武汉湖泊富营养化遥感调查与评价

利用武汉东湖各子湖多年可靠的地面监测资料和1999年9月Landsat-7的TM各波段的卫星遥感数据,建立了各子湖的营养状态指数与TMb5图像上的灰度值之间的线性关系模型,并运用该模型对武汉各湖泊进行富营养化评价。同时基于地面监测资料,用日本学者相崎守弘提出的修正富营养化指数法对武汉主要湖泊的富营养化程度进行评价。两种方法评价结果都显示,武汉大多数湖泊呈富营养化状态,一些湖泊已接近甚至达到极富营养化。在用两种方法同时评价的十个湖泊中,有四个湖泊的评价结果完全一致,其余的六个湖泊富营养化程度只相差一个级别。两种方法评价结果存在差异,可能有以下三个原因;（1）遥感方法反映了是图像所在时段的某一个区域上的平均值,营养化指数法反映的是若干个采样站的年平均值;（2）TM图像的获取时间比地面监测的时间晚;（3）遥感影像可能受到云、泥沙等悬浮物、高等水生植物以及湖泊水深等的影响。遥感评价结果与地面监测结果基本一致,利用遥感进行湖泊水体富营养化监测价是可行的,有效的,利用该方法可进行大范围的湖泊富营养化调查评价。     

印度大地震的可预警信息研究

20 0 1 0 1 2 6印度西北部的普杰地区发生了 7 8级强烈地震。对这次强震事件 ,利用卫星遥感监测地气系统射出长波辐射的数值产品资料 ,分析了以普杰为中心整个西亚范围内 ,事件发生前后共计 6个月的月平均辐射场的分布特征及其演变过程。发现自震前 2个月至震时当月 ,普杰地区始终是一个辐射 (热 )场的高值中心 ,震后明显消散。据此认为印度大地震有可识别的预警信息 ,提出利用卫星遥感技术及其产品 ,有可能为“突破”短临地震预报开拓出一种新的预测技术生长点     

环境物探技术在岩溶勘察中的应用及其效果

将高密度电阻率法及工程地震映像法两种环境物探技术同时应用于实际的地质灾害(岩溶)勘察中,结果表明:对于岩溶这样的地质灾害,单一环境物探技术虽然能清楚反映其埋深、规模和发育情况,但各有缺陷。而多种环境物探技术的综合使用,相互补充,将能大大提高岩溶勘察的准确性,提高勘察效果和效率。     

基于3S技术的震害快速评估

地震是人类面临的重大自然灾害之一，破坏性地震发生后，对震害的快速评估有利于政府及有关部门对灾情迅速做出应急反应，实施救援。地理信息系统（GIS）、遥感（RS）和全球定位系统（GPS）合称为3S技术。随着计算机技术和地球空间科学的发展。3S技术已逐渐应用于防灾减灾领域。探讨了应用3S技术替代传统的经验性估计决速评估震害的技术路线、方法和前景。首先，归纳了目前防震减灾信息及辅助决策系统建设取得的成绩和存在的问题。通过两个破坏性地震的震害实例，说明了应用基于GIS的系统快速评估震害的可能性和有待重点解决的问题。然后。通过新疆一次地震的遥感图像的变化检测，展示了震害快速评估中借助遥感数字图像处理技术的前景。在上述综合分析的基础上，讨论了三者结合的重要性、潜在功能和优点。     

浅谈水质在线监控中遥感技术的应用

空间信息技术以及计算机技术的发展，给环境监控提供了先进、快速和科学的方法。其中，遥感技术由于能够快速、宏观地获得所监控区域的数据，近年来已逐渐成为环境监控系统中的重要技术手段。遥感信息是被控区域的电磁辐射能量及其结构特征与时空状态在遥感图像上的表现。今后，遥感技术、在线监控系统和地理信息系统等多种信息处理工具的结合将是环境信息监控系统发展的主要方向。     

数字隐写技术及发展趋势

笔者通过强调数字隐写算法和隐写分析算法间的矛盾统一,介绍数字隐写算法的发展历程和趋势以及国内外的研究现状。重点介绍具有代表性的空域LSB隐写算法和频域JPEG图像隐写算法。通过基本算法、对基本算法的分析方法、基本算法改进措施的顺序,介绍算法的发展历程,分析算法的性能。对当前实验研究的进展和数字隐写技术存在的问题进行说明,并提出一些建设性意见,对隐写技术的发展前景和方向进行展望,指出数字隐写技术会成为密码术的重要补充,在信息安全传输方面发挥巨大的作用。     

ACCURACY OF IMPERVIOUS AREA VALUES ESTIMATED USING REMOTELY SENSED DATA1

ABSTRACT: Remote sensing offers an attractive alternative to conventional data collection employed in the estimation of certain hydrologic model parameters. In this investigation, the standard error of parameters estimated from Landsat data are examined. Relationships between the standard error and the size of the spatial-modeling units are developed that allow extending results to larger areas. Based upon the investigations conducted, a generalized model of the error relationships could not be developed.     

ESTIMATION OF SOIL MOISTURE WITH API ALGORITHMS AND MICROWAVE EMISSION1

Large area soil moisture estimations are required to describe input to cloud prediction models, rainfall distribution models, and global crop yield models. Satellite mounted microwave sensor systems that as yet can only detect moisture at the surface have been suggested as a means of acquiring large area estimates. Relations previously discovered between microwave emission at the 1.55 cm wavelength and surface moisture as represented by an antecedent precipitation index were used to provide a pseudo infiltration estimation. Infiltration estimates based on surface wetness on a daily basis were then used to calculate the soil moisture in the surface 0–23 cm of the soil by use of a modified antecedent precipitation index. Reasonably good results were obtained (R²= 0.7162) when predicted soil moisture for the surface 23 cm was compared to measured moisture. Where the technique was modified to use only an estimate of surface moisture each three days an R² value of 0.7116 resulted for the same data set. Correlations between predicted and actual soil moisture fall off rapidly for repeat observations more than three days apart. The algorithms developed in this study may be used over relatively flat agricultural lands to provide improved estimates of soil moisture to a depth greater than the depth of penetration for the sensor.     

Satellites viewing our world: The NASA landsat and the NOAA SMS/GOES

Thousands of individuals throughout the world are now users of satellite data. Hundreds of satellites have been launched—military, navigation, communications, educational, weather, and earth resources. One of the weather satellites (the SMS/GOES) and the NASA earth resources mapping satellite (Landsat) are the subjects of this article. Data from these systems have been highly cost beneficial, not only in the United States, but in developed and developing nations all over the globe as well. There is an increasing demand both for data and for training in data use.Data samples are shown and applications are discussed. Strong reference is made to the value of the digital computer in natural and man-made features mapping and monitoring. Procedures for acquiring NASA data are explained so that the reader may order data for his home region, or for other regions throughout the world which are of interest for their agriculture, forestry, hydrology, marine resources, geology, or land use. The cost of data is incredibly low; some products cost as little as three dollars.Also discussed are the remotely based data-collection platforms that acquire ground or water data daily and relay results to the NASA Landsat or to the NOAA SMS/GOES.     

ESTIMATING THE SUSPENDED SEDIMENT LOAD IN RESERVOIRS1

ABSTRACT: The total suspended sediment loads of four north Mississippi reservoirs were determined from measurements of concentrations of suspended sediment in a vertical profile at several locations on each reservoir made during the year. These data were combined with the stage-height and known stage-volume relationships for each reservoir in a numerical integration to determine the total suspended sediment in the water body. Total suspended sediments were estimated using the product of the suspended sediment concentration in the surface water by the appropriate reservoir volume. The averaged ratios of the estimated to measured suspended sediment loads for each reservoir exceeded 0.90. Since the concentration of suspended sediments in surface waters of north Mississippi reservoirs has been shown as highly correlated with spectral reflectance, estimating the total suspended sediment of these reservoirs using remotely sensed spectral reflectance data is possible.