利用NOAA/AVHRR资料监测南方林区森林火灾的研究

本文论述了南方林区森林火灾时间分布集中、发生率高、面积小,并以地表火为主的特征;总结了气象卫星资料的林火信息特征和非林火干扰信息规律;研究了建造林火监测专家系统的理论方法,进而提出了林火宏观实时监测系统的总体设计,并建立了以计算机图像处理为基础的、以林火背景数据库支持的、以专家系统为核心的林火监测系统。并利用南方林火模拟实验和历史林火资料对该监测系统进行了改进。最后讨论了林火监测系统改进方向和研究体会。     

基于多时相GF-1和Landsat影像的连云港市44年海岸线遥感监测与演变分析

海岸线的动态变化监测可为海岸带防护、海岸带资源开发利用和可持续发展过程中的决策支持提供理论支撑。文中基于1973-2017年覆盖连云港市的Landsat系列和GF系列卫星影像数据,结合海岸线分类体系,提取了连云港市10期海岸线信息,并分析了海岸线演变特征及其成因。结果表明:(1) 2017年连云港市海岸线总长度为205.90 km,主要岸线类型为建设围堤和港口岸线,两类岸线总长为120.52 km,占总岸线长度的58.53%;(2) 1973-2017年连云港市海岸线长度整体呈现增长态势,44年间海岸线长度共增长了57.17 km,年增长率约为1.3 km/a。连云港市海岸线主要增长的岸线类型为建设围堤、港口岸线和生物岸线;(3) 44年间,连云港市海岸变化主要的海岸线类型为粉砂淤泥质岸线、生物岸线、港口岸线、建设围堤和盐田围堤;(4) 2017年连云港市自然岸线长度为69.15 km,占总岸线长度的33.6%,44年间,自然岸线长度减少了28.8km,年减少率为0.65 km/a。自然岸线减少的原因主要为养殖业发展、城市扩张建设和港口建设。     

热水——日月山断裂带遥感特征初步探讨

热水—日月山断裂带在遥感影像上具有明显的线性构造特征,通过解译认为该断裂带由6条不连续的断裂段右阶羽列组成,活动特征很明显,造成一系列水系断错,最大水平位错940 m,并沿断裂带形成一系列小拉分盆地,认为该断裂带具有较强的右旋走滑特征。其中牧场部—大崖根段北西西向沿湟水河河谷发育,除其本身具有发生强震的构造能力外,其延伸是否与西宁市区中的沿湟水河谷地附近的地表断层相连,对西宁盆地的构造活动形式及地震构造特征有十分重要的意义。历史地震表明曾在热水煤矿与大通山构造复合部位于1927年连续发生多次M4.5～5.5级中强地震。     

History of the Photogrammetric Society

The Photogrammetric Society was formed in 1952. The Council of the Society considered that the twentieth anniversary was a good point at which to record the events which led to its formation and the significant occasions and decisions which have taken place since 1952. Consequently, Paul Lamboit was invited to compile this History. He has placed the birth and development of the society within the national and international photogrammetric context and his record of the deliberations which took place between 1947 and 1952 will be of particular interest to historians of our subject.
This account was first published in a limited edition in 1971. Sufficient interest has since been expressed to prompt a wider circulation through publication in the Photogrammetric Record .
The author served the Society continuously in several official capacities from 1953 to 1969 and he was elected to Honorary Membership in 1969.     

农牧交错带土地沙化遥感监测

以内蒙古多伦县为研究对象,作时隔5a的两次遥感调查,对内蒙古东南部农牧业交错带的土地沙化进行监测。建立了土地沙化分类体系,把土地沙化与土地利用紧密联系,依据植被指数概念,采用了一组比值组合,有效地将土地沙化类别分层分离。通过第一次遥感调查,了解到多伦县由于过度耕种和过度放牧,致使土地沙化十分严重。经第二次调查对比分析,退耕还林、退牧还草的治沙效果显著,土地沙化发展趋势得到遏制,遥感监测为地方政府的防沙治沙起了重要作用。     

非接触测量系统的布设和精度

本文介绍了非接触测量的基本原理,探讨了其布设图形与精度的关系,得出了供作业参考的几点结论。     

基于GIS服务链的遥感影像分布式融合处理

提出了基于Web服务技术、OGC规范和工作流技术,以实现与平台无关的、具备流程编排能力的地理空间处理服务链框架,用于支持复杂的在线空间处理任务.在该框架基础上实现了一个在线遥感影像融合处理示例.该示例展示了利用OGC WCS、WPS,WSDL,UDDI和BPEL4WS等成熟的标准规范来构建GIS服务链,使得客户应用程序...     

Monitoring urban growth on the European side of the Istanbul metropolitan area: A case study

Istanbul is the largest city in Turkey with an area of around 5750 km² and a population of around 10.8 M (2000). In 1980, the population was only around 4.7 M and so has more than doubled in only 2 decades. In 2000, around 65% of the population were living on the European side of the city with its large industrial/commercial and trade centres. The population is increasing as a result of both births exceeding deaths and mass immigration. Consequently, planned and unplanned housing are increasing while green areas are decreasing in area. Monitoring urban growth will enable the Municipality of Istanbul to better manage this complex urban area.     

Combining Lidar Elevation Data and IKONOS Multispectral Imagery for Coastal Classification Mapping

This article studies the effect of airborne lidar (surface) elevation data on the classification of multispectral IKONOS images over a coastal area. The lidar data and IKONOS images are treated as independent multiple bands to conduct the classification. To do so, the lidar elevation data is first resampled to the same ground spacing interval and stretched to the same radiometric range as the IKONOS images. An unsupervised classification based on the ISODATA algorithm is then used to determine a class schema of six classes: road, water, marsh, roof, tree, and sand. Training sites and checking sites are selected over the lidar-IKONOS merged data set for the subsequent supervised classification and quality evaluation. The complete confusion matrices and average quality indices are presented to assess and compare the classification results. It is shown that the inclusion of the lidar elevation data benefits the separation of classes that have similar spectral characteristics, such as roof and road, water and marsh. The overall classification errors, especially the false positive errors, are reduced by up to 50%. Moreover, by using the lidar elevation data, the classification results show more realistic and homogeneous distribution of geographic features. This property will benefit the subsequent vectorization of the classification maps and the integration of the vector data into a geographical information system.