E Cognition User Summit2009 R Lucas University Wales National Vegetation Mapping
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The document summarizes a project using object-based image analysis to revise national vegetation mapping in Wales. High-resolution satellite imagery from multiple sensors was segmented and classified using a rule-based approach in Definiens software to map habitats at multiple scales, achieving over 80% accuracy compared to existing maps. The project established a baseline habitat map for 2006 and is developing a rolling program to regularly update the maps using new imagery and refine the classification system.
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This document presents a new method for hydrological mapping of vegetation using remote sensing products. The method is based on the Forest Canopy Density model and uses vegetation indexes like Advanced Vegetation Index, Bare Soil Index, and Shadow Index calculated from Landsat TM satellite imagery. These indexes are classified and combined to categorize vegetation into hydrological classes. The method was tested in Upper Tărlung Watershed and showed high correlation with traditional methods, providing an accurate and up-to-date alternative for hydrological mapping.
Forest monitoring through remote sensing
To meet the various information requirements in forest management, different data sources like field survey, aerial photography, and satellite imagery is used, depending on the level of detail required and the extension of the area under study.
BioSAR2010-aSARcampaigninsupportofthebiomassmission.ppt
The document summarizes the BioSAR 2010 airborne SAR campaign in Sweden which collected P-band and L-band SAR data using the ONERA SETHI system. The objectives were to detect forest changes, cross-calibrate sensors, evaluate biomass retrieval algorithms, and assess long-term coherence. SAR data was collected over a 1200 hectare forest test site with stands of varying biomass. Helicopter lidar and extensive field data were also collected. Preliminary analysis showed the SAR data delineated clear-cuts and subtle changes due to thinning and growth compared to a 2007 dataset.
Ecological Connectivity in Delaware, Ohio
This is an overview of my MS in Sustainability thesis project. It is a baseline structural investigation of connectivity within the exurban construct using Delaware, Ohio as a case study. Delaware was chosen because it exhibits exurban characteristics with landscape typologies that span the urban to rural continuum and because the area is under intense development pressure from the large urban area of Columbus, Ohio 10 miles to the south.
Vital Signs: An integrated monitoring system for agricultural landscapes
Presented by Roseline Remans, Columbia University at the Africa RISING–CSISA Joint Monitoring and Evaluation Meeting, Addis Ababa, Ethiopia, 11-13 November 2013
Remote sensing of biophysical parameters: linking field, airborne and contine...
The document discusses the Australian Supersites Network (ASN) and AusCover program for collecting field, airborne, and satellite data on biophysical parameters across Australia. AusCover establishes consistent field sites and collects ground measurements of vegetation structure and composition to validate satellite-derived maps of persistent green vegetation cover. Airborne lidar and hyperspectral data are also collected and compared to Landsat imagery and field data. The goal is to link multi-scale data to further ecosystem monitoring and understanding of productivity, biomass, and vegetation change over time. National collaborations support ongoing data collection and research using the unique datasets.
Assessing ecosystem services over large areas
This document summarizes research assessing ecosystem services over large areas in Scotland. Satellite data was integrated with other data to model various ecosystem services indicators at high spatial resolution, including net primary productivity, crop production, livestock density, water services, nutrient retention, and biodiversity. Hotspots with high levels of multiple ecosystem services were identified. Tools were developed to help stakeholders explore tradeoffs and advise on sustainable land management and land use change options based on ecosystem services priorities and spatial context. Limitations included lack of data on biodiversity's role and need for frequent monitoring to assess change over time.
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Wireless Sensor Networks and Drones for Measuring Forest Photosynthetic Bioph...
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Use of remote sensing techniques for nutrient studies in soil and plant _Knig...
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Hydrological mapping of the vegetation using remote sensing products
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BioSAR2010-aSARcampaigninsupportofthebiomassmission.ppt
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More from Trimble Geospatial Munich
What’s New in eCognition 8.9
eCognition 8.9 features new capabilities for analyzing land mobile data from different perspectives, improved point cloud analysis using a temporary point cloud concept, and increased flexibility when developing rule sets. It provides multi-perspective feature extraction from land mobile data, enhanced point cloud handling through temporary vector layers, and allows rule sets to use different information types and machine learning algorithms.
Whats new in eCognition 8.8
Pioneered a decade ago for satellite remote sensing, eCognition enables geospatial data such as images, point clouds and Geographic Information System (GIS) vectors to be integrated and analyzed to quantify features or detect changes over time. eCognition 8.8 now extends these capabilities for mobile terrestrial data collection applications.
Whats new in eCognition 8.7
eCognition 8.7 introduces new point cloud analysis capabilities that allow users to directly analyze 3D point clouds and combine them with 2D image segments and 3D statistical attributes. It also features advanced machine learning algorithms like CART and SVM for complex classification problems. The development environment has been improved with more flexibility to build rulesets that can adapt to varying input data.
eCognition 8.64 Highlights
The document describes eCognition 8.64, a new version that provides native 64-bit support for large scale image analysis. Key advantages include being able to generate billions of image objects and segment very large image mosaics in high detail by fully leveraging state-of-the-art hardware. The update also offers better usability with no need for complex tiling/stitching and the ability to generate unlimited image objects. It further prepares users for large, high resolution datasets by allowing analysis of combinations of datasets. All users with a valid maintenance contract as of December 2010 are eligible for the free update, which is available for both 64-bit and 32-bit environments.
E Cognition User Summit2009 G Binnig Definiens
1. The document discusses principles of human cognition that can be utilized for automated image analysis, including context-driven and object-oriented thinking.
2. It describes a Cognitive Network Language (CNL) that allows programming through multiple choices, natural formulation, and directed local processing to evolve object hierarchies.
3. The document provides examples of context-driven image segmentation and analysis in various domains like cell biology, medical imaging, and earth observation.
E Cognition User Summit2009 M Wurm Dlr Structure Types C
This document summarizes a method for deriving urban structure types from remote sensing data. It involves segmenting and classifying very high resolution imagery and digital surface models to extract buildings and characterize urban landscapes. A multi-step workflow segments the images, optimizes the segments, classifies buildings and land cover, then aggregates the results into homogeneous urban structure types at the block level for applications like urban planning, risk assessment, and analyzing local heating potentials.
E Cognition User Summit2009 Pregesbauer Geo Info Li Dar Basic Landcover
The document discusses using LiDAR and optical data to classify basic landcover in a public sector context. It aims to classify sealed areas, buildings, road networks, and vegetation across a region of 20,000 square kilometers with 95% reliability. The classification process involves tiling, creating initial objects, and defining classes. Results showed buildings were 88% accurately classified with improvements to 94.3% accuracy using additional mask layers.
E Cognition User Summit2009 Jo Neil Dunne Uvm Mapping Green Infrastructure
1) Jarlath O'Neil-Dunne from the University of Vermont Spatial Analysis Laboratory presented on using object-based image analysis (OBIA) to map green infrastructure.
2) Existing data and traditional pixel-based classification are insufficient to meet decision-maker needs, while OBIA can extract meaningful information by combining data with advanced analysis.
3) The presentation demonstrated OBIA techniques like multi-sensor data fusion, contextual operations, and object hierarchy to map features like tree canopy and impervious surfaces at fine scales, going beyond human cognition.
E Cognition User Summit2009 F Groesz Blom Forestry And Urban Vegetation Mapping
E Cognition User Summit2009 F Groesz Blom Forestry And Urban Vegetation MappingTrimble Geospatial Munich
The document discusses Blom's use of eCognition software for various forestry and vegetation mapping applications, including automatic forest stand delineation, mapping vegetation near powerlines, and delineating individual trees in urban areas. eCognition provides powerful analysis capabilities and versatile rulesets that allow easy adaptation to new tasks. While it does not work directly with LiDAR point clouds, eCognition is a valuable tool that complements Blom's other software.E Cognition User Summit2009 C Storch Gaf Emlc
Euro-Maps Land Cover
The Definiens Enterprise Image Intelligence Suite for operational landcover map production
E Cognition User Summit2009 A Tewkesbury Infoterra Semi Automated Landscape A...
E Cognition User Summit2009 A Tewkesbury Infoterra Semi Automated Landscape A...Trimble Geospatial Munich
1. The document discusses a semi-automated process for classifying high resolution land cover imagery into a standardized land cover scheme using Definiens software.
2. It describes challenges with processing a large volume of data from multiple sources and the need to change strategies to a more generic classification approach.
3. The process involves automated classification of image objects using rulesets, with manual editing to manage errors and achieve detailed attribution, allowing for thematic map creation and applications like habitat mapping and change detection.E Cognition User Summit2009 S Lang Zgis Object Validity
Object validity for high-standard information products. Between theoretical foundations and operational use
eCognition 8 Highlights
eCognition 8 introduces several new features including Quickmap mode for simple tasks like land cover mapping, improved manual editing tools, multi-user workspace collaboration, native LiDAR support, object generalization tools, and improved performance for image segmentation and data loading. A trial version is available for download on the eCognition website.
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E Cognition User Summit2009 M Wurm Dlr Structure Types C
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E Cognition User Summit2009 Jo Neil Dunne Uvm Mapping Green Infrastructure
E Cognition User Summit2009 Jo Neil Dunne Uvm Mapping Green Infrastructure
E Cognition User Summit2009 F Groesz Blom Forestry And Urban Vegetation Mapping
E Cognition User Summit2009 F Groesz Blom Forestry And Urban Vegetation Mapping
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Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean Lotus cyber threat actors represent a sophisticated, persistent, and politically motivated group that poses a significant risk to organizations and individuals in the Southeast Asian region. Their continuous evolution and adaptability underscore the need for robust cybersecurity measures and international cooperation to identify and mitigate the threats posed by such advanced persistent threat groups.
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
ここ3000字までしか入らないけどタイトルの方がたくさん文字入ると思います。
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
CAKE: Sharing Slices of Confidential Data on Blockchain
Presented at the CAiSE 2024 Forum, Intelligent Information Systems, June 6th, Limassol, Cyprus.
Synopsis: Cooperative information systems typically involve various entities in a collaborative process within a distributed environment. Blockchain technology offers a mechanism for automating such processes, even when only partial trust exists among participants. The data stored on the blockchain is replicated across all nodes in the network, ensuring accessibility to all participants. While this aspect facilitates traceability, integrity, and persistence, it poses challenges for adopting public blockchains in enterprise settings due to confidentiality issues. In this paper, we present a software tool named Control Access via Key Encryption (CAKE), designed to ensure data confidentiality in scenarios involving public blockchains. After outlining its core components and functionalities, we showcase the application of CAKE in the context of a real-world cyber-security project within the logistics domain.
Paper: https://doi.org/10.1007/978-3-031-61000-4_16
June Patch Tuesday
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Columbus Data & Analytics Wednesdays - June 2024
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Everything I found interesting about the irresponsible use of machine intelligence in May 2024
Climate Impact of Software Testing at Nordic Testing Days
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
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Everything I found interesting about machines behaving intelligently during May 2024
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.
Removing Uninteresting Bytes in Software Fuzzing
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
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
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- 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
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Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
AI 101: An Introduction to the Basics and Impact of Artificial Intelligence
Imagine a world where machines not only perform tasks but also learn, adapt, and make decisions. This is the promise of Artificial Intelligence (AI), a technology that's not just enhancing our lives but revolutionizing entire industries.
Mind map of terminologies used in context of Generative AI
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Choosing The Best AWS Service For Your Website + API.pptx
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
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Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
Ocean lotus Threat actors project by John Sitima 2024 (1).pptx
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
みなさんこんにちはこれ何文字まで入るの？40文字以下不可とか本当に意味わからないけどこれ限界文字数書いてないからマジでやばい文字数いけるんじゃないの？えこ...
Presentation of the OECD Artificial Intelligence Review of Germany
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E Cognition User Summit2009 R Lucas University Wales National Vegetation Mapping
- 1. Revision of National Vegetation Mapping in Wales using eCognition Professor Richard Lucas University of Wales, Aberystwyth In collaboration with Environment Systems Countryside Council of Wales Definiens
- 3. Wales or Cymru AU: Proud to be a Definiens Centre of Excellence
- 7. The Pilot: Classification of habitats & agricultural land, Berwyn Mountains NE Wales Based on time-series of Landsat sensor data Rule-based approach that coupled knowledge of ecology with that of remote sensing scientists
- 9. Sequential use of rules
- 10. The Approach to Mapping in Wales
- 13. SPOT-5 (March) Landsat (March) SPOT-5 (April) IRS (May) Landsat (July) Landsat (Sept) Multiple sensors, seasonal observations
- 14. Landsat ASTER IRS SPOT Geometric Correction: Orthorectification
- 18. Wet & Dry; Bogs, Bracken & Grassland Bogs (outlined in white) mapped by lower vegetation (photosynthetic) and greater moisture fraction (based on ASTER data). Areas of purple moor grass (black) and bracken (orange) mapped using a combination of SPOT non photosynthetic vegetation and shade/moisture fraction images.
- 19. Wales is a land of fields Image segmented using unit (field) boundaries Multi-resolution segmentation (using larger scale factors) applied within the unit boundaries Areas outside of field boundaries (mainly uplands) using a small scale factor (1 - 2 pixels)
- 20. Hierarchical Layers Super level Level 1 Sub level
- 25. Fuzzy Membership
- 27. Cambrian Mountains: An example of mapping complex habitats in the uplands
- 28. Cambrian Mountains: Example of mapping in uplands
- 29. Cambrian Mountains: An example of mapping complex habitats in the uplands
- 30. Comparison of Habitat Maps Vexcel Aerial Photography Sub-habitat Classification Original Phase 1 Survey
- 31. Hedgerow Mapping
- 33. Examples of Revised Phase 1 Maps Black Mountains The Welsh Valleys Ceredigion
- 34. Revised Phase 1 Mapping for Blaenavon World Heritage Sites