scholarly journals UAV and LiDAR Data in the Service of Bank Gully Erosion Measurement in Rambla de Algeciras Lakeshore

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2748
Author(s):  
Radouane Hout ◽  
Véronique Maleval ◽  
Gil Mahe ◽  
Eric Rouvellac ◽  
Rémi Crouzevialle ◽  
...  
Keyword(s):  
High Resolution ◽  
Point Clouds ◽  
Sediment Budget ◽  
Lidar Data ◽  
Different Types ◽  
The Subject ◽  
Geomorphological Changes ◽  
Uncertainty Models ◽  
Geological Formations ◽  
Different Sources

The Rambla de Algeciras lake in Murcia is a reservoir for drinking water and contributes to the reduction of flooding. With a semi-arid climate and a very friable nature of the geological formations at the lakeshore level, the emergence and development of bank gullies is favored and poses a problem of silting of the dam. A study was conducted on these lakeshores to estimate the sediment input from the bank gullies. In 2018, three gullies of different types were the subject of three UAV photography missions to model in high resolution their low topographic change, using the SfM-MVS photogrammetry method. The combination of two configurations of nadir and oblique photography allowed us to obtain a complete high-resolution modeling of complex bank gullies with overhangs, as it was the case in site 3. To study annual lakeshore variability and sediment dynamics we used LiDAR data from the PNOA project taken in 2009 and 2016. For a better error analysis of UAV photogrammetry data we compared spatially variable and uniform uncertainty models, while taking into account the different sources of error. For LiDAR data, on the other hand, we used a spatially uniform error model. Depending on the geomorphology of the gullies and the configuration of the data capture, we chose the most appropriate method to detect geomorphological changes on the surfaces of the bank gullies. At site 3 the gully topography is complex, so we performed a 3D distance calculation between point clouds using the M3C2 algorithm to estimate the sediment budget. On sites 1 and 2 we used the DoD technique to estimate the sediment budget as it was the case for the LiDAR data. The results of the LiDAR and UAV data reveal significant lakeshore erosion activity by bank gullies since the annual inflow from the banks is estimated at 39 T/ha/year.

scholarly journals Improve Building Façades in Open Lidar Data Using Ground Imagery

2018 ◽  
Author(s):  
Shenman Zhang ◽  
Pengjie Tao
Keyword(s):  
Point Cloud ◽  
Open Data ◽  
Point Clouds ◽  
Lidar Data ◽  
Free Access ◽  
Registration Accuracy ◽  
Incomplete Coverage ◽  
Meta Information ◽  
Coherent Point Drift ◽  
Different Sources

Recent advances in open data initiatives allow us to free access to a vast amount of open LiDAR data in many cities. However, most of these open LiDAR data over cities are acquired by airborne scanning, where the points on façades are sparse or even completely missing due to the viewpoint and object occlusions in the urban environment. Integrating other sources of data, such as ground images, to complete the missing parts is an effective and practical solution. This paper presents an approach for improving open LiDAR data coverage on building façades by using point cloud generated from ground images. A coarse-to-fine strategy is proposed to fuse these two different sources of data. Firstly, the façade point cloud generated from terrestrial images is initially geolocated by matching the SFM camera positions to their GPS meta-information. Next, an improved Coherent Point Drift algorithm with normal consistency is proposed to accurately align building façades to open LiDAR data. The significance of the work resides in the use of 2D overlapping points on the outline of buildings instead of limited 3D overlap between the two point clouds and the achievement to a reliable and precise registration under possible incomplete coverage and ambiguous correspondence. Experiments show that the proposed approach can significantly improve the façades details of buildings in open LiDAR data and improving registration accuracy from up to 10 meters to less than half a meter compared to classic registration methods.

scholarly journals Improving Details of Building Façades in Open LiDAR Data Using Ground Images

2019 ◽  
Vol 11 (4) ◽  
pp. 420 ◽  
Author(s):  
Shenman Zhang ◽  
Pengjie Tao ◽  
Lei Wang ◽  
Yaolin Hou ◽  
Zhihua Hu
Keyword(s):  
Point Cloud ◽  
Open Data ◽  
Point Clouds ◽  
Lidar Data ◽  
Free Access ◽  
Registration Accuracy ◽  
Building Facades ◽  
Incomplete Coverage ◽  
Coherent Point Drift ◽  
Different Sources

Recent open data initiatives allow free access to a vast amount of light detection and ranging (LiDAR) data in many cities. However, most open LiDAR data of cities are acquired by airborne scanning, where points on building façades are sparse or even completely missing due to occlusions in the urban environment, leading to the absence of façade details. This paper presents an approach for improving the LiDAR data coverage on building façades by using point cloud generated from ground images. A coarse-to-fine strategy is proposed to fuse these two-point clouds of different sources with very limited overlaps. First, the façade point cloud generated from ground images is leveled by adjusting the facade normal to perpendicular to the upright direction. Then leveling façade point cloud is geolocated by alignment between images GPS data and their structure from motion (SfM) coordinates. Next, a modified coherent point drift algorithm with (surface) normal consistency is proposed to accurately align the façade point cloud to the LiDAR data. The significance of this work resides in the use of 2D overlapping points on the building outlines instead of the limited 3D overlap between the two-point clouds. This way we can still achieve reliable and precise registration under incomplete coverage and ambiguous correspondence. Experiments show that the proposed approach can significantly improve the façade details in open LiDAR data, and achieve 2 to 10 times higher registration accuracy, when compared to classic registration methods.

scholarly journals Methods for tree cover extraction from high resolution orthophotos and airborne LiDAR scanning in Spanish dehesas

2019 ◽  
pp. 17 ◽  
Author(s):  
I. Borlaf-Mena ◽  
M. A. Tanase ◽  
A. Gómez-Sal
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Remote Sensing Data ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Tree Cover ◽  
Lidar Data ◽  
Homogeneous Tree ◽  
Visual Interpretation ◽  
Management Changes

<p>Dehesas are high value agroecosystems that benefit from the effect tree cover has on pastures. Such effect occurs when tree cover is incomplete and homogeneous. Tree cover may be characterized from field data or through visual interpretation of remote sensing data, both time-consuming tasks. An alternative is the extraction of tree cover from aerial imagery using automated methods, on spectral derivate products (i.e. NDVI) or LiDAR point clouds. This study focuses on assessing and comparing methods for tree cover estimation from high resolution orthophotos and airborne laser scanning (ALS). RGB image processing based on thresholding of the ‘Excess Green minus Excess Red’ index with the Otsu method produced acceptable results (80%), lower than that obtained by thresholding the digital canopy model obtained from the ALS data (87%) or when combining RGB and LiDAR data (87.5%). The RGB information was found to be useful for tree delineation, although very vulnerable to confusion with the grass or shrubs. The ALS based extraction suffered for less confusion as it differentiated between trees and the remaining vegetation using the height. These results show that analysis of historical orthophotographs may be successfully used to evaluate the effects of management changes while LiDAR data may provide a substantial increase in the accuracy for the latter period. Combining RGB and Lidar data did not result in significant improvements over using LIDAR data alone.</p>

scholarly journals Nanotoxicity: Dimensional and Morphological Concerns

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Mohmmad Younus Wani ◽  
Mohd Ali Hashim ◽  
Firdosa Nabi ◽  
Maqsood Ahmad Malik
Keyword(s):  
Molecular Level ◽  
Toxic Effects ◽  
New Materials ◽  
Safety Test ◽  
Wide Range ◽  
Different Types ◽  
Potential Applications ◽  
The Subject ◽  
Living Organisms ◽  
Different Sources

Nanotechnology deals with the construction of new materials, devices, and different technological systems with a wide range of potential applications at the atomic and molecular level. Nanomaterials have attracted great attention for numerous applications in chemical, biological, and industrial world because of their fascinating physicochemical properties. Nanomaterials and nanodevices are being produced intentionally, unintentionally, and manufactured or engineered by different methods and released into the environment without any safety test. Nantoxicity has become the subject of concern in nanoscience and nanotechnology because of the increasing toxic effects of nanomaterials on the living organisms. Nanomaterials can move freely as compared to the large-sized particles; therefore, they can be more toxic than bulky materials. This review article delineates the toxic effects of different types of nanomaterials on the living organisms through different sources, like water, air, contact with skin, and the methods of determinations of these toxic effects.

scholarly journals UPDATING LIDAR DSM USING HIGH RESOLUTION STEREO-BASED DSM FROM WORLDVIEW-2

2014 ◽  
Vol XL-2/W3 ◽  
pp. 59-64
Author(s):  
H. Arefi ◽  
H. Hashemi ◽  
Th. Krauss ◽  
M. Gharibia
Keyword(s):  
High Resolution ◽  
Satellite Images ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Lidar Data ◽  
High Quality ◽  
Qualitative And Quantitative ◽  
Surface Models ◽  
Dense Point ◽  
Processing Techniques

In recent years, the acquisition and processing techniques of high resolution Digital Surface Models (DSM) have been rapidly improved. Airborne LiDAR production as a well-known and high quality DSM is still unbeatable in elevation accuracy and highly produced dense point clouds. In this paper, the objective is to update an old but high quality DSM produced by LiDAR data using a DSM generated from high resolution stereo satellite images. A classification-base algorithm is proposed to extract building changes between DSMs in two epochs. For image classification procedure, the DSM and Worldview-2 orthorectified images have been used as input data for a fuzzy-based classification method. Then, extracted buildings are classified into unchanged, destroyed, new, and changed classes. In this study a dataset related to Munich city, has been utilized to test the experimental investigation. The implemented qualitative and quantitative assessments demonstrate high quality as well as high feasibility of the proposed approach.

Backscattered Electron Imaging of GaAs/AlGaAs Super Lattice Structures with an Ultra-High- Resolution SEM

1988 ◽  
Vol 46 ◽  
pp. 204-205
Author(s):  
Kazumichi Ogura ◽  
Michael M. Kersker
Keyword(s):  
High Resolution ◽  
Layer Structure ◽  
High Sensitivity ◽  
Beam Current ◽  
Electron Beam Current ◽  
Lattice Structures ◽  
Super Lattice ◽  
Different Types ◽  
Backscattered Electron ◽  
Electron Imaging

Backscattered electron (BE) images of GaAs/AlGaAs super lattice structures were observed with an ultra high resolution (UHR) SEM JSM-890 with an ultra high sensitivity BE detector. Three different types of super lattice structures of GaAs/AlGaAs were examined. Each GaAs/AlGaAs wafer was cleaved by a razor after it was heated for approximately 1 minute and its crosssectional plane was observed.First, a multi-layer structure of GaAs (100nm)/AlGaAs (lOOnm) where A1 content was successively changed from 0.4 to 0.03 was observed. Figures 1 (a) and (b) are BE images taken at an accelerating voltage of 15kV with an electron beam current of 20pA. Figure 1 (c) is a sketch of this multi-layer structure corresponding to the BE images. The various layers are clearly observed. The differences in A1 content between A1 0.35 Ga 0.65 As, A1 0.4 Ga 0.6 As, and A1 0.31 Ga 0.69 As were clearly observed in the contrast of the BE image.

Point and planar defects in the iron sulfide compounds Fe1-xS

1984 ◽  
Vol 42 ◽  
pp. 434-435
Author(s):  
Thao A. Nguyen
Keyword(s):  
Low Temperatures ◽  
Direct Evidence ◽  
Iron Sulfide ◽  
Planar Defects ◽  
Selective Area ◽  
Vacancy Ordering ◽  
Different Types ◽  
Lattice Images ◽  
The Subject ◽  
Beam Lattice

It is well known that the large deviations from stoichiometry in iron sulfide compounds, Fe1-xS (0≤x≤0.125), are accommodated by iron vacancies which order and form superstructures at low temperatures. Although the ordering of the iron vacancies has been well established, the modes of vacancy ordering, hence superstructures, as a function of composition and temperature are still the subject of much controversy. This investigation gives direct evidence from many-beam lattice images of Fe1-xS that the 4C superstructure transforms into the 3C superstructure (Fig. 1) rather than the MC phase as previously suggested. Also observed are an intrinsic stacking fault in the sulfur sublattice and two different types of vacancy-ordering antiphase boundaries. Evidence from selective area optical diffractograms suggests that these planar defects complicate the diffraction pattern greatly.

Geological Field Sketches and Illustrations

2019 ◽  
Author(s):  
Matthew J. Genge
Keyword(s):  
Cross Sections ◽  
Earth Science ◽  
Three Dimensional ◽  
Worked Examples ◽  
Scientific Publications ◽  
Thin Sections ◽  
Geological Features ◽  
Different Types ◽  
The Subject

Drawings, illustrations, and field sketches play an important role in Earth Science since they are used to record field observations, develop interpretations, and communicate results in reports and scientific publications. Drawing geology in the field furthermore facilitates observation and maximizes the value of fieldwork. Every geologist, whether a student, academic, professional, or amateur enthusiast, will benefit from the ability to draw geological features accurately. This book describes how and what to draw in geology. Essential drawing techniques, together with practical advice in creating high quality diagrams, are described the opening chapters. How to draw different types of geology, including faults, folds, metamorphic rocks, sedimentary rocks, igneous rocks, and fossils, are the subjects of separate chapters, and include descriptions of what are the important features to draw and describe. Different types of sketch, such as drawings of three-dimensional outcrops, landscapes, thin-sections, and hand-specimens of rocks, crystals, and minerals, are discussed. The methods used to create technical diagrams such as geological maps and cross-sections are also covered. Finally, modern techniques in the acquisition and recording of field data, including photogrammetry and aerial surveys, and digital methods of illustration, are the subject of the final chapter of the book. Throughout, worked examples of field sketches and illustrations are provided as well as descriptions of the common mistakes to be avoided.

scholarly journals How to measure uncertainty in uncertainty sampling for active learning

2021 ◽  
Author(s):  
Vu-Linh Nguyen ◽  
Mohammad Hossein Shaker ◽  
Eyke Hüllermeier
Keyword(s):  
Machine Learning ◽  
Active Learning ◽  
Sampling Strategies ◽  
Total Uncertainty ◽  
Uncertainty Sampling ◽  
Different Types ◽  
Alternative Approaches ◽  
Active Learner ◽  
Probabilistic Nature ◽  
Different Sources

AbstractVarious strategies for active learning have been proposed in the machine learning literature. In uncertainty sampling, which is among the most popular approaches, the active learner sequentially queries the label of those instances for which its current prediction is maximally uncertain. The predictions as well as the measures used to quantify the degree of uncertainty, such as entropy, are traditionally of a probabilistic nature. Yet, alternative approaches to capturing uncertainty in machine learning, alongside with corresponding uncertainty measures, have been proposed in recent years. In particular, some of these measures seek to distinguish different sources and to separate different types of uncertainty, such as the reducible (epistemic) and the irreducible (aleatoric) part of the total uncertainty in a prediction. The goal of this paper is to elaborate on the usefulness of such measures for uncertainty sampling, and to compare their performance in active learning. To this end, we instantiate uncertainty sampling with different measures, analyze the properties of the sampling strategies thus obtained, and compare them in an experimental study.

scholarly journals Model-Based Probabilistic Inversion Using Magnetic Data: A Case Study on the Kevitsa Deposit

Geosciences ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 150
Author(s):  
Nilgün Güdük ◽  
Miguel de la Varga ◽  
Janne Kaukolinna ◽  
Florian Wellmann
Keyword(s):  
Structural Parameters ◽  
Rock Properties ◽  
Magnetic Data ◽  
Geological Model ◽  
Borehole Data ◽  
Likelihood Functions ◽  
Different Types ◽  
Geophysical Information ◽  
Different Sources

Structural geological models are widely used to represent relevant geological interfaces and property distributions in the subsurface. Considering the inherent uncertainty of these models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that integrate different types of data consistently and consider the uncertainties quantitatively. Probabilistic inference provides a suitable tool for this purpose. Using a Bayesian framework, geological modeling can be considered as an integral part of the inversion and thereby naturally constrain geophysical inversion procedures. This integration prevents geologically unrealistic results and provides the opportunity to include geological and geophysical information in the inversion. This information can be from different sources and is added to the framework through likelihood functions. We applied this methodology to the structurally complex Kevitsa deposit in Finland. We started with an interpretation-based 3D geological model and defined the uncertainties in our geological model through probability density functions. Airborne magnetic data and geological interpretations of borehole data were used to define geophysical and geological likelihoods, respectively. The geophysical data were linked to the uncertain structural parameters through the rock properties. The result of the inverse problem was an ensemble of realized models. These structural models and their uncertainties are visualized using information entropy, which allows for quantitative analysis. Our results show that with our methodology, we can use well-defined likelihood functions to add meaningful information to our initial model without requiring a computationally-heavy full grid inversion, discrepancies between model and data are spotted more easily, and the complementary strength of different types of data can be integrated into one framework.

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