an invaluable tool for such purposes. In this study, the number of species, the exponent Shannon and the reciprocal Simpson indices, calculated from 141 quadrat sites sampled in a tropical forest were used to compare the performance of several spatial interpolation techniques used to prepare a map of plant diversity, starting from sample (point) data over the landscape. Means of mapped classes, inverse distance functions, kriging and co-kriging, both, applied over the entire studied landscape and also applied within vegetation classes, were the procedures compared. Significant differences in plant diversity indices between classes demonstrated the usefulness of boundaries between vegetation types, mapped through satellite image classification, in stratifying the variability of plant diversity over the landscape. These mapped classes, improved the accuracy of the interpolation methods when they were used as prior information for stratification of the area. Spatial interpolation by co-kriging performed among the poorest interpolators due to the poor correlation between the plant diversity variables and vegetation indices computed by remote sensing and used as covariables. This indicated that the latter are not suitable covariates of plant diversity indices. Finally, a within-class kriging interpolator yielded the most accurate estimates of plant diversity values. This interpolator not only provided the most accurate estimates by accounting for the indices' intra-class variability, but also provided additional useful interpretations of the structure of spatial variability of diversity values through the interpretation of their semi-variograms. This additional role was found very useful in aiding decisions in conservation planning.     

Integrating Remote Sensing Approach with Pollution Monitoring Tools for Aquatic Ecosystem Risk Assessment and Managment: A Case Study of Lake Victoria(UGANDA)

Aquatic ecosystems around the world, lake, estuaries and coastal areas are increasingly impacted by anthropogenic pollutants through different sources such as agricultural, industrial and urban discharges, atmospheric deposition and terrestrial drainage. Lake Victoria is the second largest lake in the world and the largest tropical lake. Bordered by Tanzania, Uganda, and Kenya, it provides a livelihood for millions of Africans in the region. However, the lake is under threat from eutrophication, a huge decline in the number of native fish species caused by several factors including loss of biodiversity, over fishing and pollution has been recently documented. Increasing usage of pesticides and insecticides in the adjacent agricultural areas as well as mercury contamination from processing of gold ore on the southern shores are currently considered among the most emergent phenomena of chemical contamination in the lake. By the application of globally consistent and comprehensive geospatial data-sets based on remote sensing integrated with information on heavy metals accumulation and insecticides exposure in native and alien fish populations, the present study aims at assessing the environmental risk associated to the contamination of the Lake Victoria water body on fish health, land cover distribution, biodiversity and the agricultural area surrounding the lake. By the elaboration of Landsat 7 TM data of November 2002 and Landsat 7 TM 1986 we have calculated the agriculture area which borders the Lake Victoria bay, which is an upland plain. This process has greatly enhanced nutrient loading to the soil, which is subsequently transported to the lake by rain or as dry fall. All the data has been insert in the Geographical information System (ARCGIS) to be upgraded and consulted. Heavy metals in fish fillets showed concentrations rather low except for mercury being higher than others as already described in previous investigations. In the same tissue, cholinesterases activity (ChE) as an indicator of insecticides exposure showed significant differences among fish species in both activity and sensitivity of selected inhibitor insecticides. This integrated approach aims at identifying and quantifying selected aquatic environmental issues which integrated with monitoring techniques such as contaminant concentrations and biological responses to insecticides exposure in fish populations will provide a scientific basis for aquatic zones management and assist in policy formulations at the national and international levels.     

基于MERIS数据的太湖悬浮物与叶绿素a遥感估算研究

基于MERIS数据,采用最大叶绿素指数算法,分别建立太湖悬浮物浓度与叶绿素a浓度的估算模型。经误差分析证明,该模型适宜检测悬浮物与叶绿素a质量浓度范围分别为15 g/m3～80 g/m3与10 mg/m3～20 mg/m3的水域,可用于太湖水体悬浮物与叶绿素a的MERIS遥感估算。     

Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore,Maryland1

Smith, Monica Lipscomb, Weiqi Zhou, Mary Cadenasso, Morgan Grove, and Lawrence E. Band, 2010. Evaluation of the National Land Cover Database for Hydrologic Applications in Urban and Suburban Baltimore, Maryland. Journal of the American Water Resources Association (JAWRA) 46(2):429-442. DOI: 10.1111/j.1752-1688.2009.00412.x Abstract: We compared the National Land Cover Database (NLCD) 2001 land cover, impervious, and canopy data products to land cover data derived from 0.6-m resolution three-band digital imagery and ancillary data. We conducted this comparison at the 1 km², 9 km², and gauged watershed scales within the Baltimore Ecosystem Study to determine the usefulness and limitations of the NLCD in heterogeneous urban to exurban environments for the determination of land-cover information for hydrological applications. Although the NLCD canopy and impervious data are significantly correlated with the high-resolution land-cover dataset, both layers exhibit bias at <10 and >70% cover. The ratio of total impervious area and connected impervious area differs along the range of percent imperviousness – at low percent imperviousness, the NLCD is a better predictor of pavement alone, whereas at higher percent imperviousness, buildings and pavement together more resemble NLCD impervious estimates. The land-cover composition and range for each NLCD urban land category (developed open space, low-intensity, medium-intensity, and high-intensity developed) is more variable in areas of low-intensity development. Fine-vegetation land-cover/lawn area is incorporated in a large number of land use categories with no ability to extract this land cover from the NLCD. These findings reveal that the NLCD may yield important biases in urban, suburban, and exurban hydrologic analyses where land cover is characterized by fine-scale spatial heterogeneity.