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automatic analysis and mining of remote sensing big data

Social Sensing and Big Data Computing for Disaster Management

GIBD has been conducting research on leveraging social sensing data (geo-tweets) to enhance situational awareness from several aspects including rapid flood mapping, evacuation analysis, and on-topic disaster-related information (tweets) automatic extraction. Big Geo-tweets Computing Social Sensing for Rapid Flood Mapping

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Application of data mining technology in alarm analysis of ...

Nov 1, 2020In the mining of alarm data association rules in communication network, rule A = > B indicates that alarms in A may derive alarms in B. According to the definition, association rules mining mainly includes two steps: finding frequent item sets and generating strong association rules from frequent item sets.

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Spatial Data Mining : Theory and Application - Google Books

his majors are the analytic and digital photogrammetry, remote sensing, mathematical morphology and its application in spatial databases, theories of object-oriented gis and spatial data mining in...

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Automated Inspection of Railway Tunnels' Power Line Using ... - MDPI

remote sensing Article Automated Inspection of Railway Tunnels' Power Line Using LiDAR Point Clouds Ana Sánchez-Rodríguez 1,*, Mario Soilán 1, Manuel Cabaleiro 1 and Pedro Arias 2 1 Department of Materials Engineering, Applied Mechanics and Construction, School of Industrial Engineering, University of Vigo, 36310 Vigo, Spain; [email protected] (M.S.); [email protected] (M.C.)

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Dynamic Surface Water Extent | Land Imaging Report Site - USGS

The USGS is developing a Dynamic Surface Water Extent (DSWE) product that maps surface water as detected in cloud-free, shadow-free, and snow-free pixels collected by Landsat sensors over any location in the United States and its territories. When more than one Landsat satellite is in operation, images may be collected every 8 days.

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Research - Center for Data Analytics and Biomedical Informatics

"Prospective Analysis of Large and Complex Partially Observed Temporal Social Networks," Defense Advanced Projects Agency, DARPA-GRAPHS, AFOSR award number FA 9550-12-1-0406. "A Discriminative Modeling Framework for Mining of Spatio-Temporal Data in Remote Sensing," National Science Foundation, NSF-IIS-1117433.

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Automated Remote Sensing of Underground Features - GIS Lounge

In seismic research, the use of convolutional neural networks (CNNs) has been applied to determine better positioning of sensors so that better data quality can be achieved. This has resulted in very high precision and recall rates at over 0.99.

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Processing and Analyzing Geographical Data - directionsmag

as a computer technology, gis is characterized by the heavy use of algorithms representing computational geometry (such as the polygon intersection algorithm) and topological operations.gis also deals with relatively large and complex objects such as polygons with high fractal dimensions, polygons with attached topological information, networks .

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Automatic Analysis and Mining of Remote Sensing Big Data

Automatic Analysis and Mining of Remote Sensing Big Data LI Deren;ZHANG Liangpei;XIA Guisong;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University;Collaborative Innovation Center of Geo-informatics;

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Calls for Papers (special): International Journal of Data Warehousing ...

AI and big data in the response of covid-19 pandemic. Big data analytics for business & society. Submission Procedure. Researchers and practitioners are invited to submit papers for this special theme issue on Big Data for E-Society: Realizing the Potential of Data Analytics for the Future Digital Era on or before December 30, 2022. All ...

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IRO Journals

Classification of Remote Sensing Image Scenes Using Double Feature Extraction Hybrid Deep Learning Approach ... Internet of things and big data analytics for health care with cloud computing ... Geospatial and social media analytics for emotion analysis of theme park visitors using text mining and gis Volume-2 | Issue-2. A Novel Information ...

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Hyperspectral sensing data analysis based on quasiconformal mapping ...

1 Department of Automatic Test and Control, Harbin Institute of Technology, Harbin 150080, China. 2 Science and Technology on Optical Radiation Laboratory, Beijing 100854, China. 3 Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of Technology, Fujian 350108, China. PMID: 28668006 DOI: 10.1063/1.4985634

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10 Trending Geo Science and Remote Sensing Projects - PHD TOPIC

Remote-Sensing for Agriculture. Remote Sensing of Atmosphere and Cloud. Atmosphere Remote Sensing. Hyper-Spectral Sensing. Environmental Remote Sensing /GIS and also Earth Resources Applications. High Performance Computing. Environmental Monitoring also Using Active and Passive Microwave Remote Senisng. Lidar Technology.

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A Systematic Review and IoMT Based Big Data Framework for COVID-19 ...

These layers are altogether built as a comprehensive framework that provides remote sensing, data integration, data analytics, and various applications specific to COVID-19. ... for mining big data and Tableau for big data visualization . The acquired COVID-19 data are shared to improve the efficiency of patients' diagnosis and monitor them ...

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100 Applications or Uses of LiDAR Technology

Robotic mining: Mining is a high-risk business and gathering data from the ore inside the mines can be a difficult undertaking. This is why robots are sometimes used in the mining business to penetrate the mines to reduce the risk of loss of human life. LiDAR sensors are used in obstacle detection during mining by the robotic mining vehicles.

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Mapping Glacier Changes Using Clustering Techniques on Cloud Computing ...

analysis of such large amounts of data, a problem that can be characterized as Remote Sensing Big Data analysis (Ghamisi, 2017) (Li, 2017) (Chi, 2016). Machine learning techniques have the potential to improve the analysis of RS data; however, most current machine learning algorithms are unable to properly process very large volumes of

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Emerging trends in geospatial artificial intelligence (geoAI ...

geospatial artificial intelligence (geoai) is an emerging science that utilizes advances in high-performance computing to apply technologies in ai, particularly machine learning (e.g., deep learning) and data mining to extract meaningful information from spatial big data. geoai is both a specialized field within spatial science because particular .

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Detecting, Extracting, and Monitoring Surface Water From Space Using ...

Remote sensing data sets provide spatially explicit and temporally frequent observational data of a number of physical attributes about the Earth's surface that can be appropriately leveraged to map the extent of water bodies at regional or even global scale, and to monitor their dynamics at regular and frequent time intervals.

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‪Sani muhamad isa‬ - ‪Google Scholar‬

Signal/Image Processing Biomedical Engineering Data Mining Remote Sensing. Articles Cited by Co-authors. Title. Sort. Sort by citations Sort by year Sort by title. Cited by. Cited by. ... Journal of Big Data 8 (1), ... Automatic sleep stage classification using weighted ELM and PSO on imbalanced data from single lead ECG. OK Utomo, N Surantha ...

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Feature Enhancement Network for Object Detection in Optical Remote ...

In the experiments, we evaluate our proposed method on two large-scale remote sensing image object detection datasets including DIOR and DOTA and demonstrate its effectiveness compared with the...

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Integration and Fusion of Geologic Hazard Data under Deep ... - Hindawi

discussed the landslides, but research on applying big data mining and analysis methods to landslides is rare. In the meantime, there is less research that combines big data technology and deep learning on landslides. On this basis, to explore the evaluation and analysis of highway landslides, the Image Quality Assessment (IQA)

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Advances in High-throughput Plant Phenotyping by Multi-platform Remote ...

This research topic is a unique attempt to simultaneously tackle optical and radar sensors, high-throughput phenotyping platform development, remote sensing big data analysis algorithms, quantitative inversion or evaluation models of plant traits, as well as the integration of UGV, CSV, UAV, sensors and algorithmic applications.

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Deep-learning-based information mining from ocean remote-sensing ...

in this review paper, we first systematically review two deep-learning frameworks that carry out ocean remote-sensing image classification and then present eight typical applications in ocean internal-wave/eddy/oil-spill/coastal-inundation/sea-ice/green-algae/ship/coral-reef mapping from different types of ocean remote-sensing imagery to show how .

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Agricultural remote sensing big data: Management and applications

Big data with its vast volume and complexity is increasingly concerned, developed and used for all professions and trades. Remote sensing, as one of the sources for big data, is generating earth-observation data and analysis results daily from the platforms of satellites, manned/unmanned aircrafts, and ground-based structures.

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Medical Big Data and Internet of Medical Things - Routledge & CRC Press

Big data and the Internet of Things (IoT) play a vital role in prediction systems used in biological and medical applications, particularly for resolving issues related to disease biology at different scales. Modelling and integrating medical big data with the IoT helps in building effective prediction systems for automatic recommendations of diagnosis and treatment. The ability to mine ...

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Xuanyan Chen

Responsibilities include: Map data quality control (Data check) Upgrading the data format of road cameras Improving the accuracy of ADAS raod data Contact [email protected] +86 13429831928 129 Luoyu Road, Wuhan, Hubei Provience 430018

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Statistical Data Analytics: Foundations for Data Mining, Informatics ...

A comprehensive introduction to statistical methods for data mining and knowledge discovery. Applications of data mining and 'big data' increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet ...

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Emerging trends in geospatial artificial intelligence (geoAI ...

Remote sensing is another type of spatial big data capturing characteristics of objects from a distance such as imagery from satellite sensors . Depending on the sensor, remote sensing spatial big data can be expansive in both its geographic coverage (spanning the entire globe) as well as its temporal coverage (with frequent revisit times).

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Wearable Technology Applications in Healthcare: A Literature Review

The big data generated by wearable devices is both a challenge and opportunity for researchers who can apply more artificial intelligence (AI) techniques on these data in the future. ... A smartphone is typically used to collect information and transmit it to a remote server for storage and analysis. There are two major types of wearable ...

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MS thesis in Remote Sensing - PhD Direction

For new projects in remote sensing, we listed few more unique topics below.MS thesis in Remote Sensing provides a brief overview of the historical development of remote sensing, highlighting the difficulties, research topics, systems development and other tasks in MS research. MS Thesis Topics in Remote Sensing. LIDAR and LASER Analysis

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A Review of Geological Applications of High-Spatial-Resolution Remote ...

Furthermore, a multi-standard maturity analysis of the geological applications of HR images reveals that optical remote sensing data are superior to radar data for mining, geological disaster, lithologic, and volcanic applications, but inferior for earthquake, glacial, and fault applications.

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Hyperspectral sensing data analysis based on quasiconformal mapping ...

Hyperspectral remote sensing has a strong ability of object information expression, so it provides better support for object classification. ... Hyperspectral sensing data analysis based on quasiconformal mapping-based multiple kernels learning machine ... 3 Fujian Provincial Key Lab of Big Data Mining and Applications, Fujian University of ...

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A cloud-based remote sensing data production system

2.2. Remote sensing data production system. The remote sensing production system architecture can be broadly categorized into (1) personal computers (PCs) or a single workstation that acts as the remote sensing processing system, and (2) high-performance cluster-based remote sensing processing system.

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Special Issue "Data Mining in Multi-Platform Remote Sensing" - MDPI

Jan 15, 2022Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI. Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge () for publication in this open access journal is 2500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English.

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A New Technique for Remote Sensing Image Classification Based on ...

In remote sensing image classification, distance measurements and classification criteria are equally important; and less accuracy of either would affect classification accuracy. Remote sensing image classification was performed by combining support vector machine (SVM) and k-nearest neighbor (KNN). This was based on the separability of classes ...

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Social Sensing and Big Data Computing for Rapid Flood Mapping

The system will seamlessly integrate social sensing (SS), remote sensing (RS), and in-situ sensing/stream gauges (IS) using advanced big data computing techniques to support rapid flood detection and mapping in a highly automated manner (see figure below).

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Introduction to Data Handling - University of Southern Mississippi

4 Find a Needle in a Haystack 8 Why Data Mining? The Explosive Growth of Data: from terabytes to petabytes Data collection and data availability Automated data collection tools, database systems, Web, computerized society Major sources of abundant data Business: Web, e-commerce, transactions, stocks, . Science: Remote sensing, bioinformatics, scientific

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What is remote sensing and what is it used for? - USGS

Remote sensing is the process of detecting and monitoring the physical characteristics of an area by measuring its reflected and emitted radiation at a distance (typically from satellite or aircraft). Special cameras collect remotely sensed images, which help researchers "sense" things about the Earth. Some examples are:

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Donghui Yan's Home Page - UMass D

Web log mining for anomaly detection (@Bell Labs) Analysis of remote sensing images for land use and land cover applications Analysis of tissue images for automatic scoring Analysis of Illumina 450K assay ( DNA methylation) for study of hermone replacement therapy Analysis and modeling of social networks

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Monitoring of buildings and the environment - Automatic Sensing

Wireless monitoring Industry proven, proprietary design automatic gathering station which wireless deliver data from your sensors for Automatic Sensing cloud. Power by batteries or land lines, wireless or wired and small enough to fit into boreholes. Wireless operation for up two year without any maintenance required. Online data analytics

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