卫星数据融合技术在环境遥感监测中的应用

在丹东典型区域环境遥感监测中,将CBERS-1（“中巴地球资源一号”卫星）信息与地面监测站、数据传输与处理系统、地理信息系统（GIS）相结合,采用多源卫星遥感数据融合技术,实现了对区域环境准确、客观、动态、简捷、快速的监测。     

虚拟振动试验与真实试验相关性分析

卫星虚拟振动试验是当今应用研究的前沿课题。以某中心承力筒为对象,由设计单位提供了承力筒的分析模型和承力筒试件,在相同的试验条件下分别独立地进行虚拟试验和真实试验,对比两者的试验数据,分析虚拟试验与真实试验结果的异同及其产生的原因,对建立的振动台分析模型和虚拟试验研究方法作出评价。     

卫星遥感技术在本溪典型区域的应用

以本溪典型区域为研究区,以高分辨率卫星数据为主要信息源,利用不同波段的组合图像,借助eCognition软件,对地表地物光谱特征和空间特征进行分析,建立卫星遥感分析成果信息库。基于不同时相分类结果的变化检测,以及对研究区水体污染、矿区复垦、耕地变化、林地变化等的分析,定量分析了研究区生态环境的动态变化。此项研究工作为研究区的生态环境规划、建设和管理,特别是对土地利用的管理工作提供了有用的资料。     

美国GOES系列卫星的发展

首先介绍了美国GOES系列静止轨道气象卫星的基本情况、职能和使命任务,然后分别对第一代、第二代/改进型第二代以及第三代GOES系列卫星的发展历程、载荷情况和卫星产品进行了概述,并对目前在轨运行第三代GOES系列卫星先进基线成像仪、同步闪电测绘仪、远紫外与X射线辐照度探测器等载荷参数和主要用途进行了详细介绍.最后总结了G...     

基于不同卫星降雨产品的澴水花园流域径流模拟比较研究

卫星降雨产品作为缺资料或无资料地区估算流域降雨径流的一种途径,适用性尚需大量实验研究。以澴水花园流域为研究区,综合评估了TRMM(3B42V7)、TRMM_RT(3B42V7)、PERSIANN CDR和CMORPH 4个卫星降雨产品在流域平均雨量计算与径流模拟中的精度,设置多方案与多种水文模拟情景全面检验各降雨产品的可靠性与适用性。研究表明：(1)在研究期2002~2013年,没有一个卫星降雨产品对所有精度评价指标均表现最优,PERSIANN始终表现为最差;(2)各卫星降雨产品对于不同年代和不同统计时段的精度差异明显,且一般汛期精度高于全年精度。各年代精度最高的卫星降雨产品在年与汛期尺度上与实测雨量相关系数均超过0.9;(3)各卫星降雨产品对有雨日降雨探测能力较强,但空报率较高,所有卫星降雨产品对于年最大1 d、3 d和7 d降雨估算误差较大,无法达到可利用精度;(4)采用卫星降雨产品进行径流模拟时,以相应的卫星降雨进行水文模型参数率定可获得更高的模拟精度。TRMM_RT与CMORPH日径流模拟精度较好,CMORPH月径流模拟精度较好。总体而言,CMORPH更适用于径流模拟。对于典型的3场大洪水模拟结果表明,TRMM_RT和CMORPH对洪峰与洪量（径流深）的模拟精度相对较高。     

卫星影像和高程数据在农村环境质量试点监测中的应用

大量长期地使用农用塑料薄膜,导致邻苯二甲酸酯类的监测结果出现超标。邻苯二甲酸酯类的污染形势不容乐观。结合桂林市农村环境质量试点监测工作,参考全国生态环境监测与评价工作的技术方法,利用高分辨率卫星遥感影像对试点监测村进行了农膜覆盖面积的统计。针对桂林市的丘陵地貌特征,利用高程数据对统计结果进行修正,提高了农膜覆盖面积统计的准确度。同时还对试点监测村周边区域的农膜覆盖情况进行了粗略统计和分析,确定了将来的重点调查目标区域,为将来深入调查邻苯二甲酸酯类污染状况、制定防治方案提供了一定的参考。     

近30年来鄱阳湖环湖区土地利用与景观格局变化研究

以1988—2018年7期Landsat遥感卫星影像为数据源,采用土地利用转移矩阵、景观格局指数等方法探究了鄱阳湖环湖区近30年来土地利用与景观格局变化特征.结果表明：(1)近30年来鄱阳湖环湖区建设用地和林地面积显著增加,耕地、草地、水域和未利用地面积减少.(2)建设用地的转入类型以耕地为主,30年间共侵占耕地面积1243.66 km²,占建设用地面积增加量的71.19%.林地的转入类型主要为耕地和草地,其中,耕地转入占比56.95%.耕地的转出类型以建设用地、草地和林地为主,且1999年以后随着城镇化的发展耕地主要转向建设用地.(3)近30年来鄱阳湖环湖区景观总体破碎程度逐渐增大,景观斑块个数共增加63492个,增幅为11.68%.景观连通性降低,各类型土地呈均衡化趋势分布,景观异质性增加.研究结果可为推动鄱阳湖环湖区土地资源保护、生态环境保护和经济协同发展提供参考依据.     

Validation of Satellite Precipitation Adjustment Methodology From Seven Basins in the Continental United States1

Tobin, Kenneth J. and Marvin E. Bennett, 2012. Validation of Satellite Precipitation Adjustment Methodology From Seven Basins in the Continental United States. Journal of the American Water Resources Association (JAWRA) 48(2): 221‐234. DOI: 10.1111/j.1752‐1688.2011.00604.x Abstract: The precipitation science community has expressed concern regarding the ability of satellite‐based precipitation products to accurately capture rainfall values over land. There has been some work that has focused on addressing the deficiencies of satellite precipitation products, particularly on the adjustment of bias. This article outlines a methodology that adjusts satellite products utilizing ground‐based precipitation data. The approach is not a simple bias adjustment, but is a three‐step process that transforms a satellite product based on a ground‐based precipitation product (NEXRAD‐derived Multisensor Precipitation Estimator [MPE] product or rain‐gauge data). The developed methodology was successfully applied to seven moderate‐to‐large sized watersheds from continental United States (CONUS) and northern Mexico over a spectrum of climatic regimes ranging from dry to humid settings. Methodology validation is based on comparison of observed and simulated streamflow generated with SWAT (Soil and Water Assessment Tool) model using unadjusted and adjusted precipitation products as input. Streamflow comparison is based on mass balance error and Nash‐Sutcliffe efficiency coefficient. Finally, the contribution of how adjustment to correct misses, false alarms, and bias impacts adjusted datasets and the potential impact that the adjustment methodology can have on hydrological applications such as water resource monitoring and flood prediction are explored.     

Classifying environmentally significant urban land uses with satellite imagery

We investigated Bayesian networks to classify urban land use from satellite imagery. Landsat Enhanced Thematic Mapper Plus (ETM(+)) images were used for the classification in two study areas: (1) Marina del Rey and its vicinity in the Santa Monica Bay Watershed, CA and (2) drainage basins adjacent to the Sweetwater Reservoir in San Diego, CA. Bayesian networks provided 80-95% classification accuracy for urban land use using four different classification systems. The classifications were robust with small training data sets with normal and reduced radiometric resolution. The networks needed only 5% of the total data (i.e., 1500 pixels) for sample size and only 5- or 6-bit information for accurate classification. The network explicitly showed the relationship among variables from its structure and was also capable of utilizing information from non-spectral data. The classification can be used to provide timely and inexpensive land use information over large areas for environmental purposes such as estimating stormwater pollutant loads.     

Image Themes and Frames in US Print News Stories about Climate Change

Research on frames in climate change (CC) news coverage has advanced substantially over the past decade, but the emerging understanding of the framing role of visual imagery that often accompanies news texts remains fragmented. We report on a set of image frames identified through content analysis of 350 images associated with 200 news articles from 11 US newspaper and magazine sources from 1969 through late 2009. We reliably identified and quantified the occurrence of 118 image themes. We then hierarchically clustered the themes based on their co-occurrence in images to identify an integrated framework of 42 image frames. We highlight frames associated with particular types of images (e.g., photographs and maps) or geographic regions. From among the full set of frames, we identify 15 that commonly appear in US CC news imagery and discuss the ways in which image frames make salient (or render invisible) particular categories of people, geographic regions, aspects of science, and spheres of activity.