scholarly journals Dynamic monitoring of urban built-up object expansion trajectories in Karachi, Pakistan with time series images and the LandTrendr algorithm

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Xinrong Yan ◽  
Juanle Wang
Keyword(s):  
Dynamic Monitoring ◽  
Detection Methods ◽  
Annual Growth Rate ◽  
Spatiotemporal Change ◽  
Urban Regions ◽  
Computing Platform ◽  
Spatiotemporal Information ◽  
Complex Process ◽  
Time Series Images ◽  
Salt And Pepper

AbstractIn the complex process of urbanization, retrieving its dynamic expansion trajectories with an efficient method is challenging, especially for urban regions that are not clearly distinguished from the surroundings in arid regions. In this study, we propose a framework for extracting spatiotemporal change information on urban disturbances. First, the urban built-up object areas in 2000 and 2020 were obtained using object-oriented segmentation method. Second, we applied LandTrendr (LT) algorithm and multiple bands/indices to extract annual spatiotemporal information. This process was implemented effectively with the support of the cloud computing platform of Earth Observation big data. The overall accuracy of time information extraction, the kappa coefficient, and average detection error were 83.76%, 0.79, and 0.57 a, respectively. These results show that Karachi expanded continuously during 2000–2020, with an average annual growth rate of 4.7%. However, this expansion was not spatiotemporally balanced. The coastal area developed quickly within a shorter duration, whereas the main newly added urban regions locate in the northern and eastern inland areas. This study demonstrated an effective framework for extract the dynamic spatiotemporal change information of urban built-up objects and substantially eliminate the salt-and-pepper effect based on pixel detection. Methods used in our study are of general promotion significance in the monitoring of other disturbances caused by natural or human activities.

scholarly journals Acoustic Vibration Approach for Detecting Faults in Hydroelectric Units: A Review

Energies ◽  
2021 ◽  
Vol 14 (23) ◽  
pp. 7840
Author(s):  
Fang Dao ◽  
Yun Zeng ◽  
Yidong Zou ◽  
Xiang Li ◽  
Jing Qian
Keyword(s):  
Fault Diagnosis ◽  
New Technology ◽  
High Sensitivity ◽  
Acoustic Vibration ◽  
Dynamic Monitoring ◽  
Detection Methods ◽  
State Monitoring ◽  
Existing Problems ◽  
Hydroelectric Generator ◽  
Continuous Dynamic

The health of the hydroelectric generator determines the safe, stable, and reliable operation of the hydropower station. In order to keep the hydroelectric generator in a better state of health and avoid accidents, it is crucial to detect its faults. In recent years, fault detection methods based on sound and vibration signals have gradually become research hotspots due to their high sensitivity, achievable continuous dynamic monitoring, and easy adaptation to complex environments. Therefore, this paper is a supplement to the existing state monitoring and fault diagnosis system of the hydroelectric generator; it divides the hydroelectric generator into two significant parts: hydro-generator and hydro-turbine, and summarizes the research and application of fault detect technology based on sound signal vibration in hydroelectric generator and introduces some new technology developments in recent years, and puts forward the existing problems in the current research and future development directions, and it is expected to provides some reference for the research on fault diagnosis of the hydroelectric generator.

scholarly journals A Spectral–Temporal Patch-Based Missing Area Reconstruction for Time-Series Images

2018 ◽  
Vol 10 (10) ◽  
pp. 1560 ◽  
Author(s):  
Wei Wu ◽  
Luoqi Ge ◽  
Jiancheng Luo ◽  
Ruohong Huan ◽  
Yingpin Yang
Keyword(s):  
Time Series ◽  
Spatial Configuration ◽  
Reference Image ◽  
Linear Regression Method ◽  
Reconstruction Method ◽  
Wide Field ◽  
Salt And Pepper Noise ◽  
Similar Measure ◽  
Time Series Images ◽  
Salt And Pepper

Clouds, cloud shadows (CCS), and numerous other factors will cause a missing data problem in passive remote sensing images. A well-known reconstruction method is the selection of a similar pixel (with an additional clear reference image) from the remaining clear part of an image to replace the missing pixel. Due to the merit of filling the missing value using a pixel acquired on the same image with the same sensor and the same date, this method is suitable for time-series applications when a time-series profile-based similar measure is utilized for selecting the similar pixel. Since the similar pixel is independently selected, the improper reference pixel or various accuracies obtained by different land covers causes the problem of salt-and-pepper noise in the reconstructed part of an image. To overcome these problems, this paper presents a spectral–temporal patch (STP)-based missing area reconstruction method for time-series images. First, the STP, the pixels of which have similar spectral and temporal evolution characteristics, is extracted using multi-temporal image segmentation. However, some STP have Missing Observations (STPMO) in the time series, which should be reconstructed. Next, for an STPMO, the most similar STP is selected as the reference STP; then, the mean and standard deviation of the STPMO is predicted using a linear regression method with the reference STP. Finally, the textural information, which is denoted by the spatial configuration of color or intensities of neighboring pixels, is extracted from the clear temporal-adjacent STP and “injected” into the missing area to obtain synthetic cloud-free images. We performed an STP-based missing area reconstruction experiment in Jiangzhou, Chongzuo, Guangxi with time-series images acquired by wide field view (WFV) onboard Chinese Gao Fen 1 on 12 different dates. The results indicate that the proposed method can effectively recover the missing information without salt-and-pepper noise in the reconstructed area; also, the reconstructed part of the image is consistent with the clear part without a false edge. The results confirm that the spectral information from the remaining clear part of the same image and textural information from the temporal-adjacent image can create seamless time-series images.

scholarly journals Unsupervised Multitemporal Building Change Detection Framework Based on Cosegmentation Using Time-Series SAR

2021 ◽  
Vol 13 (3) ◽  
pp. 471
Author(s):  
Kaiyu Zhang ◽  
Xikai Fu ◽  
Xiaolei Lv ◽  
Jili Yuan
Keyword(s):  
Time Series ◽  
Change Detection ◽  
Accuracy Assessment ◽  
Detection Methods ◽  
Sar Images ◽  
Assessment Index ◽  
Moment Maps ◽  
Marketing Planning ◽  
Frequency Map ◽  
Time Series Images

Building change detection using remote sensing images is essential for various applications such as urban management and marketing planning. However, most change detection approaches can only detect the intensity or type of change. The aim of this study is to dig for more change information from time-series synthetic aperture radar (SAR) images, such as the change frequency and the change moments. This paper proposes a novel multitemporal building change detection framework that can generate change frequency map (CFM) and change moment maps (CMMs) from multitemporal SAR images. We first give definitions of CFM and CMMs. Then we generate change feature using four proposed generators. After that, a new cosegmentation method combining raw images and change feature is proposed to divide time-series images into changed and unchanged areas separately. Secondly, the proposed cosegmentation and the morphological building index (MBI) are combined to extract changed building objects. Then, the logical conjunction between the cosegmentation results and the binarized MBI is performed to recognize every moment of change. In the post-processing step, we use fragment removal to increase accuracy. Finally, we propose a novel accuracy assessment index for CFM. We call this index average change difference (ACD). Compared to the traditional multitemporal change detection methods, our method outperforms other approaches in terms of both qualitative results and quantitative indices of ACD using two TerraSAR-X datasets. The experiments show that the proposed method is effective in generating CFM and CMMs.

scholarly journals Analysis of high-rise building safety detection methods based on big data and artificial intelligence

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772093530
Author(s):  
Jiaojiao Xu ◽  
Chuanjie Yan ◽  
Yangyang Su ◽  
Yong Liu
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Model Building ◽  
Test System ◽  
Dynamic Monitoring ◽  
Detection Methods ◽  
Sensor Technology ◽  
Land Resource ◽  
Time Dynamic ◽  
High Rise

With rapid industrialization, the construction of high-rise buildings is a good and effective solution to the rational and effective use of land resources and alleviation of existing land resource tensions. Especially in the construction process, if there is a problem with the pile foundation, the building will inevitably be tilted, which will directly affect the personal safety of the construction workers and resident users. The experiments in this article use the concept of big data to divide the system into modules such as data collection, data preprocessing, feature extraction, prediction model building, and model application in order to provide massive data storage and parallel computing services to form a security test system. The experimental data show that wireless sensor technology is applied to the inclination monitoring of buildings, and a monitoring system based on wireless inclination sensors is designed to enable real-time dynamic monitoring of buildings to ensure human safety. When the experimental model frame is stable under normal environmental conditions, a nonstationary vibration is artificially produced for a period of time from the outside world, which is about 60 s higher than the traditional method, and the efficiency is also increased by about 80%, a situation where a building has a reversible tilt change.

scholarly journals Implementing canny edge detection algorithm for noisy image

2020 ◽  
Vol 9 (4) ◽  
pp. 1404-1410
Author(s):  
Ehsan Akbari Sekehravani ◽  
Eduard Babulak ◽  
Mehdi Masoodi
Keyword(s):  
Edge Detection ◽  
Median Filter ◽  
Detection Algorithm ◽  
Detection Methods ◽  
Canny Edge Detection ◽  
Edge Detection Algorithm ◽  
Canny Edge ◽  
Significant Stage ◽  
Salt And Pepper ◽  
Canny Edge Detection Algorithm

Edge detection is a significant stage in different image processing operations like pattern recognition, feature extraction, and computer vision. Although the Canny edge detection algorithm exhibits high precision is computationally more complex contrasted to other edge detection methods. Due to the traditional Canny algorithm uses the Gaussian filter, which gives the edge detail represents blurry also its effect in filtering salt-and-pepper noise is not good. In order to resolve this problem, we utilized the median filter to maintain the details of the image and eliminate the noise. This paper presents implementing and enhance the accuracy of Canny edge detection for noisy images. Results present that this proposed method can definitely overcome noise disorders, preserve the edge useful data, and likewise enhance the edge detection precision.

Flexible Wireless Research Oriented System for Human Performance Studies

2008 ◽  
Author(s):  
Jonathan M. Hill ◽  
Majdi Atallah ◽  
Kevin Ball
Keyword(s):  
Performance Studies ◽  
Human Performance ◽  
Low Cost ◽  
Dynamic Monitoring ◽  
Computing Platform ◽  
Gate Arrays ◽  
Research Platform ◽  
Field Programmable ◽  
Programmable Gate Arrays ◽  
Performance Research

The availability of low-cost field programmable gate arrays (FPGAs) and wireless technologies provides new opportunities for the development of a wearable computing platform for human performance research. Our goal is a flexible research platform that is configurable for a number of sensor types, provides various options for information processing, and is useful in various simple protocols. This dynamic monitoring device will enable further investigations of the feasibility of use in clinical research and practice settings.

Complex Image Recognition Method of Train Wheels Based on Contour Feature

2014 ◽  
Vol 937 ◽  
pp. 409-415
Author(s):  
Dong Yao Jia ◽  
Po Hu
Keyword(s):  
Image Recognition ◽  
Detection Algorithm ◽  
Dynamic Monitoring ◽  
Detection Methods ◽  
Constraint Condition ◽  
Recognition Method ◽  
Complex Image ◽  
Contour Feature ◽  
Identification Function ◽  
Fast Dynamic

At present, most of the domestic train wheel detection is still manual. Existing image detection methods do not fully consider the characteristics of wheel profiles, as the algorithm is very complicated, they do not apply to fast dynamic monitoring. The paper proposes a dynamic image recognition method of train wheels based on contour feature. Firstly, wheel contour curve is extracted using RCD circular arc detection algorithm with constraint condition. Then, after analyzing the wheel contour curves, vector contour is constructed to describe them. At last, images of wheels are rapid recognized, and the recognition is based on identification function. Experimental results show that this method can achieve 95% accuracy when the similarity of complete wheel is set to 0.98 or more. This method can adapt to railway environment and has a certain application value.

DNA nick end labeling: a reliable marker for apoptosis?

1995 ◽  
Vol 53 ◽  
pp. 962-963
Author(s):  
Anne F. Bushnell ◽  
Sarah Webster ◽  
Lynn S. Perlmutter
Keyword(s):  
Cell Death ◽  
Cultured Cells ◽  
Apoptotic Cell ◽  
Morphological Characteristics ◽  
Detection Methods ◽  
Tissue Preparation ◽  
Preparation Methods ◽  
Dna Laddering ◽  
Disease States ◽  
Reliable Marker

Apoptosis, or programmed cell death, is an important mechanism in development and in diverse disease states. The morphological characteristics of apoptosis were first identified using the electron microscope. Since then, DNA laddering on agarose gels was found to correlate well with apoptotic cell death in cultured cells of dissimilar origins. Recently numerous DNA nick end labeling methods have been developed in an attempt to visualize, at the light microscopic level, the apoptotic cells responsible for DNA laddering.The present studies were designed to compare various tissue processing techniques and staining methods to assess the occurrence of apoptosis in post mortem tissue from Alzheimer's diseased (AD) and control human brains by DNA nick end labeling methods. Three tissue preparation methods and two commercial DNA nick end labeling kits were evaluated: the Apoptag kit from Oncor and the Biotin-21 dUTP 3' end labeling kit from Clontech. The detection methods of the two kits differed in that the Oncor kit used digoxigenin dUTP and anti-digoxigenin-peroxidase and the Clontech used biotinylated dUTP and avidinperoxidase. Both used 3-3' diaminobenzidine (DAB) for final color development.

ultrastructural process of intestinal wound healing

1995 ◽  
Vol 53 ◽  
pp. 1024-1025
Author(s):  
Rick L. Vaughn ◽  
Shailendra K. Saxena ◽  
John G. Sharp
Keyword(s):  
Wound Healing ◽  
Epithelial Cells ◽  
Smooth Muscles ◽  
Microscopic Level ◽  
Light Microscopic Level ◽  
Ileal Mucosa ◽  
Wound Model ◽  
Serosal Surface ◽  
Complex Process ◽  
Orderly Fashion

We have developed an intestinal wound model that includes surgical construction of an ileo-cecal patch to study the complex process of intestinal wound healing. This allows approximation of ileal mucosa to the cecal serosa and facilitates regeneration of ileal mucosa onto the serosal surface of the cecum. The regeneration of ileal mucosa can then be evaluated at different times. The wound model also allows us to determine the rate of intestinal regeneration for a known size of intestinal wound and can be compared in different situations (e.g. with and without EGF and Peyer’s patches).At the light microscopic level it appeared that epithelial cells involved in regeneration of ileal mucosa originated from the enlarged crypts adjacent to the intestinal wound and migrated in an orderly fashion onto the serosal surface of the cecum. The migrating epithelial cells later formed crypts and villi by the process of invagination and evagination respectively. There were also signs of proliferation of smooth muscles underneath the migratory epithelial cells.

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