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

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 %.     

A literature synthesis of LiDAR applications in transportation: feature extraction and geometric assessments of highways

Interest in using Light Detection and Ranging (LiDAR) technology in Transportation Engineering has grown over the past decade. The high accuracy of LiDAR datasets and the efficiency by which they can be collected has led many transportation agencies to consider mobile LiDAR as an alternative to conventional tools when surveying roadway infrastructure. Nonetheless, extracting semantic information from LiDAR datasets can be extremely challenging. Although extracting roadway features from LiDAR has been considered in previous research, the extraction of some features has received more attention than others. In fact, for some roadway design elements, attempts to extract those elements from LiDAR have been extremely scarce. To document the research that has been done in this area, this paper conducts a thorough review of existing studies while also highlighting areas where more research is required. Unlike previous research, this paper includes a thorough review of the previous attempts at data extraction from LiDAR while summarizing the detailed steps of the extraction procedure proposed in each study. Moreover, the paper also identifies common tools and techniques used to extract information from LiDAR for transportation applications. The paper also highlights common limitations in existing algorithms that could be improved in future research. This paper represents a valuable resource for researchers and practitioners interested in knowing the current state of research on the applications of LiDAR in the field of Transportation Engineering while also understanding the opportunities and challenges that lie ahead.     

基于光能利用率模型的玉米遥感估产研究

农作物长势监测和产量预测对于国家制定相关粮食政策、农业发展等都具有重要的意义,如何获得高效、宏观、精确的估产方法一直是学者关注的重点问题。以吉林省德惠市的玉米作为研究对象,利用光能利用率模型对玉米进行产量估算的研究,并且使用空间数据插值方法中的反距离权重法获得了每月平均温度数据的格网数据。通过玉米的净初级生产力NPP的累计值以及玉米的收获指数来获得最终的玉米产量值,利用验证点实测产量值与估算值的相关性和相对误差进行精度验证,相关系数R^2为0.649 9,平均相对误差值为1.676%,证明基于光能利用率模型的玉米估产在研究区具有一定的可行性。     

遥感监测下的渝东南小城镇镇区拓展特征探究

DUAN Songjiang     

沈阳市建成区扩展动态监测

以辽宁省沈阳市为研究对象,以该地区1995年、2000年、2005年以及2016年不同时相的遥感影像为信息源。首先,利用ENVI影像处理软件进行数据预处理;然后,对沈阳地区土地类型进行MLC监督分类并评定分类精度;最后,采用分类后对比的方法并通过Arc GIS软件对沈阳建成区扩展情况进行研究。     

基于Landsat遥感数据武汉地区植被覆盖度动态变化监测分析

旨在研究受人类经济活动影响的植被资源及其动态变化趋势的程度,采用基于归一化植被指数的像素二分模型,利用2002—2010年(武汉市每年8月)的卫星遥感数据,对武汉地区6年间的植被覆盖变化进行监测分析。结果表明,植被覆盖度变化与武汉GDP增长率有着紧密联系:2002—2007年,武汉经济较缓慢上升,植被覆盖度基本维持在55%左右;而2007—2008年武汉GDP总值增长率高达26.06%,但随之而来的是植被覆盖度由高峰期的61.68%下降到49.18%,是历年来的最低水准; 2008—2010年经济发展放缓,植被指数有小幅度回升。人类经济活动是影响植被资源的重要因素。     

湿地资源调查更新若干问题探讨

对古浪县第二次全国湿地资源调查的技术、结果进行了系统分析,探索了研究区内湿地资源调查更新的方法,通过"天空地"协同和"互联网+"的调查更新技术全面更新研究区内湿地资源调查数据库,以全面掌握湿地资源状况。研究结果:1)古浪县第二次湿地资源调查范围内的非湿地类型面积达4 615.35 hm2,占全县第二次湿地调查总面积的59.31%。2)变更后县域内湿地资源总面积4 131.54 hm2,以河流水面、内陆滩涂、水库水面、沟渠为主要用地类型,较第二次调查湿地面积净减少3 650.25 hm2。3)"天空地"协同遥感监测技术为湿地资源变更监测提供高精度多源数据,保证了调查、监测的精度和准确性。     

基于压缩感知法对法拉第色散函数的重构

观测到的偏振量与法拉第色散函数之间是傅里叶变换对,而法拉第色散函数反映了辐射区域和辐射传播途径的磁场结构。如何通过这一关系精确重构出法拉第色散函数对于研究银河系及河外星系磁场具有重要的作用。目前已提出了基于压缩感知的法拉第色散函数重构方法,模拟结果要优于传统方法,然而是否具有实用性仍然未知。主要探究该方法应用于实际观测频率范围时是否依然可行,并进行了大样本统计学实验。结果表明:重构结果受多种因素的影响,具有很大的随机性,对重构结果在峰值附近再次进行最小二乘拟合后,重构的法拉第深度更接近真实值。     

Assessing the performance of a large-scale irrigation system by estimations of actual evapotranspiration obtained by Landsat satellite images resampled with cubic convolution

Remote sensing techniques allow monitoring the Earth surface and acquiring worthwhile information that can be used efficiently in agro-hydrological systems. Satellite images associated to computational models represent reliable resources to estimate actual evapotranspiration fluxes, ET_a, based on surface energy balance. The knowledge of ET_a and its spatial distribution is crucial for a broad range of applications at different scales, from fields to large irrigation districts. In single plots and/or in irrigation districts, linking water volumes delivered to the plots with the estimations of remote sensed ET_a can have a great potential to develop new cost-effective indicators of irrigation performance, as well as to increase water use efficiency. With the aim to assess the irrigation system performance and the opportunities to save irrigation water resources at the “SAT Llano Verde” district in Albacete, Castilla-La Mancha (Spain), the Surface Energy Balance Algorithm for Land (SEBAL) was applied on cloud-free Landsat 5 Thematic Mapper (TM) images, processed by cubic convolution resampling method, for three irrigation seasons (May to September 2006, 2007 and 2008). The model allowed quantifying instantaneous, daily, monthly and seasonal ET_a over the irrigation district. The comparison between monthly irrigation volumes distributed by each hydrant and the corresponding spatially averaged ET_a, obtained by assuming an overall efficiency of irrigation network equal to 85%, allowed the assessment of the irrigation system performance for the area served by each hydrant, as well as for the whole irrigation district. It was observed that in all the investigated years, irrigation volumes applied monthly by farmers resulted generally higher than the corresponding evapotranspiration fluxes retrieved by SEBAL, with the exception of May, in which abundant rainfall occurred. When considering the entire irrigation seasons, it was demonstrated that a considerable amount of water could have been saved in the district, respectively equal to 26.2, 28.0 and 16.4% of the total water consumption evaluated in the three years.     

利用Sentinel-2A多光谱成像仪与Landsat8陆地成像仪影像进行普陀山岛植被分类效果比较

卫星遥感技术可用于海岛资源调查。Sentinel-2A与Landsat 8两颗卫星都可免费提供空间分辨率较高的多光谱遥感影像,在海岛调查中的应用潜力较大。本文以浙江舟山普陀山岛为例开展了针对这两种影像在海岛植被分类中的应用效果的研究,分别利用Sentinel-2A多光谱成像仪（MSI）和Landsat 8陆地成像仪（OLI）影像基于最大似然法分类获得了该岛阔叶林、针阔混交林、针叶林、灌丛、草丛等植被及其他地物的分布情况,并进行了精度检验,结果表明MSI的总体分类精度略高于OLI。