Hasil untuk "Applied optics. Photonics"

Tao Hu, Fengjun Wei, Jintao Wang et al.

Mastering the movement laws of hard overlying rock layers is the foundation of the development of coal mining technology and plays an important role in improving coal mine safety production. Therefore, an indoor similar simulation experiment was conducted based on an actual coal mining face to test the strain variations of the pre-embedded optical fibers in the model using distributed fiber optic sensing. Finally, the fiber optic strain distribution curve was used to characterize the movement form and state of the overlying rock layer and fractured rock blocks. The experimental results showed the following. (1) The strain distribution of horizontally laid optical fibers is characterized by an upward trapezoidal convex platform, reflecting the evolution law of various horizontal movement forms of overlying rock layers: voussoir beam → cantilever beam → reverse cantilever beam → voussoir beam. The strain curve of vertically laid optical fibers is characterized by two levels of right-handed trapezoidal protrusions above and below, representing the motion state of the upper voussoir beam–lower cantilever beam structure of the overburden. (2) In addition, as excavation progresses, the range and height of the failure deformation of the overlying rock layers develop in a stepped shape. (3) In the end, the final vertical development heights of the cantilever beam structure and the voussoir beam structure in the overburden were 90.27 m and 24.99 m, respectively. The experimental results are highly consistent with the UDEC numerical simulation and mandatory calculation formulas, thus verifying the feasibility of the experiment. These research results provide theoretical and experimental support for safe coal mining in practical working faces.

M. Jin, M. Handrich, B. Bienzeisler

Accurate detection of on-street parking occupancy is crucial for urban traffic management. We present DroneVision, a low code solution that enables municipalities to analyze parking occupancy using drone-acquired aerial imagery and vision language models (VLM). This approach allows municipal authorities to upload commercial drone imagery and parking space information, automatically processes these inputs, and generates comprehensive analysis reports. We evaluated two state-of-the-art open-source VLMs against traditional pretrained convolutional neural networks (CNNs) for drone imagery analysis. Results demonstrate the effectiveness of our VLM-based approach, offering a scalable solution that can be integrated into smart city infrastructures while making advanced AI technology accessible to municipal authorities through a low-code interface.

Hongbing Zhou, Rumao Tao, Xi Feng et al.

Machine learning has already shown promising potential in tiled-aperture coherent beam combining (CBC) to achieve versatile advanced applications. By sampling the spatially separated laser array before the combiner and detuning the optical path delays, deep learning techniques are incorporated into filled-aperture CBC to achieve single-step phase control. The neural network is trained with far-field diffractive patterns at the defocus plane to establish one-to-one phase-intensity mapping, and the phase prediction accuracy is significantly enhanced thanks to the strategies of sin-cos loss function and two-layer output of the phase vector that are adopted to resolve the phase discontinuity issue. The results indicate that the trained network can predict phases with improved accuracy, and phase-locking of nine-channel filled-aperture CBC has been numerically demonstrated in a single step with a residual phase of λ/70. To the best of our knowledge, this is the first time that machine learning has been made feasible in filled-aperture CBC laser systems.

Runxin Zhang, Jian Xiong, Menghan Li et al.

Visible light communications (VLC) has experienced rapid development in recent years as a strong competitor for next-generation wireless applications due to its wider bandwidth, higher security, and better electromagnetic immunity compared with conventional radio frequency (RF) microwaves. Although state-of- the-art VLC systems can achieve Gbps data rates by employing equalization schemes, designing a general low-complexity VLC transmitter with hundreds of MHz 3-dB bandwidth is still challenging due to the narrow modulation bandwidth nature of light emitting diodes (LEDs). In this paper, we first present a second-order equivalent circuit model for the LED, based on which we propose a general second-order equalizer (GSE) with low complexities, consisting of less than 5 passive capacitors, inductors, and resistors. We show that the GSE can enlarge the LED transmitter&#x0027;s bandwidth to a few hundred MHz. To validate our GSE, we build a broadband VLC transmitter using commercial-off-the-shelf (COTS) red, green and blue (RGB) LEDs, whose bandwidth is 14 MHz, by summing up three colours. Experimental results show that our proposed GSE can extend the transmitter&#x0027;s 3-dB bandwidth from 14 MHz to 1.5 GHz. Furthermore, we demonstrate that a VLC system utilizing the proposed GSE transmitter can achieve 1.15 Gbps data rates at a distance of 250 cm with a bit error ratios (BERs) below the forward error correction (FEC) limit <inline-formula><tex-math notation="LaTeX">$3.8 \times 10^{-3}$</tex-math></inline-formula>.

Riccardo Antonello, Roberto Oboe, Daniele D’Elia et al.

The angular motion of quasi-static micromirrors used for raster scanning projection applications is typically affected by undesired oscillations related to high-frequency resonant modes triggered by the sawtooth-like driving signal. This paper proposes a novel closed-loop tracking controller for improving the linearity of the trace motion, and hence the image brightness. It includes a feedforward action to achieve the required tracking performance under nominal conditions, and a feedback control for robustness against disturbances and other nonidealities. Notch filtering prevents resonance-induced ringing. The simplicity of the architecture enables an easy implementation on FPGA or ASIC. Experimental tests carried out on two different micromirrors with Lead-Zirconate-Titanate (PZT) piezoelectric actuation and piezoresistive sensing demonstrate an average linearity of [Formula: see text] and reproducibility of [Formula: see text] for sawtooth reference trajectories with up to [Formula: see text] amplitude and 120 Hz frequency, thus meeting the performance requirements mandated by the standards for high-resolutions projection applications.

Y. Wang, R. Sun

High accuracy positioning is crucial for various applications that require accurate and reliable positioning data, such as autonomous vehicles (AVs), agriculture, and intelligent transportation. Global Positioning System (GPS) is widely used in integration with Inertial Measurement Unit (IMU) and Visual Odometry (VO) to implement an accurate and robust navigation system. However, the performance of the integrated system can be severely degraded in urban environments due to non-line-of-sight (NLOS) reception and multipath interference. To overcome these challenges, a novel Fault Detection and Exclusion (FDE) algorithm aided with IMU and VO measurements is proposed to identify and isolate the contaminated satellite signals. The algorithm utilizes instantaneous measurements from IMU and VO to predict the current vehicle position, enabling the estimation of pseudorange errors in GPS measurements. A FDE algorithm based on Hierarchical clustering is then developed to identify GPS signals with significant errors based on the predicted pseudorange error. An experimental field test was conducted using a land vehicle to evaluate the effectiveness of the proposed algorithm. The results show that the GPS/IMU/VO integrated navigation system with the proposed FDE algorithm has significantly improved the positioning accuracy and reliability compared to the traditional system. The proposed algorithm achieves a positioning accuracy with a 3D Root Mean Square Error (RMSE) of 11.18m in urban environment, making an improvement of 68.2% over the traditional GPS/IMU/VO integrated navigation system.

Ryuga Yajima, Kei Kamada, Yui Takizawa et al.

In this study, it was demonstrated that Zn3Ta2O8 crystals containing zinc oxide with high vapor pressure can grow in melt by the shielded arc melting method. The radiation response characteristics of the crystals were evaluated. The grown crystals showed an emission peak at 410 nm, ascribed to self-trapped excitation, Ta4+–O2−. The full width at half maximum of the X-ray rocking curve was 655 arcsec. The light output under 662 keV gamma-ray irradiation of Zn3Ta2O8 was approximately 4,700 photons/MeV. The decay time was 17.3 μs? Thus, the shielded arc melting method was shown to be a quick and economic growth technique for the survey of new scintillator materials containing high-vapor-pressure starting components.

E. Colucci, A. M. Lingua, M. Kokla et al.

The main topic of this work focuses on the semantic, historical and spatial documentation of Minor Historical Centres (MHC) with a focus on (semi-abandoned alpine) hamlets. The key point is the possibility to standardise spatial information in the domain of MHC and their related cultural, architectural, built and landscape heritage. This work analyses the notions of historical centre and ancient area, which took different meanings and evolved over the centuries. MHC are historical part of cities, villages and hamlets (urban, rural, minor or abandoned) with cultural, social and economic values. Thus, MHC need to be preserved, documented and safeguarded. The spatial and semantic documentation is a fundamental tool for increasing their knowledge. In these places, many actors and stakeholders are involved in different activities, and for this reason, they need to share common knowledge and use a unique language. In this regard, spatial ontology is of relevant interest and usability. Ontologies are conceptual structures that formalise specific knowledge and create a unique and standard thesaurus that ensures semantic interoperability. This paper is part of a PhD research targeted at developing an ontology containing helpful information to manage, share and collect data on MHC due to the lack of an interoperable structure to formalise such knowledge. The main aim is to populate and enrich the already developed ontological structure with data of a mountain semi-abandoned hamlet: Pomieri. The methodological workflow is validated, enriching and populating the ontology, adding classes and instances with information and unstructured data of a real data case study.

Jui-Hung Weng, Wei-Chi Lo, Jiaxing Wang et al.

Directly modulated 850-nm multimode vertical-cavity surface-emitting lasers (MM-VCSELs) with different oxide apertures and transmission microstrip lengths are compared on the transmission performance of the non-return-to-zero on-off keying (NRZ-OOK) and four-level pulse amplitude modulation (PAM-4) data formats. In this work, intrinsic and extrinsic responses of the MM-VCSEL are also discussed concurrently. By tuning the length of the transmission microstrip in VCSEL, the low reflection coefficient and the enhanced 3-dB modulation bandwidth are achieved. The inductance of the transmission microstrip in the series connection with the capacitance in the active region is optimized to reduce the power loss induced by imaginary impedance. The different oxide aperture sizes for MM-VCSEL are also studied to control the capacitance and photon density. More importantly, the 3-dB modulation bandwidth, impedance matching, slope efficiency, relative intensity noise (RIN), and mode partition noise (MPN) for the MM-VCSEL with various designs are discussed to determine the best device with the high-speed transmission capability. The optimal MM-VCSEL with a diameter of 7 µm oxide aperture and a length of 25 µm transmission microstrip successfully demonstrates 50-Gbit/s OOK and 84-Gbit/s PAM4 after using the pre-emphasis technique for future data-center applications.

E. Bontempo, E. Bontempo, M. C. Demirel et al.

The mapping of vegetation and Land Cover (LC) is important for research and for public policy planning but, in Brazil, although diverse maps exist there are few studies comparing them. The semiarid region of the Caatinga, in northeastern Brazil is an area long neglected by scientific research and its vegetation is diverse and relatively rich despite years of human occupation and very little preservation effort. In this study we make a comparison between the main maps made for the Caatinga from four different sources: IBGE (Brazilian Institute of Geography and Statistics), TCN (Third National Communication), ProBio (Project for Conservation and Sustainable Use of Biological Biodiversity) and MapBiomas. We also test these maps against well-known Land Cover maps from ESA and NASA: ESA’s GlobCover and Climate Change Initiative (CCI) Land Cover, and NASA’s MODIS MCD12Q1. This was done on a sample area where many of the Caatinga’s vegetation physiognomies can be found, using well-established Difference metrics and the new SPAtial EFficiency (SPAEF) algorithm as they present complementary viewpoints to test the correspondence of mapped classes as well as that of their spatial patterns. Our results show considerable disagreement between the maps tested and their class semantics, with IBGE’s and ProBio’s being the most similar among all national maps and MapBiomas’ the most closely related to global LC maps. The nature of the observed disagreement between these maps shows they diverge not only in the application of their classification systems, but also in their mapped spatial pattern, signaling the need for a better classification system and a better map of vegetation and land cover for the region.

N. Börlin, A. Murtiyoso, P. Grussenmeyer

<p>The Damped Bundle Adjustment Toolbox (DBAT) is a free, open-source, toolbox for bundle adjustment. The purpose of DBAT is to provide an independent, open-source toolkit for statistically rigorous bundle adjustment computations. The capabilities include bundle adjustment, network analysis, point filtering, forward intersection, spatial intersection, plotting functions, and computations of quality indicators such as posterior covariance estimates and parameter correlations. DBAT is written in the high-level Matlab language and includes several processing example files. The input formats have so far been restricted to PhotoModeler export files and Photoscan (Metashape) native files. Fine-tuning of the processing has so far required knowledge of the Matlab language.</p><p>This paper describes the development of a scripting language based on the XML (eXtensible Markup Language) language that allow the user a fine-grained control over what operations are applied to the input data, while keeping the needed programming skills at a minimum. Furthermore, the scripting language allows a wide range of input formats. Additionally, the XML format allows simple extension of the script file format both in terms of adding new operations, file formats, or adding parameters to existing operations. Overall, the script files will in principle allow DBAT to process any kind of photogrammetric input and should extend the usability of DBAT as a scientific and teaching tool for photogrammetric computations.</p>

J. Son, P. Lim, J. Seo et al.

Nowadays, UAVs(Unmanned aerial vehicles) are being used in spatial information construction. To construct spatial information, it is important to select appropriate data. Therefore, in this paper, we analyzed the characteristics of UAV flight paths and their effects on accuracy of bundle adjustments and epipolar models. We analyzed the flight path characteristics in three aspects: body stability, linearity of path and overlap between images. Firstly, in case of the body stability, ideal body stability is defined when images are taken in vertical direction. We calculated the body stability by the photographed angle, which is a difference between the vertical direction and actual photographed direction. Secondly, in case of the linearity of path, we are calculated the residual after fitting ground coordinates of orthogonal UAV positions or image centers by a straight line. Finally, in case of the overlap between images, we selected two closest images along vertical and horizontal direction as a pair and calculated the overlap of the pair on the ground space. We performed bundle adjustments and extracted EOPs(Exterior Orientation Parameters). Using the EOPs, we constructed an orthoimage, a DSM(Digital Surface model), and an epipolar model. By verified orthoimage and DSM, we were able to obtain accuracy of bundle adjustments. We also analyzed y-parallax of epipolar models to obtain its accuracy. Results showed that the body stability show very little affect vertical error of bundle adjustments. In case of linearity of path, there was little effect on the accuracy of bundle adjustment and epipolar models. The overlap between images affected all accuracy of bundle adjustments and epipolar model. The best accuracy was obtained when the overlap was about 70%.

J. Yu, Z. Gan, L. Zhong et al.

The objective of this paper is to investigate the use of UAV remote sensing in the monitoring and management of construction projects in riparian areas through the case study of embankment construction projects’ monitoring in the Three Gorges Reservoir area. A three-step approach is proposed to address the problem: data acquisition with UAV, data processing, and monitoring information extraction. The results of the case study demonstrate that UAV remote sensing is capable of providing fast and accurate measurements and calculations for the needs of monitoring of riparian constructions.

J. Wu, M. Liao, N. Li

With the rapid development of urban economy, convenient, safe, and efficient urban rail transit has become the preferred method for people to travel. In order to ensure the safety and sustainable development of urban rail transit, the PS-InSAR technology with millimeter deformation measurement accuracy has been widely applied to monitor the deformation of urban rail transit. In this paper, 32 scenes of COSMO-SkyMed descending images and 23 scenes of Envisat ASAR images covering the Shanghai Metro Line 6 acquired from 2008 to 2010 are used to estimate the average deformation rate along line-of-sight (LOS) direction by PS-InSAR method. The experimental results show that there are two main subsidence areas along the Shanghai Metro Line 6, which are located between Wuzhou Avenue Station to Wulian Road Station and West Gaoke Road Station to Gaoqing Road Station. Between Wuzhou Avenue Station and Wulian Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is &minus;9.92&thinsp;mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is &minus;8.53&thinsp;mm/year. From the West Gaoke Road Station to the Gaoqing Road Station, the maximum displacement rate in the vertical direction of COSMO-SkyMed images is &minus;15.53&thinsp;mm/year, and the maximum displacement rate in the vertical direction of Envisat ASAR images is &minus;17.9&thinsp;mm/year. The results show that the ground deformation rates obtained by two SAR platforms with different wavelengths, different sensors and different incident angles have good consistence with each other, and also that of spirit leveling.

B. Chen, B. Chen

Understanding the spatiotemporal change trend of global crop growth and multiple cropping system under climate change scenarios is a critical requirement for supporting the food security issue that maintains the function of human society. Many studies have predicted the effects of climate changes on crop production using a combination of filed studies and models, but there has been limited evidence relating decadal-scale climate change to global crop growth and the spatiotemporal distribution of multiple cropping system. Using long-term satellite-derived Normalized Difference Vegetation Index (NDVI) and observed climate data from 1982 to 2012, we investigated the crop growth trend, spatiotemporal pattern trend of agricultural cropping intensity, and their potential correlations with respect to the climate change drivers at a global scale. Results show that 82.97&thinsp;% of global cropland maximum NDVI witnesses an increased trend while 17.03&thinsp;% of that shows a decreased trend over the past three decades. The spatial distribution of multiple cropping system is observed to expand from lower latitude to higher latitude, and the increased cropping intensity is also witnessed globally. In terms of regional major crop zones, results show that all nine selected zones have an obvious upward trend of crop maximum NDVI (<i>p</i>&thinsp;&lt;&thinsp;0.001), and as for climatic drivers, the gradual temperature and precipitation changes have had a measurable impact on the crop growth trend.

Z. Zheng, Z. Y. Chang, Y. F. Fei

Installation Planning is constrained by both natural and social conditions, especially for spatially sparse but functionally connected facilities. Simulation is important for proper deploy in space and configuration in function of facilities to make them a cohesive and supportive system to meet users’ operation needs. Based on requirement analysis, we propose a framework to combine GIS and Agent simulation to overcome the shortness in temporal analysis and task simulation of traditional GIS. In this framework, Agent based simulation runs as a service on the server, exposes basic simulation functions, such as scenario configuration, simulation control, and simulation data retrieval to installation planners. At the same time, the simulation service is able to utilize various kinds of geoprocessing services in Agents’ process logic to make sophisticated spatial inferences and analysis. This simulation-as-a-service framework has many potential benefits, such as easy-to-use, on-demand, shared understanding, and boosted performances. At the end, we present a preliminary implement of this concept using ArcGIS javascript api 4.0 and ArcGIS for server, showing how trip planning and driving can be carried out by agents.

P. Maillard, M. F. Gomes

This article presents an original algorithm created to detect and count trees in orchards using very high resolution images. The algorithm is based on an adaptation of the “template matching” image processing approach, in which the template is based on a “geometricaloptical” model created from a series of parameters, such as illumination angles, maximum and ambient radiance, and tree size specifications. The algorithm is tested on four images from different regions of the world and different crop types. These images all have < 1 meter spatial resolution and were downloaded from the GoogleEarth application. Results show that the algorithm is very efficient at detecting and counting trees as long as their spectral and spatial characteristics are relatively constant. For walnut, mango and orange trees, the overall accuracy was clearly above 90%. However, the overall success rate for apple trees fell under 75%. It appears that the openness of the apple tree crown is most probably responsible for this poorer result. The algorithm is fully explained with a step-by-step description. At this stage, the algorithm still requires quite a bit of user interaction. The automatic determination of most of the required parameters is under development.

A. Hadavand, M. Saadatseresht, S. Homayouni

In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS), a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

M. Hirschmugl, H. Gallaun, R. Wack et al.

Forests play a key role in the European economy and environment. This role incorporates ecological functions which can be affected by the occurrence of insect infestations, forest fire, heavy snowfall or windfall events. Local or Regional Authorities (LRAs) thus require detailed information on the degradation status of their forests to be able to take appropriate measures for their forest management plans. In the EUFODOS project, state-of-the-art satellite and laser scanning technologies are used to provide forest authorities with cost-effective and comprehensive information on forest structure and damage. One of the six test sites is located in the Austrian province of Styria where regional forest authorities have expressed a strong need for detailed forest parameters in protective forest. As airborne laser-scanning data is available, it will be utilized to derive detailed forest parameters such as the upper forest border line, tree height, growth classes, forest density, vertical structure or volume. At the current project status, the results of (i) the forest border line, (ii) the segmentation of forest stands and (iii) the tree top detection are available and presented including accuracy assessment and interim results are shown for timber volume estimations. The final results show that the forest border can be mapped operationally with an overall accuracy of almost 99% from LiDAR data. For the segmentation of forest stands, a comparison of the automatically derived result with visual-manual delineation showed in general a more detailed segmentation result, but for all visual-manual segments a congruence of 87% within a 4 m buffer. Tree top detections were compared to stem numbers estimated based on angle-count samplings in a field campaign, which led to a correlation coefficient (R) of 0.79.

R. Bahmanyar, G. Rigoll, M. Datcu

The volume of Earth Observation data is increasing immensely in order of several Terabytes a day. Therefore, to explore and investigate the content of this huge amount of data, developing more sophisticated Content-Based Information Retrieval (CBIR) systems are highly demanded. These systems should be able to not only discover unknown structures behind the data, but also provide relevant results to the users' queries. Since in any retrieval system the images are processed based on a discrete set of their features (i.e., feature descriptors), study and assessment of the structure of feature space, build by different feature descriptors, is of high importance. In this paper, we introduce a clustering-based approach to study the content of image collections. In our approach, we claim that using both internal and external evaluation of clusters for different feature descriptors, helps to understand the structure of feature space. Moreover, the semantic understanding of users about the images also can be assessed. To validate the performance of our approach, we used an annotated Synthetic Aperture Radar (SAR) image collection. Quantitative results besides the visualization of feature space demonstrate the applicability of our approach.