水准测量野外数据处理采用手机取代PC1500的研究

通过易县地震台水准数据处理手机程序的设计,研究了用手机取代PC1500的可行性。结果表明,用手机取代PC1500,进行水准数据的存储计算是完全可行的。     

应对巨大地震的应急流动观测系统

通过“十五”数字地震观测网络项目建设,目前。我国的地震观测系统和地震观测信号传输几乎完全依赖于公共通讯网络。但是,大地震常常严重破坏公共通讯系统,应对巨大地震的流动观测系统就提到迫切的日程。2007年,通过采用无线竞带接入技术,结合中国地震局数字地震观测网络技术,初步建成了应对巨大地震的应急流动观测系统,并在汶川地震现场观测初期发挥了重要作用。     

基于LiDAR-DP的机载激光雷达数据处理

基于国产机载LiDAR数据处理软件LiDAR-DP,总结了机载LiDAR数据处理的技术流程,并根据该流程对LiDARDP的相关功能进行了研究。利用LiDAR-DP对实际数据进行了DEM生产试验,并与同类商业软件进行了功能对比。结果表明,LiDAR-DP是一款优秀的国产机载LiDAR数据处理软件,完全能满足DEM的生产需求。     

基于Flex的跨平台移动土地信息管理系统设计与实现

将具有跨平台性的Flex移动开发技术与ArcGIS Server ,ArcGIS Flex API等GIS相关技术结合,构建了跨平台移动GIS并应用于山西省襄汾县土地信息管理工作中,在多平台的移动智能终端上实现了土地信息数据查询、地块信息实时更新、移动GPS定位等功能。提高了国土资源管理信息化程度,提高了工作效率和业务管理水平,为移动GIS在土地管理中的应用与研究上提供补充和参考。     

2008年7月5日长泰M_L4.7地震前流动地磁观测结果的分析

摘要利用2002年7月～2008年11月的流动地磁观测资料进行分析研究,结果表明:2007年4月福建南部的流磁观测结果出现异常,可能是福建长泰M_L4.7地震前的震磁效应;震前靠近北西向断裂,并沿该断裂走向分布的流磁测点同步出现异常,可能与断裂构造应力作用有关。     

电力巡线LiDAR点云电塔自动定位和提取算法

针对电力巡线机载激光雷达(LiDAR)激光点云电塔自动提取问题,提出了一种电塔自动定位和点云提取算法。首先,基于点云进行二维空间网格划分,利用网格点云高程偏差和方差特征提取潜在电塔网格;其次,基于电塔点云的高程连续特性完成电塔自动定位和点云粗提取;然后,利用点云分层密度信息和图像开运算,实现电塔精细提取;最后,利用轻小型无人机载激光雷达数据验证本文算法的有效性。试验结果表明,本文所提出的自动提取算法,能够有效解决LiDAR数据中电塔自动定位和点云提取问题,在LiDAR数据质量较差时仍能够取得良好效果,算法对于噪点数据具有较强的稳健性。本文所提出的电塔自动提取算法在LiDAR电力巡检数据处理中具有一定的应用价值。     

海岸线及其测绘技术探讨

海岸线是人类所使用的最古老的边界线之一,然而,由于其动态特征,加之当今社会对海岸带的需求越来越多,这条边界线的位置存在争议,因而,如何使用客观手段测绘海岸线尤为重要。文中针对海岸线定义及其位置确定不明确的现状,指出海岸线定义存在的问题,给出完善定义的意见;分析海岸线常规的测绘方法,探讨海岸线精确测绘的新方法和技术。     

Retrieving aboveground biomass of wetland Phragmites australis (common reed) using a combination of airborne discrete-return LiDAR and hyperspectral data

Wetland biomass is essential for monitoring the stability and productivity of wetland ecosystems. Conventional field methods to measure or estimate wetland biomass are accurate and reliable, but expensive, time consuming and labor intensive. This research explored the potential for estimating wetland reed biomass using a combination of airborne discrete-return Light Detection and Ranging (LiDAR) and hyperspectral data. To derive the optimal predictor variables of reed biomass, a range of LiDAR and hyperspectral metrics at different spatial scales were regressed against the field-observed biomasses. The results showed that the LiDAR-derived H_p99 (99th percentile of the LiDAR height) and hyperspectral-calculated modified soil-adjusted vegetation index (MSAVI) were the best metrics for estimating reed biomass using the single regression model. Although the LiDAR data yielded a higher estimation accuracy compared to the hyperspectral data, the combination of LiDAR and hyperspectral data produced a more accurate prediction model for reed biomass (R² = 0.648, RMSE = 167.546 g/m², RMSE_r = 20.71%) than LiDAR data alone. Thus, combining LiDAR data with hyperspectral data has a great potential for improving the accuracy of aboveground biomass estimation.     

Automated landslide mapping using spectral analysis and high-resolution topographic data: Puget Sound lowlands, Washington, and Portland Hills, Oregon

Landslide inventory maps are necessary for assessing landslide hazards and addressing the role slope stability plays in landscape evolution over geologic timescales. However, landslide inventory maps produced with traditional methods — aerial photograph interpretation, topographic map analysis, and field inspection — are often subjective and incomplete. The increasing availability of high-resolution topographic data acquired via airborne Light Detection and Ranging (LiDAR) over broad swaths of terrain invites new, automated landslide mapping procedures. We present two methods of spectral analysis that utilize LiDAR-derived digital elevation models of the Puget Sound lowlands, Washington, and the Tualatin Mountains, Oregon, to quantify and automatically map the topographic signatures of deep-seated landslides. Power spectra produced using the two-dimensional discrete Fourier transform and the two-dimensional continuous wavelet transform identify the characteristic spatial frequencies of deep-seated landslide morphologic features such as hummocky topography, scarps, and displaced blocks of material. Spatial patterns in the amount of spectral power concentrated in these characteristic frequency bands highlight past slope instabilities and allow the delineation of landslide terrain. When calibrated by comparison with detailed, independently compiled landslide inventory maps, our algorithms correctly classify an average of 82% of the terrain in our five study areas. Spectral analysis also allows the creation of dominant wavelength maps, which prove useful in analyzing meter-scale topographic expressions of landslide mechanics, past landslide activity, and landslide-modifying geomorphic processes. These results suggest that our automated landslide mapping methods can create accurate landslide maps and serve as effective, objective, and efficient tools for digital terrain analysis.     

上海市精细时空尺度人口分布估计与特征分析

城市人口实时分布与动态变化特征是城市规划与综合治理的重要依据。受数据获取手段的局限性,准确地获取城市人口的实时分布状况一直是技术瓶颈,而移动通讯技术的迅速普及为这一问题的解决提供了技术途径。本文基于移动通讯信令的连续轨迹数据,实现了城市精细尺度人口分布时空估算的方法流程,并以上海市为研究区,对城市人口分布特征及时空移动过程进行了量化分析。研究表明：① 在数据方面,基于移动通讯信令数据估算城市人口分布的方式样本覆盖广、时空精度高、时效性较强且支持时空尺度灵活多变的应用研究需求,能够定量地描述城市人口分布时空动态特征且能推算城市真实人口规模;② 在人口分布时空特征方面,上海市在全市尺度上,各时段人口空间分布较为稳定且差异较小,而在中心城区日间人口较夜间人口呈现更为显著的空间集聚特征;③ 在人口移动时空特征方面,城市功能承载区与其它区域之间人口移动很少,早晚高峰期各城市功能承载区之间人口移动均体现为中心城区与其它新城之间的移动,且2个方向移动人数较为平衡;各城市功能承载区内均有超过半数的人口全天仅在其所在城区内部活动。本文的研究成果可为上海城市规划、应急管理、交通出行等提供更精准的科学依据。