This document presents a study that used SAR intensity and coherence to detect a fire scar in a degraded moorland environment in the UK. It describes the methodology, which involved preprocessing SAR data and extracting backscatter values for different land cover classes within the fire scar over time. The results show that precipitation and land cover affected the SAR intensity signal inside the fire scar, with peat bog having the highest returns. InSAR coherence was also analyzed for pairs before and after the fire. The summary concludes that SAR intensity can detect large fire scars but coherence needs more exploration, and recommends investigating different fire scenarios and radar frequencies.
A Balloon-Borne Light Source for Precision Photometric CalibrationMax Fagin
ALTAIR (Airborne Laser for Telescopic Atmospheric Interference Reduction) is a balloon-borne optical calibration source used to calibrate the next generation of supernova surveys for probing the nature of the dark energy. The project is a collaboration among colleagues at Harvard University, the University of Victoria, and Dartmouth College. The Dartmouth component has responsibility for vehicle development, telemetry, ground tracking, and flight operations.
A Balloon-Borne Light Source for Precision Photometric CalibrationMax Fagin
ALTAIR (Airborne Laser for Telescopic Atmospheric Interference Reduction) is a balloon-borne optical calibration source used to calibrate the next generation of supernova surveys for probing the nature of the dark energy. The project is a collaboration among colleagues at Harvard University, the University of Victoria, and Dartmouth College. The Dartmouth component has responsibility for vehicle development, telemetry, ground tracking, and flight operations.
Evaluating effectiveness of radiometric correction for optical satellite imag...Dang Le
One of our published researches in ACRS 31st in Hanoi.
It has been used for our project in processing optical satellite imagery to detect environmental pollution.
An Extended Tropospheric Scintillation Model for Free Space Optical Communica...ijeei-iaes
Fluctuations caused mostly by tropospheric scintillation at the free space optical receiver end have been a major problem in the rapid development of telecommunication and the increasing demands for larger bandwidth is forcing the use of free space optical (FSO) technology. This paper examined existing tropospheric scintillation models of Karasawa, Van de Kamp model, Otung, Ortgies and ITU-R, and discovered that all of them operate at the microwave range, which limits their application in FSO laser beam technology that operates in PHz frequency-range. ITU-R model was later selected owing to its global application and modified for use in FSO communication system. The new model can serve as basis for communication engineers to use as platform in the link budgetary for planning and design of low margin systems of free space optical communication link.
CSP Training series : solar resource assessment 2/2Leonardo ENERGY
Fifth session of the 2nd Concentrated Solar Power Training dedicated to solar resource assessment.
* DNI Variability, Frequency Distributions
* Typical Meteorological Years
* DNI measurements: broadband vs. spectral, and their limitations
* What is circumsolar radiation and why should we care in CSP/CPV?
* How much diffuse irradiance can be used in concentrators?
* How to measure and model the circumsolar irradiance?
* Spectral irradiance standards and their use for PV/CPV rating
* The AM1.5 direct standard spectrum: Why did it change? Why AM1.5?
* Use of the SMARTS radiative code to evaluate clear-sky spectral irradiances
* Sources of measured spectral irradiance data
* Spectral effects on silicon and multijunction cells and their dependence on climate
This work measured experimentally, and calculated theoretically using the existing Friis Fomula, the Attenuation of 92.1 MHz (Ajilete FM) Signals along Gambari(Lat 8o291N; Long 4o291) – Oyo-Road(Lat 7o501N; Long 3o561E), Oyo State Nigeria. The two results were compared. The experimental Measurement campaign was achieved by using an appropriate design dipole antenna, well matched to (810 GSP Analyser), to determine the attenuation. The calculated results correlated very well with the measurements (Correlation Coefficient Value R2=1). But, they are not accurate when compared with the measurements (Chi- square values equal zero for received power, measured attenuation). The inaccuracies of the results for the existing formula with the measurements may be due to hills, valleys, trees and bends along the links. Hence the accuracy of the model used can only be effectively confirmed in areas free of the obstacles mentioned above. By applying LEAST SQUARE fit method to the experimental measured data, the analytical models, P(x)= 0.0154x2-1.3575x-38.7620 and A(x)= 0132x2 -1.2464x-104.8487, in the form of polynomial of degree two, were obtained respectively for received power and measured attenuation. The analytical model obtained is therefore recommended for use in an area characterised with bends, valleys, hills and trees, since the model has taken into consideration all these factors. In addition, repeater stations should be installed for effective transmission and for wider coverage in forested and valley areas. Moreover, transmitter of higher value like ten kilowatts should be employed for long distance transmission
Operational exploitation of the Sentinel-1 mission: implications for geosciencepetarmar
Poster presented at American Geophysical Union (AGU), Fall Meeting, San Francisco, 12-16 December 2016
Title: Operational exploitation of the Sentinel-1 mission: implications for geoscience
Sub-title: Lessons learned from ESA SEOM InSARap project
Authors: Yngvar Larsen (Norut), Petar Marinkovic (PPO.labs), John Dehls (NGU), Zbigniew Perski (PGI), Andy Hooper(Uni.Leeds), Tim Wright(Uni.Leeds)
Acknowledgment: ESA SEOM programme
This presentation was part of a webinar run by Jisc RSC on 03/06/14 called 'Learning Providers as MakARs - how Augmented Reality is being used in practice'.
Evaluating effectiveness of radiometric correction for optical satellite imag...Dang Le
One of our published researches in ACRS 31st in Hanoi.
It has been used for our project in processing optical satellite imagery to detect environmental pollution.
An Extended Tropospheric Scintillation Model for Free Space Optical Communica...ijeei-iaes
Fluctuations caused mostly by tropospheric scintillation at the free space optical receiver end have been a major problem in the rapid development of telecommunication and the increasing demands for larger bandwidth is forcing the use of free space optical (FSO) technology. This paper examined existing tropospheric scintillation models of Karasawa, Van de Kamp model, Otung, Ortgies and ITU-R, and discovered that all of them operate at the microwave range, which limits their application in FSO laser beam technology that operates in PHz frequency-range. ITU-R model was later selected owing to its global application and modified for use in FSO communication system. The new model can serve as basis for communication engineers to use as platform in the link budgetary for planning and design of low margin systems of free space optical communication link.
CSP Training series : solar resource assessment 2/2Leonardo ENERGY
Fifth session of the 2nd Concentrated Solar Power Training dedicated to solar resource assessment.
* DNI Variability, Frequency Distributions
* Typical Meteorological Years
* DNI measurements: broadband vs. spectral, and their limitations
* What is circumsolar radiation and why should we care in CSP/CPV?
* How much diffuse irradiance can be used in concentrators?
* How to measure and model the circumsolar irradiance?
* Spectral irradiance standards and their use for PV/CPV rating
* The AM1.5 direct standard spectrum: Why did it change? Why AM1.5?
* Use of the SMARTS radiative code to evaluate clear-sky spectral irradiances
* Sources of measured spectral irradiance data
* Spectral effects on silicon and multijunction cells and their dependence on climate
This work measured experimentally, and calculated theoretically using the existing Friis Fomula, the Attenuation of 92.1 MHz (Ajilete FM) Signals along Gambari(Lat 8o291N; Long 4o291) – Oyo-Road(Lat 7o501N; Long 3o561E), Oyo State Nigeria. The two results were compared. The experimental Measurement campaign was achieved by using an appropriate design dipole antenna, well matched to (810 GSP Analyser), to determine the attenuation. The calculated results correlated very well with the measurements (Correlation Coefficient Value R2=1). But, they are not accurate when compared with the measurements (Chi- square values equal zero for received power, measured attenuation). The inaccuracies of the results for the existing formula with the measurements may be due to hills, valleys, trees and bends along the links. Hence the accuracy of the model used can only be effectively confirmed in areas free of the obstacles mentioned above. By applying LEAST SQUARE fit method to the experimental measured data, the analytical models, P(x)= 0.0154x2-1.3575x-38.7620 and A(x)= 0132x2 -1.2464x-104.8487, in the form of polynomial of degree two, were obtained respectively for received power and measured attenuation. The analytical model obtained is therefore recommended for use in an area characterised with bends, valleys, hills and trees, since the model has taken into consideration all these factors. In addition, repeater stations should be installed for effective transmission and for wider coverage in forested and valley areas. Moreover, transmitter of higher value like ten kilowatts should be employed for long distance transmission
Operational exploitation of the Sentinel-1 mission: implications for geosciencepetarmar
Poster presented at American Geophysical Union (AGU), Fall Meeting, San Francisco, 12-16 December 2016
Title: Operational exploitation of the Sentinel-1 mission: implications for geoscience
Sub-title: Lessons learned from ESA SEOM InSARap project
Authors: Yngvar Larsen (Norut), Petar Marinkovic (PPO.labs), John Dehls (NGU), Zbigniew Perski (PGI), Andy Hooper(Uni.Leeds), Tim Wright(Uni.Leeds)
Acknowledgment: ESA SEOM programme
This presentation was part of a webinar run by Jisc RSC on 03/06/14 called 'Learning Providers as MakARs - how Augmented Reality is being used in practice'.
Interferometric and Geodetic Validation of Sentinel-1petarmar
Experiences and summary of SAR/InSAR calibration and validation results from the 1st year of Sentinel-1 operation.
Authors: Petar Marinkovic (PPO.labs), Yngvar Larsen (Norut), Zbigniew Perski (PGI), Tom Rune Lauknes (Norut), John Dehls (NGU)
Presented at CEOS Calibration and Validation Workshop 2015, October 27-29, 2015, at ESA-ESTEC, in Noordwijk, The Netherlands
Speckle is the major multiplicative noise in the SAR(Radar) images, Improvement is done by using stochastic distance methods by assuming data as gamma distribution which enhances the images by 78% overall....
Characterizing Landslide Deformation Using InSARguest06bc949
Alberta Geological Survey's work with corner reflector InSAR at the Little Smoky landslide in Alberta.
Presented in 2008 at the 4th Canadian Conference on Geohazards.
Measuring Change with Radar Imagery_Richard Goodman - Intergraph Geospatial W...IMGS
ERDAS IMAGINE Radar Tools:
Radar Mapping Suite - Add-on module
Operational software - Not a toolkit!
Directly read data into viewer - No import required - No resampling of data
New Radar Analyst ribbon - Fast feature extraction -
Visualisation aids
Interferometry tools - CCD - D-InSAR
Presented by Dadang Hilman (ICCC) on ICCC Coffee Morning on Climate Change series on Drivers of Forest Fires: Identification of Comprehensive Solution, April 15, 2014 at Indonesia National Council on Climate Change, Jakarta, Indonesia.
Mapping fire: Can spatially explicit criteria and indicators be developed?CIFOR-ICRAF
Presented by Solichin Manuri, Senior Advisor at Diameter Consulting, Bogor, Indonesia, at "Online Webinar 2: Biophysical Attributes and Peatland Fires", on 14 October 2020
In this session the speaker shared information on mapping fire (extent and occurrences) in tropical peatlands including in Indonesia. This session also shared insights on the existing methods that can be used for fire mapping and comparisons. This session also emphasized that spatial explicit criteria for fire should be developed depending on the method and data used.
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel TypesBeniamino Murgante
On the Use of Satellite Remote Sensing Data to Characterize and Map Fuel Types
Antonio Lanorte, Rosa Lasaponara - Institute of Methodologies for Environmental Analysis, National Research Council, Italy
Application of Seismic Reflection Surveys to Detect Massive Sulphide Deposits...iosrjce
Seismic reflection techniques, the most widely used geophysical method for hydrocarbon exploration
has the capability to delineate and provide better images of regional structure for exploration of mineral
deposits in any geological settings. Previous tests on detection and imaging of massive sulphide ores using
seismic reflection techniques have been done mostly in crystalline environments. Application of seismic
reflection techniques for imaging sedimentary hosted massive sulphide is relatively new and the few experiments
carried out are at local scale (<500m). In this study, we analyze the feasibility of such regional exploration by
modelling three massive sulphide ore and norite lenses scenario using 2D seismic survey with relatively sparse
source-receiver geometry to image these deposits within 1.5km depth range. Results from the modelling
experiment demonstrate that 2-Dimensional seismic reflections survey can be used to detect massive sulphides
at any scale. The test further indicates that geologic setting and acquisition parameters are very important for
the detection of these ore bodies. Overall, the outcomes of the results support our started objective which is to
demonstrate that seismic reflection surveys can be used to detect the presence of sediment hosted massive
sulphides at regional scale
Slides presented as part of my PhD Confirmation of Candidature.
The project is about evaluating the cooling effectiveness of green infrastructure in urban environments. Skills demonstrated include GIS, data grids, image processing, machine learning, data processing and visualization, environmental modelling,
The performance of portable mid-infrared spectroscopy for the prediction of s...ExternalEvents
This presentation was presented during the 3 Parallel session on Theme 1, Monitoring, mapping, measuring, reporting and verification (MRV) of SOC, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Martin Soriano-Disla, CSIRO Land and Water - Australia, in FAO Hq, Rome
The challenges found on the route to developing quantitative wildfire spread models are two-fold. First, there is the modeling challenge associated with providing accurate mathematical representations of the multi-physics processes that govern wildfire dynamics. Second, there is the data challenge associated with providing accurate estimates of the input data and parameters required by the models.
One recent strategy to better account for time-varying weather conditions near the flame and the smoke plume consists in coupling a cost-effective front-tracking simulator of surface fire spread with a meso-scale three-dimensional atmospheric model. This system relies on a two-way coupling between the surface and the atmosphere. It is a promising strategy to predict fine-scale features of wildfire behavior as well as the atmospheric behavior (in terms of plume size, transport dispersion and smoke concentration) as demonstrated by the ANR-IDEA project.
➞ ANR-IDEA, see https://www.youtube.com/watch?v=C1-cfMmS1WM
Similar to Using SAR Intensity and Coherence to Detect A Moorland Wildfire Scar (20)
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
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Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
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A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
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We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
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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.
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We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
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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.
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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/
2. Presentation Structure
• Fire
– Fires & Moorlands
– UK Wildfires (news clip)
– Fire Scar Detection
• Research question & objectives (pilot study)
• Methodology
– Why SAR?
– Study Site
– SAR pre-processing chain
• Results
– Intensity
– Coherence
• Conclusion & Future Work
3. Why Fire is Important in Moorlands?
Destroy vegetation
Fuel load, adaptation
Climate Wildlife
Vegetation
Soil
Humans
CO2 emissions Remove habitat
Adaptation
Managed burns
Arson
Degradation
ErosionRate of re vegetation
5. UK Fire Scar Detection
Source: http://effis.jrc.ec.europa.eu/
6. Research Question (Pilot Study)
How well can the C-band SAR intensity and coherence
signal detect a fire scar within a degraded UK moorland
environment?
Objectives
• Determine the ability of SAR intensity and InSAR
coherence to detect the fire scar over time in a moorland
environment
• Analyse qualitatively how scene variables such as
precipitation and CORINE land cover classes affect the
SAR intensity and coherence signal, both inside and
outside the fire scar
7. Why SAR?
• See through cloud
and smoke
• Active sensor: acquire
images day and night
• Good temporal
resolution of data
• SAR very sensitive to
moisture content ideal
for mapping fire scars
Source: Landmap Radar Imaging Course
http://landmap.mimas.ac.uk
10. Nearest Neighbour resampling method
One image used as the input reference file, the
other image is coregistered to this.
ENVI Band Math using the formula 10*alog10(b1)
Degraded to 100m using a Nearest Neighbour
resampling method in ENVI.
5 backscatter sample points for each land cover class
was extracted from the radar data.
Equivalent looks variable set to -1 threshold for
speckle filtering is calc by the software – 0.5227/sqrt
Multitemporal DeGrandi Filter used
25m DEM
No GCP (however a sub-pixel accuracy can still be
achieved when DORIS data has been used)
Generated Sigma Nought values
Calculate Ground Range GR (m) = Rg ÷ sin IA
Calculate number of Azimuth Looks = GR ÷ Az
1. Basic Import for ASAR or ERS-2
Single Look Complex (slc)
Intensity Image (pwr)
3.A Amplitude Coregistration
Resampled & resized images (rsp)
Filtered image(fil)
5. Geocoding Radiometric Calibration
Geocoded 25m images (geo)
Level 1 SLC from ESA
4. Multi-temporal Despeckling
2. Focusing and Multilooking
6. Geocoded images to dB
100m Greyscale
Geocoded SAR image
Process Outputs/Inputs
Processes
Final Product
Key
3. Amplitude Coregistration
15. Summary & Conclusion
• Precipitation & land cover are key variables for
understanding the SAR intensity and coherence
– Within the fire scar peat bog gave highest intensity return
– Rainfall just prior to image acquisition increased intensity values
for all land cover classes inside the fire scar
• Image results are sensitive to:
– Filtering algorithm applied > recommend Degrandi multitemporal
– Initial baseline of InSAR pairs > temporal decorrelation
• A large fire scar in a degraded moorland environment
can be detected using SAR intensity. InSAR coherence
needs to be further explored.
16. Future Work
• Investigate fire scars of different sizes, severity, land
cover & precipitation conditions
• Analyse the affect of radar polarisation and frequency on
fire scar detection
– X band & L band data
– Cross polarised and co-polarised data
• Applying classification method for fire scar mapping
• Explore Kinder 2008 & Wainstalls 2011 case studies
– GPS boundary collected this summer
– Kinder boundary obtained from MFF
17. Acknowledgements
Access to fire log and fire scar GPS data
PDNP Fire Operations Group
Access to ERS-2, ALOS PALSAR & ASAR data as part of
Category 1 Project 2999
School of Environment & Development for funding to support this research
Mimas & Landmap for funding, time & resources to support this research
References
KEELEY, J. (2009) Fire intensity, fire severity and burn severity: a brief review and suggested
usage. International Journal of Wildland Fire, 18, 116-126.
LENTILE, L. B et al., (2006) Remote sensing techniques to assess active fire characteristics and
post-fire effects. International Journal of Wildland Fire, 15, 319-345.
Martin Evans & Juan Yang at SED for Upper North Grain weather data
19. Images for Intensity Analysis
SAR
Data/
Mode/
Swath
Acquisition
Date/Time
dd/mm/yyyy
Time
relative to
fire
(JD Julian
day)
Incidence
Angle
(IA)
Az pixel
spacing
(m)
Rg pixel
spacing
(m)
Ground
Range
(GR) (m)
Pass
Type
ERS-2 08/02/2003
11:01
-69 days
(39 JD)
23.23º 3.97 7.90 20.26 Desc-
ending
ERS-2 15/03/2003
11:01
-34 days
(74 JD)
23.23º 3.97 7.90 20.26 Desc-
ending
ASAR
IM I2
22/03/2003
21:37
-27 days
(81 JD)
22.82º 4.04 7.80 20.00 Asc-
ending
ASAR
AP I2
HHVV
03/04/2003
10:36
-15 days
(93 JD)
22.76º 4.04 7.80 20.00 Desc-
ending
ERS-2 24/05/2003
11:01
+36 days
(144 JD)
23.21º 3.97 7.90 20.26 Desc-
ending
ERS-2 28/06/2003
11:01
+71 days
(179 JD)
23.28º 3.97 7.90 19.75 Desc-
ending
Editor's Notes
Fires cause an increase in greenhouse gas emissions e.g. Carbon dioxide, methane and nitrous oxide.UK social impacts occur during the Spring Bank Holidays – discarded cigarette ends and disposable BBQ + hotter drier temperatures happening at that time of year e.g. Spring of 2003, 2008 and 2011.
Video Clip of WainstallsWildfires are unwanted vegetation fires. UK causes Arson Accidental ignition cigarettes and disposable BBQ Lack of rainfall in the spring in combination with winter drying effects on the vegetation decreasing the FMC will increase the potential for a fire Major impact on moorland ecosystems, especially peatlands. The impact varies with the amount of area burnt and severity of the burn.Wildfire EffectsNegativeDOC concentrations increase in drinking waterDeep seated blanket peat fires release CO2into the atmosphereErode landscapePositiveChange ecological composition of moorland environmentDestroy habitat for grouseIncrease in graminoids and decrease in ericoid sub-shrubs
European Forest Fire Information SystemEFFIS Burnt Area Locator managed to identify and produce a burnt area outline for the 1017 hectares Anglezarke Fire in Lancashire 29/04/11 Did not locate the Wainstalls fire which began on 30/04/11 and burnt approximately 300 hectares of moorland Burnt area product for EFFIS is produced using either 32m DMC data or Advanced Wide Field Sensor on board IRS with spatial ground resolution of 56mThreshold for size of burnt areas detectable is 5 to 10 ha or largerOvenden MoorTherefore use of Optical Data is an issue for monitoring burnt areas of UK fires due to cloud cover. Other approaches need to be explored i.e. Radar which can see through cloud and smoke Fire scar monitoring is important for assessing the recovery of the moorland landscape as some fires such as Wainstalls are deep seated and burn into the peat destroying the roots of heather and impeding recovery
This research will inform the next steps in my PhD
Essential requirement in the UK, due to microwaves having a longer wavelength compared to optical dataSAR sensors emit their own illumination source in the form of microwaves For this research C-band data will be used Future research using more recent case studies will also analyse L-band data which can penetrate deeper into the ground due to the longer wavelength.
There have been many studies in the literature for using SAR for forest fires in the tropics, Mediterranean and boreal ecozones but there is little research on the use of SAR for detecting fire scars in moorland environments. This is a feasibility study.Radar is a distance measuring device There is a Transmitter, a Receiver, an Antenna, and an Electronic system to process and record the data. Transmitter generates pulses of microwaves at regular intervals which are focused by the antenna into a beam The radar beam illuminates the surface obliquely at a right angle to the motion of the platform. The antenna receives a portion of the transmitted energy reflected known as ‘backscatter’ from various objects on the ground in this case a tree
PDNP would be very vulnerable to temperature increases predicted b the UK Climate Impacts Programme (UKCIP) as its one of the most southern moorland landscapes One of the most visited national parks especially around Bank Holidays18th AprilBleaklow experienced intense fire which burnt deep into the peat, covering 7Km2, 700 hectares Previous fires have occurred in this area logged by the PDNP rangers Vegetation consists of heather, cottongrass and mosses
Exposed peat bog inside the fire scar had the highest pre-fire intensity signal at 0.16 dB JD 39 Can see relative brightness on the east side of the fire scar Fig a-d Peat bog values stay high post-fire (0.78 dB JD 144 and -0.57 dB JD 179) as shown in fig e & f. Very dry during JD 72 – JD 90 with only one notable rain event of 15.2mm on JD 91, this could explain the downward trend in backscatter intensity then peak in intensity for the ASAR AP image acquired on JD 93 (d). After the fire event rainfall frequently occurred with Fig e and f exhibiting strong backscatter.
Explain Axis Average intensity values in dB inside and outside the Bleaklow fire scar for CORINE land cover classes. ERS-2 image acquired on JD 74 and ASAR Image Mode image acquired JD 81 show a downward trend in backscatter intensity for all land cover classes except natural grassland intact peat bog outside the fire scar
Baseline should not be greater than 500m to avoid temporaldecorrelation. Coherence images measure the degree of correlation between two SAR images acquired at different times. Produced during Interferometric SAR (InSAR) pre-processing, using the phase portion of the radar signal and the amplitude (Rykhus and Zhong, 2011) Step 1 Interferogram Generation: this measures the phase difference between two SLC coregistered SAR images. One image is multiplied by the other image producing an interferogram of phase difference. Step 2 Interferogram Flattening: the constant phase (due to the acquisition geometry) and the phase expected for the topography (25m DEM of the site used) usually known as the „low frequency phase‟ is separated out from the residual differential phase known as the „high frequency phase‟ which relates to the temporal phase variation between the master and slave image. Step 3 Interferogram Adaptive Filter and Coherence Generation: The filtering of the flattened interferogram produces a product with reduced phase noise. As a byproduct the coherence is generated as an indicator of phase quality and the intensity filtered images. Step 4 Phase UnwrappingStep 5 Generate Ground Control Points: The _fint and _cc images were opened and a New Vector Layer was generated in ENVI 4.7. GCP‟s were selected off the _fint image using the _cc image as a guide to select points where there is high coherence values (white areas), avoiding fringes and black areas. Step 6 Phase to Displacement Conversion and Geocoding: This step was run to produce a geocoded version of the coherence image.
1stInSAR pair there is low coherence ranging from 0.14 – 0.24 depending on the CORINE defined land cover class. 2ndInSAR pair shows a slight increase of coherence for all land cover classes except natural grassland inside the fire scar which remains constant at 0.19 3rdInSAR pair acquired after the fire s(19/04/03 – 24/05/03) show all 3 land cover classes inside the fire scar exhibit an increase in coherence. Greatest increase is moors and heathlands class inside the fire scar value of 0.46 compared to 2nd pair at 0.29Can see this increase visually on the west side of the fire scar Coherence for moors and heathlands outside the fire scar decreased from 0.29 to 0.23 this could be due to phenological change of the heathlands. 4thInSAR pair shows an overall decrease in coherence for all classes, I think this result is due to temporal decorrelation as the initial baseline was highe at 654. Reseeding also occurred on the east side of the fire scar during this time.
Data selected from ESA Small incidence angle as Huang and Siegert (2006) found backscatter decreased with an increase in incidence angle from the fire scarSARScape 4.2 pre-processing. Focusing and multilooking to produce intensity image Frost, Lee and Degrandi filtering algorithms tested with 2 ERS-2 data – Degrandi smoothed speckle more effectively (amplitude coregistration must be done using this filter as it is a multi temporal filter)Geocoding and radiometic calibration was applied to produce geocoded greyscale images at 25m