Preparation of 3 d model of international space stationRabi Shrestha
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Our project aims to show the 3D model of satellite communication station. From the 3D model one can get idea about the satellite communication. It also shows ground station and space station. We have included one satellite space station and 3 ground sation. Two of them are receiver and one is transmitter.
A force directed approach for offline gps trajectory mapeXascale Infolab
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SIGSPATIAL 2018 paper
A Force-Directed Approach for Offline GPS Trajectory Map Matching
Efstratios Rappos (University of Applied Sciences of Western Switzerland (HES-SO)),
Stephan Robert (University of Applied Sciences of Western Switzerland (HES-SO)),
Philippe CudrĂŠ-Mauroux (University of Fribourg)
Preparation of 3 d model of international space stationRabi Shrestha
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Our project aims to show the 3D model of satellite communication station. From the 3D model one can get idea about the satellite communication. It also shows ground station and space station. We have included one satellite space station and 3 ground sation. Two of them are receiver and one is transmitter.
A force directed approach for offline gps trajectory mapeXascale Infolab
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SIGSPATIAL 2018 paper
A Force-Directed Approach for Offline GPS Trajectory Map Matching
Efstratios Rappos (University of Applied Sciences of Western Switzerland (HES-SO)),
Stephan Robert (University of Applied Sciences of Western Switzerland (HES-SO)),
Philippe CudrĂŠ-Mauroux (University of Fribourg)
Making the most of raster data from the arcgis living atlas of the worldAileen Buckley
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The image services in the Living Atlas of the World are raster datasets. They work and are used just like the raster datasets on your computerâs hard drive. It requires a little more effort to explore, learn about, and gain trust in the data behind image services. We will show you how to confidently minimize this effort and start saving time as you join the ranks of those who have discovered the value of Web GIS.
Making the most of raster data from the arcgis living atlas of the worldAileen Buckley
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Whatâs in the Living Atlas, focusing on imagery and raster data
How to find that content and add it to a project in ArcGIS Pro, and
How to use it in raster analysis.
Large Scale Tag Recommendation Using Different Image RepresentationsRabeeh Abbasi
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Nowadays, geographical coordinates (geo-tags), social annotations (tags), and low-level features are available in large image datasets. In our paper, we exploit these three kinds of image descriptions to suggest possible annotations for new images uploaded to a social tagging system. In order to compare the benefits each of these description types brings to a tag recommender system on its own, we investigate them independently of each other. First, the existing data collection is clustered separately for the geographical coordinates, tags, and low-level features. Additionally, random clustering is performed in order to provide a baseline for experimental results. Once a new image has been uploaded to the system, it is assigned to one of the clusters using either its geographical or low-level representation. Finally, the most representative tags for the resulting cluster are suggested to the user for annotation of the new image. Large-scale experiments performed for more than 400,000 images compare the different image representation techniques in terms of precision and recall in tag recommendation.
Rasters contain observed or derived data, or both.
Data sources include:
Sample points monitoring stations, elevation points): Resulting raster: air pollution surface, digital elevation model
Classification of imagery (e.g., satellite image): Resulting raster: land-cover grid
Conversion of vector data
2018 GIS in the Rockies Vendor Showcase (Th): ERDAS Imagine What's New and Ti...GIS in the Rockies
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This presentation will cover the latest release highlights as well as tips and tricks for processing LiDAR data, ERDAS Imagine modeling capabilities and a roadmap for cloud based processing.
The session will highlight exploiting the full spectrum of LiDAR from viewing and measurements to surface and terrain modeling as well as extraction of point clouds from imagery.
In addition we will discuss the migration of our image exploitation capabilities from the desktop to the cloud.
http://www.fao.org/globalsoilpartnership
This Presentation was made during the Digital Soil Mapping training that took place in Amman - Jordan from 29 November - 7 December 2015, and it presents the Remote sense analysis
Š FAO: http://www.fao.org
Making the most of raster data from the arcgis living atlas of the worldAileen Buckley
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The image services in the Living Atlas of the World are raster datasets. They work and are used just like the raster datasets on your computerâs hard drive. It requires a little more effort to explore, learn about, and gain trust in the data behind image services. We will show you how to confidently minimize this effort and start saving time as you join the ranks of those who have discovered the value of Web GIS.
Making the most of raster data from the arcgis living atlas of the worldAileen Buckley
Â
Whatâs in the Living Atlas, focusing on imagery and raster data
How to find that content and add it to a project in ArcGIS Pro, and
How to use it in raster analysis.
Large Scale Tag Recommendation Using Different Image RepresentationsRabeeh Abbasi
Â
Nowadays, geographical coordinates (geo-tags), social annotations (tags), and low-level features are available in large image datasets. In our paper, we exploit these three kinds of image descriptions to suggest possible annotations for new images uploaded to a social tagging system. In order to compare the benefits each of these description types brings to a tag recommender system on its own, we investigate them independently of each other. First, the existing data collection is clustered separately for the geographical coordinates, tags, and low-level features. Additionally, random clustering is performed in order to provide a baseline for experimental results. Once a new image has been uploaded to the system, it is assigned to one of the clusters using either its geographical or low-level representation. Finally, the most representative tags for the resulting cluster are suggested to the user for annotation of the new image. Large-scale experiments performed for more than 400,000 images compare the different image representation techniques in terms of precision and recall in tag recommendation.
Rasters contain observed or derived data, or both.
Data sources include:
Sample points monitoring stations, elevation points): Resulting raster: air pollution surface, digital elevation model
Classification of imagery (e.g., satellite image): Resulting raster: land-cover grid
Conversion of vector data
2018 GIS in the Rockies Vendor Showcase (Th): ERDAS Imagine What's New and Ti...GIS in the Rockies
Â
This presentation will cover the latest release highlights as well as tips and tricks for processing LiDAR data, ERDAS Imagine modeling capabilities and a roadmap for cloud based processing.
The session will highlight exploiting the full spectrum of LiDAR from viewing and measurements to surface and terrain modeling as well as extraction of point clouds from imagery.
In addition we will discuss the migration of our image exploitation capabilities from the desktop to the cloud.
http://www.fao.org/globalsoilpartnership
This Presentation was made during the Digital Soil Mapping training that took place in Amman - Jordan from 29 November - 7 December 2015, and it presents the Remote sense analysis
Š FAO: http://www.fao.org
WorldPosta Professional Email For BusinessNeviTech
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WorldPosta; Business Cloud Mail Solution, that offers the next generation of messaging technologies so you can fit the modern business challenges.
Premium Availability, Huge Storage, Outlook Anywhere, Backup, Highest Security, Powerful Control and Fair Price are your vocabulary when getting WorldPosta.
ďź Large Mailboxes: 200 GB Mailbox storage with availability to send larger attached files up to 35 MB.
ďź High Availability: WorldPosta servers are integrated with Amazon (AWS); which guarantees the scalability, high availability and stability in a premium level.
ďź Powerful Control: Enhanced and Friendly Control Panel, Mobile control and Huge Library of policies.
ďź Backup: user can restore his (Shift + Delete) items within 60 days.
ďź Outlook Anywhere: â access your emails, calendar, contacts and even sent items anywhere by Outlook client, Web client, mobile...
ďź Security: Multilayer of Firewall and Antivirus, Intelligent Anti-Spam and End-to-End Encryption.
ďź Always Up to Date: No patches, No Downtime, No technical skills need.
ďź Shared Calendar: and Centralized Contacts information between colleagues in the same domain.
ďź Incredible Search: find your desired message in your large mailbox in no time!!
ďź Free 24/7 Technical support.
For a new better version of this tutorial see my Google Slides with embedded videos.
https://docs.google.com/presentation/d/1MftEOT3uvYpCVwUaLMhsesm5Que-Kr7GQRV4pKZ2SNQ/edit?usp=sharing
This is a 2019 tutorial on how to do watershed delineation using ArcMap 10. It is an open education resource. Please let me know if you find it useful or see something that could be improved. Feel free to use it for teaching Geographic Information Science.
For a new better version of this tutorial see my Google Slides with embedded videos.
https://docs.google.com/presentation/d/1MftEOT3uvYpCVwUaLMhsesm5Que-Kr7GQRV4pKZ2SNQ/edit?usp=sharing
This is a 2016 tutorial on how to do watershed delineation using ArcMap 10. It is an open education resource. Please let me know if you find it useful or see something that could be improved. Feel free to use it for teaching Geographic Information Science.
Automated features extraction from satellite images.HimanshuGupta1081
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This is the final year civil engineering project presentation in which different features i.e. Buildings, Road Network, Vegetation and Water are extracted automatically from satellite images with the help of Ecognition software. We have done our analysis on satellite images of sikar, rajasthan. In this project object based image analysis (OBIA) approach are used.
The first open-source platform for sharing crowd-sourced asteroid imagery! Including observations that have already have been logged, as well as newly observed Near Earth Objects.
ACT Science Coffee, Towards super-resolution for astronomical applications, A...Advanced-Concepts-Team
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Super-resolution techniques enable measurements beyond the resolution limit
of conventional systems. Although such techniques have already been
demonstrated in some fields like microscopy, there is still no practically
applicable method that would enable super-resolution in astronomy.
By applying quantum estimation theory, we have taken the first steps towards a
super-resolution strategy that could find various applications in astronomy,
from the characterization of binary star and exoplanet systems, to high-precision
measurement of stellar magnetic fields. In this talk, the main principles,
potential applications, and further challenges of our method will be discussed.
In recent years, statistical machine learning approaches have been extremely popular largely due to its superior performance in prediction. Of all the commonly used machine learning tools, the gradient boosting tree is usually the favored vehicle for many practitioners. On the popular data analytics competition platform Kaggle, gradient boosting is the winning algorithm for almost every structured data. Besides its superior prediction performance, the gradient boosting trees also enjoy the interpretability of a non-parametric additive model and its fitting algorithm can be paralleled. In this project, we extend this powerful machine learning technique to the realm of spatial data analysis. The proposed approach does not require any parametric assumption on spatial correlations and enjoy all the advantages of gradient boosting. We illustrate the potential of the data with application on prediction of HIV new diagnose rates for all counties of the United States.
(Paper Review)A versatile learning based 3D temporal tracker - scalable, robu...MYEONGGYU LEE
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review date: 2018/04/09 (by Meyong-Gyu.LEE @Soongsil Univ.)
Eng review of 'A versatile learning based 3D temporal tracker - scalable, robust, online'(ICCV 2015)
Using Deep Learning to Derive 3D Cities from Satellite ImageryAstraea, Inc.
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Detection and reconstruction of 3D buildings in urban areas has been a hot topic of research due to its many applications, including 3D population density studies, emergency planning, and building value estimation. Standard approaches to extract building footprint and measure building height rely on either aerial or space borne point cloud data, which in many areas is unavailable. In contrast, high resolution satellite imagery has become more readily available in recent years, and could provide enough information to estimate a buildingâs height. Recent successes of deep learning on semantic segmentation have shown that convolutional neural networks can be effective tools at extracting 2D building footprints. Using a digital surface model derived using FOSS and LiDAR data as ground truth, this study goes a step further by employing state of the art deep learning architectures such as U-net to infer both building footprints and estimated building heights in one pass from a single satellite image. This application of open deep learning frameworks can bring the benefits of 3D cities to a larger portion of the world.
Unsupervised Building Extraction from High Resolution Satellite Images Irresp...CSCJournals
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Extraction of geospatial data from the photogrammetric sensing images becomes more and more important with the advances in the technology. Today Geographic Information Systems are used in a large variety of applications in engineering, city planning and social sciences. Geospatial data like roads, buildings and rivers are the most critical feeds of a GIS database. However, extracting buildings is one of the most complex and challenging tasks as there exist a lot of inhomogeneity due to varying hierarchy. The variety of the type of buildings and also the shapes of rooftops are very inconstant. Also in some areas, the buildings are placed irregularly or too close to each other. For these reasons, even by using high resolution IKONOS and QuickBird satellite imagery the quality percentage of building extraction is very less. This paper proposes a solution to the problem of automatic and unsupervised extraction of building features irrespective of rooftop structures in multispectral satellite images. The algorithm instead of detecting the region of interest, eliminates areas other than the region of interest which extract the rooftops completely irrespective of their shapes. Extensive tests indicate that the methodology performs well to extract buildings in complex environments.
This project is to retrieve the similar geographic images from the dataset based on the features extracted.
Retrieval is the process of collecting the relevant images from the dataset which contains more number of
images. Initially the preprocessing step is performed in order to remove noise occurred in input image with
the help of Gaussian filter. As the second step, Gray Level Co-occurrence Matrix (GLCM), Scale Invariant
Feature Transform (SIFT), and Moment Invariant Feature algorithms are implemented to extract the
features from the images. After this process, the relevant geographic images are retrieved from the dataset
by using Euclidean distance. In this, the dataset consists of totally 40 images. From that the images which
are all related to the input image are retrieved by using Euclidean distance. The approach of SIFT is to
perform reliable recognition, it is important that the feature extracted from the training image be
detectable even under changes in image scale, noise and illumination. The GLCM calculates how often a
pixel with gray level value occurs. While the focus is on image retrieval, our project is effectively used in
the applications such as detection and classification.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
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Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
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http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasnât one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Thinking of getting a dog? Be aware that breeds like Pit Bulls, Rottweilers, and German Shepherds can be loyal and dangerous. Proper training and socialization are crucial to preventing aggressive behaviors. Ensure safety by understanding their needs and always supervising interactions. Stay safe, and enjoy your furry friends!
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
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Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
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Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
1. Intro to Raster
Prof. Dr. Sajid Rashid Ahmad
sajidpu@yahoo.com
Atiqa Ijaz Khan _ Demonstrator
atiqa_ss09@yahoo.com
2. Raster
⢠âA raster is a matrix of identically squared size cells.â
⢠Each cell store a specific value.
⢠Like: rainfall, temperature, elevation etc.
⢠It could be from integers or real numbers.
⢠Raster does not have associated attribute table, unless created by some means.
⢠It can never have text data in it.
⢠Examples:
⢠Satellite images, scanned map, aerial photographs etc.
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3. Tuesday, March 3, 2015Institute of Geology, University of the Punjab
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Satellite Imagery
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Topo-sheet
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Aerial Photography
6. Raster Attribute
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Raster does not have associated attribute table, unless
created by some means.
7. Pyramids
⢠Pyramids are used to improve the performance.
⢠They are down-sampled version of the original raster.
⢠Each successive layer is down-sampled at scale of 2:1.
⢠Every successive layer is down-sampled at a fixed resolution.
⢠Only that particular resolution is accessed for display.
⢠This process speeds up the drawing.
⢠Larger datasets required more time to create pyramids as compare to smaller
ones.
⢠Pyramids are created for each raster datasets individually, not as a whole for
raster mosaics or catalog.
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8. ⢠Pyramids are the version of the raster datasets.
⢠They are used to control the speed of the drawing a raster as one zoom in
or out.
⢠Generally, two types of resolutions are used:
⢠Coarser: As zoom out.
⢠Finer: As zoom in.
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9. Tuesday, March 3, 2015Institute of Geology, University of the Punjab
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Pyramid Performance
Zoom In
Zoom Out
10. Types of Pyramids
⢠Two types of pyramids files:
⢠Reduced Resolution Datasets (.rrd) created in ERDAS (a Remote Sensing software)
⢠Overview (.ovr) created in ArcGIS 10.1
⢠ArcGIS can read both of these files.
⢠But only write Overview file.
⢠An overview file is created in two cases:
⢠File format is not an ERDAS IMAGINE file (.img)
⢠Pyramids are created in ArcGIS 10.1 or higher.
⢠Benefit over (.rrd) file:
⢠Overview file (.ovr) controls the compression type and quality of pyramids.
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11. Pyramids Re-sampling Techniques
⢠3 types of techniques are available with pyramids.
⢠Nearest:
⢠Uses the values of the closest cell to assign value. It is by Default.
⢠Examples: Discrete raster data, like land use map, scanned map etc.
⢠Bilinear:
⢠Uses the weighted average distance for the 4 nearest cells to assign value.
⢠Examples: Continuous data, like satellite images, or aerial photography, 1-bit TIFFs or
IMGs
⢠Cubic:
⢠Uses a smooth curve to pass through the 16 nearest cellâs centers to assign value.
⢠Examples: Continuous data, like satellite images, or aerial photography.
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12. Tuesday, March 3, 2015Institute of Geology, University of the Punjab
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Pyramids Re-sampling
Techniques
13. Hill Shade Effect
⢠It adds a hypothetical source of illumination to light up the areas for each cell of
raster.
⢠It usually enhances the visualization for display.
⢠It is also known as âShaded Reliefâ.
⢠It simulates how the terrain will look like as with the interaction between sunlight
and surface.
⢠It has integer values from 0 â 255.
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14. Parameters of Hill Shade Effect
⢠Azimuth
⢠The azimuth is the angular direction of the sun, measured from north in clockwise
degrees from 0 to 360.
⢠An azimuth of 90º is east.
⢠The default azimuth is 315º (NW).
⢠Altitude
⢠The altitude is the slope or angle of the illumination source above the horizon.
⢠The units are in degrees, from 0 (on the horizon) to 90 (overhead).
⢠The default is 45 degrees.
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Azimuth Altitude
Azimuth: 315Âş
Altitude: 45Âş
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