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。     

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。     

扬州市土地利用与覆盖的遥感监测

应用遥感技术监测分析扬州市2009—2012年土地利用与覆盖状况。结果表明,扬州市土地利用及覆盖以耕地、城乡工矿居民用地及水域为主,主要生态红线区土地覆盖类型未发生人为改变,生态环境状况总体良好,呈略有改善的态势。提出,应坚持开展污染治理和生态建设,优化发展空间,统筹城乡建设用地管理。     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.     

太湖蓝藻水华时空分布与预警监测响应的分析

选择2007和2008年200幅EOS/MODIS太湖蓝藻监测遥感影像,统计分析了梅梁湾、竺山湾宜兴段、贡湖湾、东太湖胥口湾和湖州方向湖体蓝藻水华爆发的空间和时间分布规律。并在得出全太湖蓝藻水华空间和时间分布规律的基础上,从环境监测部门蓝藻预警监测工作的实际出发,将蓝藻水华预警监测的响应划分为常规监测和应急监测,提出了具体的监测要求,为环太湖地区的相关部门更好地开展蓝藻预警监测工作提供了科学依据。     

南通市生态环境遥感监测及其动态变化研究

应用遥感技术对南通市生态环境进行监测,利用GIS技术对遥感监测结果进行解译与分析,同时对2006-2009年南通市生态环境时空动态变化进行了分析与评价.结果表明,南通市生态环境类型以耕地、水域和城乡、工矿、居民用地为主,未利用土地面积极小.其生态环境动态变化的主要特点是耕地面积普遍有小幅度减少,以城镇建设用地为主的城乡、工矿、居民用地增加较多,林地面积无明显变化;未利用土地面积有所减少,以盐碱地面积减少为主,减少的面积主要用于耕地和建设用地.     

基于环境一号卫星的PM2.5浓度遥感反演研究

2014年12月29—30日,青岛市发生了一次空气污染过程,利用环境一号卫星CCD遥感影像数据和实测PM_(2.5)浓度数据,分析了该过程前后5 d的实测PM_(2.5)浓度与环境一号卫星CCD遥感影像的DN值之间的相关性,分别按日期和区域建立了反演模型。结果表明,按日期拟合反演模型相关系数为0.02~0.51,按区域拟合反演模型相关系数为0.01~0.80,总体来说,区域拟合结果较好。     

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。     

大气环境无人机监测方法研究

目前地面常规大气监测手段难以对垂直方向污染源监测,也难以应对环境突发事件,采用无人机大气监测与数值模拟结合的方法可以解决该问题。实验开发了基于无人机平台的空气质量监测平台,采用数值模拟方法确定平台搭载方案,再对无人机监测系统得到的监测数据与数值模拟计算结果作对比分析,得到各项污染物浓度。分析了该方法存在的问题,提出了提高数据链路传输能力,开展无人机遥感系统相关环境质量评价方法学研究,开发精度高、质量轻的无人机大气监测吊舱,开展地面静止比对和飞行测量比对实验等建议。