igarss11_2.ppt
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The document presents a method for detecting estuary wetlands in SAR images using the spatial chaotic model (SCM). SCM models the fractal geometry of SAR signals using fractal dimension. Wetland areas like mud flats have lower fractal dimensions than other land types. The method estimates fractal dimension across the image then applies thresholding to the fractal dimension values to detect wetland pixels. It was tested on a SAR image of a nature reserve site containing sandy beaches, marshes and mud flats, with preliminary results finding mud flats were detectable using this approach.
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This document discusses recent advances in synthetic aperture radar (SAR) enhancement and information extraction. It summarizes three methods presented in the paper: 1) A wavelet-based despeckling and information extraction method using a Generalized Gauss-Markov Random Field (GGMRF) and Bayesian inference; 2) A method using GMRF and an Auto-binomial model with Bayesian inference; 3) A third method that also uses GMRF and an Auto-binomial model with Bayesian inference. The despeckling performance of these three methods is compared and texture parameter estimation is presented.
1998278
This document summarizes an approach for classifying seafloor textures in high resolution sonar images using multiscale discriminant analysis. The approach extracts statistical parameters from wavelet decompositions of the sonar images at multiple scales. A discriminant analysis is then used to reduce the feature space and generate an optimal subspace for classification. The method was tested on real sonar images containing speckle noise and showed improved classification of seabed textures like pebbles, dunes, ridges and sand.
Digital Image Processing
Digital image processing involves applying computer algorithms to digital images. It allows a wide range of algorithms to be used and avoids problems like noise and distortion. Digital images are made of pixels, the discrete picture elements. Sampling rate must be high enough to capture required detail. Karst terrain has distinctive features like sinkholes and caves formed by limestone dissolution in water. Remote sensing data at different resolutions can identify karst landforms of various sizes for mapping and analysis.
EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
Radar images can reveal information about the shape of the surface terrain as well as its
physical and biophysical properties. Radar images have long been used in geological studies to
map structural features that are revealed by the shape of the landscape. Radar imagery also has
applications in vegetation and crop type mapping, landscape ecology, hydrology, and
volcanology. Image processing is using for detecting for objects in radar images. Edge
detection; which is a method of determining the discontinuities in gray level images; is a very
important initial step in Image processing. Many classical edge detectors have been developed
over time. Some of the well-known edge detection operators based on the first derivative of the
image are Roberts, Prewitt, Sobel which is traditionally implemented by convolving the image
with masks. Also Gaussian distribution has been used to build masks for the first and second
derivative. However, this distribution has limit to only symmetric shape. This paper will use to
construct the masks, the Weibull distribution which was more general than Gaussian because it
has symmetric and asymmetric shape. The constructed masks are applied to images and we
obtained good results.
EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
Radar images can reveal information about the shape of the surface terrain as well as its physical and biophysical properties. Radar images have long been used in geological studies to
map structural features that are revealed by the shape of the landscape. Radar imagery also has applications in vegetation and crop type mapping, landscape ecology, hydrology, and
volcanology. Image processing is using for detecting for objects in radar images. Edge detection; which is a method of determining the discontinuities in gray level images; is a very
important initial step in Image processing. Many classical edge detectors have been developed over time. Some of the well-known edge detection operators based on the first derivative of the image are Roberts, Prewitt, Sobel which is traditionally implemented by convolving the image with masks. Also Gaussian distribution has been used to build masks for the first and second derivative. However, this distribution has limit to only symmetric shape. This paper will use to construct the masks, the Weibull distribution which was more general than Gaussian because it has symmetric and asymmetric shape. The constructed masks are applied to images and we obtained good results.
A statistical assessment of GDEM using LiDAR data
This document presents a statistical assessment of the accuracy of the Global Digital Elevation Model (GDEM) using LiDAR data. It proposes a framework to evaluate GDEM accuracy by assessing absolute elevation errors, positional accuracy of hydrological features, surface roughness representation, and user satisfaction. Case studies in four areas show regression models can evaluate elevation fit, with an R-squared value above 0.995 indicating satisfactory accuracy for GDEM in areas of medium relief. The document concludes GDEM has little usefulness in areas of low relief.
Rocca.ppt
The document discusses advances in SAR interferometry over the past 20 years for measuring millimeter-scale land motion. Key points include:
1) Revisit times have decreased from 35 days with ERS-1 to 12 days with Sentinel-1 constellations, improving ground motion recovery.
2) Persistent scatterer interferometry techniques like SqueeSAR can now measure motions to the millimeter by using all available interferograms.
3) Atmospheric phase screens still limit accuracy but can be estimated and removed using numerical weather models, GPS, and other independent datasets.
4) Future opportunities include using wide Doppler bandwidths from satellites to achieve high-resolution azimuth measurements of ground motion.
Taramelli Melelli
The document summarizes research using remote sensing data and quantitative analysis to identify and characterize alluvial fans. Satellite imagery was used to calculate surface roughness as a proxy for distinguishing alluvial areas. Digital elevation models from SRTM data were analyzed to delineate geometric parameters of landforms. A fuzzy logic model populated with roughness, elevation, and curvature data was able to classify terrain into categories corresponding to different parts of alluvial fans. The method provided initial identification and spatial extent of alluvial fans while also assigning fuzzy membership values.
Noise Removal in SAR Images using Orthonormal Ridgelet Transform
Development in the field of image processing for reducing speckle noise from digital images/satellite images is a challenging task for image processing applications. Previously many algorithms were proposed to de-speckle the noise in digital images. Here in this article we are presenting experimental results on de-speckling of Synthetic Aperture RADAR (SAR) images. SAR images have wide applications in remote sensing and mapping the surfaces of all planets. SAR can also be implemented as "inverse SAR" by observing a moving target over a substantial time with a stationary antenna. Hence denoising of SAR images is an essential task for viewing the information. Here we introduce a transformation technique called ―Ridgelet‖, which is an extension level of wavelet. Ridgelet analysis can be done in the similar way how wavelet analysis was done in the Radon domain as it translates singularities along lines into point singularities under different frequencies. Simulation results were show cased for proving that proposed work is more reliable than compared to other de-speckling processes, and the quality of de-speckled image is measured in terms of Peak Signal to Noise Ratio and Mean Square Error
Noise Removal in SAR Images using Orthonormal Ridgelet Transform
Development in the field of image processing for reducing speckle noise from digital images/satellite images is a challenging task for image processing applications. Previously many algorithms were proposed to de-speckle the noise in digital images. Here in this article we are presenting experimental results on de-speckling of Synthetic Aperture RADAR (SAR) images. SAR images have wide applications in remote sensing and mapping the surfaces of all planets. SAR can also be implemented as "inverse SAR" by observing a moving target over a substantial time with a stationary antenna. Hence denoising of SAR images is an essential task for viewing the information. Here we introduce a transformation technique called ―Ridgelet‖, which is an extension level of wavelet. Ridgelet analysis can be done in the similar way how wavelet analysis was done in the Radon domain as it translates singularities along lines into point singularities under different frequencies. Simulation results were show cased for proving that proposed work is more reliable than compared to other de-speckling processes, and the quality of de-speckled image is measured in terms of Peak Signal to Noise Ratio and Mean Square Error.
Delineating faults using multi-trace seismic attributes: Example from offshor...
1) The document describes a workflow for delineating faults in a 3D seismic dataset from offshore Niger Delta using multi-trace seismic attributes.
2) Dip-steering and multi-trace similarity attributes were computed to highlight discontinuities and improve fault detection. This revealed a major NE-SW trending strike-slip fault separating compressional deformation to the north and extensional deformation to the south.
3) Vertical cross-sections show faults and fault zones are more clearly resolved when computing multi-trace similarity along structural dips using dip-steering, rather than directly from seismic reflectivity alone.
SPECTROSCOPIC CONFIRMATION OF THE EXISTENCE OF LARGE, DIFFUSE GALAXIES IN THE...
We recently identified a population of low surface brightness objects in the field of the z = 0.023 Coma cluster,
using the Dragonfly Telephoto Array. Here we present Keck spectroscopy of one of the largest of these “ultradiffuse
galaxies” (UDGs), confirming that it is a member of the cluster. The galaxy has prominent absorption
features, including the Ca II H+K lines and the G-band, and no detected emission lines. Its radial velocity of
cz=6280±120 km s−1 is within the 1σ velocity dispersion of the Coma cluster. The galaxy has an effective
radius of 4.3 ± 0.3 kpc and a Sérsic index of 0.89 ± 0.06, as measured from Keck imaging. We find no indications
of tidal tails or other distortions, at least out to a radius of ∼2re. We show that UDGs are located in a previously
sparsely populated region of the size—magnitude plane of quiescent stellar systems, as they are ∼6 mag fainter
than normal early-type galaxies of the same size. It appears that the luminosity distribution of large quiescent
galaxies is not continuous, although this could largely be due to selection effects. Dynamical measurements are
needed to determine whether the dark matter halos of UDGs are similar to those of galaxies with the same
luminosity or to those of galaxies with the same size.
Using Sentinel-1 with InSAR Land Subsidence Presentor Minh
This document discusses the use of satellite radar interferometry and atmospheric modeling to measure land subsidence in a study region. It finds that correcting for atmospheric effects using the ERA-Interim model reduces noise and the correlation between pixel elevation and measured displacement in interferograms. Deformation rate maps from Sentinel-1A and TerraSAR-X data show broad subsidence in some areas and adjacent subsidence and uplift in others. Time series analysis reveals subsidence coinciding with wetland areas that correlates with declining local groundwater levels.
Multi-Resolution Analysis: MRA Based Bright Band Height Estimation with Preci...
A method for reconstruction of cross section of rainfall situations with precipitation radar data based on wavelet analysis of Multi-Resolution Analysis (MRA) which allows extract a peak of the radar reflectivity is proposed in order to detect bright band height. It is found that the bright band height can be estimated by using the MRA with the basis of Daubechies wavelet family. It is also found that the boundaries in rainfall structure can be clearly extracted with MRA.
Wavelet estimation for a multidimensional acoustic or elastic earth
A new and general wave theoretical wavelet estimation
method is derived. Knowing the seismic wavelet
is important both for processing seismic data and for
modeling the seismic response. To obtain the wavelet,
both statistical (e.g., Wiener-Levinson) and deterministic
(matching surface seismic to well-log data) methods
are generally used. In the marine case, a far-field
signature is often obtained with a deep-towed hydrophone.
The statistical methods do not allow obtaining
the phase of the wavelet, whereas the deterministic
method obviously requires data from a well. The
deep-towed hydrophone requires that the water be
deep enough for the hydrophone to be in the far field
and in addition that the reflections from the water
bottom and structure do not corrupt the measured
wavelet. None of the methods address the source
array pattern, which is important for amplitude-versus-
offset (AVO) studies.
Wavelet estimation for a multidimensional acoustic or elastic earth- Arthur W...
A new and general wave theoretical wavelet estimation
method is derived. Knowing the seismic wavelet
is important both for processing seismic data and for
modeling the seismic response. To obtain the wavelet,
both statistical (e.g., Wiener-Levinson) and deterministic
(matching surface seismic to well-log data) methods
are generally used. In the marine case, a far-field
signature is often obtained with a deep-towed hydrophone.
The statistical methods do not allow obtaining
the phase of the wavelet, whereas the deterministic
method obviously requires data from a well. The
deep-towed hydrophone requires that the water be
deep enough for the hydrophone to be in the far field
and in addition that the reflections from the water
bottom and structure do not corrupt the measured
wavelet. None of the methods address the source
array pattern, which is important for amplitude-versus-
offset (AVO) studies
DRONES IN HYDROLOGY
A network of scientists is cooperating within the COST Action "Harmonious" to promote UAS monitoring strategies and establish harmonized practices. The action has 36 partner countries and aims to transfer advances in UAS methods through a global network. It has five working groups focused on data processing, vegetation monitoring, soil moisture, streamflow monitoring, and harmonization. The overall goal is to increase the capacity to describe water resources and assist management through consistent UAS monitoring of key variables.
1002 THE LEADING EDGE AUGUST 2007
This study used ground-penetrating radar (GPR) to analyze the Quaternary stratigraphy of a sandy portion of the Marambaia Isthmus in Brazil. Five radar facies were identified in one GPR profile, representing different depositional environments: facies A and A' showed planar reflections indicating a low-energy beach or shore environment; facies B showed sigmoidal reflections indicating transport of shelf sediments during a marine transgression; facies C showed oblique reflections indicating eolian dune deposition during lower sea levels; and facies D showed well-sorted sand grains deposited by reworking. Together, the facies suggest periods of marine transgression and lower sea levels with dune formation, providing information on the
Spectroscopic confirmation of_the_existence_of_large_diffuse_galaxies_in_the_...
Artigo descreve como uma equipe de astrônomos usou o telescópio Keck I para confirmar a existência das Galáxias Ultra Difusas, ou UDGs no Universo.
FR01_01_GlezetalIGARSS2011.ppt
This document summarizes a study that used wide-swath interferometric synthetic aperture radar (InSAR) time series to map large-scale ground deformation over the Danakil depression in the Afar region of Ethiopia between 2006 and 2009. The time series analysis revealed deformation signals consistent with magmatic intrusions and inflation/deflation of volcanic centers. Modeling of the deformation supported deep magma intrusion beneath the central segment and lateral magma propagation and chamber inflation beneath Dabbahu volcano in the northern segment. The study demonstrated the potential of wide-swath InSAR time series for mapping long-wavelength ground deformation over large areas.
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EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
EDGE DETECTION IN RADAR IMAGES USING WEIBULL DISTRIBUTION
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Noise Removal in SAR Images using Orthonormal Ridgelet Transform
Noise Removal in SAR Images using Orthonormal Ridgelet Transform
Noise Removal in SAR Images using Orthonormal Ridgelet Transform
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Delineating faults using multi-trace seismic attributes: Example from offshor...
SPECTROSCOPIC CONFIRMATION OF THE EXISTENCE OF LARGE, DIFFUSE GALAXIES IN THE...
SPECTROSCOPIC CONFIRMATION OF THE EXISTENCE OF LARGE, DIFFUSE GALAXIES IN THE...
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Multi-Resolution Analysis: MRA Based Bright Band Height Estimation with Preci...
Wavelet estimation for a multidimensional acoustic or elastic earth
Wavelet estimation for a multidimensional acoustic or elastic earth
Wavelet estimation for a multidimensional acoustic or elastic earth- Arthur W...
Wavelet estimation for a multidimensional acoustic or elastic earth- Arthur W...
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1) The document describes a segmentation algorithm for polarimetric SAR (PolSAR) data that can model both scalar-texture and multi-texture scattering.
2) The algorithm uses log-cumulants and hypothesis testing to determine whether a scalar-texture or dual-texture model best fits the data within each segment.
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This document discusses using wavelet transforms to analyze two-point statistics of polarimetric synthetic aperture radar (PolSAR) data. It introduces wavelet variance and kurtosis as metrics that can be applied to PolSAR data transformed using a wavelet frame. It then provides an example of applying this analysis to ALOS PALSAR data over Hawaii's Papau Seamount to characterize sea surface features.
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The Sentinel-1 mission is part of the GMES program and consists of two satellites to provide C-band SAR data for emergency response, marine and land monitoring, and other applications. The satellites operate in a near-polar orbit with a 12 day repeat cycle. The main acquisition mode is an interferometric wide swath mode with 5m range and 20m azimuth resolution over a 250km swath. Sentinel-1 will support operational services and create a long-term SAR data archive.
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EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
1) The EO-1 Hyperion instrument has collected over 65,000 scenes over its 12-year mission to study land and coastal ecosystems using imaging spectroscopy.
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1) The EO-1 Hyperion instrument has collected over 65,000 scenes over its 12-year mission to study land and coastal ecosystems using imaging spectroscopy.
2) Studies using Hyperion data have identified spectral indices related to chlorophyll that correlate with carbon flux measurements at different forest, grassland, and woodland sites globally.
3) Time series of Hyperion data at sites in Zambia, North Carolina, and Kansas show seasonal changes in these spectral indices that match patterns in ecosystem carbon uptake and release measured by flux towers.
EO-1/HYPERION: NEARING TWELVE YEARS OF SUCCESSFUL MISSION SCIENCE OPERATION A...
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This document is a return and exchange form for a wetsuit company. It provides instructions for customers to fill out when returning an undamaged item for a refund, exchange, or size change. The form requests information like the customer's order details, contact information, the suit being returned and its size, the reason for return, and if applicable, the new desired size. It also provides the return shipping address and notifies customers that the company is not responsible for lost or damaged return packages.
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The document discusses mapping wetlands in North America using MODIS 500m imagery. It describes wetlands and existing global wetland databases. The methodology uses MODIS data from 2008, digital elevation models, and reference data to classify wetlands into three types - forest/shrub dominant wetlands, herbaceous dominant wetlands, and sea grass dominant wetlands. Training data is collected from existing land cover maps and Landsat imagery. A decision tree model and maximum likelihood classification are applied to extract wetlands from other land covers.
Solaro_IGARSS_2011.ppt
The document summarizes research using SBAS-DInSAR (Small BAseline Subset differential interferometric synthetic aperture radar) techniques to analyze ground deformation at Mt. Etna volcano in Italy over the last 18 years using ERS and ENVISAT satellite data. The analysis revealed three main deformation processes: inflation of the volcanic edifice, subsidence of sectors on the eastern flank due to gravitational spreading, and deflation-inflation cycles associated with eruptive and post-eruptive activity. More recent analysis using higher resolution COSMO-SkyMed data from 2009-2010 detected deformation related to faults and a 2010 earthquake more precisely than lower resolution ENVISAT data.
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HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Monitoring and Managing Anomaly Detection on OpenShift.pdf
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
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igarss11_2.ppt
- 1. ESTUARY WETLAND DETECTION IN SAR IMAGES Presented By Yu-Chang Tzeng
- 14. Location of the Test Site Wazihwei Nature Reserve
- 15. An Optical Image of the Test Site Google Earth (July 31, 2006) mud flats marshes
- 16. An SAR Image of the Test Site TerraSAR X-band and HH polarization (May 15, 2008)
- 17. Histogram of the Normalized SAR Scattering Coefficient
- 18. A Fractal Image of the Test Site
- 19. Histogram of the Fractal Dimension
- 21. Thresholding Marshes Mud Flats
- 22. Detection Procedures Detected Image Thresholding SAR Image Edge Detection Filtering Filling SCM
- 24. A Close Look of the Detected Wetland
Editor's Notes
- My name is Yu-Chang Tzeng from National United University, Miao-Li, Taiwan. My topic is ESTUARY WETLAND DETECTION IN SAR IMAGES.
- First of all, an introduction to estuary wetland detection in SAR images is given. Then, the Spatial Chaotic Model is briefly introduced. Experimental results of applying the Spatial Chaotic Model to estuary wetland detection in SAR images are followed. Finally, some concluding remarks are drawn.
- Statistically , C ( m , r ) is a measure of the probability that the two points x ( n ) and x ( j ) in the state space are separated by a distance r .
- The differential box-counting (DBC) technique is adopted to estimate the fractal dimension.