基于倾斜摄影技术在农村房屋权籍调查测量中的应用

介绍了基于无人机倾斜摄影系统,快速实现真实三维自动建模并利用三维模型进行立体量测的技术流程和作业方法。利用上述技术在农村房屋权籍调查测量中进行了应用探索,为突破以往只能依靠野外实地测量提供了另外一种高效的解决方案。     

The First World War from above and below. Historical aerial photographs and mine craters in the Ypres Salient

During the First World War, ancient siege techniques were used in an attempt to break through the stalemate in the trenches. This paper approaches the mine crater war from a completely new perspective and focuses on a landscape-scale approach rather than on fragmented individual sites. Thousands of contemporary aerial photographs have been used as a primary source of information to detect and understand the historical mine crater landscape along the former Western Front in Belgium. The paper presents a methodology for dating war features by means of a time series analysis of aerial photographs, confronting this historical landscape with a high-resolution Airborne Laser Scanning (ALS) dataset.     

利用资源三号测绘卫星影像实现多尺度4D产品更新

4D产品的快速生产与更新一直以来是测绘地理信息部门研究的重点,采用传统航摄技术生产和更新无图区或陈旧的地理信息资料时,生产困难,成本高,周期长,且消耗大量的人力和物力。针对这些问题,本文采用资源三号测绘卫星影像实现4D产品更新,使得更新速度加快,为多尺度4D产品的生产与更新提供了高效可靠的技术手段。     

旋翼无人机数字摄影在大比例尺正射影像图制作中的应用

旋翼无人机具有起降条件简单、便于操控、垂直起降、影像清晰、安全系数高等诸多优点,适合应用于小范围平坦地区的摄影测量。本文以六旋翼无人机航摄系统完成小区域大比例尺正射影像图制作为实例,介绍了该型无人机系统的组成、功能特点及作业方法,并对航测成果精度进行检核。结果表明:在像控点布设位置、密度符合要求的情况下,旋翼无人机航摄基本能满足1∶2 000正射影像图制作的要求。     

南极1∶5000地形图测绘关键技术及相关问题处理——以南极维多利亚地站为例

从国家南极科学考察工作的实际需求出发,以南极拟新建站址维多利亚地1∶5 000地形图测绘为例,阐述进行南极特殊区域地形图测绘工作在数据获取及地形图测绘相关数据处理方面所遇到的问题,介绍南极特殊区域测绘与常规区域测绘生产的不同,以及在关键工序存在的问题及处理方法,为今后开展相关的地形图测绘工作提供技术依据。     

Estimation of surface chlorophyll on an exposed mudflat using digital colour-infrared (CIR) photography

The usefulness of field-based digital Colour-InfraRed (CIR) photography to quantify concentrations of chlorophyll on the surface of exposed mudflats is investigated. Multiple images, each 626 mm by 467 mm, were acquired during Austral summertime using a Duncantech three-band CIR camera from two areas of mudflat in the upper reaches of Sydney Harbour. Sediment samples were obtained from within the field of view of the camera and their chlorophyll concentration was estimated spectrophotometrically. After the camera images were normalised to compensate for the effects of variations in the intensity of downwelling solar radiation, chlorophyll was estimated for each 0.9 mm square pixel using a suite of five different vegetation indices. Regression analysis was used to determine the strength of the relationship between the index values and the estimates of chlorophyll from the in situ samples. Indices constructed from near-infrared and red bands were found to have the strongest relationships with in situ chlorophyll estimates (R² ranging from 0.28 to 0.79) and indices derived from near-infrared and green bands the weakest (R² ranging from 0.16 to 0.22). The vegetation indices highlighted complex small-scale variability in chlorophyll distribution that was not evident in the original camera images. These findings indicate that field-based CIR photography will provide a useful tool for the non-destructive determination of benthic chlorophyll.     

Seasonal and inter-annual variation in occurrence and biomass of rooted macrophytes and drift algae in shallow bays

Submerged rooted macrophytes and drift algae were studied in shallow (0–1 m) brackish soft-bottom bays in the Åland Islands, N Baltic Sea, in 1997–2000. The study was performed by aerial photography and ground-truth sampling and the compatibility of the methods was evaluated. The study provided quantitative results on seasonal and inter-annual variation in growth, distribution and biomass of submerged macrophytes and drift algae.On an average, 18 submerged macrophyte species occurred in the studied bays. The most common species, by weight and occurrence, were Chara aspera, Cladophora glomerata, Pilayella littoralis and Potamogeton pectinatus. Filamentous green algae constituted 45–70% of the biomass, charophytes 25–40% and vascular plants 3–18%. A seasonal pattern with a peak in biomass in July–August was found and the mean biomass was negatively correlated with exposure. There were statistically significant differences in coverage among years, and among levels of exposure. The coverage was highest when exposure was low. Both sheltered and exposed bays were influenced by drift algae (30 and 60% occurrence in July–August) and there was a positive correlation between exposure and occurrence of algal accumulations. At exposed sites, most of the algae had drifted in from other areas, while at sheltered ones they were mainly of local origin.Data obtained by aerial photography and ground-truth sampling showed a high concordance, but aerial photography gave a 9% higher estimate than the ground-truth samples. The results can be applied in planning of monitoring and management strategies for shallow soft-bottom areas under potential threat of drift algae.     

Historical Landscape Change in Yellowstone National Park: Demonstrating the Value of Intensive Field Observation and Repeat Photography

Although transportation and outdoor recreation are well‐recognized aspects of national parks, few studies have explored these aspects from the perspective of human geography as a means of analyzing historical landscape change. This paper offers an innovative synthesis of methods for studying cultural landscape change over time through a case study of the historical geography of transportation, tourism, and outdoor recreation along the Howard Eaton Trail (HET) in Yellowstone National Park. We conducted research through a field course that combined repeat photography, archival research, Geographic Information Systems (GIS), and traditional field methods. Results indicate that a combination of repeat photography and other methods can create an effective means of evaluating cultural landscape change; even short field courses provide opportunities for students and faculty to conduct collaborative research that provides powerful, multidimensional, situated‐learning experiences; and repeat photography creates datasets that may benefit future research and teaching.     

Stream network expansion: a riparian water quality factor

Little is known about how active stream network expansion during rainstorms influences the ability of riparian buffers to improve water quality. We used aerial photographs to quantify stream network expansion during the wet winter season in five agricultural catchments in western Oregon, USA. Winter stream drainage densities were nearly two orders of magnitude greater than summer stream densities, and agricultural land use was much more abundant along transient portions (e.g. swales, road ditches) of stream networks. Water moving from agricultural fields into expanded stream networks during large hydrologic events has the opportunity to bypass downstream riparian buffers along perennial streams and contribute nonpoint‐source pollutants directly into perennial stream channels. Copyright © 2005 John Wiley & Sons, Ltd.     

Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

Mapping saturation areas during rainfall events is important for understanding the dynamics of overland flow. In this study, we evaluate the potential of high temporal resolution time‐lapse photography for mapping the dynamics of saturation areas (i.e., areas where water is visually ponding on the surface) on the hillslope scale during natural rainfall. We take 1 image per minute over a 100 × 15 m² depression area on an agricultural field in the Hydrological Open Air Laboratory, Austria. The images are georectified and classified by an automated procedure, using grey intensity as a threshold to identify saturation area. The optimum threshold T is obtained by comparing saturation areas from the automated analysis with the manual analysis of 149 images. T is found to be highly correlated with an image brightness characteristic defined as the greyscale image histogram mode M (Pearson correlation r = 0.91). We estimate T as T = M + C where C is a calibration parameter assumed to be constant during each event. The automated procedure estimates the total saturation area close to the manual analysis with mean normalized root mean square error of 9% and 21% if C is calibrated for each event and taken constant for all events, respectively. The spatial patterns of saturation are estimated with a geometric mean accuracy index of 94% as compared to the manual analysis of the same photos. The patterns are tested against field observations for one date as a preliminary demonstration, which yields a root mean square error of the shortest distance between the measured boundary points and the automatically classified boundary as 23 cm. The usefulness of the patterns is illustrated by exploring run‐off generation processes of an example event. Overall, the proposed classification method based on grey intensity is found to process images with highly varying brightnesses well. It is more efficient than the manual tracing for a large number of images, which allows the exploration of surface flow processes at high temporal resolution.