复杂地势下轻小型无人机LiDAR自主航线设计     

陈玥  李英成  李兵  刘晓龙 《测绘科学》2021,46(3):104-109,132

针对现有的LiDAR航线设计软件绝大多数针对大中型无人机,主要依靠飞行人员根据实际经验敷设航线,少数采用传统摄影测量改变基线长度的方式实现复杂地势下LiDAR航线自动敷设,但高地势地区航线较密,飞行成本高,有局限性,目前能实现轻小型无人机载LiDAR航线自主敷设的软件很少等问题,参照轻小型机载LiDAR的特点,该文提出一种复杂地势下基于DEM改变航高的航线设计方法。以延庆某山区进行试验。结果表明:该方法适当放宽分区高差限制,综合考虑地形信息、飞机性能等要素,使得单条航带点云密度得到保证,提高航线规划效率,节约飞行时间。将考虑DEM与未考虑DEM两种方式对比,确保重叠度,满足工程点云密度,便于后期数据处理。  相似文献   

基于共享单车时空大数据的细粒度聚类     

张强  白征东  辛浩浩  程宇航  郭锦萍 《测绘通报》2021,(5):15-19,29

针对传统上单独采用K-means或DBSCAN等方法对共享单车位置数据聚类时造成的聚类结果与真实的聚类结构不符的问题,本文提出了一种基于共享单车时空大数据的细粒度聚类方法(FGCM)。该方法通过DBSCAN进行初始聚类,并在此基础上采用GMM-EM算法进行细部聚类,以提取细粒度层级的热点区域。试验表明,该方法可根据密度阈值排除噪声和离群值,无需指定细部聚类簇数,簇的形状和大小比较灵活。在对共享单车大数据位置特征进行聚类时,与传统的单独采用K-means或DBSCAN的方法相比,FGCM具备更高的精细程度,能够充分展现共享单车的实际聚集特征,可用于规划共享单车电子围栏等设施,在不降低通勤效率的基础上规范共享单车的停放问题。  相似文献   

Spatiotemporal variability in hydrochemistry of shallow groundwater in a small pre‐alpine catchment: The importance of landscape elements     

Leonie Kiewiet  Jana von Freyberg  H.J. van Meerveld 《水文研究》2019,33(19):2502-2522

Topography and landscape characteristics affect the storage and release of water and, thus, groundwater dynamics and chemistry. Quantification of catchment scale variability in groundwater chemistry and groundwater dynamics may therefore help to delineate different groundwater types and improve our understanding of which parts of the catchment contribute to streamflow. We sampled shallow groundwater from 34 to 47 wells and streamflow at seven locations in a 20‐ha steep mountainous catchment in the Swiss pre‐Alps, during nine baseflow snapshot campaigns. The spatial variability in electrical conductivity, stable water isotopic composition, and major and trace ion concentrations was large and for almost all parameters larger than the temporal variability. Concentrations of copper, zinc, and lead were highest at sites that were relatively dry, whereas concentrations of manganese and iron were highest at sites that had persistent shallow groundwater levels. The major cation and anion concentrations were only weakly correlated to individual topographic or hydrodynamic characteristics. However, we could distinguish four shallow groundwater types based on differences from the catchment average concentrations: riparian zone‐like groundwater, hillslopes and areas with small upslope contributing areas, deeper groundwater, and sites characterized by high magnesium and sulfate concentrations that likely reflect different bedrock material. Baseflow was not an equal mixture of the different groundwater types. For the majority of the campaigns, baseflow chemistry most strongly resembled riparian‐like groundwater for all but one subcatchment. However, the similarity to the hillslope‐type groundwater was larger shortly after snowmelt, reflecting differences in hydrologic connectivity. We expect that similar groundwater types can be found in other catchments with steep hillslopes and wet areas with shallow groundwater levels and recommend sampling of groundwater from all landscape elements to understand groundwater chemistry and groundwater contributions to streamflow.  相似文献   

不同密度团头鲂(Megalobrama amblycephala)对轮叶黑藻(Hydrilla verticillata)和密刺苦草(Vallisneria denseserrulata)群落结构的影响     

王倩红  刘正文  甄伟  张秀梅  郝征  莫家勇  赵雪枫 《湖泊科学》2019,31(3):862-868

冠层型水草轮叶黑藻在富营养情况下，生长迅速，覆盖水面，对于草甸型水草密刺苦草具有明显的竞争优势.为控制轮叶黑藻的竞争优势，于湖北省鄂州市团头鲂原种场的一个池塘进行了原位围隔（10 m×10 m）实验，研究不同密度（0、0.5和1尾/m²）团头鲂牧食作用对轮叶黑藻和密刺苦草群落结构的影响，并通过无人机数字图像处理获取水草覆盖度信息.实验过程中，沉水植物总覆盖度未发生变化.研究发现，团头鲂选择性牧食使得密刺苦草生物量和覆盖度显著增加.随着牧食强度的加大，团头鲂对轮叶黑藻的控制效果显著，放养密度为1尾/m²的围隔中轮叶黑藻比例降幅最明显.群落中轮叶黑藻与密刺苦草的生物量之比迅速下降，由6.14减少至0.002，覆盖度之比由4.88左右减少至约1.44.图像处理结果与实际采样情况相吻合，且通过误差矩阵得到图像分类平均精度达到90%以上，表明无人机数字图像处理在一定条件下可以作为获取沉水植物覆盖度的一种有效辅助手段.实验结束后，1尾/m²组的围隔中密刺苦草成为优势种，其植株密度、株高、株重和单株叶片数均显著增加，草甸更加密实.实验结果表明，放养1尾/m²密度的团头鲂可以有效控制轮叶黑藻并维持密刺苦草种群优势，结果为团头鲂对湖泊沉水植物群落的控制提供了参考.  相似文献   

A density-based approach for detecting network-constrained clusters in spatial point events     

Min Deng  Xuexi Yang  Jianya Gong  Yang Liu  Huimin Liu 《International journal of geographical information science》2019,33(3):466-488

Existing spatial clustering methods primarily focus on points distributed in planar space. However, occurrence locations and background processes of most human mobility events within cities are constrained by the road network space. Here we describe a density-based clustering approach for objectively detecting clusters in network-constrained point events. First, the network-constrained Delaunay triangulation is constructed to facilitate the measurement of network distances between points. Then, a combination of network kernel density estimation and potential entropy is executed to determine the optimal neighbourhood size. Furthermore, all network-constrained events are tested under a null hypothesis to statistically identify core points with significantly high densities. Finally, spatial clusters can be formed by expanding from the identified core points. Experimental comparisons performed on the origin and destination points of taxis in Beijing demonstrate that the proposed method can ascertain network-constrained clusters precisely and significantly. The resulting time-dependent patterns of clusters will be informative for taxi route selections in the future.  相似文献   

Estimation of crowd density from UAVs images based on corner detection procedures and clustering analysis     

Ali Almagbile 《地球空间信息科学学报》2019,22(1):23-34

With rapid developments in platforms and sensors technology in terms of digital cameras and video recordings, crowd monitoring has taken a considerable attentions in many disciplines such as psychology, sociology, engineering, and computer vision. This is due to the fact that, monitoring of the crowd is necessary to enhance safety and controllable movements to minimize the risk particularly in highly crowded incidents (e.g. sports). One of the platforms that have been extensively employed in crowd monitoring is unmanned aerial vehicles (UAVs), because UAVs have the capability to acquiring fast, low costs, high-resolution and real-time images over crowd areas. In addition, geo-referenced images can also be provided through integration of on-board positioning sensors (e.g. GPS/IMU) with vision sensors (digital cameras and laser scanner). In this paper, a new testing procedure based on feature from accelerated segment test (FAST) algorithms is introduced to detect the crowd features from UAV images taken from different camera orientations and positions. The proposed test started with converting a circle of 16 pixels surrounding the center pixel into a vector and sorting it in ascending/descending order. A single pixel which takes the ranking number 9 (for FAST-9) or 12 (for FAST-12) was then compared with the center pixel. Accuracy assessment in terms of completeness and correctness was used to assess the performance of the new testing procedure before and after filtering the crowd features. The results show that the proposed algorithms are able to extract crowd features from different UAV images. Overall, the values of Completeness range from 55 to 70 % whereas the range of correctness values was 91 to 94 %.  相似文献   

Simulation of landscape spatial layout evolution in rural-urban fringe areas: a case study of Ganjingzi District   总被引：2，自引：0，他引：2  

Jun Yang  Andong Guo  Yonghua Li  Yuqing Zhang  Xueming Li 《地理信息系统科学与遥感》2019,56(3):388-405

In recent years, the rapid expansion of urban spaces has accelerated the mutual evolution of landscape types. Analyzing and simulating spatio-temporal dynamic features of urban landscape can help to reveal its driving mechanisms and facilitate reasonable planning of urban land resources. The purpose of this study was to design a hybrid cellular automata model to simulate dynamic change in urban landscapes. The model consists of four parts: a geospatial partition, a Markov chain (MC), a multi-layer perceptron artificial neural network (MLP-ANN), and cellular automata (CA). This study employed multivariate land use data for the period 2000–2015 to conduct spatial clustering for the Ganjingzi District and to simulate landscape status evolution via a divisional composite cellular automaton model. During the period of 2000–2015, construction land and forest land areas in Ganjingzi District increased by 19.43% and 15.19%, respectively, whereas farmland, garden lands, and other land areas decreased by 43.42%, 52.14%, and 75.97%, respectively. Land use conversion potentials in different sub-regions show different characteristics in space. The overall land-change prediction accuracy for the subarea-composite model is 3% higher than that of the non-partitioned model, and misses are reduced by 3.1%. Therefore, by integrating geospatial zoning and the MLP-ANN hybrid method, the land type conversion rules of different zonings can be obtained, allowing for more effective simulations of future urban land use change. The hybrid cellular automata model developed here will provide a reference for urban planning and policy formulation.  相似文献   

A geospatial study of the drought impact on surface water reservoirs: study cases from Texas,USA     

Zachary Asbury 《地理信息系统科学与遥感》2019,56(6):894-910

Satellite images have been used historically to measure and monitor fluctuations in the surface water reservoirs. This study integrates remote sensing and Geographic Information System (GIS) technologies to investigate the impact of drought on 10 selected surface water reservoirs in San Angelo and Dallas, Texas. Oscillations in summer and winter months throughout the 2005–2016 period were assessed using multispectral images from Landsat-5, ?7, and ?8, and changes in the reservoirs were characterized and correlated against local climate data of each reservoir. For quantitative comparisons of the time-series measurements, a robust density slicing approach was employed to classify the range of values of the raster cells in the near-infrared band of Landsat images for each lake into three desired classes (deep water, shallow water, and dry area) based on the natural breaks inherent in the dataset. Statistical analysis shows that the overall accuracy of the classification is about 94%, which demonstrates the efficiency of the density slicer to accurately estimate surface water area changes from an individual Landsat band. Shrinkage in the surface water area over the study period reveals the concrete impact that the drought along with other factors have on the 10 selected lakes. The San Angelo lakes located in west central Texas experienced a nearly consistent pattern of change during most of the study period; whereas the Dallas lakes in northeast Texas followed the oscillating pattern of drought and correlated closely to the local conditions. Shockingly, the extreme drought caused complete vanishing of several lakes, and consequently Texas had to remove them from its recreational plans. Our new findings can certainly help with the water resource management in Texas and our study approach can be adapted for monitoring lake oscillations in other areas across the world. This geospatial study demonstrates the societal benefits from incorporating remote sensing and GIS in investigating geo-environmental problems associated with severe climate changes.  相似文献   

A natural language processing and geospatial clustering framework for harvesting local place names from geotagged housing advertisements     

Yingjie Hu  Huina Mao  Grant McKenzie 《International journal of geographical information science》2019,33(4):714-738

Local place names are frequently used by residents living in a geographic region. Such place names may not be recorded in existing gazetteers, due to their vernacular nature, relative insignificance to a gazetteer covering a large area (e.g. the entire world), recent establishment (e.g. the name of a newly-opened shopping center) or other reasons. While not always recorded, local place names play important roles in many applications, from supporting public participation in urban planning to locating victims in disaster response. In this paper, we propose a computational framework for harvesting local place names from geotagged housing advertisements. We make use of those advertisements posted on local-oriented websites, such as Craigslist, where local place names are often mentioned. The proposed framework consists of two stages: natural language processing (NLP) and geospatial clustering. The NLP stage examines the textual content of housing advertisements and extracts place name candidates. The geospatial stage focuses on the coordinates associated with the extracted place name candidates and performs multiscale geospatial clustering to filter out the non-place names. We evaluate our framework by comparing its performance with those of six baselines. We also compare our result with four existing gazetteers to demonstrate the not-yet-recorded local place names discovered by our framework.  相似文献   

不同初始扰动对电离层扩展F影响的数值模拟          下载免费PDF全文

高泽  方涵先  汪四成  杨升高 《地球物理学报》2017,60(2):470-479

重力波、中性风场、电场是激发电离层扩展F的主要影响因子,本文基于中低纬电离层扩展F发展的物理模型,通过电场强度、背景风场对扩展F影响作用的分析和经验对比,首先验证了模型的有效性,后借助该模型数值模拟了给定背景环境下三种尺度初始电子密度扰动条件下扩展F的发展情况,同时研究了利用化学物质释放实现一定尺度扰动,进而激发扩展F的过程.结果表明,较强的背景电场、东向风场有利于扩展F的形成和抬升,与经验结论相吻合;电离层从被作用初始扰动到激发扩展F的过程中存在拐点效应,拐点之后扩展F被激发形成并且抬升迅速,同时短波长扰动相对于长波长扰动更有利于扩展F的激发和发展;化学物质H_2O释放通过耗散电子密度,形成了一定尺度扰动并诱发了扩展F的形成,该方法可作为一种人工激发扩展F的探索手段.  相似文献