scholarly journals Accuracy Verification of Airborne Large-Footprint Lidar based on Terrain Features

2020 ◽  
Vol 12 (5) ◽  
pp. 879
Author(s):  
Weiqi Lian ◽  
Shaoning Li ◽  
Guo Zhang ◽  
Yanan Wang ◽  
Xinyang Chen ◽  
...  
Keyword(s):  
Hunan Province ◽  
Surface Model ◽  
Lidar Data ◽  
Data Application ◽  
Novel Method ◽  
Series Of Experiments ◽  
Aircraft Trajectory ◽  
Echo Pulse ◽  
Terrain Features ◽  
Better Than

Accuracy verification of airborne large-footprint lidar data is important for proper data application but is difficult when ground-based laser detectors are not available. Therefore, we developed a novel method for lidar accuracy verification based on the broadened echo pulse caused by signal saturation over water. When an aircraft trajectory crosses both water and land, this phenomenon and the change in elevation between land and water surfaces can be used to verify the plane and elevation accuracy of the airborne large-footprint lidar data in conjunction with a digital surface model (DSM). Due to the problem of echo pulse broadening, the center-of-gravity (COG) method was proposed to optimize the processing flow. We conducted a series of experiments on terrain features (i.e., the intersection between water and land) in Xiangxi, Hunan Province, China. Verification results show that the elevation accuracy obtained in our experiments was better than 1 m and the plane accuracy was better than 5 m, which is well within the design requirements. Although this method requires specific terrain conditions for optimum applicability, the results can lead to valuable improvements in the flexibility and quality of lidar data collection.

Research of the activity and viability of spermatozoa at different concentrations and proportions of diluents after incubation

2020 ◽  
pp. 88-95
Author(s):  
Svitlana Lobchenko ◽  
Tetiana Husar ◽  
Viktor Lobchenko
Keyword(s):  
Plasma Concentration ◽  
Incubation Time ◽  
Coefficient Of Variation ◽  
Incubation Medium ◽  
Wide Range ◽  
Series Of Experiments ◽  
The Subject ◽  
Boar Spermatozoa ◽  
Native Plasma ◽  
Better Than

The results of studies of the viability of spermatozoa with different incubation time at different concentrations and using different diluents are highlighted in the article. (Un) concentrated spermatozoa were diluented: 1) with their native plasma; 2) medium 199; 3) a mixture of equal volumes of plasma and medium 199. The experiment was designed to generate experimental samples with spermatozoa concentrations prepared according to the method, namely: 0.2; 0.1; 0.05; 0.025 billion / ml. The sperm was evaluated after 2, 4, 6 and 8 hours. The perspective of such a study is significant and makes it possible to research various aspects of the subject in a wide range. In this regard, a series of experiments were conducted in this area. The data obtained are statistically processed and allow us to highlight the results that relate to each stage of the study. In particular, in this article it was found out some regularities between the viability of sperm, the type of diluent and the rate of rarefaction, as evidenced by the data presented in the tables. As a result of sperm incubation, the viability of spermatozoa remains at least the highest trend when sperm are diluted to a concentration of 0.1 billion / ml, regardless of the type of diluent used. To maintain the viability of sperm using this concentration of medium 199 is not better than its native plasma, and its mixture with an equal volume of plasma through any length of time incubation of such sperm. Most often it is at this concentration of sperm that their viability is characterized by the lowest coefficient of variation, regardless of the type of diluent used, which may indicate the greatest stability of the result under these conditions. The viability of spermatozoa with a concentration of 0.1 billion / ml is statistically significantly reduced only after 6 or even 8 hours of incubation. If the sperm are incubated for only 2 hours, regardless of the type of diluent used, the sperm concentrations tested do not affect the viability of the sperm. Key words: boar, spermatozoa, sperm plasma, concentration, incubation, medium 199, activity, viability, rarefaction.

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

scholarly journals SPPD: A Novel Reassembly Method for 3D Terracotta Warrior Fragments Based on Fracture Surface Information

2021 ◽  
Vol 10 (8) ◽  
pp. 525
Author(s):  
Wenmin Yao ◽  
Tong Chu ◽  
Wenlong Tang ◽  
Jingyu Wang ◽  
Xin Cao ◽  
...  
Keyword(s):  
Fracture Surface ◽  
Principal Component ◽  
Point Clouds ◽  
Three Dimension ◽  
Registration Method ◽  
Series Of Experiments ◽  
Coarse To Fine ◽  
Fine Registration ◽  
Common Situation ◽  
Better Than

As one of China′s most precious cultural relics, the excavation and protection of the Terracotta Warriors pose significant challenges to archaeologists. A fairly common situation in the excavation is that the Terracotta Warriors are mostly found in the form of fragments, and manual reassembly among numerous fragments is laborious and time-consuming. This work presents a fracture-surface-based reassembling method, which is composed of SiamesePointNet, principal component analysis (PCA), and deep closest point (DCP), and is named SPPD. Firstly, SiamesePointNet is proposed to determine whether a pair of point clouds of 3D Terracotta Warrior fragments can be reassembled. Then, a coarse-to-fine registration method based on PCA and DCP is proposed to register the two fragments into a reassembled one. The above two steps iterate until the termination condition is met. A series of experiments on real-world examples are conducted, and the results demonstrate that the proposed method performs better than the conventional reassembling methods. We hope this work can provide a valuable tool for the virtual restoration of three-dimension cultural heritage artifacts.

Cuckoo Search Based Decision Fusion Techniques for Natural Terrain Understanding

2014 ◽  
Vol 5 (2) ◽  
pp. 1-21 ◽  
Author(s):  
Arpita Sharma ◽  
Samiksha Goel
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Cuckoo Search ◽  
Decision Fusion ◽  
Majority Voting ◽  
Natural Terrain ◽  
Terrain Features ◽  
Level Fusion ◽  
Better Than

This paper proposes two novel nature inspired decision level fusion techniques, Cuckoo Search Decision Fusion (CSDF) and Improved Cuckoo Search Decision Fusion (ICSDF) for enhanced and refined extraction of terrain features from remote sensing data. The developed techniques derive their basis from a recently introduced bio-inspired meta-heuristic Cuckoo Search and modify it suitably to be used as a fusion technique. The algorithms are validated on remote sensing satellite images acquired by multispectral sensors namely LISS3 Sensor image of Alwar region in Rajasthan, India and LANDSAT Sensor image of Delhi region, India. Overall accuracies obtained are substantially better than those of the four individual terrain classifiers used for fusion. Results are also compared with majority voting and average weighing policy fusion strategies. A notable achievement of the proposed fusion techniques is that the two difficult to identify terrains namely barren and urban are identified with similar high accuracies as other well identified land cover types, which was not possible by single analyzers.

scholarly journals Quantitative Ultrafast Spectroscopy and Microscopy of Traditional and Soft Condensed Matter

2018 ◽  
Vol 8 (8) ◽  
pp. 1317
Author(s):  
Adam Card ◽  
Mohammad Mokim ◽  
Feruz Ganikhanov
Keyword(s):  
Condensed Matter ◽  
Potassium Titanyl Phosphate ◽  
Soft Condensed Matter ◽  
Phonon Modes ◽  
Third Order ◽  
Unit Cells ◽  
Coherent Optical Spectroscopy ◽  
Series Of Experiments ◽  
Tio6 Octahedron ◽  
Better Than

We demonstrate and analyze a series of experiments in traditional and soft condensed matter using coherent optical spectroscopy and microscopy with ultrafast time resolution. We show the capabilities of resolving both real and imaginary parts of the third-order nonlinearity in the vicinity of Raman resonances from a medium probed within microscopic volumes with an equivalent spectral resolution of better than 0.1 cm−1. We can differentiate between vibrations of various types within unit cells of crystals, as well as perform targeted probes of areas within biological tissue. Vibrations within the TiO6 octahedron and the ones for the Ti-O-P intergroup were studied in potassium titanyl phosphate crystal to reveal a multiline structure within targeted phonon modes with closely spaced vibrations having distinctly different damping rates (~0.5 ps−1 versus ~1.1 ps−1). We also detected a 1.7–2.6 ps−1 decay of C-C stretching vibrations in fat tissue and compared that with the corresponding vibration in oil.

scholarly journals A Novel Method for Feature Extraction and Classification for an Aerial Image and LiDAR Data with Genetic Algorithm

2012 ◽  
pp. 264-270
Author(s):  
Manjunath B. E ◽  
D. G. Anand ◽  
Mahant. G. Kattimani
Keyword(s):  
Feature Extraction ◽  
Light Detection And Ranging ◽  
Aerial Image ◽  
Lidar Data ◽  
Light Detection ◽  
Aerial Photos ◽  
The Earth ◽  
Digital Elevation ◽  
Land Surveying ◽  
Novel Method

Airborne Light Detection and Ranging (LiDAR) provides accurate height information for objects on the earth, which makes LiDAR become more and more popular in terrain and land surveying. In particular, LiDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. Aerial photos with LiDAR data were processed with genetic algorithms not only for feature extraction but also for orthographical image. DSM provided by LiDAR reduced the amount of GCPs needed for the regular processing, thus the reason both efficiency and accuracy are highly improved. LiDAR is an acronym for Light Detection and Ranging, which is typically defined as an integration of three technologies into a single system, which is capable of acquiring a data to produce accurate Digital Elevation Models.

scholarly journals CHANGE DETECTION AND DEFORMATION ANALYSIS BASED ON MOBILE LASER SCANNING DATA OF URBAN AREAS

2020 ◽  
Vol V-2-2020 ◽  
pp. 703-710
Author(s):  
J. Gehrung ◽  
M. Hebel ◽  
M. Arens ◽  
U. Stilla
Keyword(s):  
Change Detection ◽  
Urban Areas ◽  
Laser Scanning ◽  
State Of The Art ◽  
Point Clouds ◽  
Deformation Analysis ◽  
Lidar Data ◽  
Efficient Manner ◽  
Incomplete Observations ◽  
Novel Method

Abstract. Change detection is an important tool for processing multiple epochs of mobile LiDAR data in an efficient manner, since it allows to cope with an otherwise time-consuming operation by focusing on regions of interest. State-of-the-art approaches usually either do not handle the case of incomplete observations or are computationally expensive. We present a novel method based on a combination of point clouds and voxels that is able to handle said case, thereby being computationally less expensive than comparable approaches. Furthermore, our method is able to identify special classes of changes such as partially moved, fully moved and deformed objects in addition to the appeared and disappeared objects recognized by conventional approaches. The performance of our method is evaluated using the publicly available TUM City Campus datasets, showing an overall accuracy of 88 %.

scholarly journals AN OBJECT-BASED WORKFLOW DEVELOPED TO EXTRACT AQUACULTURE PONDS FROM AIRBORNE LIDAR DATA: A TEST CASE IN CENTRAL VISAYAS, PHILIPPINES

2016 ◽  
Vol XLI-B8 ◽  
pp. 1147-1152 ◽  
Author(s):  
R. A. Loberternos ◽  
W. P. Porpetcho ◽  
J. C. A. Graciosa ◽  
R. R. Violanda ◽  
A. G. Diola ◽  
...  
Keyword(s):  
Detection Algorithm ◽  
The Philippines ◽  
Airborne Lidar ◽  
Surface Model ◽  
Lidar Data ◽  
Flat Surfaces ◽  
Water Classification ◽  
Object Based ◽  
Aquaculture Ponds ◽  
Model Layer

Traditional remote sensing approach for mapping aquaculture ponds typically involves the use of aerial photography and high resolution images. The current study demonstrates the use of object-based image processing and analyses of LiDAR-data-generated derivative images with 1-meter resolution, namely: CHM (canopy height model) layer, DSM (digital surface model) layer, DTM (digital terrain model) layer, Hillshade layer, Intensity layer, NumRet (number of returns) layer, and Slope layer. A Canny edge detection algorithm was also performed on the Hillshade layer in order to create a new image (Canny layer) with more defined edges. These derivative images were then used as input layers to perform a multi-resolution segmentation algorithm best fit to delineate the aquaculture ponds. In order to extract the aquaculture pond feature, three major classes were identified for classification, including land, vegetation and water. Classification was first performed by using assign class algorithm to classify Flat Surfaces to segments with mean Slope values of 10 or lower. Out of these Flat Surfaces, assign class algorithm was then performed to determine Water feature by using a threshold value of 63.5. The segments identified as Water were then merged together to form larger bodies of water which comprises the aquaculture ponds. The present study shows that LiDAR data coupled with object-based classification can be an effective approach for mapping coastal aquaculture ponds. The workflow currently presented can be used as a model to map other areas in the Philippines where aquaculture ponds exist.

scholarly journals An approximate method for 1-D simulation of pollution transport in streams with dead zones

2018 ◽  
Vol 66 (4) ◽  
pp. 437-447 ◽  
Author(s):  
Marek Sokáč ◽  
Yvetta Velísková ◽  
Carlo Gualtieri
Keyword(s):  
Approximate Method ◽  
Statistical Evaluation ◽  
Pollution Transport ◽  
Dead Zones ◽  
Advection Diffusion Equation ◽  
Gumbel’S Distribution ◽  
Novel Method ◽  
Substance Transport ◽  
Better Than ◽  
Tracer Experiments

Abstract Analytical solutions describing the 1D substance transport in streams have many limitations and factors, which determine their accuracy. One of the very important factors is the presence of the transient storage (dead zones), that deform the concentration distribution of the transported substance. For better adaptation to such real conditions, a simple 1D approximation method is presented in this paper. The proposed approximate method is based on the asymmetric probability distribution (Gumbel’s distribution) and was verified on three streams in southern Slovakia. Tracer experiments on these streams confirmed the presence of dead zones to various extents, depending mainly on the vegetation extent in each stream. Statistical evaluation confirms that the proposed method approximates the measured concentrations significantly better than methods based upon the Gaussian distribution. The results achieved by this novel method are also comparable with the solution of the 1D advection-diffusion equation (ADE), whereas the proposed method is faster and easier to apply and thus suitable for iterative (inverse) tasks.

Experimental study of the adaptive gain feature for improved position-sensitive ion spectroscopy with Timepix2

2022 ◽  
Vol 17 (01) ◽  
pp. C01025
Author(s):  
B. Bergmann ◽  
P. Smolyanskiy ◽  
P. Burian ◽  
S. Pospisil
Keyword(s):  
Energy Content ◽  
High Energy ◽  
Relative Energy ◽  
Ion Spectroscopy ◽  
Spatially Resolved ◽  
Deposited Energy ◽  
Novel Method ◽  
Thickness Variations ◽  
Sigma E ◽  
Better Than

Abstract In the present work, we study the Timepix2 pixels’ high energy response in the so-called adaptive gain mode. Therefore, Timepix2 with a 500 μm thick silicon sensor was irradiated with protons of energies in the range from 400 keV to 2 MeV and α-particles of 5.5 MeV from 241Am. A novel method was developed to determine the energy deposit in single pixels of particle imprints, which are spread out over a set of neighbor pixels (cluster). We show that each pixel is capable of measuring the deposited energy from 4 keV up to ∼3.2 MeV. Reconstructing the full energy content of the clusters, we found relative energy resolutions ( σ E ) better than 2.7% and better than 4% for proton and α-particle data, respectively. In a simple experiment with a 5.5 MeV α-particle source, we demonstrate that energy losses in thin (organic) specimen can be spatially resolved, mapping out sample thickness variations, with a resolution around 1–2 μm, across the sensor area. The inherent spatial resolution of the device was determined to be 350 nm in the best case.

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