基于环境卫星CCD数据的黄海浒苔遥感监测

2007年以来,黄海海域每年夏季都发生大面积浒苔绿藻潮,影响沿岸人民的生活、生产。考虑到其分布范围动则几千、上万平方公里,水面监测很难实施,尝试利用遥感技术对其分布和发展变化情况进行监测。基于中国自主产权的环境卫星(HJ1)数据,采用经典植被指数算法和人工辅助判读方法,对2013年黄海浒苔暴发全过程进行了连续遥感监测,分析了此次浒苔过程的分布和漂移路线。监测结果表明,浒苔绿藻潮首发于江苏盐城东部海域,由南向北逐渐漂移,面积逐渐扩大,结束于青岛东北部海域;该期间,浒苔最大覆盖面积达663.54平方公里。     

A combinated approach to investigate the biochemistry and hydrography of a shallow bay in the South Adriatic Sea: the Gulf of Manfredonia (Italy)

The main goal of this study is to understand the hydrological and biochemical set up and processes of a marine coastal area located in the western side of the south Adriatic sea (the gulf of Manfredonia) by the use of both satellite images and in situ investigations A water sampling in the gulf of Manfredonia was performed at 18 fixed stations in June 2003; physico-chemical and biological parameters (temperature, salinity, dissolved oxygen and fluorescence) were measured along the water column and water samples were collected to analyse dissolved nutrients (ammonia, nitrite, nitrate, phosphate and silicate), total nutrients (nitrogen and phosphorus), chlorophyll a and total suspended solids. Surface spatial distributions of field collected data were examined to characterize biochemical and hydrographic conditions of the Gulf of Manfredonia and these results were related with the remote sensing analysis data. Remote sensed data (obtained by Landsat 7 TM and Modis Terra) were processed to obtain maps of chlorophyll a, temperature and optical characteristics of the gulf; these maps were compared to in situ data. From physico-chemical measurements no stratification was observed in the water column except for the south-eastern area. High concentrations of silicate and ammonia were observed in the northern zone of the gulf, while nitrate, phosphate, chlorophyll a and total suspended solids distributions showed higher values in the central coastal zone. These results were confirmed by remote sensing analysis; Modis elaboration showed a distribution with higher concentrations of chlorophyll a near the coast and Landsat images highlighted the extension of the surrounding agricultural areas crossed by the two main rivers which discharge into the gulf. The integration between field data with the remote sensing analysis showed to be a valid support in coastal zone management.     

Multiple Effects of Environmental Factors on Algal Growth and Nutrient Thresholds for Harmful Algal Blooms: Application of Response Surface Methodology

Systematic understanding of the co-effects of environmental factors on phytoplankton proliferation can enable more effective control of harmful algal blooms in eutrophic lakes and reservoirs. A batch of statistically designed experiments using response surface methodology was recently conducted on mixed algae samples collected from Changtan Reservoir. The central composite designed response surface model was established to evaluate multiple effects of various physical and chemical factors (total nitrogen, total phosphorus, temperature, and light intensity) on algal density and chlorophyll a content. Analysis of variance indicated an excellent correlation between modeling results and experimental responses. Among the selected environmental variables, promotion of the interactive effects of nitrogen and phosphorus together with the optimum total nitrogen/phosphorus mass ratio (between 7.9 and 10.1) was determined to be the most significant stimulating parameter associated with algal blooming development dominated by non-nitrogen-fixing species. The favorable effects of strong illumination were shown to be greater than those of high temperature. The border values of total nitrogen and phosphorus concentrations leading to a critical value of algal density under different water temperatures and light intensities could be predicted as nutrient loading thresholds for harmful algal blooms by our second-order polynomial regression model.     

生物监测中叶绿素a浓度与藻类密度的关联性研究

通过测定叶绿素a浓度、藻类密度和藻类分类计数等,获取"水华"水体生物监测数据。统计分析结果表明,叶绿素a浓度和藻类密度在蓝藻"水华"(微囊藻为优势种)暴发期间存在显著相关,并拟合出了回归直线。且叶绿素a浓度和藻类密度的自然对数比值也与藻类发生和兴衰存在着规律性联系。     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82–90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.     

Preliminary investigation of submerged aquatic vegetation mapping using hyperspectral remote sensing

The use of airborne hyperspectral remote sensing imagery for automated mapping of submerged aquatic vegetation (SAV) in the tidal Potomac River was investigated for near to real-time resource assessment and monitoring. Airborne hyperspectral imagery and field spectrometer measurements were obtained in October of 2000. A spectral library database containing selected ground-based and airborne sensor spectra was developed for use in image processing. The spectral library is used to automate the processing of hyperspectral imagery for potential real-time material identification and mapping. Field based spectra were compared to the airborne imagery using the database to identify and map two species of SAV (Myriophyllum spicatum and Vallisneria americana). Overall accuracy of the vegetation maps derived from hyperspectral imagery was determined by comparison to a product that combined aerial photography and field based sampling at the end of the SAV growing season. The algorithms and databases developed in this study will be useful with the current and forthcoming space-based hyperspectral remote sensing systems.     

Effects of Disturbance on Nitrogen Export from Forested Lands of the Chesapeake Bay Watershed

The objective of this research project is to develop, test, validate, and demonstrate an analytical framework for assessing regional-scale forest disturbance in the mid-Atlantic region by linking forest disturbance and forest nitrogen export to surface waters at multiple spatial scales. It is hypothesized that excessive nitrogen (N) leakage (export) from forested watersheds is a potentially useful, integrative "indicator" of a negative change in forest function which occurs in synchrony with changes in forest structure and species composition. Our research focuses mainly on forest disturbance associated with recent defoliations by the gypsy moth larva (Lymantria dispar) at spatial scales ranging from small watersheds to the entire Chesapeake Bay watershed. An approach for assessing the magnitude of forest disturbance and its impact on surface water quality will be based on an empirical model relating forest N leakage and gypsy moth defoliation that will be calibrated using data from 25 intensively-monitored forested watersheds in the region and tested using data from more than 60 other forested watersheds in Virginia. Ultimately, the model will be extended to the region using spatially-extensive data describing: 1) the spatial distribution of dominant forest types in the mid-Atlantic region based on both remote sensing imagery and plot-scale vegetation data; 2) the spatial pattern of gypsy moth defoliation of forested areas from aerial mapping; and 3) measurements of dissolved N concentrations in streams from synoptic water quality surveys.     

On applications of remote sensing for environmental monitoring

Modern airborne and satellite remote sensing techniques offer attractive opportunities to coastal monitoring systems. Improvements of the evaluation of larger scales phenomena and processes due to the synopticity of the remote sensing data are of particular interest. However, some uncertainties and limitations about remote sensing must be considered. Microwave, infrared and visible radiation methods and their applications are briefly discussed and some applications are demonstrated. Special attention is paid to the remote sensing of various pollutants in the sea, in particular with respect to oil pollution.Promising developments of the remote sensing methods for coastal monitoring are to be expected from the European remote sensing satellite missions ERS 1 and ERS 2.Combination of these observations with simultaneous in situ measurements from ships (sea truth) appears to be most advantageous for the interpretation of the collected data.     

The use of lichen growth abnormalities as an early warning indicator of forest dieback

Combinations of pollutants including acidic fog and ozone occur at high levels at a number of sites in eastern North America and Europe. Mountainous regions such as the Laurentians (Quebec), Appalachians (N.Y.) and the Green Mountains (Vermont) are especially vulnerable, with both conifers and hardwoods being affected. Ongoing measurements of atmospheric chemistry (e.g. The Chemistry of High Elevation Fog-CHEF project of the Canadian Atmospheric Environment Service) reveal that extreme cloudwater events of less than pH 3.0 and ozone episodes in excess of 100 ppb are common occurrences. The purpose of this study was to gather information about the response of epiphytic lichens to deteriorating air quality at selected locations for which atmospheric chemical data are readily available. A multidisciplinary approach is being used to analyse the lichens.Morphological and cellular aberrations previously documented by the authors to occur in terricolous lichens exposed to simulated acidic rain events will be evaluated for their usefulness are early warning indicators of forest decline. In addition, tissue chemistry of species such as Hypogymnia physodes will be correlated with parameters such as altitude and decline index and compared with published elemental values for lichens from similarly polluted sites in Europe and Scandinavia.     

Foraminifera as bioindicators in coral reef assessment and monitoring: the FORAM Index. Foraminifera in Reef Assessment and Monitoring

Coral reef communities are threatened worldwide. Resource managers urgently need indicators of the biological condition of reef environments that can relate data acquired through remote-sensing, water-quality and benthic-community monitoring to stress responses in reef organisms. The FORAM (Foraminifera in Reef Assessment and Monitoring) Index (FI) is based on 30 years of research on reef sediments and reef-dwelling larger foraminifers. These shelled protists are ideal indicator organisms because: Foraminifers are widely used as environmental and paleoenvironmental indicators in many contexts; Reef-building, zooxanthellate corals and foraminifers with algal symbionts have similar water-quality requirements; The relatively short life spans of foraminifers as compared with long-lived colonial corals facilitate differentiation between long-term water-quality decline and episodic stress events; Foraminifers are relatively small and abundant, permitting statistically significant sample sizes to be collected quickly and relatively inexpensively, ideally as a component of comprehensive monitoring programs; and Collection of foraminifers has minimal impact on reef resources.USEPA guidelines for ecological indicators are used to evaluate the FI. Data required are foraminiferal assemblages from surface sediments of reef-associated environments. The FI provides resource managers with a simple procedure for determining the suitability of benthic environments for communities dominated by algal symbiotic organisms. The FI can be applied independently, or incorporated into existing or planned monitoring efforts. The simple calculations require limited computer capabilities and therefore can be applied readily to reef-associated environments worldwide. In addition, the foraminiferal shells collected can be subjected to morphometric and geochemical analyses in areas of suspected heavy-metal pollution, and the data sets for the index can be used with other monitoring data in detailed multidimensional assessments.     

Monitoring of ocean surface algal blooms in coastal and oceanic waters around India

The National Aeronautics and Space Administration’s (NASA) sensor MODIS-Aqua provides an important tool for reliable observations of the changing ocean surface algal bloom paradigms in coastal and oceanic waters around India. A time series of the MODIS-Aqua-derived OSABI (ocean surface algal bloom index) and its seasonal composite images report new information and comprehensive pictures of these blooms and their evolution stages in a wide variety of events occurred at different times of the years from 2003 to 2011, providing the first large area survey of such phenomena around India. For most of the years, the results show a strong seasonal pattern of surface algal blooms elucidated by certain physical and meteorological conditions. The extent of these blooms reaches a maximum in winter (November–February) and a minimum in summer (June–September), especially in the northern Arabian Sea. Their spatial distribution and retention period are also significantly increased in the recent years. The increased spatial distribution and intensity of these blooms in the northern Arabian Sea in winter are likely caused by enhanced cooling, increased convective mixing, favorable winds, and atmospheric deposition of the mineral aerosols (from surrounding deserts) of the post-southwest monsoon period. The southward Oman coastal current and southwestward winds become apparently responsible for their extension up to the central Arabian Sea. Strong upwelling along this coast further triggers their initiation and growth. Though there is a warming condition associated with increased sea surface height anomalies along the coasts of India and Sri Lanka in winter, surface algal bloom patches are still persistent along these coasts due to northeast monsoonal winds, enhanced precipitation, and subsequent nutrient enrichment in these areas. The occurrence of the surface algal blooms in the northern Bay of Bengal coincides with a region of the well-known Ganges–Brahmaputra Estuarine Frontal (GBEF) system, which increases supply of nutrients in addition to the land-derived inputs triggering surface algal blooms in this region. Low density (initiation stage) of such blooms observed in clear oceanic waters southeast and northeast of Sri Lanka may be caused by the vertical mixing processes (strong monsoonal winds) and the occurrence of Indian Ocean Dipole events. Findings based on the analyses of time series satellite data indicate that the new information on surface algal blooms will have important bearing on regional fisheries, ecosystem and environmental studies, and implications of climate change scenarios.     

Pond bank access as an approach for managing toxic cyanobacteria in beef cattle pasture drinking water ponds

Forty-one livestock drinking water ponds in Alabama beef cattle pastures during were surveyed during the late summer to generally understand water quality patterns in these important water resources. Since livestock drinking water ponds are prone to excess nutrients that typically lead to eutrophication, which can promote blooms of toxigenic phytoplankton such as cyanobacteria, we also assessed the threat of exposure to the hepatotoxin, microcystin. Eighty percent of the ponds studied contained measurable microcystin, while three of these ponds had concentrations above human drinking water thresholds set by the US Environmental Protection Agency (i.e., 0.3 μg/L). Water quality patterns in the livestock drinking water ponds contrasted sharply with patterns typically observed for temperate freshwater lakes and reservoirs. Namely, we found several non-linear relationships between phytoplankton abundance (measured as chlorophyll) and nutrients or total suspended solids. Livestock had direct access to all the study ponds. Consequently, the proportion of inorganic suspended solids (e.g., sediment) increased with higher concentrations of total suspended solids, which underlies these patterns. Unimodal relationships were also observed between microcystin and phytoplankton abundance or nutrients. Euglenoids were abundant in the four ponds with chlorophyll concentrations >?250 μg/L (and dominated three of these ponds), which could explain why ponds with high chlorophyll concentrations would have low microcystin concentrations. Based on observations made during sampling events and available water quality data, livestock-mediated bioturbation is causing elevated total suspended solids that lead to reduced phytoplankton abundance and microcystin despite high concentrations of nutrients, such as phosphorus and nitrogen. Thus, livestock could be used to manage algal blooms, including toxic secondary metabolites, in their drinking water ponds by allowing them to walk in the ponds to increase turbidity.     

基于机器学习遥感算法的大型漂浮藻面积提取方法研究

采用基于机器学习的多层感知机算法,利用GOCI(Geostationary Ocean Color Imager)传感器获取的瑞利校正反射率数据,对东中国海大型漂浮藻进行遥感自动识别,采用线性混合像元分解来计算大型漂浮藻的覆盖面积,并利用膨胀和侵蚀法进行大型漂浮藻的分布面积计算。利用L8/OLI(Landsat 8/Operational Land Imager)高空间分辨率资料进行验证,结果表明,基于机器学习遥感算法针对GOCI提取的大型漂浮藻覆盖面积,与L8/OLI结果十分接近,R2达到0. 959,平均绝对误差和平均相对误差分别为39. 32 km2和18. 15%。     

遥感监测土壤湿度综述

遥感技术具有大面积同步观测,时效性、经济性强等特点,为大面积动态监测土壤湿度提供了可能。本文对近年来国内外遥感监测土壤湿度的理论、方法的发展和应用进行了回顾,重点介绍了目前已经比较成熟和广泛应用的基于可见光与热红外波段的植被指数方法以及在干旱、半干旱地区的应用,通过对比分析了各种遥感监测方法的优缺点,指出了土壤湿度遥感监测方法存在的不足,展望了土壤湿度遥感监测方法的发展趋势。     

Comparative Toxicological Evaluation of Untreated and Treated Tannery Effluent with Nostoc Muscorum L. (Algal Assay) and Microtox Bioassay

The relative sensitivity of tannery effluent before and after treatment was compared by employing Nostoc muscorum and microtox assay in laboratory. The effect on chlorophyll, protein and biomass content of Nostoc muscorum was studied with the luminescent property inhibition of Photobacterium phosphorium and compared with algal bioassay. The results of microtox assay after 5, 15 and 30 min of exposure were compared with data obtained from algal bioassay. It was observed that the luminescent property of Photobacterium phosphorium in microtox assay as well as the chlorophyll content of Nostoc muscorum in algal assay were the most sensitive parameters in toxicity evaluation of tannery effluent. The microtox assay produced notably comparable EC50 values with that of algal bioassay. The microtox assay of toxicity showed that EC50 (%) in 30 min was 3.19 and 63.49 for untreated and treated tannery effluent, respectively while in algal bioassay the EC50 for chlorophyll was in between 0-2.5% and 100%, respectively, in untreated and treated effluent. More than 60% reduction of toxicity was noted in treated tannery effluent in both test system.     

The MYSound Project: building an estuary-wide monitoring network for Long Island Sound,USA

A network of five water quality monitoring stations has been established in Long Island Sound, measuring temperature, salinity, and dissolved oxygen since 1999. The stations are located in areas of extreme water quality degradation (western Long Island Sound) as well as in pristine areas (eastern Long Island Sound). The data from these stations are collected every 15 minutes and posted to the project web site in real time as provisional data. After subsequent quality assurance procedures, the data are archived to the project File Transfer Protocol (FSP) site for downloading by the user community. The network of stations is in part supported logistically by a number of partners, including state and local agencies, schools, and non-governmental organizations. Data from the monitoring programs of some of these partners are also published to the project website providing a more comprehensive and complete picture of the status of the Sound than can be provided independently. This repository of information is used by marine educators, resource managers, scientists, and the general public, each with a different end purpose. We use the data from two of the stations to show that these high frequency time series measurements can be used to complement and enhance other monitoring programs within the Sound, documenting in greater detail the occurrence and duration of hypoxic events.     

核电站温排水卫星遥感监测应用研究

选取我国 HJ－1 B卫星红外相机为遥感数据源,在介绍了温排水卫星遥感监测的技术流程和基本原理之后,重点论述了海表温度反演的算法和基准温度提取的基本原则。以2013年1月17日大亚湾核电站和2013年5月22日田湾核电站2景 HJ－1 B红外相机数据为应用实例,说明了卫星遥感监测可作为开展核电站温排水影响监测与热污染评价的首选技术方向和主要监测手段,阐述了其在核电站温排水影响后评估中的作用和意义。     

基于EOS/MODIS卫星遥感数据的渤海海冰变化趋势及特征应用研究

根据卫星遥感数据的分辨率、采集频次、获取方式等特点,将MODIS卫星遥感数据应用到渤海海冰遥感监测中。通过海冰在可见光和红外光波段的光谱存在特定差异的特性,对海冰发生面积进行提取。同时对渤海海冰进行了遥感监测,并完整地监测到海冰从发生到极盛再到消退的全过程。同时,在海冰发生最为严重的时段,对辽东湾海域进行了密集监测。研究结果表明,MODIS卫星遥感数据在海冰监测中有着及时、准确的优势。     

The coastal component of the U.S. integrated ocean observing system

The combined effects of human activities and natural variability present significant challenges to the goals of protecting, restoring, and sustaining coastal ecosystems. Meeting these challenges and resolving conflicts in an informed fashion will require: (1) more timely detection and prediction of environmental changes and their consequences; and (2) more timely access to relevant environmental information. The achievement of these goals depends on the development of a sustained and integrated coastal ocean observing system (ICOOS) that insures timely access to the data and information required to improve: (1) climate predictions and the effects of changes in the weather on coastal populations; (2) efforts to sustain and restore healthy coastal marine ecosystems and living marine resources; and (3) compliance monitoring and evaluations of the efficacy of environmental policies. Although the responsible federal and state agencies all require similar environmental information, many separate programs have evolved for collecting, managing, and analyzing data for various purposes. Consequently, there is too much redundancy; access to diverse data from disparate sources is limited and time consuming; and individual programs are inevitably underfunded and too limited in scope. A system is needed that coordinates and integrates many of the elements of these programs to minimize redundancy, be more comprehensive, provide more timely access to data and information, and satisfy the information needs of a greater number of user groups in a more cost-effective fashion. This is the purpose of the ICOOS.