This paper takes the geological disaster-prone area of Mayang County of Hunan Province as the test area.The results of the GNSS station time series calculation show that the vertical shape variable of the regional overall crustal plate ranges from 3.39mm to 4.85mm, indicating the overall upward trend;According to the calculation based on the InSAR long time series, the absolute vertical shape variable of the whole surface ranges from -41mm to 31mm, indicating the overall subsidence and local uplift trend.This paper explains the difference between the two methods and the reasons for the difference.It determines the difference is the difference between the bedrock plate movement and the bare surface absolute movement and forms a set of regional pure deformation field calculation methods. In the study area, the GNSS bedrock observation and InSAR surface observation results were respectively fitted with the global spatial difference. Then the difference was calculated to obtain the relative shape variable of the exposed surface movement compared with the bedrock, and the regional pure settlement field was -34.46mm~34.89mm. In this paper, it is proved by experiments that there are significant differences between the monitoring results of bedrock GNSS station and InSAR technology in the geological disaster research area. If the absolute surface shape variable observed by the InSAR method is not deducted from the relative shape variable, it is easy to misjudge the landslide hidden danger trend. To better reflect the surface subsidence trend, when studying the subsidence of geological disaster areas, it is necessary to subtract the bedrock shape variable from the analysis and to use the surface’s movement trend (pure deformation field) relative to the crustal bedrock as a variable.
以卷积神经网络为代表的深度学习方法大幅提高了遥感影像建筑物自动检测精度,但由于建筑物复杂多样,为了提取区分能力更强的图像特征,现有卷积神经网络方法往往倾向于构建层次复杂、参数庞大的深度模型.这使得模型的存储和内存开销都较高、检测速率也容易受到影响,一定程度上造成在移动设备平台或灾害应急等场合的应用受限.针对此问题,提出一种用于航空影像建筑物检测的轻量化卷积神经网络建模方法,采用深度可分离卷积方法对复杂网络进行简化,大幅减少了计算量,并较好地维持了原有精度.实验表明新方法相比改进前,在计算量和参数量分别减少86%和87%、训练时间缩短10%的情况下,建筑物检测的精度仅降低3%.
以广州市南沙区自然资源调查为例,针对高分六号遥感影像的特点,建立了高分六号影像可以适应的自然资源分类体系.分析了面向对象的遥感影像分类过程中的各个过程,研究了多尺度影像分割在不同参数设置下的分类效果,得出了较为合适的多尺度分割参数,进行了面向对象分类实验和分类精度评价,影像分类精度达到了78.66％.通过对南沙区影像在实验各个流程中的区别及联系进行了横向对比,总结了其中的规律,显示了基于高分六号的面向对象遥感影像分类方法在自然资源调查中的应用价值.
近年来,受城市周边建设发展导致的基准站环境变化搬迁、设备使用年限增长和恶劣天气影响,各省GNSS基准站信息发生很大变化.随着我国北斗卫星导航系统(BDS)的发展,需要全面了解基准站信息状况,及时更新维护现代测绘基准体系.以HBCORS为例,探索了GNSS基准站普查的目的、内容和方法,提出了普查的技术流程、关键问题和解决方法,并在湖北省GNSS基准站普查工作中进行了实践.结果表明,该方法可在其他地区推广,具有实践意义.
目前高精度地图仍采取半自动交互形式制作,因此控制与评价高精度地图质量显得尤为重要.根据高精度地图制图规范、产品规格书等开发地图要素检查系统,可实现部分自动修正功能.依据空间拓扑关系与要素逻辑检查,设立三级检查机制,实现程序自动查、改、报错等功能,并根据错误要素重要性修改占比自动计算地图品质率.经杭州亚运会测试场与德清测试场实验可知,该方法可极大地提高审图效率,客观、公正地评价地图的品质率;其建立的检查机制模型不仅为地图从业者提供了借鉴方法,也为国家确立地图相关评价规范提供了参考.
