<b>目的</b>阐述了无人机遥感兴起的背景。从无人飞行平台、飞行姿态控制与导航、数据传输与存储、数据处理、传感器技术、空域使用政策等方面探讨了发展无人机遥感系统的基础、问题、研究进展和趋势。通过描述无人机遥感系统在大量相关行业领域的应用与实践,点出了发展无人机遥感系统的必要性与意义所在。最后,从科技、政策等方面给出了发展无人机遥感技术和产业的建议。

<p>针对无人机遥感技术应用中信息提取自动化、智能化不足的问题,提出了一种基于面向对象分割的农村房屋信息提取方法。该方法首先利用双边滤波器滤掉影像中的噪声,然后利用移动均值算法分割影像,最后根据分割后房屋对象的特征建立提取规则,对房屋信息进行提取。实验结果表明,该方法可有效提取无人机遥感影像中的农村房屋信息,平均提取精度约为92%。</p>

<p>无人机影像的质量与成像时的光线、成像角度及所拍摄地物的特征有着密切关系。很多影像都存在着视觉对比度差、影像畸变大及分辨率低等缺点,给后续影像匹配和正射纠正带来困难。为了提高无人机影像的匹配效果,首先利用原始影像的离散灰度信息计算每个像元灰度值与整个影像灰度平均值的离散程度,并把影像划分为不同区域; 然后利用距离加权插值方法计算的变换函数对各区域影像进行不同程度的增强处理,对增强后影像的直方图进行修正; 最后利用核线约束法对影像进行匹配和均匀度检验。研究结果表明,由于增强后影像的灰度梯度差变大,在畸变较大及灰度变化较小的林地分布区域,影像的匹配成功率和均匀度都有一定程度的提高。</p>

<p>研究了利用遥感技术开展矿山动态监测的方法与技术路线，即通过遥感图像的信息提取、解译，结合实地调查，对矿山开发状况和矿山生态环境进行客观的反映。通过对比分析不同时相遥感数据的解译结果，指出工作区存在部分违规采矿行为，很好地实现了对本区采矿行为及影像的动态监测。</p>

<p>为了给地质灾害调查中无人机(unmanned aerial vehicle,UAV)遥感影像处理软件的选择提供参考,对国内外使用较多的DPGrid,PixelGrid,DPMatrix和Inpho等4款软件进行了评价。以固定翼无人机搭载的Cannon 5D MARK Ⅱ相机获取的江西省龙南县丘陵地区1个架次644张无人机影像作为实验数据,由同一操作者在同一实验环境下分别使用上述4款软件进行了影像预处理、空三平差、数字高程模型(digital elevation model,DEM)生产及数字正射影像图(digital orthophoto map,DOM)生产等实验,从软件功能、效率、成果质量及操作流程等方面进行了对比分析。研究结果表明:4款软件都具有完整的无人机遥感影像处理功能。在利用原始数据生成正射影像的处理效率方面,从高到低依次是Inpho,DPMatrix,DPGrid和PixelGrid;在地质灾害应急调查方面,比较适宜使用DPGrid和DPMatrix进行快速拼图,而对于地质灾害详查,4款软件都能满足需要,其中DPGrid和PixelGrid更方便进行精度控制;在数据处理方面,影像匀光匀色适宜使用Inpho和DPGrid,DEM和DOM成果编辑适宜使用DPGrid。</p>

Among the anthropogenic topographic signatures on Earth, open-pit mines are of great importance. Mining is of interest to geomorphologists and environmental researchers because of its implication in geomorphic hazards and processes. In addition, open-pit mines and quarries are considered the most dangerous industrial sector, with injuries and accidents occurring in numerous countries. Their fast, accurate and low-cost investigation, therefore, represents a challenge for the Earth science community. The purpose of this work is to characterise the open-pit mining features using high-resolution topography and a recently published landscape metric, the Slope Local Length of Auto-Correlation (SLLAC) (Sofia et al., 2014). As novel steps, aside from the correlation length, the terrace orientation is also calculated, and a simple empirical model to derive the percentage of artificial surfaces is tested. The research focuses on two main case studies of iron mines, both located in the Beijing district (P.R. China). The main topographic information (Digital Surface Models, DSMs) was derived using an Unmanned Aerial Vehicle (UAV) and the Structure from Motion (SfM) photogrammetric technique. The results underline the effectiveness of the adopted methodologies and survey techniques in the characterisation of the main mine geomorphic features. Thanks to the SLLAC, the terraced area given by open-cast/open-pit mining for iron extraction is automatically depicted, thus, allowing researchers to quickly estimate the surface covered by the open-pit. This information could be used as a starting point for future research (i) given the availability of multi-temporal surveys to track the changes in the extent of the mine; (ii) to relate the extent of the mines to the amount of processes in the area (e.g. pollution, erosion, etc.), and to (iii) combine the two points, and analyse the effects of the change related to changes in erosion. The analysis of the correlation length orientation also allows researchers to identify the terrace鈥檚 orientation and to understand the shape of the open-pit area. The tectonic environment and history, or inheritance, of a given slope can determine if and how it fails, and the orientation of the topographic surface or excavation face, with respect to geologic features, is of major significance. Therefore, the proposed approach can provide a basis for a large-scale and low-cost topographic survey for sustainable environmental planning and, for example, for the mitigation of environmental anthropogenic impacts due to mining.

Recent research in fluvial geomorphology has emphasized the spatially distributed feedbacks amongst river channel topography, flow hydraulics and sediment transport. Although understanding of the behaviour of dynamic river channels has been increased markedly through detailed within-channel process studies, less attention has been given to the accurate monitoring and terrain modelling of river channel form using three-dimensional measurements. However, such information is useful in two distinct senses. Firstly, it is one of the necessary boundary conditions for a physically based, deterministic modelling approach in which three-dimensional topography and river discharge drive within-channel flow hydraulics and ultimately spatial patterns of erosion and deposition and therefore channel change. Secondly, research has shown that an alternative means of estimating the medium-term bedload transport rate can be based upon monitoring spatial patterns of erosion and deposition within the river channel. This paper presents a detailed assessment of the distributed monitoring and terrain modelling of river bed topography using a technique that combines rigorous analytical photogrammetry with rapid ground survey. The availability of increasingly sophisticated terrain modelling packages developed for civil engineering application allows the representation of topographic information as a landform surface. Intercomparison of landform surfaces allows visualization and quantification of spatial patterns of erosion and deposition. A detailed assessment is undertaken of the quality of the morphological information acquired. This allow some general comments to be made concerning the use of more traditional methods to monitor and represent small-scale river channel morphology.

Repeat topographic surveys are increasingly becoming more affordable, and possible at higher spatial resolutions and over greater spatial extents. Digital elevation models (DEMs) built from such surveys can be used to produce DEM of Difference (DoD) maps and estimate the net change in storage terms for morphological sediment budgets. While these products are extremely useful for monitoring and geomorphic interpretation, data and model uncertainties render them prone to misinterpretation. Two new methods are presented, which allow for more robust and spatially variable estimation of DEM uncertainties and propagate these forward to evaluate the consequences for estimates of geomorphic change. The first relies on a fuzzy inference system to estimate the spatial variability of elevation uncertainty in individual DEMs while the second approach modifies this estimate on the basis of the spatial coherence of erosion and deposition units. Both techniques allow for probabilistic representation of uncertainty on a cell-by-cell basis and thresholding of the sediment budget at a user-specified confidence interval. The application of these new techniques is illustrated with 5 years of high resolution survey data from a 1 km long braided reach of the River Feshie in the Highlands of Scotland. The reach was found to be consistently degradational, with between 570 and 1970 m3 of net erosion per annum, despite the fact that spatially, deposition covered more surface area than erosion. In the two wetter periods with extensive braid-plain inundation, the uncertainty analysis thresholded at a 95% confidence interval resulted in a larger percentage (57% for 2004-2005 and 59% for 2006-2007) of volumetric change being excluded from the budget than the drier years (24% for 2003-2004 and 31% for 2005-2006). For these data, the new uncertainty analysis is generally more conservative volumetrically than a standard spatially-uniform minimum level of detection analysis, but also produces more plausible and physically meaningful results. The tools are packaged in a wizard-driven Matlab software application available for download with this paper, and can be calibrated and extended for application to any topographic point cloud (x,y,z). Copyright 漏 2009 John Wiley & Sons, Ltd.

The estimation of fluvial sediment transport rate from measurements of morphological change has received growing recent interest. The revival of the ‘morphological method’ reflects continuing concern over traditional methods of rate determination but also the availability of new survey methods capable of high-precision, high-resolution topographic monitoring. Remote sensing of river channels through aerial digital photogrammetry is a potentially attractive alternative to labour intensive ground surveys. However, while photogrammetry presents the opportunity to acquire survey data over large areas, data precision and accuracy, particularly in the vertical dimension are lower than in traditional ground survey methods. This paper presents results of recent research in which digital elevation models (DEMs) have been developed for a reach of a large braided gravel-bed river in Scotland using both digital photogrammetry and high-resolution RTK GPS ground surveys. A statistical level of change detection is assessed by comparing surfaces with independent check points. The methodological sensitivity of the annual channel sediment budget (1999–2000) to the threshold is presented. Results suggest that while the remote survey methods employed here can be used to develop qualitatively convincing, moderate precision DEMs of channel topography (RMSE=±0.21 m), the remaining errors imply significant limits on reliable change detection which lead to important information losses. Tests at a 95% confidence interval for change detection show that over 60% of channel deposition and 40% of erosion may be obscured by the lower level of precision associated with photogrammetric monitoring when compared to ground survey measurements. This bias reflects the difficulty of detecting the topographic signature of widespread, but shallow deposition on bar tops.