Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Characterizing physical habitat preferences and thermal refuge occupancy of brook trout (Salvelinus fontinalis) and Atlantic salmon (Salmo salar) at high river temperatures

Anthropogenic influences, including climate change, are increasing river temperatures in northern and temperate regions and threatening the thermal habitats of native salmonids. When river temperatures exceed the tolerance levels of brook trout and Atlantic salmon, individuals exhibit behavioural thermoregulation by seeking out cold‐water refugia – often created by tributaries and groundwater discharge. Thermal infrared (TIR) imagery was used to map cold‐water anomalies along a 53 km reach of the Cains River, New Brunswick. Trout and salmon parr did not use all identified thermal anomalies as refugia during higher river temperature periods (>21°C). Most small‐bodied trout (8–30 cm) were observed in 80% of the thermal anomalies sampled. Large‐bodied trout (>35 cm) required a more specific set of physical habitat conditions for suitable refugia, that is, 100% of observed large trout used 30% of the anomalies sampled and required water depths >65 cm within or adjacent to the anomaly. Densities of trout were significantly higher within anomalies compared with areas of ambient river temperature. Salmon parr were less aligned with thermal anomalies at the observed temperatures, that is, 59% were found in 65% of the sampled anomalies; and densities were not significantly different within/ outside anomalies. Salmon parr appeared to aggregate at 27°C, and after several events over 27°C variability in aggregation behaviour was observed – some fish aggregated at 25°C, others did not. We stipulate this is due to variances of thermal fatigue. Habitat suitability curves were developed for velocity, temperature, depth, substrate, and deep water availability to characterize conditions preferred by fish during high‐temperature events. These findings are useful for managers as our climate warms, and can potentially be used as a tool to help conserve and enhance thermal refugia for brook trout and Atlantic salmon in similar systems.     

无人机影像目标检测技术研究进展

无人机影像目标检测技术是无人机影像智能化分析中的关键技术，开展无人机影像目标检测技术的研究有着广阔的应用前景和价值。介绍了无人机影像中目标检测技术的发展历程，简述了无人机影像目标检测技术在森林防火、农业信息采集、电力线路检测、路桥损害检测以及军事侦察等5种特定领域的应用情况，总结归纳了目标检测性能评价时常用的数据集和标准，并对未来无人机影像目标检测技术的发展态势进行了展望。     

谈环境雕塑在城市建设中的意义

介绍了雕塑设计的要求和内容，分析了环境雕塑的发展演变过程以及具有的特征，探讨了环境雕塑在城市建设中具有的作用，表明了环境雕塑在城市空间环境景观设计中具有重要的意义。     

Evaluation of image-based modeling and laser scanning accuracy for emerging automated performance monitoring techniques

Accurate and rapid assessment of the as-built status on any construction site provides the opportunity to understand the current performance of a project easily and quickly. Rapid project assessment further identifies discrepancies between the as-built and as-planned progress, and facilitates decision making on the necessary remedial actions. Currently, manual visual observations and surveying are the most dominant data capturing techniques but they are time-consuming, error-prone, and infrequent, making quick and reliable decision-making difficult. Therefore, research on new approaches that allow automatic recognition of as-built performance and visualization of construction progress is essential. This paper presents and compares two methods for obtaining point cloud models for detection and visualization of as-built status for construction projects: (1) A new method of automated image-based reconstruction and modeling of the as-built project status using unordered daily construction photo collections through analysis of Structure from Motion (SfM); (2) 3D laser scanning and analysis of the as-built dense point cloud models. These approaches provide robust means for recognition of progress, productivity, and quality on a construction site. In this paper, an overview of the newly developed automated image-based reconstruction approach and exclusive features which distinct it from other image-based or conventional photogrammetric techniques is presented. Subsequently the terrestrial laser scanning approach carried out for reconstruction and comparison of as-built scenes is presented. Finally the accuracy and usability of both of these techniques for metric reconstruction, automated production of point cloud models, 3D CAD shape modeling, and as-built visualizations is evaluated and compared on eight different case studies. It is shown that for precise defect detection or alignment tasks, image-based point cloud models may not be as accurate and dense as laser scanners' point cloud models. Nonetheless image-based point cloud models provide an opportunity to extract as-built semantic information (i.e., progress, productivity, quality and safety) through the content of the images, are easy to use, and do not need add burden on the project management teams by requiring expertise for data collection or analysis. Finally image-based reconstruction automatically provides photo alignment with point cloud models and enables image-based renderings which can remarkably impact automated performance monitoring and as-built visualizations.     

高分辨率卫星遥感影像在城市和工程中的应用潜力分析

本文结合最近完成的一个试验研究项目 ,对 1m分辨率IKONOS影像的几何精度、分辨率及影像质量进行初步评价 ,并分析它在城市和工程中应用的可能性和潜力。     

浅水三角洲分流河道沉积模式分类

通过浅水三角洲现代沉积考察分析,结合探地雷达(GPR)资料,对浅水三角洲分类方案和对应的沉积模式进行探讨。结果表明:根据分流河道弯曲指数和分叉参数,将浅水三角洲分为分叉平直河三角洲、分叉曲流河三角洲、分汇曲流河三角洲和分汇辫状河三角洲4种类型,并建立了各类型的沉积模式; 浅水三角洲沉积模式的控制因素是分流河道下蚀作用和侧蚀作用的强度。将该沉积模式应用于渤海南部海域BZ25-1油田新近系明化镇组下段砂体内部构型的研究认为:明化镇组下段4油层组2小层(NmⅣ₂)时期是低位体系域早期,发育分汇曲流河三角洲,河道间为侧积隔夹层; 明化镇组下段4油层组1小层(NmⅣ₁)时期湖平面上升,发育分汇辫状河三角洲,河道间为垂积隔夹层。这为下一步的开发方案设计提供了指导。     

Rapid and robust slope failure appraisal using aerial photogrammetry and 3D slope stability models

Slope failures are an inevitable aspect of economic pit slope designs in the mining industry. Large open pit guidelines and industry standards accept up to 30% of benches in open pits to collapse provided that they are controlled and that no personnel are at risk. Rigorous ground control measures including real time monitoring systems at TARP(trigger-action-response-plan) protocols are widely utilized to prevent personnel from being exposed to slope failure risks. Technology and computing capability are rapidly evolving. Aerial photogrammetry techniques using UAV(unmanned aerial vehicle) enable geotechnical engineers and engineering geologists to work faster and more safely by removing themselves from potential line-of-fire near unstable slopes. Slope stability modelling software using limit equilibrium(LE) and finite element(FE) methods in three dimensions(3D) is also becoming more accessible, user-friendly and faster to operate. These key components enable geotechnical engineers to undertake site investigations,develop geotechnical models and assess slope stability faster and in more detail with less exposure to fall of ground hazards in the field. This paper describes the rapid and robust process utilized at BHP Limited for appraising a slope failure at an iron ore mine site in the Pilbara region of Western Australia using a combination of UAV photogrammetry and 3D slope stability models in less than a shift(i.e. less than 12 h).