Search results for: Sentinel-2 satellite image
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3260

Search results for: Sentinel-2 satellite image

1580 A Study on the Application of Machine Learning and Deep Learning Techniques for Skin Cancer Detection

Authors: Hritwik Ghosh, Irfan Sadiq Rahat, Sachi Nandan Mohanty, J. V. R. Ravindra

Abstract:

In the rapidly evolving landscape of medical diagnostics, the early detection and accurate classification of skin cancer remain paramount for effective treatment outcomes. This research delves into the transformative potential of Artificial Intelligence (AI), specifically Deep Learning (DL), as a tool for discerning and categorizing various skin conditions. Utilizing a diverse dataset of 3,000 images representing nine distinct skin conditions, we confront the inherent challenge of class imbalance. This imbalance, where conditions like melanomas are over-represented, is addressed by incorporating class weights during the model training phase, ensuring an equitable representation of all conditions in the learning process. Our pioneering approach introduces a hybrid model, amalgamating the strengths of two renowned Convolutional Neural Networks (CNNs), VGG16 and ResNet50. These networks, pre-trained on the ImageNet dataset, are adept at extracting intricate features from images. By synergizing these models, our research aims to capture a holistic set of features, thereby bolstering classification performance. Preliminary findings underscore the hybrid model's superiority over individual models, showcasing its prowess in feature extraction and classification. Moreover, the research emphasizes the significance of rigorous data pre-processing, including image resizing, color normalization, and segmentation, in ensuring data quality and model reliability. In essence, this study illuminates the promising role of AI and DL in revolutionizing skin cancer diagnostics, offering insights into its potential applications in broader medical domains.

Keywords: artificial intelligence, machine learning, deep learning, skin cancer, dermatology, convolutional neural networks, image classification, computer vision, healthcare technology, cancer detection, medical imaging

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1579 The Role of the Youth in Rebranding Nigeria

Authors: Hamzah Kamil Adeyemi, Oyesikun Abayomi Nathaniel

Abstract:

The plural nature of Nigeria state has created a leadership gap in the 21st century. The leadership problem encapsulated socio-economic system has called for a reorientation in youth to channel a programme that will redeem the image (OT) the country among the committee of nations and chart a way forward in bailing the country out of bad governance unemployment corruption and other anti-development policies. The touth need to raise up to the challenges of nation building. This study engaged theoretical analysis, both written records was used to add value to its quality and recommendation was made with conclusion.

Keywords: youth, education, unempolyment, rebranding, Nigeria

Procedia PDF Downloads 410
1578 Random Variation of Treated Volumes in Fractionated 2D Image Based HDR Brachytherapy for Cervical Cancer

Authors: R. Tudugala, B. M. A. I. Balasooriya, W. M. Ediri Arachchi, R. W. M. W. K. Rathnayake, T. D. Premaratna

Abstract:

Brachytherapy involves placing a source of radiation near the cancer site which gives promising prognosis for cervical cancer treatments. The purpose of this study was to evaluate the effect of random variation of treated volumes in between fractions in the 2D image based fractionated high dose rate brachytherapy for cervical cancer at National Cancer Institute Maharagama, Sri Lanka. Dose plans were analyzed for 150 cervical cancer patients with orthogonal radiographs (2D) based brachytherapy. ICRU treated volumes was modeled by translating the applicators with the help of “Multisource HDR plus software”. The difference of treated volumes with respect to the applicator geometry was analyzed by using SPSS 18 software; to derived patient population based estimates of delivered treated volumes relative to ideally treated volumes. Packing was evaluated according to bladder dose, rectum dose and geometry of the dose distribution by three consultant radiation oncologist. The difference of treated volumes depends on types of the applicators, which was used in fractionated brachytherapy. The means of the “Difference of Treated Volume” (DTV) for “Evenly activated tandem (ET)” length” group was ((X_1)) -0.48 cm3 and ((X_2)) 11.85 cm3 for “Unevenly activated tandem length (UET) group. The range of the DTV for ET group was 35.80 cm3 whereas UET group 104.80 cm3. One sample T test was performed to compare the DTV with “Ideal treatment volume difference (0.00cm3)”. It is evident that P value was 0.732 for ET group and for UET it was 0.00 moreover independent two sample T test was performed to compare ET and UET groups and calculated P value was 0.005. Packing was evaluated under three categories 59.38% used “Convenient Packing Technique”, 33.33% used “Fairly Packing Technique” and 7.29% used “Not Convenient Packing” in their fractionated brachytherapy treatments. Random variation of treated volume in ET group is much lower than UET group and there is a significant difference (p<0.05) in between ET and UET groups which affects the dose distribution of the treatment. Furthermore, it can be concluded nearly 92.71% patient’s packing were used acceptable packing technique at NCIM, Sri Lanka.

Keywords: brachytherapy, cervical cancer, high dose rate, tandem, treated volumes

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1577 Communicating Corporate Social Responsibility in Kuwait: Assessment of Environmental Responsibility Efforts and Targeted Stakeholders

Authors: Manaf Bashir

Abstract:

Corporate social responsibility (CSR) has become a tool for corporations to meet the expectations of different stakeholders about economic, social and environmental issues. It has become indispensable for an organization’s success, positive image and reputation. Equally important is how corporations communicate and report their CSR. Employing the stakeholder theory, the purpose of this research is to analyse CSR content of leading Kuwaiti corporations. No research analysis of CSR reporting has been conducted in Kuwait and this study is an attempt to redress in part this empirical deficit in the country and the region. It attempts to identify the issues and stakeholders of the CSR and if corporations are following CSR reporting standards. By analysing websites, annual and CSR reports of the top 100 Kuwaiti corporations, this study found low mentions of the CSR issues and even lower mentions of CSR stakeholders. Environmental issues were among the least mentioned despite an increasing global concern toward the environment. ‘Society’ was mentioned the most as a stakeholder and ‘The Environment’ was among the least mentioned. Cross-tabulations found few significant relationships between type of industry and the CSR issues and stakeholders. Independent sample t-tests found no significant difference between the issues and stakeholders that are mentioned on the websites and the reports. Only two companies from the sample followed reporting standards and both followed the Global Reporting Initiative. Successful corporations would be keen to identify the issues that meet the expectations of different stakeholders and address them through their corporate communication. Kuwaiti corporations did not show this keenness. As the stakeholder theory suggests, extending the spectrum of stakeholders beyond investors can open mutual dialogue and understanding between corporations and various stakeholders. However, Kuwaiti corporations focus on few CSR issues and even fewer CSR stakeholders. Kuwaiti corporations need to pay more attention to CSR and particularly toward environmental issues. They should adopt a strategic approach and allocate specialized personnel such as marketers and public relations practitioners to manage it. The government and non-profit organizations should encourage the private sector in Kuwait to do more CSR and meet the needs and expectations of different stakeholders and not only shareholders. This is in addition to reporting the CSR information professionally because of its benefits to corporate image, reputation, and transparency.

Keywords: corporate social responsibility, environmental responsibility, Kuwait, stakeholder theory

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1576 Clinical Application of Measurement of Eyeball Movement for Diagnose of Autism

Authors: Ippei Torii, Kaoruko Ohtani, Takahito Niwa, Naohiro Ishii

Abstract:

This paper shows developing an objectivity index using the measurement of subtle eyeball movement to diagnose autism. The developmentally disabled assessment varies, and the diagnosis depends on the subjective judgment of professionals. Therefore, a supplementary inspection method that will enable anyone to obtain the same quantitative judgment is needed. The diagnosis are made based on a comparison of the time of gazing an object in the conventional autistic study, but the results do not match. First, we divided the pupil into four parts from the center using measurements of subtle eyeball movement and comparing the number of pixels in the overlapping parts based on an afterimage. Then we developed the objective evaluation indicator to judge non-autistic and autistic people more clearly than conventional methods by analyzing the differences of subtle eyeball movements between the right and left eyes. Even when a person gazes at one point and his/her eyeballs always stay fixed at that point, their eyes perform subtle fixating movements (ie. tremors, drifting, microsaccades) to keep the retinal image clear. Particularly, the microsaccades link with nerves and reflect the mechanism that process the sight in a brain. We converted the differences between these movements into numbers. The process of the conversion is as followed: 1) Select the pixel indicating the subject's pupil from images of captured frames. 2) Set up a reference image, known as an afterimage, from the pixel indicating the subject's pupil. 3) Divide the pupil of the subject into four from the center in the acquired frame image. 4) Select the pixel in each divided part and count the number of the pixels of the overlapping part with the present pixel based on the afterimage. 5) Process the images with precision in 24 - 30fps from a camera and convert the amount of change in the pixels of the subtle movements of the right and left eyeballs in to numbers. The difference in the area of the amount of change occurs by measuring the difference between the afterimage in consecutive frames and the present frame. We set the amount of change to the quantity of the subtle eyeball movements. This method made it possible to detect a change of the eyeball vibration in numerical value. By comparing the numerical value between the right and left eyes, we found that there is a difference in how much they move. We compared the difference in these movements between non-autistc and autistic people and analyzed the result. Our research subjects consists of 8 children and 10 adults with autism, and 6 children and 18 adults with no disability. We measured the values through pasuit movements and fixations. We converted the difference in subtle movements between the right and left eyes into a graph and define it in multidimensional measure. Then we set the identification border with density function of the distribution, cumulative frequency function, and ROC curve. With this, we established an objective index to determine autism, normal, false positive, and false negative.

Keywords: subtle eyeball movement, autism, microsaccade, pursuit eye movements, ROC curve

Procedia PDF Downloads 264
1575 Field Emission Scanning Microscope Image Analysis for Porosity Characterization of Autoclaved Aerated Concrete

Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

Abstract:

Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

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1574 New Approach for Constructing a Secure Biometric Database

Authors: A. Kebbeb, M. Mostefai, F. Benmerzoug, Y. Chahir

Abstract:

The multimodal biometric identification is the combination of several biometric systems. The challenge of this combination is to reduce some limitations of systems based on a single modality while significantly improving performance. In this paper, we propose a new approach to the construction and the protection of a multimodal biometric database dedicated to an identification system. We use a topological watermarking to hide the relation between face image and the registered descriptors extracted from other modalities of the same person for more secure user identification.

Keywords: biometric databases, multimodal biometrics, security authentication, digital watermarking

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1573 Ill-Posed Inverse Problems in Molecular Imaging

Authors: Ranadhir Roy

Abstract:

Inverse problems arise in medical (molecular) imaging. These problems are characterized by large in three dimensions, and by the diffusion equation which models the physical phenomena within the media. The inverse problems are posed as a nonlinear optimization where the unknown parameters are found by minimizing the difference between the predicted data and the measured data. To obtain a unique and stable solution to an ill-posed inverse problem, a priori information must be used. Mathematical conditions to obtain stable solutions are established in Tikhonov’s regularization method, where the a priori information is introduced via a stabilizing functional, which may be designed to incorporate some relevant information of an inverse problem. Effective determination of the Tikhonov regularization parameter requires knowledge of the true solution, or in the case of optical imaging, the true image. Yet, in, clinically-based imaging, true image is not known. To alleviate these difficulties we have applied the penalty/modified barrier function (PMBF) method instead of Tikhonov regularization technique to make the inverse problems well-posed. Unlike the Tikhonov regularization method, the constrained optimization technique, which is based on simple bounds of the optical parameter properties of the tissue, can easily be implemented in the PMBF method. Imposing the constraints on the optical properties of the tissue explicitly restricts solution sets and can restore uniqueness. Like the Tikhonov regularization method, the PMBF method limits the size of the condition number of the Hessian matrix of the given objective function. The accuracy and the rapid convergence of the PMBF method require a good initial guess of the Lagrange multipliers. To obtain the initial guess of the multipliers, we use a least square unconstrained minimization problem. Three-dimensional images of fluorescence absorption coefficients and lifetimes were reconstructed from contact and noncontact experimentally measured data.

Keywords: constrained minimization, ill-conditioned inverse problems, Tikhonov regularization method, penalty modified barrier function method

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1572 Uncontrolled Urbanization Leads to Main Challenge for Sustainable Development of Mongolia

Authors: Davaanyam Surenjav, Chinzolboo Dandarbaatar, Ganbold Batkhuyag

Abstract:

Primate city induced rapid urbanization has been become one of the main challenges in sustainable development in Mongolia like other developing countries since transition to market economy in 1990. According due to statistical yearbook, population number of Ulaanbaatar city has increased from 0.5 million to 1.5 million for last 30 years and contains now almost half (47%) of total Mongolian population. Rural-Ulaanbaatar and local Cities-Ulaanbaatar city migration leads to social issues like uncontrolled urbanization, income inequality, poverty, overwork of public service, economic over cost for redevelopment and limitation of transport and environmental degradation including air, noise, water and soil pollution. Most thresholds of all of the sustainable urban development main and sub-indicators over exceeded from safety level to unsafety level in Ulaanbaatar. So, there is an urgent need to remove migration pull factors including some administrative and high education functions from Ulaanbaatar city to its satellite cities or secondary cities. Moreover, urban smart transport system and green and renewable energy technologies should be introduced to urban development master plan of Ulaanbaatar city.

Keywords: challenge for sustainable urban development, migration factors, primate city , urban safety thresholds

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1571 Spatiotemporal Analysis of Land Surface Temperature and Urban Heat Island Evaluation of Four Metropolitan Areas of Texas, USA

Authors: Chunhong Zhao

Abstract:

Remotely sensed land surface temperature (LST) is vital to understand the land-atmosphere energy balance, hydrological cycle, and thus is widely used to describe the urban heat island (UHI) phenomenon. However, due to technical constraints, satellite thermal sensors are unable to provide LST measurement with both high spatial and high temporal resolution. Despite different downscaling techniques and algorithms to generate high spatiotemporal resolution LST. Four major metropolitan areas in Texas, USA: Dallas-Fort Worth, Houston, San Antonio, and Austin all demonstrate UHI effects. Different cities are expected to have varying SUHI effect during the urban development trajectory. With the help of the Landsat, ASTER, and MODIS archives, this study focuses on the spatial patterns of UHIs and the seasonal and annual variation of these metropolitan areas. With Gaussian model, and Local Indicators of Spatial Autocorrelations (LISA), as well as data fusion methods, this study identifies the hotspots and the trajectory of the UHI phenomenon of the four cities. By making comparison analysis, the result can help to alleviate the advent effect of UHI and formulate rational urban planning in the long run.

Keywords: spatiotemporal analysis, land surface temperature, urban heat island evaluation, metropolitan areas of Texas, USA

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1570 Image-Based UAV Vertical Distance and Velocity Estimation Algorithm during the Vertical Landing Phase Using Low-Resolution Images

Authors: Seyed-Yaser Nabavi-Chashmi, Davood Asadi, Karim Ahmadi, Eren Demir

Abstract:

The landing phase of a UAV is very critical as there are many uncertainties in this phase, which can easily entail a hard landing or even a crash. In this paper, the estimation of relative distance and velocity to the ground, as one of the most important processes during the landing phase, is studied. Using accurate measurement sensors as an alternative approach can be very expensive for sensors like LIDAR, or with a limited operational range, for sensors like ultrasonic sensors. Additionally, absolute positioning systems like GPS or IMU cannot provide distance to the ground independently. The focus of this paper is to determine whether we can measure the relative distance and velocity of UAV and ground in the landing phase using just low-resolution images taken by a monocular camera. The Lucas-Konda feature detection technique is employed to extract the most suitable feature in a series of images taken during the UAV landing. Two different approaches based on Extended Kalman Filters (EKF) have been proposed, and their performance in estimation of the relative distance and velocity are compared. The first approach uses the kinematics of the UAV as the process and the calculated optical flow as the measurement; On the other hand, the second approach uses the feature’s projection on the camera plane (pixel position) as the measurement while employing both the kinematics of the UAV and the dynamics of variation of projected point as the process to estimate both relative distance and relative velocity. To verify the results, a sequence of low-quality images taken by a camera that is moving on a specifically developed testbed has been used to compare the performance of the proposed algorithm. The case studies show that the quality of images results in considerable noise, which reduces the performance of the first approach. On the other hand, using the projected feature position is much less sensitive to the noise and estimates the distance and velocity with relatively high accuracy. This approach also can be used to predict the future projected feature position, which can drastically decrease the computational workload, as an important criterion for real-time applications.

Keywords: altitude estimation, drone, image processing, trajectory planning

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1569 Hand Gesture Detection via EmguCV Canny Pruning

Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

Abstract:

Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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1568 Normal and Peaberry Coffee Beans Classification from Green Coffee Bean Images Using Convolutional Neural Networks and Support Vector Machine

Authors: Hira Lal Gope, Hidekazu Fukai

Abstract:

The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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1567 Test Bench Development and Functional Analysis of a Reaction Wheel for an Attitude Determination and Control System Prototype

Authors: Pablo Raul Yanyachi, Alfredo Mamani Saico, Jorch Mendoza, Wang Xinsheng

Abstract:

The Attitude Determination and Control System (ADCS) plays a pivotal role in the operation of nanosatellites such as Cubesats, managing orientation and stability during space missions. Within the ADCS, Reaction Wheels (RW) are electromechanical devices responsible for adjusting and maintaining satellite orientation through the application of kinetic moments. This study focuses on the characterization and analysis of a specific Reaction Wheel integrated into an ADCS prototype developed at the National University of San Agust´ın, Arequipa (UNSA). To achieve this, a single-axis Test Bench was constructed, where the reaction wheel consists of a brushless motor and an inertia flywheel driven by an Electronic Speed Controller (ESC). The research encompasses RW characterization, energy consumption evaluation, dynamic modeling, and control. The results have allowed us to ensure the maneuverability of ADCS prototypes while maintaining energy consumption within acceptable limits. The characterization and linearity analysis provides valuable insights for sizing and optimizing future reaction wheel prototypes for nanosatellites. This contributes to the ongoing development of aerospace technology within the scientific community at UNSA.

Keywords: test bench, nanosatellite, control, reaction wheel

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1566 Numerical Simulation of Fluid-Structure Interaction on Wedge Slamming Impact by Using Particle Method

Authors: Sung-Chul Hwang, Di Ren, Sang-Moon Yoon, Jong-Chun Park, Abbas Khayyer, Hitoshi Gotoh

Abstract:

The slamming impact problem has a very important engineering background. For seaplane landing, recycling for the satellite re-entry capsule, and the impact load of the bow in the adverse sea conditions, the slamming problem always plays the important role. Due to its strong nonlinear effect, however, it seems to be not easy to obtain the accurate simulation results. Combined with the strong interaction between the fluid field and the elastic structure, the difficulty for the simulation leads to a new level for challenging. This paper presents a fully Lagrangian coupled solver for simulations of fluid-structure interactions, which is based on the Moving Particle Semi-implicit (MPS) method to solve the governing equations corresponding to incompressible flows as well as elastic structures. The developed solver is verified by reproducing the high velocity impact loads of deformable thin wedges with two different materials such as aluminum and steel on water entry. The present simulation results are compared with analytical solution derived using the hydrodynamic Wagner model and linear theory by Wan.

Keywords: fluid-structure interaction, moving particle semi-implicit (MPS) method, elastic structure, incompressible flow, wedge slamming impact

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1565 Emotion Recognition in Video and Images in the Wild

Authors: Faizan Tariq, Moayid Ali Zaidi

Abstract:

Facial emotion recognition algorithms are expanding rapidly now a day. People are using different algorithms with different combinations to generate best results. There are six basic emotions which are being studied in this area. Author tried to recognize the facial expressions using object detector algorithms instead of traditional algorithms. Two object detection algorithms were chosen which are Faster R-CNN and YOLO. For pre-processing we used image rotation and batch normalization. The dataset I have chosen for the experiments is Static Facial Expression in Wild (SFEW). Our approach worked well but there is still a lot of room to improve it, which will be a future direction.

Keywords: face recognition, emotion recognition, deep learning, CNN

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1564 From De Soto’s Solution to Urban Disaster: The Effects of Land Titling Policies on the Development of Cities of the Global South in the Case of Lima Peru

Authors: Jitka Molnarova

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Based on De Soto’s idea that a formal land title can provide a secure home and access to credit to poor urban families, a large number of developing countries accepted the formalization of informal settlements as the ultimate solution for their housing crises and struggles with poverty. After two decades of implementation, very little is known about the effects this policy has on the quality of the neighborhoods it produces and on the development of cities in general. Using the capital of Peru -where the solution originated- as a case study, this paper illustrates the negative outcomes this policy has on urban development arguing that land titling encourages 1) expansion of the city often to areas of high physical risk, 2) production of precarious housing on unserviced land, and 3) practices of illegal land trafficking. The evidence is based on interviews with community leaders and officials working at the Cooperation for Formalization of Informal Property (COFOPRI), comparison of satellite images documenting the expansion of Lima in the past twenty years, and a technical evaluation of dozens of houses that have been or are in the process of being granted a land title.

Keywords: COFOPRI, De Soto, housing policies, land titling, land trafficking, Lima, Peru, precarious housing, urban expansion

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1563 Yacht DB Construction Based on Five Essentials of Sailing

Authors: Jae-Neung Lee, Myung-Won Lee, Jung-Su Han, Keun-Chang Kwak

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The paper established DB on the basis of five sailing essentials in the real yachting environment. It obtained the yacht condition (tilt, speed and course), surrounding circumstances (wind direction and speed) and user motion. Gopro camera for image processing was used to recognize the user motion and tilt sensor was employed to see the yacht balance. In addition, GPS for course, wind speed and direction sensor and marked suit were employed.

Keywords: DB consturuction, yacht, five essentials of sailing, marker, Gps

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1562 Verification of Simulated Accumulated Precipitation

Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

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Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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1561 Remote Sensing and Gis Use in Trends of Urbanization and Regional Planning

Authors: Sawan Kumar Jangid

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The paper attempts to study various facets of urbanization and regional planning in the framework of the present conditions and future needs. Urbanization is a dynamic system in which development and changes are prominent features; which implies population growth and changes in the primary, secondary and tertiary sector in the economy. Urban population is increasing day by day due to a natural increase in population and migration from rural areas, and the impact is bound to have in urban areas in terms of infrastructure, environment, water supply and other vital resources. For the organized way of planning and monitoring the implementation of Physical urban and regional plans high-resolution satellite imagery is the potential solution. Now the Remote Sensing data is widely used in urban as well as regional planning, infrastructure planning mainly telecommunication and transport network planning, highway development, accessibility to market area development in terms of catchment and population built-up area density. With Remote Sensing it is possible to identify urban growth, which falls outside the formal planning control. Remote Sensing and GIS technique combined together facilitate the planners, in making a decision, for general public and investors to have relevant data for their use in minimum time. This paper sketches out the Urbanization modal for the future development of Urban and Regional Planning. The paper suggests, a dynamic approach towards regional development strategy.

Keywords: development, dynamic, migration, resolution

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1560 Remote Sensing Approach to Predict the Impacts of Land Use/Land Cover Change on Urban Thermal Comfort Using Machine Learning Algorithms

Authors: Ahmad E. Aldousaria, Abdulla Al Kafy

Abstract:

Urbanization is an incessant process that involves the transformation of land use/land cover (LULC), resulting in a reduction of cool land covers and thermal comfort zones (TCZs). This study explores the directional shrinkage of TCZs in Kuwait using Landsat satellite data from 1991 – 2021 to predict the future LULC and TCZ distribution for 2026 and 2031 using cellular automata (CA) and artificial neural network (ANN) algorithms. Analysis revealed a rapid urban expansion (40 %) in SE, NE, and NW directions and TCZ shrinkage in N – NW and SW directions with 25 % of the very uncomfortable area. The predicted result showed an urban area increase from 44 % in 2021 to 47 % and 52 % in 2026 and 2031, respectively, where uncomfortable zones were found to be concentrated around urban areas and bare lands in N – NE and N – NW directions. This study proposes an effective and sustainable framework to control TCZ shrinkage, including zero soil policies, planned landscape design, manmade water bodies, and rooftop gardens. This study will help urban planners and policymakers to make Kuwait an eco–friendly, functional, and sustainable country.

Keywords: land cover change, thermal environment, green cover loss, machine learning, remote sensing

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1559 Towards Visual Personality Questionnaires Based on Deep Learning and Social Media

Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

Abstract:

Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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1558 Long-Term Subcentimeter-Accuracy Landslide Monitoring Using a Cost-Effective Global Navigation Satellite System Rover Network: Case Study

Authors: Vincent Schlageter, Maroua Mestiri, Florian Denzinger, Hugo Raetzo, Michel Demierre

Abstract:

Precise landslide monitoring with differential global navigation satellite system (GNSS) is well known, but technical or economic reasons limit its application by geotechnical companies. This study demonstrates the reliability and the usefulness of Geomon (Infrasurvey Sàrl, Switzerland), a stand-alone and cost-effective rover network. The system permits deploying up to 15 rovers, plus one reference station for differential GNSS. A dedicated radio communication links all the modules to a base station, where an embedded computer automatically provides all the relative positions (L1 phase, open-source RTKLib software) and populates an Internet server. Each measure also contains information from an internal inclinometer, battery level, and position quality indices. Contrary to standard GNSS survey systems, which suffer from a limited number of beacons that must be placed in areas with good GSM signal, Geomon offers greater flexibility and permits a real overview of the whole landslide with good spatial resolution. Each module is powered with solar panels, ensuring autonomous long-term recordings. In this study, we have tested the system on several sites in the Swiss mountains, setting up to 7 rovers per site, for an 18 month-long survey. The aim was to assess the robustness and the accuracy of the system in different environmental conditions. In one case, we ran forced blind tests (vertical movements of a given amplitude) and compared various session parameters (duration from 10 to 90 minutes). Then the other cases were a survey of real landslides sites using fixed optimized parameters. Sub centimetric-accuracy with few outliers was obtained using the best parameters (session duration of 60 minutes, baseline 1 km or less), with the noise level on the horizontal component half that of the vertical one. The performance (percent of aborting solutions, outliers) was reduced with sessions shorter than 30 minutes. The environment also had a strong influence on the percent of aborting solutions (ambiguity search problem), due to multiple reflections or satellites obstructed by trees and mountains. The length of the baseline (distance reference-rover, single baseline processing) reduced the accuracy above 1 km but had no significant effect below this limit. In critical weather conditions, the system’s robustness was limited: snow, avalanche, and frost-covered some rovers, including the antenna and vertically oriented solar panels, leading to data interruption; and strong wind damaged a reference station. The possibility of changing the sessions’ parameters remotely was very useful. In conclusion, the rover network tested provided the foreseen sub-centimetric-accuracy while providing a dense spatial resolution landslide survey. The ease of implementation and the fully automatic long-term survey were timesaving. Performance strongly depends on surrounding conditions, but short pre-measures should allow moving a rover to a better final placement. The system offers a promising hazard mitigation technique. Improvements could include data post-processing for alerts and automatic modification of the duration and numbers of sessions based on battery level and rover displacement velocity.

Keywords: GNSS, GSM, landslide, long-term, network, solar, spatial resolution, sub-centimeter.

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1557 Atlantic Sailfish (Istiophorus albicans) Distribution off the East Coast of Florida from 2003 to 2018 in Response to Sea Surface Temperature

Authors: Meredith M. Pratt

Abstract:

The Atlantic sailfish (Istiophorus albicans) ranges from 40°N to 40°S in the Western Atlantic Ocean and has great economic and recreational value for sport fishers. Off the eastern coast of Florida, charter boats often target this species. Stuart, Florida, bills itself as the sailfish capital of the world. Sailfish tag data from The Billfish Foundation and NOAA was used to determine the relationship between sea surface temperature (SST) and the distribution of Atlantic sailfish caught and released over a fifteen-year period (2003 to 2018). Tagging information was collected from local sports fishermen in Florida. Using the time and location of each landed sailfish, a satellite-derived SST value was obtained for each point. The purpose of this study was to determine if sea surface warming was associated with changes in sailfish distribution. On average, sailfish were caught at 26.16 ± 1.70°C (x̄ ± s.d.) over the fifteen-year period. The most sailfish catches occurred at temperatures ranging from 25.2°C to 25.5°C. Over the fifteen-year period, sailfish catches decreased at lower temperatures (~23°C and ~24°C) and at 31°C. At ~25°C and ~30°C there was no change in catch numbers of sailfish. From 26°C to 29°C, there was an increase in the number of sailfish. Based on these results, increasing ocean temperatures will have an impact on the distribution and habitat utilization of sailfish. Warming sea surface temperatures create a need for more policy and regulation to protect the Atlantic sailfish and related highly migratory billfish species.

Keywords: atlantic sailfish, Billfish, istiophorus albicans, sea surface temperature

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1556 Characterization of Fateh Sagar Wetland and Its Catchment Area at Udaipur City, (Raj.) India, Using High Resolution Data

Authors: Parul Bhalla, Sarvesh Palria

Abstract:

Wetlands are areas of land that are either temporarily or permanently covered by water. Wetlands exhibit enormous diversity according to their genesis, geographical location, water regime and chemistry, dominant plants and soil or sediment characteristics. The spatial and temporal characteristics of wetland in terms of turbidity and aquatic vegetation could serve as guiding tool, in conservation prioritization of wetlands. The aquatic vegetation in the wetland is an indicator of the trophic status of the wetland which has a bearing on the water quality, the turbidity level in any wetland is indicative of the quality of the water in it. To conserve and manage wetland resources, it is important to have inventory of wetland and its catchment. Fateh Sagar wetland in Udaipur city is the one of the important wetland for tourism industry and other economic activities in the region. Realizing the importance of the wetland, the present study has been taken up with the specific objective of delineation and characterization of Fateh Sagar wetland in terms of turbidity and aquatic vegetation, using high resolution satellite data such as Cartosat and LISS IV multi-temporal data, which will efficiently bring out the changes in water spread and quality parameters. The catchment of wetland has been also characterized for various features. The study leads in to takes necessary steps to conserve the wetland and its resources.

Keywords: aquatic vegetation, catchment, turbidity status, wetland

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1555 Femoropatellar Groove: An Anatomical Study

Authors: Mamatha Hosapatna, Anne D. Souza, Vrinda Hari Ankolekar, Antony Sylvan D. Souza

Abstract:

Introduction: The lower extremity of the femur is characterized by an anterior groove in which patella is held during motion. This groove separates the two lips of the trochlea (medial and lateral), prolongation of the two condyles. In humans, the lateral trochlear lip is more developed than the medial one, creating an asymmetric groove that is also specific to the human body. Because of femoral obliquity, contraction of quadriceps leads to a lateral dislocation stress on the patella, and the more elevated lateral side of the patellar groove helps the patella stays in its correct place, acting as a wall against lateral dislocation. This specific shape fits an oblique femur. It is known that femoral obliquity is not genetically determined but comes with orthostatism and biped walking. Material and Methodology: To measure the various dimensions of the Femoropatellar groove (FPG) and femoral condyle using digital image analyser. 37 dried adult femora (22 right,15 left) were used for the study. End on images of the lower end of the femur was taken. Various dimensions of the Femoropatellar groove and FP angle were measured using image J software. Results were analyzed statistically. Results: Maximum of the altitude of medial condyle of the right femur is 4.98± 0.35 cm and of the left femur is 5.20±.16 cm. Maximum altitude of lateral condyle is 5.44±0.4 and 5.50±0.14 on the right and left side respectively. Medial length of the groove is 1.30±0.38 cm on the right side and on the left side is 1.88±0.16 cm. The lateral length of the groove on the right side is 1.900±.16 cm and left side is 1.88±0.16 cm. Femoropatellar angle is 136.38◦±2.59 on the right side and on the left side it is 142.38◦±7.0 Angle and dimensions of the femoropatellar groove on the medial and lateral sides were measured. Asymmetry in the patellar groove was observed. The lateral lip was found to be wider and bigger which correlated with the previous studies. An asymmetrical patellar groove with a protruding lateral side associated with an oblique femur is a specific mark of bipedal locomotion. Conclusion: Dimensions of FPG are important in maintaining the stability of patella and also in knee replacement surgeries. The implants used in to replace the patellofemoral compartment consist of a metal groove to fit on the femoral end and a plastic disc that attaches to the undersurface of the patella. The location and configuration of the patellofemoral groove of the distal femur are clinically significant in the mechanics and pathomechanics of the patellofemoral articulation.

Keywords: femoral patellar groove, femoro patellar angle, lateral condyle, medial condyle

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1554 Dosimetry in Interventional Radiology Examinations for Occupational Exposure Monitoring

Authors: Ava Zarif Sanayei, Sedigheh Sina

Abstract:

Interventional radiology (IR) uses imaging guidance, including X-rays and CT scans, to deliver therapy precisely. Most IR procedures are performed under local anesthesia and start with a small needle being inserted through the skin, which may be called pinhole surgery or image-guided surgery. There is increasing concern about radiation exposure during interventional radiology procedures due to procedure complexity. The basic aim of optimizing radiation protection as outlined in ICRP 139, is to strike a balance between image quality and radiation dose while maximizing benefits, ensuring that diagnostic interpretation is satisfactory. This study aims to estimate the equivalent doses to the main trunk of the body for the Interventional radiologist and Superintendent using LiF: Mg, Ti (TLD-100) chips at the IR department of a hospital in Shiraz, Iran. In the initial stage, the dosimeters were calibrated with the use of various phantoms. Afterward, a group of dosimeters was prepared, following which they were used for three months. To measure the personal equivalent dose to the body, three TLD chips were put in a tissue-equivalent batch and used under a protective lead apron. After the completion of the duration, TLDs were read out by a TLD reader. The results revealed that these individuals received equivalent doses of 387.39 and 145.11 µSv, respectively. The findings of this investigation revealed that the total radiation exposure to the staff was less than the annual limit of occupational exposure. However, it's imperative to implement appropriate radiation protection measures. Although the dose received by the interventional radiologist is a bit noticeable, it may be due to the reason for using conventional equipment with over-couch x-ray tubes for interventional procedures. It is therefore important to use dedicated equipment and protective means such as glasses and screens whenever compatible with the intervention when they are available or have them fitted to equipment if they are not present. Based on the results, the placement of staff in an appropriate location led to increasing the dose to the radiologist. Manufacturing and installation of moveable lead curtains with a thickness of 0.25 millimeters can effectively minimize the radiation dose to the body. Providing adequate training on radiation safety principles, particularly for technologists, can be an optimal approach to further decreasing exposure.

Keywords: interventional radiology, personal monitoring, radiation protection, thermoluminescence dosimetry

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1553 Star Images Constructed Based on Kramer vs. Kramer

Authors: Huailei Wen

Abstract:

The Kramers vs. Kramers (1979) is a film that comprehensively examines the role and status of women under the traditional secular vision, where women have become subordinate to the patriarchal society and family. Through the construction of the protagonist Joanna's dissatisfaction with the social and ethical status quo, her struggle to subvert the existing status of women, and her return to her own self, the story comprehensively reflects the difficult journey of women, represented by Joanna, to subvert the stereotypes and return to their own selves in the specific historical context of the time, revealing the self-value of Joanna's phenomenon to modern women.

Keywords: star image, feminism, Kramers vs. Kramers, Hollywood

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1552 Digital Image Correlation Based Mechanical Response Characterization of Thin-Walled Composite Cylindrical Shells

Authors: Sthanu Mahadev, Wen Chan, Melanie Lim

Abstract:

Anisotropy dominated continuous-fiber composite materials have garnered attention in numerous mechanical and aerospace structural applications. Tailored mechanical properties in advanced composites can exhibit superiority in terms of stiffness-to-weight ratio, strength-to-weight ratio, low-density characteristics, coupled with significant improvements in fatigue resistance as opposed to metal structure counterparts. Extensive research has demonstrated their core potential as more than just mere lightweight substitutes to conventional materials. Prior work done by Mahadev and Chan focused on formulating a modified composite shell theory based prognosis methodology for investigating the structural response of thin-walled circular cylindrical shell type composite configurations under in-plane mechanical loads respectively. The prime motivation to develop this theory stemmed from its capability to generate simple yet accurate closed-form analytical results that can efficiently characterize circular composite shell construction. It showcased the development of a novel mathematical framework to analytically identify the location of the centroid for thin-walled, open cross-section, curved composite shells that were characterized by circumferential arc angle, thickness-to-mean radius ratio, and total laminate thickness. Ply stress variations for curved cylindrical shells were analytically examined under the application of centric tensile and bending loading. This work presents a cost-effective, small-platform experimental methodology by taking advantage of the full-field measurement capability of digital image correlation (DIC) for an accurate assessment of key mechanical parameters such as in-plane mechanical stresses and strains, centroid location etc. Mechanical property measurement of advanced composite materials can become challenging due to their anisotropy and complex failure mechanisms. Full-field displacement measurements are well suited for characterizing the mechanical properties of composite materials because of the complexity of their deformation. This work encompasses the fabrication of a set of curved cylindrical shell coupons, the design and development of a novel test-fixture design and an innovative experimental methodology that demonstrates the capability to very accurately predict the location of centroid in such curved composite cylindrical strips via employing a DIC based strain measurement technique. Error percentage difference between experimental centroid measurements and previously estimated analytical centroid results are observed to be in good agreement. The developed analytical modified-shell theory provides the capability to understand the fundamental behavior of thin-walled cylindrical shells and offers the potential to generate novel avenues to understand the physics of such structures at a laminate level.

Keywords: anisotropy, composites, curved cylindrical shells, digital image correlation

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1551 Application of Remote Sensing Technique on the Monitoring of Mine Eco-Environment

Authors: Haidong Li, Weishou Shen, Guoping Lv, Tao Wang

Abstract:

Aiming to overcome the limitation of the application of traditional remote sensing (RS) technique in the mine eco-environmental monitoring, in this paper, we first classified the eco-environmental damages caused by mining activities and then introduced the principle, classification and characteristics of the Light Detection and Ranging (LiDAR) technique. The potentiality of LiDAR technique in the mine eco-environmental monitoring was analyzed, particularly in extracting vertical structure parameters of vegetation, through comparing the feasibility and applicability of traditional RS method and LiDAR technique in monitoring different types of indicators. The application situation of LiDAR technique in extracting typical mine indicators, such as land destruction in mining areas, damage of ecological integrity and natural soil erosion. The result showed that the LiDAR technique has the ability to monitor most of the mine eco-environmental indicators, and exhibited higher accuracy comparing with traditional RS technique, specifically speaking, the applicability of LiDAR technique on each indicator depends on the accuracy requirement of mine eco-environmental monitoring. In the item of large mine, LiDAR three-dimensional point cloud data not only could be used as the complementary data source of optical RS, Airborne/Satellite LiDAR could also fulfill the demand of extracting vertical structure parameters of vegetation in large areas.

Keywords: LiDAR, mine, ecological damage, monitoring, traditional remote sensing technique

Procedia PDF Downloads 378