Thin-layer chromatography (TLC) is a chromatography technique used to separate non-volatile mixtures. Thin-layer chromatography is performed on a sheet of glass, plastic, or aluminium foil, which is coated with a thin layer of adsorbent material, usually silica gel, aluminium oxide (alumina), or cellulose.
Infrared spectroscopy (IR spectroscopy) is the spectroscopy that deals with the infrared region of the electromagnetic spectrum, that is light with a longer wavelength and lower frequency than visible light. It covers a range of techniques, mostly based on absorption spectroscopy.
Thin-layer chromatography (TLC) is a chromatography technique used to separate non-volatile mixtures. Thin-layer chromatography is performed on a sheet of glass, plastic, or aluminium foil, which is coated with a thin layer of adsorbent material, usually silica gel, aluminium oxide (alumina), or cellulose.
Infrared spectroscopy (IR spectroscopy) is the spectroscopy that deals with the infrared region of the electromagnetic spectrum, that is light with a longer wavelength and lower frequency than visible light. It covers a range of techniques, mostly based on absorption spectroscopy.
IR SPECTROSCOPY, INTRODUCTION, PRINCIPLE, THEORY, FATE OF ABSORBED RADIATION, FERMI RESONANCE, FINGERPRINT REGION, VIBRATIONS, FACTORS AFFECTING ABSORPTION OF IR RADIATION, SAMPLING TECHNIQUES, APPLICATIONS OF IR SPECTROSCOPY.
A TEXT BOOK : Complete and comprehensive inputs in Learning about Biogas and Biogas digestors:We have tried to take the mystery away from biogas.
Biogas is a renewable energy source with many different production pathways and various excellent opportunities to use.
One main advantage of biogas is the waste reduction potential. Biogas production by anaerobic digestion is popular for treating biodegradable waste because valuable fuel can be produced while destroying disease-causing pathogens and reducing the volume of disposed waste products.
Biogas burns more cleanly than coal, and emits less carbon dioxide per unit of energy. The carbon in biogas was recently extracted from the atmosphere by photosynthetic plants. Releasing it back into the atmosphere adds less total atmospheric carbon than burning fossil fuels.
Thus, biogas production kills two birds with one stone: it reduces waste and produces energy. In addition, the residues from the digestation process can be used as high quality fertilizer. This closes the nutrient cycle.
Applications of IR (Infrared) Spectroscopy in Pharmaceutical Industrywonderingsoul114
Various applications of IR (Infrared) Spectroscopy in Pharmaceutical industries related to drug discovery and structural elucidation is outlined in this presentation. Various qualitative and quantitative analysis of drug products are also outlined.
IR SPECTROSCOPY, INTRODUCTION, PRINCIPLE, THEORY, FATE OF ABSORBED RADIATION, FERMI RESONANCE, FINGERPRINT REGION, VIBRATIONS, FACTORS AFFECTING ABSORPTION OF IR RADIATION, SAMPLING TECHNIQUES, APPLICATIONS OF IR SPECTROSCOPY.
A TEXT BOOK : Complete and comprehensive inputs in Learning about Biogas and Biogas digestors:We have tried to take the mystery away from biogas.
Biogas is a renewable energy source with many different production pathways and various excellent opportunities to use.
One main advantage of biogas is the waste reduction potential. Biogas production by anaerobic digestion is popular for treating biodegradable waste because valuable fuel can be produced while destroying disease-causing pathogens and reducing the volume of disposed waste products.
Biogas burns more cleanly than coal, and emits less carbon dioxide per unit of energy. The carbon in biogas was recently extracted from the atmosphere by photosynthetic plants. Releasing it back into the atmosphere adds less total atmospheric carbon than burning fossil fuels.
Thus, biogas production kills two birds with one stone: it reduces waste and produces energy. In addition, the residues from the digestation process can be used as high quality fertilizer. This closes the nutrient cycle.
Applications of IR (Infrared) Spectroscopy in Pharmaceutical Industrywonderingsoul114
Various applications of IR (Infrared) Spectroscopy in Pharmaceutical industries related to drug discovery and structural elucidation is outlined in this presentation. Various qualitative and quantitative analysis of drug products are also outlined.
Providing Sustainable Solutions - The North European Forestry
Nordic-Baltic research organisations' network PROFOR workshop
10th of December 2019, Brussels
Virgin Tropical Forests, Loathed Plantations and Everything Inbetween: Not Se...SIANI
This study was presented during the conference ““Production and Carbon Dynamics in Sustainable Agricultural and Forest Systems in Africa” held in September, 2010.
A few numbers about forestry in Europe as background information for the graduate students from the Yale School of Forestry attending the 2017 European Forestry Fieldtrip
National Forest Program and Climate Change Challenges and ChancesCIFOR-ICRAF
This presentation by Kazimierz Rykowski shows the sectors influencing forests and how that led to the design of the National Forest Program and which recommendations can be given.
Managed forest contribution to carbon sequestration under a rising atmospheric CO2
Objectives:
Forest carbon is a cycle
Define forest carbon sequestration
Summarize what is known about how rising CO2 affects tree growth and forest health.
Carbon management under rising CO2. What can be done to increase or enhance carbon sequestration?
SFM and integrated approaches at the landscape level to tackle climate change...CIFOR-ICRAF
This presentation by Magnus Fridh focuses on:
1. Forest and Forestry in Sweden
2. National policy frameworks to support SFM
3. Integrated landscape solutions to resolve land-use conflicts and tackling climate change
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
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.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Why You Should Replace Windows 11 with Nitrux Linux 3.5.0 for enhanced perfor...SOFTTECHHUB
The choice of an operating system plays a pivotal role in shaping our computing experience. For decades, Microsoft's Windows has dominated the market, offering a familiar and widely adopted platform for personal and professional use. However, as technological advancements continue to push the boundaries of innovation, alternative operating systems have emerged, challenging the status quo and offering users a fresh perspective on computing.
One such alternative that has garnered significant attention and acclaim is Nitrux Linux 3.5.0, a sleek, powerful, and user-friendly Linux distribution that promises to redefine the way we interact with our devices. With its focus on performance, security, and customization, Nitrux Linux presents a compelling case for those seeking to break free from the constraints of proprietary software and embrace the freedom and flexibility of open-source computing.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
- Reduction in onboarding time from 5 weeks to 1 day
- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
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.
Large Language Model (LLM) and it’s Geospatial Applications
Prof. ioannis gitas (au th) “forest fuel classification and mapping at large scale in mediterran
1. Forest fuel classification
and mapping at large
scale in Mediterranean
Areas
ArcFUEL Final Workshop, 18/12/2013, Thessaloniki
“Forest Fires: Fuel mapping in the Mediterranean countries”
Dr. Pericles Toukiloglou, Dr. George Eftitsidis & Prof. Ioannis Gitas
Aristotle University | Faculty of Forestry and Natural Environment |
55143, Greece
ptoukiloglou@for.auth.gr
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
18 December 2013, Aristotle University Research Dissemination Center, Thessaloniki, Greece
1
2. Methodology considerations
Low cost
Applicable across Europe
Emphasis on Mediterranean ecosystems
Medium spatial resolution (~50m)
Results compatible with existing
applications & projects (e.g. FUELMAP)
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
2
3. Pilot study sites
Greek (Taksiarhis)
Italian (Cosenza)
Portuguese (Lousã Mountains)
Spanish (Sierra de Las Nieves Natural
Park)
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
3
4. Greek study site
Area: 10400 ha
Altitude range:
320-1195m
Climate:
Mediterranean
Main
vegetation:
Trees, Shrubs
& Grasses
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
4
5. Datasets used
EEA, Corine landcover map
JRC, Forest type map
EFFIS, Forest damage assessment maps
MODIS Vegetation Continuous Fields (collection 5)
Ecoregion type map
Landsat TM & ETM+ images
ASTER, GDEM v2
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
5
6. Classification scheme
Compliance with FUELMAP
Hierarchical
Main classes
Seasonal behavior
Vegetation density
Ecoregion type
Full detail
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
6
7. Main class
Temporal detail level
Vegetation density detail level
Ecoregion type detail level
Full detail level
Scrub
Deciduous
Broadleaved
forest
Open
Dense
Scrub
Evergreen
Open
Dense
Scrub
Open
Black Sea
Mediterranean East
Anatolian
Lusitanian
Pannonic – Pontic
Continental
Mediterranean North
Deciduous
Alpine South
Scrub
Atlantic North
Dense
Boreal
Open
Nemoral
Evergreen
Alpine North
Scrub
Atlantic Central
Dense
Mediterranean South
Open
Mediterranean Mountain
Deciduous
Coniferous forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
Forest
Ecoregion
+ Scrub Deciduous Broadleaved
+ Open Deciduous Broadleaved
+ Dense Deciduous Broadleaved
+ Scrub Evergreen Broadleaved
+ Open Evergreen Broadleaved
+ Dense Evergreen Broadleaved
+ Scrub Deciduous Coniferous
+ Open Deciduous Coniferous
+ Dense Deciduous Coniferous
+ Scrub Evergreen Coniferous
+ Open Evergreen Coniferous
+ Dense Evergreen Coniferous
+ Scrub Deciduous Mixed Forest
Ecoregion + Open Deciduous Mixed Forest
Dense
Surface fuels
Ground fuels
Non Wildland
fuels
Azonic fuels
Agroforestry
Burned areas
No fuels
Grasses
Shrubs
Ecoregion + Scrub Evergreen Mixed Forest
Open
Ecoregion + Open Evergreen Mixed Forest
Dense
Evergreen
Ecoregion + Dense Deciduous Mixed Forest
Scrub
Mixed forest
Ecoregion + Dense Evergreen Mixed Forest
Ecoregion + Grasses
Ecoregion + Shrubs
Ecoregion + Ground fuels
Ecoregion + Non Wildland fuels
Ecoregion + Azonic fuels
Ecoregion + Agroforestry
Ecoregion + Burned areas
No fuels
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
7
8. Detailed FUELMAP class
Peat bogs
Wooded peat bogs
Pastures
Sparse grasslands
Mediterranean grasslands and steppes
Temperate, Alpine and Northern grasslands
Mediterranean moors and heathlands
Temperate, Alpine and Northern moors and heathlands
Basic FUELMAP class
Associated ArcFuel class
Ground fuels
Ground fuels
Surface fuels
Surface fuels
Mediterranean open shrublands (sclerophylous)
Mediterranean shrublands (sclerophylous)
Deciduous broadleaved shrublands (thermophilous)
Alpine open shrub lands (conifers)
Shrublands in Mediterranean conifer forests
Shrublands in Mediterranean sclerophylous forests
Scrub Broadleaved forest
Shrublands in Mediterranean montane conifer forests
Shrublands in thermophilous broadleaved forests
Shrublands in beech and mesophytic broadleaved forests
Transitional forest
Northern open shrublands in broadleaved forests
Shrublands in Alpine and Northern conifer forests
Mediterranean long needled conifer forest (mediterranean pines)
Scrub Coniferous forest
Scrub Mixed forest
Mediterranean scale-needled open woodlands (juniperus, cupressus)
Open Coniferous forest
Mediterranean montane long needled conifer forest (black and scots pines)
Mediterranean montane short needled conifer forest (firs, cedar)
Coniferous forest
Alpine long needled conifer forest (pines)
Alpine short needled conifer forest (fir, alp. spruce)
Northern long needled conifer forest (scots pine)
Northern short needled conifer forest (spruce)
Mediterranean evergreen broadleaved forest
Thermophilous broadleaved forest
Mesophytic broadleaved forest
Beech forest
Montane beech forest
White birch boreal forest
Mixed Mediterranean evergreen broadleaved with conifers forest
Mixed thermophilous broadleaved with conifers forest
Mixed mesophytic broadleaved with conifers forest
Mixed beech with conifers forest
Riparian vegetation
Coastal and inland halophytic vegetation and dunes
Aquatic Marshes
Agroforestry areas
No fuel
Dense Coniferous forest
Open Broadleaved forest
Broadleaved forest
Dense Broadleaved forest
Open Mixed forest
Mixed forest
Dense Mixed forest
Other fuels
No fuel
Non Wildland fuels
Azonic fuels
Burned areas
Agroforestry
No fuel
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
8
9. Data update
Use latest available dataset release
Assume fire as the primary cause of broad
land cover change between official land
cover map releases
Update land cover datasets for burned
areas using the yearly EFFIS forest
damage assessment maps
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
9
10. Data update
Collect all the
EFFIS forest
damage
assessment maps
produced since
the release year
of the landcover
map
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
10
11. Data update
Append the
burned areas
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
11
12. Data update
Convert the
land cover
dataset to
vector format
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
12
13. Data update
Update the
vector dataset
for burned
areas
CORINE, update
the “Burnt
area” class
JRC, update the
“Non Forest”
class
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
13
14. Data update
Convert the
updated
dataset back
to raster
format using a
majority filter
CORINE->50m
JRC ->25m
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
14
15. Main fuel classes originating from the
JRC forest type map
Broadleaved, Coniferous and Mixed Forest
classes
Aggregate groups of four neighboring 25m
pixels to 50m ones
The mixed class is created through the
aggregation of both broadleaved and
coniferous pixels
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
15
16. C
C
C
C
C
B
B
C
B
B
B
C
Aggregation to 50 m
B
C
C
B
B
Updated forest type
map
Aggregation rules
Number of 25m resolution pixels
Broadleaved
Coniferous
Non
Forest
4
0
0
3
0
1
3
1
0
2
0
2
2
1
1
2
2
0
1
0
3
1
1
2
1
2
1
1
3
0
0
0
4
0
1
3
0
2
2
0
3
1
0
4
0
C
C
M
B
Assigned class
Broadleaved Forest
Broadleaved Forest
Broadleaved Forest
Broadleaved Forest
Broadleaved Forest
Mixed Forest
Non Forest
Mixed Forest
Coniferous Forest
Coniferous Forest
Non Forest
Non Forest
Coniferous Forest
Coniferous Forest
Coniferous Forest
M
Forest main classes
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
16
17. JRC Forest type Aggregation
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
17
18. Main fuel classes originating from the
CORINE map
ArcFuel main class
Ground fuels
Non Wildland fuels
Azonic fuels
Agroforestry
Burned areas
No fuels
CORINE class
Peat bogs
Discontinuous urban fabric
Green urban areas
Sport and leisure facilities
Non-irrigated arable land
Vineyards
Inland marshes
Salt marshes
Agro-forestry areas
Burnt areas
Estuaries
Industrial or
commercial units
Port areas
Airports
Coastal lagoons
Fruit trees and berry plantations
Olive groves
Annual crops associated with permanent crops
Complex cultivation patterns
Permanently irrigated land
Salines
Intertidal flats
Land principally occupied by agriculture, with significant areas
of natural vegetation
Dump sites
Water courses
Beaches, dunes, sands
Road and rail networks and
associated land
Water bodies
Continuous urban fabric
Bare rocks
Rice fields
Glaciers and perpetual snow
Mineral extraction sites
Construction sites
Sea and ocean
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
18
19. Main fuel classes originating from the
CORINE map
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
19
20. Surface fuels
The area not covered by any of the other
classes
Assumed to be covered by Grasses and
Shrubs
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
20
22. Conflict resolution
In case of conflicting main classes over the
same area, the class originating from the
most recent dataset is retained
If the conflicting classes originate from
equally current datasets, then the class
originating from the highest resolution
dataset is retained
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
22
23. Temporal refinement
Certain main fuel classes contain sub-classes with distinctly
different seasonal behavior.
The physical properties of these sub-classes differ over
different seasons and thus so do their properties as a fuel.
The main fuel classes that can be further sub-classified
based on their seasonal behavior are:
the Broadleaved, Coniferous and Mixed forest fuels, which can
be sub-classified to Deciduous and Evergreen
and the Surface fuels, which can be sub-classified to Grasses
and Shrubs
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
23
25. Temporal refinement
Assumption: Distinctly different seasonal NDVI
value differences imply vegetation types with
distinctly different seasonal behavior
Assumption: Seasonal NDVI value differences are
not affected considerably by factors other than
the physical properties of the vegetation
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
25
26. Temporal refinement
Landsat images selection rules:
Captured recently and during:
Summer
Winter
Low cloud cover
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
26
27. Temporal refinement
Landsat image pre-processing
Calibration
Atmospheric correction
Cloud and shadow masking
Topographic correction
NDVI calculation
Seasonal NDVI value difference calculation
(summer-winter)
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
27
29. Temporal refinement
Over areas covered solely by trees, the highest
seasonal NDVI value differences should be
recorded over Deciduous, and the lowest over
Evergreen trees
Over areas covered solely by surface fuels, the
highest seasonal NDVI value differences should
be recorded over Grasses, and the lowest over
Shrubs
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
29
30. Temporal refinement
How can the seasonal NDVI value differences,
which are neither too high and neither too low, be
classified?
No optimum set of seasonal NDVI value criteria
for distinguishing the classes across Europe
Wide in-class variability
Wide range of possible image reception dates
Empirical criteria would be costly
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
30
31. Temporal refinement
Alternative: use an automated clustering
algorithm such as ISODATA to perform an
unsupervised classification
Two classes
Performed over an area covered solely by two vegetation
types with distinctly different seasonal behavior
Classified area should be large enough to include both
vegetation types
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
31
33. Vegetation Density
Vegetation density is an important fuel
property
At the time, the available data (MOD44B)
is restricted to tree forest fuels
Three sub-classes based on vegetation
coverage percentage:
Scrub (0-10%)
Open (10-40%)
Dense (40-100%)
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
33
35. Ecoregion type
Ecoregion type effects fire behavior
Improves the compliance with FUELMAP
15 ecoregion types identified over Europe
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
35
36. Ecoregion type
European Ecoregion types
Alpine North
Boreal
Nemoral
Atlantic North
Alpine South
Continental
Atlantic Central
Pannonic – Pontic
Lusitanian
Anatolian
Mediterranean Mountain
Mediterranean North
Mediterranean South
Mediterranean East
Black Sea
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
36
37. Full detail
Combine all the
available fuel
property layers
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
37
38. Full detail
Vegetation fuel class name
Area coverage percentage
Dense Broadleaved Deciduous
15.975%
Dense Broadleaved Evergreen
20.564%
Dense Coniferous Deciduous
0.026%
Dense Coniferous Evergreen
5.585%
Dense Mixed Evergreen
0.128%
Grasses
24.170%
Non Fuels
17.635%
Non Wildland Fuels
0.662%
Scrub Broadleaved Deciduous
5.146%
Scrub Broadleaved Evergreen
4.007%
Scrub Coniferous Deciduous
0.004%
Scrub Coniferous Evergreen
1.078%
Scrub Mixed Evergreen
0.252%
Shrubs
4.770%
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
38
40. Discussion
Optimum Landsat images may be harder
to find than originally anticipated
Topographic correction is important
Compositing Landsat images may improve
the results
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
40
41. Conclusions
The proposed methodology can be used to
regularly map forest fuel maps suitable for
policy making over Europe, at low cost
The methodology could be further
improved in the future
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
41
42. Thank you
ArcFUEL Final Workshop “Forest Fires: Fuel mapping in the Mediterranean countries”
42
Editor's Notes
BEHAVE, FARSITE, the National Fire Danger Rating System (NFDRS), the FlamMap fire potential simulator and the Prometheus
As input data set concerning the types of Ecoregion is considered the respective data layer that has been developed within FUELMAP project and which is based on the Environmental stratification of Europe Metzger et al. (2005), the Pan-European map of Biogeograhical regions of Roekaerts (2002, ETC/BD 2006) and the map of Environmental Zones in Europe (Mücher et al, 2003). The JRC Forest type map 2006 was produced based on IRS-P6 LISS-III, SPOT4 (HRVIR) and SPOT5 (HRG) data acquired in 2006. It provides the location of areas in Europe covered by Broadleaved and Coniferous forests, at a 25m spatial resolution. The JRC forest density map is produced every year based on summer-time MODIS data. It provides forest density information across Europe at a 250m spatial resolution CLC2000 discriminates between 44 land-cover classes, organised hierarchically in three levels. It was produced by visually interpreting a mosaic of Landsat 7, Enhanced Thematic Mapper Plus (ETM+) images belonging to the IMAGE2000 collection. The spatial resolution of the map is 100m and its thematic accuracy is estimated to exceed 85%the 2nd version of the Global Digital Elevation Model (GDEM) derived by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), released by the Ministry of Economy, Trade, and Industry (METI) of Japan and the United States National Aeronautics and Space Administration (NASA) in 2011. The second version (ASTER GDEM2) is an improvement of the previous release in 2009, and provides above sea level elevations over the greater part of the Earth’s surface (within the region between the 83° south and 83° north parallels) at a 30m spatial resolution the MODerate-resolution Imaging Spectroradiometer (MODIS), Collection 5, Vegetation Continuous Fields (VCF) also known as product MOD44B. The product provides global 250m sub-pixel estimates of percent tree cover, based on MODIS reflective and emissive data composites
European Forest Fire Information System
Fire behaviour simulation models are often used for assessing these fire-related characteristics. There are several existing models of this kind, such as the Rothermel’s surface fire behaviour and spread model [21], the BEHAVE [22], [23], the FARSITE [24], the National Fire Danger Rating System (NFDRS)[25], the FlamMap fire potential simulator [26], and the Prometheus [27], [28] which is part of the Canadian Wildland Fire Growth Model (CWFGM). The reliability of these models is directly linked to the quality of the environmental data they require to function, which typically include topographical, meteorological and vegetation fuel data [21]-[31].
Nowadays there are a large number of computer fire simulators (Farsite, Firestation, ArcFIRE, BehavePlus, DYNAFIRE, FLAMMAP etc) but almost all based on Rothermel’s surface fire spread model. The basic inputs for this model are related to terrain slope, wind speed and fuels description. This set of values bridges the Fuel Type term with the Fuel Model used in fire modelling. A fuel model can thus be described as a set of fuelbed inputs needed by particular fire behaviour or fire effects model. The needed inputs of fuel model for fire simulation are: • Fuel load by category (live and dead) and particle size class (0 to 0.6 mm, 0.6 to 2.5 mm, and 2.5 to 7.6 mm in diameter) • Surface-area-to-volume (SAV) ratio by component and size class • Heat content by category • Fuelbed depth • Dead fuel moisture of extinction
