关于新、旧北京1954坐标系统的转换与应用

国土部门在北京1954坐标系下,已完成大多数城镇的初始调查工作,并发放了相应的土地证等图件资料。而现在又需要在C级GPS网布设基础控制测量工作,这就产生了它们的坐标转换工作。这里举某市两种坐标转换和比较的实例,以供参考。     

Self-calibration Applied in Converting Simulation Surveying

In the field of converting simulation surveying and traditional close range photogrammetry, it has been developed so far to survey objects by commercial digital camera and this technique is applied widely in every part of production. In order to get three-dimensional information of objects, commercial digital camera must be examined. For a long time, digital camera has been examined by DLT. Then there must be a high-precision control field. For realizing surveying without control points, a method for self-calibration is proposed.     

机载LiDAR技术

机载LiDAR集成了GPS、IMU、激光扫描仪新一代航空遥感系统,能利用飞行获取的原始数据直接生成DEM和正射影像图,而无需任何或仅需少量的地面控制点。与传统的摄影测量技术相比,机载LiDAR可以节省大量的人力、时间和经费。在过去十年,机载LiDAR作为精确、快速的地球表面三维测量方法已得到广泛的认同,本文详细介绍了机载LiDAR的基本原理、技术结构及数据处理流程。     

国土资源管理信息系统的安全建设初探

随着国土资源信息系统建设的不断扩大和应用,信息系统安全问题日益突出。本文着重阐述了系统安全建设的特点、建设内容和建设原则,并对国土资源信息系统安全建设进行了探讨。     

基于三维激光扫描数据的建筑物三维建模

给出基于三维激光扫描测量仪所获得的点云数据来实现建筑物三维建模的方法。文中介绍了三维激光扫描测量仪的系统组成与工作原理,给出对点云数据处理的过程和方法,阐述建筑物三维建模的方法,并用实例介绍整体方法的实现过程和效果。     

一种面向对象的4层空间数据模型

针对“空间数据是否要建立拓扑关系并在数据库中显式地存储记录”一直是G IS领域争论的问题,给出了解决方案:融合拓扑关系数据模型和面向实体数据模型,进而在分析和总结现有数据模型的基础上提出了一种面向对象的4层空间数据模型。对模型作了4个层次划分:几何对象、基本和复杂要素、分层与分区以及多尺度表达。模型具有3个特点,即多尺度描述地理空间;能描述不同要素层、不同区之间的关系;用户可根据实际情况自定义要素层拓扑关系。最后给出了模型在自主开发的地理数据库管理平台Geoinfo中的应用情况。     

中国区域MuSyQ叶面积指数产品验证与分析

对多源遥感数据协同生产的2010年—2015年中国区域1 km空间分辨率5天合成的MuSyQ（Multi-source data Synergized Quantitative remote sensing production system）叶面积指数LAI产品进行验证。参考现有的LAI产品（MODIS c5,GLASS LAI）和中国生态系统研究网络部分农田和森林站点可用的LAI地面测量数据,从时空连续性、时空一致性、精度和准确性等方面对中国区域的MuSyQ LAI产品进行定性和定量分析与评价。结果表明：（1） MuSyQ LAI产品在保证精度优于MODIS产品的情况下,时间分辨率和时空连续性均有提高。MuSyQ LAI与其他LAI产品（MODIS c5,GLASS LAI）在整体上有很好的一致性（RMSE=1.0,RMSE=0.81）,但对常绿阔叶林高值处的描述不稳定;（2） 与LAI地面测量数据相比,MuSyQ LAI产品与地面参考图对比结果较好（最高相关性（R²=0.54）和较低总体误差（RMSE=0.96））,其在阔叶作物生长季高值处有些许低估且在某些阔叶林站点有些高估。整体上,MuSyQ LAI产品呈现出较高的精度,可靠的空间分布和连续稳定的时间分布,且对森林LAI的描述具有更可靠的动态范围。     

Re-examining urban region and inferring regional function based on spatial–temporal interaction

Urban system is shaped by the interactions between different regions and regions planned by the government, then reshaped by human activities and residents’ needs. Understanding the changes of regional structure and dynamics of city function based on the residents’ movement demand are important to evaluate and adjust the planning and management of urban services and internal structures. This paper constructed a probabilistic factor model on the basis of probabilistic latent semantic analysis and tensor decomposition, for purpose of understanding the higher order interactive population mobility and its impact on urban structure changes. First, a four-dimensional tensor of time (T)?×?week (W)?×?origin (O)?×?destination (D) was constructed to identify the day-to-day activities in three time modes and weekly regularity of weekday/weekend pattern. Then we reclassified the urban regions based on the space clustering formed by the space factor matrix and core tensor. Finally, we further analysed the space–time interaction on different time scales to deduce the actual function and connection strength of each region. Our research shows that the application of individual-based spatial–temporal data in human mobility and space–time interaction study can help to analyse urban spatial structure and understand the actual regional function from a new perspective.     

Study on the urban heat island effects and its relationship with surface biophysical characteristics using MODIS imageries

This study assesses surface urban heat island (UHI) and its associated surface physical characteristics using remote sensing approaches. TERRA/MODIS images acquired in 2005 in three different seasons were selected to generate land surface tem-perature and surface characteristics for the Changsha-Zhuzhou-Xiangtan metropolitan area in China. The intensity of urban heat is-land effects and its seasonal variations were examined. The result showed that UHI effects were significant both in the summer and the spri...     

Integrating terrain and vegetation indices for identifying potential soil erosion risk area

The present paper offers an innovative method to monitor the change in soil erosion potential by integrating terrain and vegetation indices derived from remote sensing data. Three terrain indices namely, topographic wetness index (TWI), stream power index (SPI) and slope length factor (LS), were derived from the digital elevation model. Normalized vegetation index (NDVI) was derived for the year 1988 and 2004 using remote sensing images. K-mean clustering was performed on staked indices to categorize the study area into four soil erosion potential classes. The validation of derived erosion potential map using USLE model showed a good agreement. Results indicated that there was a significant change in the erosion potential of the watershed and a gradual shifting of lower erosion potential class to next higher erosion potential class over the study period.