水环境遥感监测技术的应用研究进展

遥感技术在水环境监测方面得到了日益广泛的应用.文章综述了水环境遥感监测技术在水体富营养化、悬浮固体、油污染和热污染等四个方面的应用研究现状,并对今后的研究发展方向进行了展望.     

基于RS和GIS技术的贵州省植被生态环境监测分析

为阐明贵州省植被生态环境变化的整体状况,基于RS和GIS技术,应用美国国家航空航天局最新的全球植被指数变化研究数据（GIMMS）,通过计算月归一化植被指数（NDVI）变化率,并对研究区一元线性回归模拟,分析了贵州省1982年-2003年的地表植被覆盖。结果表明：22年来,研究区植被覆盖呈增加趋势,表明贵州省植被生态环境向好的方向发展;贵州省平均植被覆盖在春季和秋季呈上升趋势,夏季和冬季呈下降趋势,其中春季对植被覆盖总变化量的贡献最大;植被覆盖程度增减因区域不同而异,变化程度呈增加的区域主要位于贵,ki-I省的中部地区;变化程度呈减小的区域分布在贵州省的四周边缘。     

Quantification of the Impact of Land-Use Changes on Ecosystem Services: A Case Study in Pingbian County, China

Pingbian Miao Autonomous County is one of the poorest rural areas in China. Land-use changes, mainly driven by agricultural expansion and deforestation, may significantly impact ecosystem services and functions, but such effects are difficult to quantify. In the present study, Landsat image data were combined with the published coefficients about the world and China ecosystem to quantify land-use and ecosystem service changes in the mountainous area. A sensitivity analysis was employed to determine the effect of manipulating these coefficients on the estimated values. Our results show that during the past decades (from 1973 to 2004) forests and grasslands were converted into shrubland and cropland, respectively, resulting in a continuous decrease in ecosystem service (from 124.5 US$ × 10⁶ in 1973 to 100.4 US$ × 10⁶ in 2004). We found that the decrease of mixed forest in the study area was the largest contributor (i.e., 25.4 US$ × 10⁶) to the decline of the ecosystem service. Therefore we propose that future land-use policy should pay more attention to the crucial ecosystem functions of these forests (including tropical forest), and that it is necessary to balance the relationship between the livelihood of local farmers and environmental protection in order to maintain a healthy and stable ecosystem.     

Monitoring the impacts of urbanization and industrialization on the agricultural land and environment of the Torbali, Izmir region, Turkey

The aim of this research is to determine agricultural land loss and environmental pollution caused by industrialization and urban sprawl using the Geographical Information System (GIS) and Remote Sensing technique (RS). Remotely sensed data is the most powerful tool for monitoring land use changes and GIS is the best way to store and reproduce various kinds of integrated data. Considering the rapid increase of population the loss of fertile agricultural soils is a very dangerous situation for the future of the country. Thus, people are living in the cities in (with adverse) conditions of insufficient drinking water, infrastructure problems, inadequate landscape and many unsolved (extreme) environmental problems. During the last 36 years, unplanned urbanization and industrialization have led to the use of agricultural areas for non-agricultural purposes in the Torbali (Izmir) region, which has the most fertile soils of the Aegean Region. Within this study, a database was created on the parameters of land loss and environmental pollution by means of field observation, interpretation of satellite images (ASTER), aerial photos(1/25.000 scale), topographic map ,soil map, and 1/5.000 scale cadastral map. Results of previous researches and the archives of Torbali municipality were used as ancillary data. In the research, urbanization and industrialization of the town was studied by (using) GIS and RS between 1965 and 2001. Since 1965, 4.742.357 m² agricultural land, mostly of first and second land use capability classes, has been lost due to unplanned urban and industrial developments. Urbanization and industrialization involved an area of which 58% was being used as irrigated lands, 25 % rain feed (rain fed lands)and 17 % for olive growing.     

Application of artificial neural network approach and remotely sensed imagery for regional eco-environmental quality evaluation

Eco-environment quality evaluation is an important research theme in environment management. In the present study, Fuzhou city in China was selected as a study area and a limited number of 222 sampling field sites were first investigated in situ with the help of a GPS device. Every sampling site was assessed by ecological experts and given an Eco-environment Background Value (EBV) based on a scoring and ranking system. The higher the EBV, the better the ecological environmental quality. Then, three types of eco-environmental attributes that are physically-based and easily-quantifiable at a grid level were extracted: (1) remote sensing derived attributes (vegetation index, wetness index, soil brightness index, surface land temperature index), (2) meteorological attributes (annual temperature and annual precipitation), and (3) terrain attribute (elevation). A Back Propagation (BP) Artificial Neural Network (ANN) model was proposed for the EBV validation and prediction. A three-layer BP ANN model was designed to automatically learn the internal relationship using a training set of known EBV and eco-environmental attributes, followed by the application of the model for predicting EBV values across the whole study area. It was found that the performance of the BP ANN model was satisfactory and capable of an overall prediction accuracy of 82.4%, with a Kappa coefficient of 0.801 in the validation. The evaluation results showed that the eco-environmental quality of Fuzhou city is considered as satisfactory. Through analyzing the spatial correlation between the eco-environmental quality and land uses, it was found that the best eco-environmental areas were related to forest lands, whereas the urban area had the relatively worst eco-environmental quality. Human activities are still considered as a major impact on the eco-environmental quality in this area.     

Environmental Impact Assessment of the Mining and Concentration Activities in the Kola Peninsula, Russia by Multidate Remote Sensing

On the Kola Peninsula, the mining and concentration industry exerts anthropogenic impact on the environment. Tailing dumps cause airborne pollution through dusting, and waterborne pollution due to direct dumping and accidental releases. The objectives were: (1) to analyse multidate satellite imagesfor 1964–1996 to assess the environmental pollution from themining and concentration activity in the Kola in temporal perspective; (2) to evaluate remote sensing methods for integrated environmental impact assessment. The area of mining and industrial sites steadily expands and amounted to 94 km² in 1996. The polluted water surface amounted to at least 150 km² through dumping in 1978 and to 106 km² in1986 due to dusting. Thus, the impact from the mining and concentration activity should be reconsidered as more significant than it was officially anticipated. In the past the main mechanism of pollution wasdirect dumping into the lakes. Currently and in future, airborne pollution after dusting storms will dominate. The effective recultivation of the tailing dumps will be a long-term process. For effective assessment of impacts from the mining and concentration industry, remote sensing methods should be complemented by in-situ measurements, fieldwork, and mathematical modelling.     

基于Landsat 7影像的骆马湖菹草时空分布研究

近年来,骆马湖湖区菹草（麦黄草）暴发性繁殖引发了一系列水质问题。通过研究,判读2012—2013年不同时间段的骆马湖landsat 7影像,可以发现,Landsat 7影像可以准确反映湖区菹草分布,区域化明显;同时发现菹草分布受多种因素影响,人类采砂和围网养殖等活动对其影响显著。     

湖库水生植被光学遥感监测研究进展和展望

水生植被在湖库生态系统中发挥稳定沉积物、净化水质、平衡水生生态系统等作用,监测水生植被变化对湖库生态环境的监测具有重要意义。梳理了国内外利用高光谱、多光谱光学卫星遥感数据提取湖库水生植被的方法,尤其是针对其中涉及的阈值确定问题进行总结分析,介绍了典型研究区水生植被时空分布和变化以及与水质的关系,最后给出一些水生植被遥感监测的展望。     

Assessment for Salinized Wasteland Expansion and Land Use Change Using GIS and Remote Sensing in the West Part of Northeast China

Due to human impact under climatic variations, western part of Northeast China has suffered substantial land degradation during past decades. This paper presents an integrated study of expansion process of salinized wasteland in Da’an County, a typical salt-affected area in Northeast China, by using Geographic Information Systems (GIS) and remote sensing. The study explores the temporal and spatial characteristics of salinized wasteland expansion from 1954 to 2004, and land use/cover changes during this period. During the past 50 years, the salinized wasteland in study area have increased by 135,995 ha, and in 2004 covers 32.31% of the total area, in the meantime grassland has decreased by 104,697 ha and in 2004 covers only 13.15% of the study area. Grasslands, croplands and swamplands were found the three main land use types converted into salinized wasteland. Land use/cover changes shows that between 1954 and 2004, 48.6% of grasslands, 42.5% of swamplands, and 14.1% of croplands were transformed into salinized wasteland, respectively. Lastly, the major factors influencing salinized wasteland expansion and land use/cover changes were also explored. In general, climatic factors supplied a potential environment for soil salinization. Human-related factors, such as policy, population, overgrazing, and intensified and unreasonable utilization of land and water resources are the main causes of salinized wasteland expansion.     

基于多星遥感影像的太湖北部湖湾春季沉水植被分布动态监测

利用多星遥感影像动态监测了2015年春季太湖北部湖湾沉水植被分布的变化过程,并对水生植被遥感监测中的几个关键问题展开了探讨。决策树方法获取的水生植被分布结果表明,2015年4月28日太湖北部湖湾发现明显沉水植被分布面积约11.2 km~2,与2014年同期相比,新出现的较大面积沉水植被分布区域主要集中在田鸡山西和锡东水厂附近。提出应及时清理打捞,避免水生植被死亡腐烂,威胁水质安全。     

基于RS的徐州市区生态环境动态监测与评价分析

近年来,随着城市化进程推,城市生态环境正逐步恶化。徐州作为老矿业城市,情况尤其不为乐观,以徐州市区为例作生态评价分析。按照代表性、可操作性、适应性、可比性和方便性原则,选取了植被覆盖度、生物丰度、水网密度、人均绿地面积、城市环境污染负荷指数和环境质量综合指数作为评价指标来进行生态环境质量指数的计算。根据评价指标,选用1994年、2000年和2007年三个时相徐州市TM影像,对土地利用、河流水库、植被、人均绿地等方面进行遥感动态监测,然后对该地区13年来生态环境演变做了定量评价分析。评价结果表明,徐州市区生态环境质量由1994年的良好水平退化为一般水平,且有逐年下降恶化趋势,这与该区城市化进程一致。     

长荡湖围网养殖区长时序时空演变遥感监测

根据长荡湖地区1983—2020年共38景遥感影像中围网养殖区的光谱信息与纹理信息,借助ENVI和ArcGIS软件,通过人机交互目视解译的方法,提取了长荡湖的围网养殖区,分析其38 a的连续时空变化.结果表明,长荡湖围网养殖经历了无围网期(1983—1986年)、增长期(1987—1999年)、巅峰期(2000—200...     

太湖水华的遥感分析

随着太湖流域的经济迅速发展,太湖湖体的富营养化程度日趋严重,特别是在20世纪的后期,水华频繁爆发。国家环保总局常规的水质监测是基于21个点位对全湖进行评价,完成一次采样耗时近1月,其对大面积水华现象的监测具有很大的局限性。文章利用遥感技术快速、大尺度、动态监测的特点,基于多个时相的TM影像对太湖的水温、悬浮物、叶绿素等水质参数的浓度和分布进行了遥感反演,进而对太湖水华的成因、发展程度、影响因素等方面进行分析,从而对太湖水华发生的特点,太湖的水质情况有一个全面的了解。     

Integration of Remote Sensed and In-situ Data in an Analysis of the Air Pollution Effects on Terrestrial Ecosystems in the Border Areas between Norway and Russia

Transboundary air pollution from industries in Nikel and Zapolyarnij has caused severe damage to the environment in Southern-Varanger in Norway and in Pechenga municipality in Russia. The work presented in this paper focuses on the integration of in-situ air pollution data with remote sensing based land cover maps. Land cover maps have been utilised to detect changes in the major land cover types within the area. The major change in the environment was the decrease of the sensitive lichen-dominated land cover types, and the increase of bilberry-dominated land cover types and finally the increase of the land cover types with the greatest air pollution stress (industrial barren, barren, and partly damaged vegetation, defoliated forests, lichen removal). A GIS based method for assessing the relationship of the remotely sensed land cover maps with the environmental condition parameters was developed and applied. By comparing the results from this analysis we observed that the land cover types with the greatest stress had the largest concentrations of SO₂ in the ground air layer, while the land cover types with minor damage (the remaining lichen-dominated vegetation) had rather low concentrations of sulphur dioxide in the ground air layer. The area of the land cover types with the greatest stress (industrial barren, barren and partly damaged vegetation) has increased in the period 1973–1988, and the degradation is carried out in a such manner that sensitive mountain and lichen vegetation formations have been transformed into a more barren-like environment. The increase in the emissions has also transferred the natural barrens which also consisted of some sparse vegetation into a complete barren with little vegetation left. Also the epilitic lichens and mosses on bare rocks and stones were also removed by the high concentrations of SO₂. The land cover types with minor damage (with the remaining lichen-dominated vegetation) had rather low concentrations of the contaminants (SO₂, Ni and S), while the partly damaged and damaged land cover types had the highest concentrations of the contaminants. An exception was the Ni and S concentrations found in class 11 Industrial barrens which were lower than expected. Associations between the degradation and the SO₂ concentration in the air were also documented. The conclusion from this analysis is that the in-situ data support the observations of damaged vegetation and industrial barrens imaged by the Landsat satellites, especially in the surroundings of Nikel and Zapolyarnij.     

基于Landsat ETM+等影像的无锡市十年陆地生态环境遥感评价

遥感和GIS技术的发展为研究区域生态环境变化提供了有效手段,以无锡市2004-2013年的ETM＋等遥感影像和GDEM高程数据为数据源,运用遥感和GIS方法提取生态因子信息并进行陆地生态状况遥感评价。结果表明,无锡市近十年陆地生态环境整体趋好。     

东太湖湖滨带近三十年生态环境变化遥感分析与评价

利用Landsat系列卫星遥感影像对东太湖湖滨带1984—2015年生态环境变化状况进行了解译与分析。结果表明,东太湖湖滨带生态环境变化明显,人类活动影响显著;水域湿地面积有一定上升,农田持续减少,建设用地扩张约1倍;湿地类别受水产养殖活动影响较大,20世纪90年代最为明显。2010年后环保部门推动落实生态修复、航道疏浚和清淤工程,有效改善了东太湖湖滨带的水生态状况。     

江苏省霾污染遥感监测业务化运行研究

从霾污染遥感监测业务化流程出发,选取EOS/MODIS为主要数据源,MODIS气溶胶产品及气象数据为辅,在数据预处理的基础上,利用LM-BP人工神经网络模型算法反演区域大气颗粒物浓度,分析了可获取的遥感监测指标及气象指标对霾污染的贡献率,筛选出可业务化的霾污染遥感评价指标。对2013年1月江苏省2次典型的霾污染进行了星地同步分析,从分析结果来看,霾污染遥感监测结果与地面实测结果基本一致,霾污染遥感监测可以作为地面监测的有效补充,宏观反映区域霾污染空间分布,为大气污染防治提供有力的技术支撑。     

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。     

安徽省“十二五”生态环境遥感监测

利用2011—2015年安徽省遥感影像土地利用类型解译数据,结合地面调查和统计资料,依据生态环境状况评价系统对安徽省"十二五"期间生态环境状况进行动态监测与评价。结果表明,"十二五"末安徽省各市生态环境状况等级为"优"的有4个市,为"良"的有12个市;"十二五"期间,各市等级均保持不变;"十二五"始末相比,有8个市生态环境状况变化度为"略有变好"等级,生态环境状况波动度为"波动"级别,其余8个市的变化度为"无明显变化"等级,波动度为"稳定"级别;省域EI增加了0.76,生态环境质量呈现稳中向好的趋势。     

遥感技术和地理信息系统在新疆生态环境调查中的应用

介绍了遥感技术和地理信息系统在新疆生态环境调查中的作用，为新疆生态环境保护、生态监测、生态建设等方面提供动态的基础数据和科学决策的依据。