This document summarizes the validation of phenology products from the AusCover Phenocam Network. The network uses tower-mounted cameras to capture plant phenology and validate satellite-derived phenology. Comparisons between camera and MODIS satellite data show correlations between greenness indices. The network aims to improve understanding of seasonal vegetation dynamics and carbon/water fluxes at flux tower sites across Australia.
TERN Australian Transect Network ATBC 2014TERN Australia
Alan Anderson of the Terrestrial Ecosystem Research Network (TERN) presenting on the Australian Transect Network at the 51st meeting of the Association for Tropical Biology and Conservation in Cairns in July 2014.
DRI Cloud Seeding Forum - Science and Program HistoryDRIscience
This document provides an overview of the history and scientific basis of cloud seeding. It discusses the conceptual model of cloud seeding, including that seeding material must be transported to clouds containing supercooled liquid water. Past research is summarized, including studies of seeding materials, transport and dispersion modeling, measurements of supercooled liquid water, and measurements showing microphysical and precipitation responses to seeding. Current research projects aiming to further validate the effects of cloud seeding are also mentioned. Hydrologic modeling techniques used to assess the impact of cloud seeding on streamflow are briefly outlined.
Stefan Maier_New, freely available remote sensing tools to better describe fi...TERN Australia
This document summarizes new freely available remote sensing products for monitoring fires in Australia. It describes MODIS and AVHRR datasets that provide information on fire frequency, active fire detections, burned area, fire radiative power, and fire severity at resolutions of 1km or less. These datasets can be used to analyze fire seasonality, characterize fire properties like spread rate, and improve understanding of when and why fires stop spreading. The outlook discusses using over 10 years of MODIS data at 250m resolution to map smaller fires and sub-pixel burn patches with automated methods. This will provide more detailed information on fire regimes, emissions, and ecological impacts in Australia.
Remote sensing of biophysical parameters: linking field, airborne and contine...TERN Australia
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.
Researchers at the Desert Research Institute (DRI) are exploring ways in which unmanned aircraft systems are increasingly being used in civilian government work as well as the private sector for use in applications as diverse as cloud seeding to fighting forest fires.
Use of near field remote sensing to monitor vegetation structural changes and bio-geochemical responses to climate change. Presented by Eva van Gorsel, CSIRO
Rudolf B. Husar presented at the EPA on exceptional smoke and dust events. He discussed using diverse data like satellites, models, and real-time data in a decision support system to evaluate these events. The NAAPS aerosol model assimilates satellite data to provide the 3D structure of smoke, dust, and other aerosols. Long-term NAAPS data from 2006 to present show the vertical distribution of different aerosols. Satellite data help reduce biases between surface PM measurements and air quality models.
Introduce variable/ Indices using landsat imageKabir Uddin
Image Index is a “synthetic image layer” created from the existing bands of a multispectral image. This new layer often provides unique and valuable information not found in any of the other individual bands.
Image index is a calculated result or generated product from satellite band/channels
It helps to identify different land cover from mathematical definition .
TERN Australian Transect Network ATBC 2014TERN Australia
Alan Anderson of the Terrestrial Ecosystem Research Network (TERN) presenting on the Australian Transect Network at the 51st meeting of the Association for Tropical Biology and Conservation in Cairns in July 2014.
DRI Cloud Seeding Forum - Science and Program HistoryDRIscience
This document provides an overview of the history and scientific basis of cloud seeding. It discusses the conceptual model of cloud seeding, including that seeding material must be transported to clouds containing supercooled liquid water. Past research is summarized, including studies of seeding materials, transport and dispersion modeling, measurements of supercooled liquid water, and measurements showing microphysical and precipitation responses to seeding. Current research projects aiming to further validate the effects of cloud seeding are also mentioned. Hydrologic modeling techniques used to assess the impact of cloud seeding on streamflow are briefly outlined.
Stefan Maier_New, freely available remote sensing tools to better describe fi...TERN Australia
This document summarizes new freely available remote sensing products for monitoring fires in Australia. It describes MODIS and AVHRR datasets that provide information on fire frequency, active fire detections, burned area, fire radiative power, and fire severity at resolutions of 1km or less. These datasets can be used to analyze fire seasonality, characterize fire properties like spread rate, and improve understanding of when and why fires stop spreading. The outlook discusses using over 10 years of MODIS data at 250m resolution to map smaller fires and sub-pixel burn patches with automated methods. This will provide more detailed information on fire regimes, emissions, and ecological impacts in Australia.
Remote sensing of biophysical parameters: linking field, airborne and contine...TERN Australia
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.
Researchers at the Desert Research Institute (DRI) are exploring ways in which unmanned aircraft systems are increasingly being used in civilian government work as well as the private sector for use in applications as diverse as cloud seeding to fighting forest fires.
Use of near field remote sensing to monitor vegetation structural changes and bio-geochemical responses to climate change. Presented by Eva van Gorsel, CSIRO
Rudolf B. Husar presented at the EPA on exceptional smoke and dust events. He discussed using diverse data like satellites, models, and real-time data in a decision support system to evaluate these events. The NAAPS aerosol model assimilates satellite data to provide the 3D structure of smoke, dust, and other aerosols. Long-term NAAPS data from 2006 to present show the vertical distribution of different aerosols. Satellite data help reduce biases between surface PM measurements and air quality models.
Introduce variable/ Indices using landsat imageKabir Uddin
Image Index is a “synthetic image layer” created from the existing bands of a multispectral image. This new layer often provides unique and valuable information not found in any of the other individual bands.
Image index is a calculated result or generated product from satellite band/channels
It helps to identify different land cover from mathematical definition .
Plant and Animal Genome XXIII, Together for better HTP digital phenotypingXavier Sirault
This document summarizes challenges and opportunities in digital phenotyping for agriculture. It discusses the need for intensive phenotyping at multiple scales from cells to canopies to understand photosynthesis. Advanced imaging technologies can now characterize 3D plant architecture and functional traits over time. Integrating these data through models is key to predicting crop responses. Main challenges include developing methods to assimilate remote sensing data to quantify traits and link information across scales. The High Resolution Plant Phenomics Centre is working to address these through a virtual laboratory environment.
eMAST aims to integrate data from TERN and other sources to model ecosystems at all scales in Australia from 2013-2015. This will be done using data assimilation, model evaluation and optimization tools to further ecosystem science and help address questions about topics like carbon, water, climate change, fire, and biodiversity. Key products being delivered include high resolution climate and productivity datasets as well as tools for data analysis, interpolation and modeling. Progress includes the development and delivery of ANUClimate climate datasets and the ePiSaT model for estimating primary productivity across Australia using flux tower and satellite data.
This document summarizes the results of a validation study of clear sky and all-weather solar irradiance models. It analyzed over 22 ground measurement sites in Europe and the Mediterranean over periods of up to 8 years. Key findings included:
- Hourly global irradiance models showed no bias and a standard deviation of 17-20%. Beam models had no bias and standard deviation of 34-50%.
- Daily models had no bias for global irradiance with a standard deviation of 8-12%, and no bias for beam with a standard deviation of 20-32%.
- Monthly models had negligible bias and standard deviations of 3-6% for global and 9-17% for beam irradiance.
The document assesses the sensitivity of the Penman-Monteith evapotranspiration model to input parameters derived from remote sensing data across a study area in South Africa over one year. It tests the sensitivity of the model to albedo, leaf area index (LAI), and canopy height derived from MODIS and aerial imagery. The results indicate that at low LAI and canopy height, uncertainties in these remote sensing inputs translate to large uncertainties in estimated evapotranspiration, suggesting the model may not be suitable in environments where accurate LAI and height cannot be guaranteed.
This document compares multispectral data collection from unmanned aerial vehicles (UAVs) to hyperspectral data collection from field instruments for calculating vegetation indexes. In the first year, satellite multispectral data was used to calculate indexes like NDVI and NDRE for different wheat cultivars. In the second year, a UAV carried a multispectral sensor to image test wheat fields, and indexes were also calculated from ground hyperspectral measurements for comparison. Results showed good agreement between indexes calculated from UAV and field sensor data. The study aims to evaluate low-cost UAVs for precision agriculture applications like fertilizer management.
WaPOR version 3 - H Pelgrum - eLeaf - 05 May 2023.pdfWaPOR
This document provides an overview of the WaPOR process for producing biophysical models and satellite-derived data products. It describes updates made in version 3, including using higher resolution VIIRS LST data with thermal sharpening, new meteorological inputs of ERA5/AgERA5, smoothing techniques, accounting for free convection in soil moisture modeling, and infrastructure changes in computing and data registration. The goal is to improve spatial resolution and accuracy of root zone soil moisture, evapotranspiration, and net primary production models.
The document summarizes a study that evaluates the uncertainties in global moderate resolution Leaf Area Index (LAI) products derived from satellite data, including MODIS and CYCLOPES. The study uses a global database of 219 field LAI measurements from 129 sites to directly validate the satellite products. Results show that while MODIS LAI estimates have improved across product versions, current LAI products still have uncertainties of around ±1.0, which does not meet the ±0.5 accuracy requirement set by GCOS. Future work is needed to reduce uncertainties, especially for certain biomes and conditions.
Greg Smestad, Leonardo Micheli, Thomas Germer, and Eduardo Fernández presented research on characterizing the optical effects of soiling on PV glass and modules. They measured the transmission of glass coupons exposed outdoors at multiple locations over 8 weeks and found soiling reduced transmission more at shorter wavelengths. Particle area coverage on the coupons correlated linearly with reduced hemispherical transmittance. Angular measurements showed soiling impacts transmission more for direct light than hemispherical. The research aims to better understand how soiling impacts PV performance globally.
Optical Characterization of PV Glass Coupons and PV Modules Related to Soilin...Greg Smestad
Optical Characterization of PV Glass Coupons and PV Modules Related to Soiling Losses,
Greg P. Smestad, Ph.D., Sol Ideas Technology Development
December 6th, 2017, 11:35 AM - 12:00 PM
Session 5: Characterization (Chair: Xiaohong Gu, NIST)
Atlas/NIST Workshop on PV Materials Durability
December 5-6, 2017, Gaithersburg, Maryland
National Institute of Standards and Technology, Gaithersburg, Maryland
https://www.nist.gov/el/mssd/agenda
This document validates the WindSight mesoscale wind modeling system. WindSight uses the WRF model to downscale global weather data and simulate wind conditions without pre-calculated data. Validation against measurements at 34 European sites found average errors below 1 m/s for 80% of sites. Wind roses and histograms also showed good agreement. The results prove WindSight useful for early-stage wind resource assessment and energy estimation when local data is limited.
This document presents a methodology to select phenologically suitable Landsat scenes for forest change detection by analyzing MODIS NDVI time series data from 2000-2009. The methodology filters MODIS NDVI composites to reduce noise, identifies start and end of peak growing season periods, and provides a web interface to search and select replacement scenes for the Global Land Survey that fall within identified phenological bounds. The methodology was able to identify suitable replacement scenes for over 200 Global Land Survey scenes from 2000 and 2005.
Hv uav multispectral compared to hyperspectral finalTerraLab srl
The document compares using multispectral data from UAVs versus hyperspectral data from field measurements for calculating vegetation indexes to monitor durum wheat. In the first year, the study used multispectral satellite data to calculate indexes like NDVI, NDRE, and MTCI. In the second year, a UAV was used to collect multispectral imagery for the same field to calculate the indexes and compare them to field hyperspectral measurements. The results showed UAV multispectral data can provide similar vegetation index values to field hyperspectral sensors and both are useful for monitoring wheat growth and estimating yields.
This document discusses the need for environmental impact assessments and best available techniques for seawater desalination projects given their potential impacts. It notes that while desalination is a resource intensive process, mitigation measures exist to address all significant environmental impacts and make sustainable desalination technically feasible using existing technologies. These include regulatory frameworks to minimize impacts on salinity, substitution of harmful chemicals, and compensation measures like using renewable energy to offset carbon emissions.
This document describes an atmospheric algorithm suite based on neural networks for microwave imagers/sounders. The suite includes profile products like temperature, moisture and pressure profiles as well as 2D fields like total water vapor and precipitation. Neural networks are used as they offer accuracy, robustness and speed compared to linear regression. Radiative transfer models and global NWP runs are used to generate training datasets. Preliminary performance shows the potential to meet requirements for products like temperature, moisture and precipitation retrieval in both clear and cloudy conditions. Limitations include precipitation effects, land emissivity variations and sampling challenges for different land elevations.
The document evaluates the performance of the TRMM Multi-satellite Precipitation Analysis (TMPA) product in estimating daily precipitation in the Central Andes region, compared to gauge measurements. It finds large biases in daily precipitation amounts from TMPA for the regions of Cuzco, Peru and La Paz, Bolivia, though strong precipitation events are generally detected. Correlation with gauge data increases significantly when aggregating TMPA estimates to longer time periods like weekly or monthly sums. Spatial aggregation has little effect on performance. The document proposes blending TMPA with daily gauge data to improve daily estimates.
Summary of DART Electromagnetic Methodology 100111DART Project
A summary of the proposed Electromagnetic methodology to be used on the DART project. Presented at the academic and stakeholder meetings (10th and 11th January 2011 respectively) by David Stott (Leeds University).
The document discusses validation of SMOS L1c and L2 soil moisture products using airborne and ground-based observations across Australia. It describes environmental conditions and essential climate variables in Australia. It outlines the MoistureMap project which uses data assimilation to provide high-resolution soil moisture information. Field campaigns were conducted in the Murrumbidgee catchment and Arid Zone to collect validation data on soil moisture, vegetation properties, and more to compare to SMOS retrievals from overflying aircraft and satellites. Results showed SMOS L1c brightness temperatures were biased high compared to aircraft measurements but bias was reduced after further processing to L2 soil moisture products.
The document discusses validation of SMOS L1c and L2 soil moisture products using airborne and ground-based observations across Australia. It describes environmental conditions and essential climate variables in Australia. It outlines the MoistureMap project which uses data assimilation to provide high-resolution soil moisture information. Field campaigns were conducted in the Murrumbidgee catchment and Arid Zone to collect validation data on soil moisture, vegetation properties, and other variables. Results show that SMOS L1c brightness temperatures are validated within error thresholds, while L2 soil moisture products show biases around -8% that need to be corrected.
Data recovery of archival data: a temporal storyAlison Specht
This presentation discusses the challenges of data preservation over centuries as technology and interest develops and changes. The case study is in three phases: (i) a project under the Conservation program of the International Biological Program (IBP) (1966-74). (ii) a project to digitise all of the survey data recorded across the continent, to establish an objective conservation status (1975-1995). (iii) recovery of the digitised data and conversion to modern, machine-readable status under the FAIR principles.
Collaboration for Environmental Evidence 2018, ParisAlison Specht
A presentation on behalf of the Foundation for Research on Biodiversity by Alison Specht on the role of analysis and synthesis centres as knowledge brokers between science and policy.
Plant and Animal Genome XXIII, Together for better HTP digital phenotypingXavier Sirault
This document summarizes challenges and opportunities in digital phenotyping for agriculture. It discusses the need for intensive phenotyping at multiple scales from cells to canopies to understand photosynthesis. Advanced imaging technologies can now characterize 3D plant architecture and functional traits over time. Integrating these data through models is key to predicting crop responses. Main challenges include developing methods to assimilate remote sensing data to quantify traits and link information across scales. The High Resolution Plant Phenomics Centre is working to address these through a virtual laboratory environment.
eMAST aims to integrate data from TERN and other sources to model ecosystems at all scales in Australia from 2013-2015. This will be done using data assimilation, model evaluation and optimization tools to further ecosystem science and help address questions about topics like carbon, water, climate change, fire, and biodiversity. Key products being delivered include high resolution climate and productivity datasets as well as tools for data analysis, interpolation and modeling. Progress includes the development and delivery of ANUClimate climate datasets and the ePiSaT model for estimating primary productivity across Australia using flux tower and satellite data.
This document summarizes the results of a validation study of clear sky and all-weather solar irradiance models. It analyzed over 22 ground measurement sites in Europe and the Mediterranean over periods of up to 8 years. Key findings included:
- Hourly global irradiance models showed no bias and a standard deviation of 17-20%. Beam models had no bias and standard deviation of 34-50%.
- Daily models had no bias for global irradiance with a standard deviation of 8-12%, and no bias for beam with a standard deviation of 20-32%.
- Monthly models had negligible bias and standard deviations of 3-6% for global and 9-17% for beam irradiance.
The document assesses the sensitivity of the Penman-Monteith evapotranspiration model to input parameters derived from remote sensing data across a study area in South Africa over one year. It tests the sensitivity of the model to albedo, leaf area index (LAI), and canopy height derived from MODIS and aerial imagery. The results indicate that at low LAI and canopy height, uncertainties in these remote sensing inputs translate to large uncertainties in estimated evapotranspiration, suggesting the model may not be suitable in environments where accurate LAI and height cannot be guaranteed.
This document compares multispectral data collection from unmanned aerial vehicles (UAVs) to hyperspectral data collection from field instruments for calculating vegetation indexes. In the first year, satellite multispectral data was used to calculate indexes like NDVI and NDRE for different wheat cultivars. In the second year, a UAV carried a multispectral sensor to image test wheat fields, and indexes were also calculated from ground hyperspectral measurements for comparison. Results showed good agreement between indexes calculated from UAV and field sensor data. The study aims to evaluate low-cost UAVs for precision agriculture applications like fertilizer management.
WaPOR version 3 - H Pelgrum - eLeaf - 05 May 2023.pdfWaPOR
This document provides an overview of the WaPOR process for producing biophysical models and satellite-derived data products. It describes updates made in version 3, including using higher resolution VIIRS LST data with thermal sharpening, new meteorological inputs of ERA5/AgERA5, smoothing techniques, accounting for free convection in soil moisture modeling, and infrastructure changes in computing and data registration. The goal is to improve spatial resolution and accuracy of root zone soil moisture, evapotranspiration, and net primary production models.
The document summarizes a study that evaluates the uncertainties in global moderate resolution Leaf Area Index (LAI) products derived from satellite data, including MODIS and CYCLOPES. The study uses a global database of 219 field LAI measurements from 129 sites to directly validate the satellite products. Results show that while MODIS LAI estimates have improved across product versions, current LAI products still have uncertainties of around ±1.0, which does not meet the ±0.5 accuracy requirement set by GCOS. Future work is needed to reduce uncertainties, especially for certain biomes and conditions.
Greg Smestad, Leonardo Micheli, Thomas Germer, and Eduardo Fernández presented research on characterizing the optical effects of soiling on PV glass and modules. They measured the transmission of glass coupons exposed outdoors at multiple locations over 8 weeks and found soiling reduced transmission more at shorter wavelengths. Particle area coverage on the coupons correlated linearly with reduced hemispherical transmittance. Angular measurements showed soiling impacts transmission more for direct light than hemispherical. The research aims to better understand how soiling impacts PV performance globally.
Optical Characterization of PV Glass Coupons and PV Modules Related to Soilin...Greg Smestad
Optical Characterization of PV Glass Coupons and PV Modules Related to Soiling Losses,
Greg P. Smestad, Ph.D., Sol Ideas Technology Development
December 6th, 2017, 11:35 AM - 12:00 PM
Session 5: Characterization (Chair: Xiaohong Gu, NIST)
Atlas/NIST Workshop on PV Materials Durability
December 5-6, 2017, Gaithersburg, Maryland
National Institute of Standards and Technology, Gaithersburg, Maryland
https://www.nist.gov/el/mssd/agenda
This document validates the WindSight mesoscale wind modeling system. WindSight uses the WRF model to downscale global weather data and simulate wind conditions without pre-calculated data. Validation against measurements at 34 European sites found average errors below 1 m/s for 80% of sites. Wind roses and histograms also showed good agreement. The results prove WindSight useful for early-stage wind resource assessment and energy estimation when local data is limited.
This document presents a methodology to select phenologically suitable Landsat scenes for forest change detection by analyzing MODIS NDVI time series data from 2000-2009. The methodology filters MODIS NDVI composites to reduce noise, identifies start and end of peak growing season periods, and provides a web interface to search and select replacement scenes for the Global Land Survey that fall within identified phenological bounds. The methodology was able to identify suitable replacement scenes for over 200 Global Land Survey scenes from 2000 and 2005.
Hv uav multispectral compared to hyperspectral finalTerraLab srl
The document compares using multispectral data from UAVs versus hyperspectral data from field measurements for calculating vegetation indexes to monitor durum wheat. In the first year, the study used multispectral satellite data to calculate indexes like NDVI, NDRE, and MTCI. In the second year, a UAV was used to collect multispectral imagery for the same field to calculate the indexes and compare them to field hyperspectral measurements. The results showed UAV multispectral data can provide similar vegetation index values to field hyperspectral sensors and both are useful for monitoring wheat growth and estimating yields.
This document discusses the need for environmental impact assessments and best available techniques for seawater desalination projects given their potential impacts. It notes that while desalination is a resource intensive process, mitigation measures exist to address all significant environmental impacts and make sustainable desalination technically feasible using existing technologies. These include regulatory frameworks to minimize impacts on salinity, substitution of harmful chemicals, and compensation measures like using renewable energy to offset carbon emissions.
This document describes an atmospheric algorithm suite based on neural networks for microwave imagers/sounders. The suite includes profile products like temperature, moisture and pressure profiles as well as 2D fields like total water vapor and precipitation. Neural networks are used as they offer accuracy, robustness and speed compared to linear regression. Radiative transfer models and global NWP runs are used to generate training datasets. Preliminary performance shows the potential to meet requirements for products like temperature, moisture and precipitation retrieval in both clear and cloudy conditions. Limitations include precipitation effects, land emissivity variations and sampling challenges for different land elevations.
The document evaluates the performance of the TRMM Multi-satellite Precipitation Analysis (TMPA) product in estimating daily precipitation in the Central Andes region, compared to gauge measurements. It finds large biases in daily precipitation amounts from TMPA for the regions of Cuzco, Peru and La Paz, Bolivia, though strong precipitation events are generally detected. Correlation with gauge data increases significantly when aggregating TMPA estimates to longer time periods like weekly or monthly sums. Spatial aggregation has little effect on performance. The document proposes blending TMPA with daily gauge data to improve daily estimates.
Summary of DART Electromagnetic Methodology 100111DART Project
A summary of the proposed Electromagnetic methodology to be used on the DART project. Presented at the academic and stakeholder meetings (10th and 11th January 2011 respectively) by David Stott (Leeds University).
The document discusses validation of SMOS L1c and L2 soil moisture products using airborne and ground-based observations across Australia. It describes environmental conditions and essential climate variables in Australia. It outlines the MoistureMap project which uses data assimilation to provide high-resolution soil moisture information. Field campaigns were conducted in the Murrumbidgee catchment and Arid Zone to collect validation data on soil moisture, vegetation properties, and more to compare to SMOS retrievals from overflying aircraft and satellites. Results showed SMOS L1c brightness temperatures were biased high compared to aircraft measurements but bias was reduced after further processing to L2 soil moisture products.
The document discusses validation of SMOS L1c and L2 soil moisture products using airborne and ground-based observations across Australia. It describes environmental conditions and essential climate variables in Australia. It outlines the MoistureMap project which uses data assimilation to provide high-resolution soil moisture information. Field campaigns were conducted in the Murrumbidgee catchment and Arid Zone to collect validation data on soil moisture, vegetation properties, and other variables. Results show that SMOS L1c brightness temperatures are validated within error thresholds, while L2 soil moisture products show biases around -8% that need to be corrected.
Similar to Restrepo Huete phenocams ACEAS 140311 (20)
Data recovery of archival data: a temporal storyAlison Specht
This presentation discusses the challenges of data preservation over centuries as technology and interest develops and changes. The case study is in three phases: (i) a project under the Conservation program of the International Biological Program (IBP) (1966-74). (ii) a project to digitise all of the survey data recorded across the continent, to establish an objective conservation status (1975-1995). (iii) recovery of the digitised data and conversion to modern, machine-readable status under the FAIR principles.
Collaboration for Environmental Evidence 2018, ParisAlison Specht
A presentation on behalf of the Foundation for Research on Biodiversity by Alison Specht on the role of analysis and synthesis centres as knowledge brokers between science and policy.
Data Challenges and Solutions in the Environmental and Eco-social Sciences. Talk in the session: Research across Disciplinary Boundaries, at the conference Global Collaboration on Data Beyond Disciplines < https://ds.rois.ac.jp/article/dsws_2020/ >, September 23-25 2020
Retrospective Analysis of Antarctic Tracking DataAlison Specht
This document describes the SCAR Retrospective Analysis of Antarctic Tracking Data (RAATD) project. The project involves analyzing over 4060 animal tracking records from 17 Antarctic species, totaling nearly 3 million location points. The goal is to identify Areas of Ecological Significance in the Southern Ocean that are important for multiple predator species and have high biodiversity of lower trophic levels. Habitat utilization models are being developed for each species to predict habitat use globally based on environmental conditions. Preliminary results from a habitat model for Southern elephant seals are shown, identifying regions of high and low predicted habitat suitability. The project aims to improve understanding of Antarctic ecosystem processes and inform spatial management decisions.
Community assembly on remote islands: does equilibrium theory apply?Alison Specht
The presentation of the CESAB group ISLANDS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by Christophe Thébaud.
African rainforest dynamics: interactions between ecological processes and co...Alison Specht
The presentation of the CESAB group RAINBIO at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by Thomas Couvreur.
Community resistance to biological invasions : role of diversity and network ...Alison Specht
The presentation of the CESAB group LOLA-BMS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by François Massol and Patrice David
Origin and congruence of taxonomic, phylogenetic and functional diversity in ...Alison Specht
The presentation of the CESAB group LOLA-BMS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by Arndt Hampe.
How local-scale processes build up the large-scale response of butterflies to...Alison Specht
The presentation of the CESAB group LOLA-BMS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by Reto Schmucki.
NETSEED : a cross-disciplinary project to analyse how small farms contribute ...Alison Specht
The presentation of the CESAB group NETSEED at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presented by Mathieu Thomas.
The linkages between biodiversity and the transmission of emerging infectious...Alison Specht
The document discusses the linkages between biodiversity and emerging infectious diseases. It summarizes the aims of the BIODIS/CESAB working group, which are to understand how biodiversity impacts disease spillovers and transmission in wildlife, test these relationships using different host-disease models and field studies, and understand which host traits influence disease infection and transmission. The group is made up of researchers studying various disease systems like Lyme disease, West Nile virus, and Buruli ulcer. They use mathematical modeling and have published several papers investigating whether the "dilution effect" concept, where higher diversity lowers disease risk, applies broadly. Their work examines how local diversity in host reservoirs and vectors influences disease transmission patterns.
Macroecology of species pools: insights from network theoryAlison Specht
The presentation of the CESAB group DIVGRASS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presenter: Pierre Denelle
The presentation of the CESAB group gaspar at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presenter: Michel Kulbicki
Feedback of a couple of eco-informatic tools for soil invertebrate functional...Alison Specht
The presentation of the CESAB group BETSI at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presenter: Johanne Nahmani
Global patterns of insect diiversity, distribution and evolutionary distinctnessAlison Specht
The presentation of the CESAB group ACTIAS at the 2016 french ecology conference in the FRB-CESAB session "Using a treasury of knowledge to tackle complex ecological questions." Presenter: Carlos Lopez-Vaamonde
Biodiversity of intermittent rivers: analysis & synthesisAlison Specht
This document discusses synthesizing and analyzing biodiversity in intermittent rivers. It notes that intermittent rivers are prevalent globally, not just in dry climates, and are expanding due to climate change. Intermittent rivers are dynamic ecosystems that are coupled to both aquatic and terrestrial habitats. The objectives of the IRBAS group are to assemble data on biodiversity and hydrology in intermittent rivers, analyze relationships between flow patterns and biodiversity, and translate knowledge into management practices. Key results so far show increased interest in intermittent rivers but fragmented existing knowledge, and that alpha diversity declines as flow intermittence increases. A global database on intermittent river biodiversity is being developed.
Understanding properties of food webs, such as their topology or stability, and the rules underlying food web structure, has been a key issue in ecology for now more than half a century. Because obtaining data on food webs has long been a hard task by itself, this research field has progressed slowly, and its dynamical aspects have seldom been empirically considered. However, technical advances, like next generation sequencing or the possibility of retrieving past ecosystems in sediment cores, have paved the way for massive data and the analysis of time series on food webs, while new models allow better predictions about food web dynamics. Making use of such existing data sets, this working group aimed at assessing the effects of biological invasions on food web topology, the fluxes of energy and nutrients throughout the network, and its ultimate effects on biodiversity. The working group has provided an integrative view on this topic, simultaneously tackling empirical, theoretical and applied aspects of biological invasions in food webs. Obvious applications will arise both from the numerous transports of invasive species and from the reshuffling of natural communities that is expected under global change scenarios. The working group comprised theoreticians and empiricists, biological invasion specialists as well as food web and host-parasite network experts, and benefited from existing experience in the field of ecoinformatics and massive data management in ecology.
Jason Stockwell's overview of the GEISHA project (CESAB-John Wesley Powell Center) at the "Supporting Data-Intensive Freshwater and Marine Research: Integrating Informatics, Infrastructure, Databases and Open Science" session at the Association for the Sciences of Limnology and Oceanography (ASLO) meeting in Honolulu, Hawaii, in February 2017.
Data sharing archiving discovery, Bill MichenerAlison Specht
A presentation by Bill Michener (University of New Mexico and DataONE) about data sharing, archiving and discovery. It was an introduction to a session co-hosted by FRB-CESAB and CEFE (CNRS) in Montpellier.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
A Strategic Approach: GenAI in EducationPeter Windle
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1. Australian Phenology
Product Validation:
Phenocam Network
Natalia Restrepo-Coupe and Alfredo Huete
University Technology of Sydney
AusCover Sydney Phenology Node
Kevin Davies, Michael Liddell, Nicolas Weigand, Craig.Macfarlane, John
Byrne , Victor Resco de Dios, Matthias Boer, Chelsea Maier, Nicolas
Boulain, James Cleverly, Derek Eamus, Georgia Koerber, and Wayne S
Meyer
2. Introduction
Phenology – definition and how it is characterized with the use of RS
products (VIs)
AusCover at the UTS Sydney node:
Phenology product: applications in conservation, aerobiology, LSM inputs
Land Surface Temperature product
Disturbance product
3. Objective: Validation Phenology Product
AusCover UTS Sydney node
Validation of the phenology product
Link between the in-situ measurement and the remote sensing community
(this is study is conducted in collaboration with Ozflux tower PIs).
Site-specific support to the flux tower data collection (symbiosis)
Contribute to the understanding of water and carbon flux seasonal cycles
(personal objective)
5. Methods: Flux towers
Ma,
X.,
et
al.,
2013.
Spa7al
pa8erns
and
temporal
dynamics
in
savanna
vegeta7on
phenology
across
the
North
Australian
Tropical
Transect.
Remote
Sens.
Environ.
139,
97–115.
doi:10.1016/j.rse.2013.07.030
7. Methods: Phenocams
AusCover Good Practice Guidelines (A technical handbook supporting
calibration and validation activities of remotely sensed data products)
Chapter 8. Phenology Validation
Literature review
Different methods
Phenocams
Our experience
Our approach to instrument set-up, data collection and processing
8. Methods: Phenocams
Phenocams :
• RGB and spectral cameras
• Orientation, angles, azimuths
• Over- and understory
• Diurnal, daily, and seasonal settings, including frequency of observations
(e.g. 30 minutes)
• Camera settings, integration times, F-stop, etc.
• Use of White/Gray references
• Computation Red/Green (RGB) and NIR/Red ratios (spectral) with and
without use of reference
Our method is designed to support the following working hypothesis…
9. Working hypothesis
Use of tower mounted phenocam imagery of whole-canopy and tree and
understory layer vegetation to trace and evaluate the satellite phenology
profile (e.g. both measures should provide a similar start of green-up and
peak at same time, etc.).
Assessment of satellite phenology product accuracies in depicting the
timing of seasonal vegetation dynamics, phenophases, and other
transitional dates in time and space (cross-site).
Phenocams have the potential to assess and partition seasonality of the
tree layer, grass layer, and whole-canopy.
Whether the change in signal is attributed to more leaves, greener
leaves, younger-leaves, or some combination.
Although, a mechanistic understanding of phenology drivers is not a direct
requirement of validation, it does enable up-scaling of point-based phenology
to landscapes.
10. ALICE SPRINGS
CHOWILLA
ZIG ZAG
GINGIN CUMBERLAND
PLAINS
CREDO
SE QUEENSLAND
SUPERSITE
Mean annual precipitation (mm/month)
Tropical Rainfall Measuring Mission (TRMM) data (NASA, 2013)
DISCOVERY CENTER
ROBSON CREEK
DAINTREE
Phenocam
Network
Methods: Budget
We do not mind replication
We adapt our protocol to the
site (Natalia open the protocol)
http://data.auscover.org.au/
xwiki/bin/view/Teams/
GoodPracticeHanbook
11. Phenocam Network Objectives: Site specific
ALICE SPRINGS
CHOWILLA
ZIG ZAG
GINGIN CUMBERLAND
PLAINS
CREDO
SE QUEENSLAND
SUPERSITE
Special thanks to Dr. M Liddell and N. Weigand
DISCOVERY CENTER
ROBSON CREEK
DAINTREE
12. Phenocam Network Objectives: Site specific
ALICE SPRINGS
CHOWILLA
ZIG ZAG
GINGIN CUMBERLAND
PLAINS
CREDO
SE QUEENSLAND
SUPERSITE
Special thanks to Dr. V Resco de Dios, Matthias Boer and Chelsea Maier
Natalia open
document about
Cumberland
13. Phenocam Network Objectives: Site specific
ALICE SPRINGS
CHOWILLA
ZIG ZAG
GINGIN CUMBERLAND
PLAINS
CREDO
SE QUEENSLAND
SUPERSITE
Special thanks to Prof D. Chittleborough, Prof W. Meyer, Dr. G. Whiteman and T. Luckbe
14. Phenocam Network Objectives: Site specific
ALICE SPRINGS
CHOWILLA
ZIG ZAG
GINGIN CUMBERLAND
PLAINS
CREDO
SE QUEENSLAND
SUPERSITE
Special thanks to Dr. J. Cleverly, Dr. N Boulain, R Faux, Dr. N. Grant and Prof Derek Eamus
15. Alice Springs Mulga, NT
Wingscapes
Alice Springs Mulga, NT
Campbell Sci cameras
Phenocam Network:
Sensor Comparison
16. Phenocam
Network:
Camera
Calibration
Figure 1. Relationship between camera
incoming radiation (x-axis) and the raw output
signal (DN) for a Spectralon white panel in 6
bands: Red (centered at wavelengths of 655),
Green (555), NIR (857), Blue (460) and
wavebands 923 and 728. Camera settings: f-
stop 5.6, gain =1 and integration time = 15.
Digital number DN for non calibrated images. An
incident PAR a light meter (umol m-2 s-1) was
used to guide the experiment.
17. Phenocam
Network:
Linking RGB
indices to
physiological
response Red/Green
2
1.5
1
0.5
Wet Dry Mulga site biological
crust (>50%
Cyanobacteria) Green/
Red response after
wetting (1.57 mm).
-2 -1 0 1 2 3 4
Time (hours)
-2 -1 0 1 2 3 4
3
2.5
2
1.5
1
0.5
Red/Green
Riverbed/Red Gum
site biological crust
(>50% Moss) Green/
Red response after
wetting (1.57 mm).
Special thanks to J. Jamieson, Dr
N. Boulain, and Dr A. Leight
Wet
18. Calperum-Chowilla Flux Tower Site
25-Oct-2012 12:00:00 Red/Green
0
0.5
1
1.5
2
Rainfall(mm)
0
20
40
04/01 05/01 06/01 07/01 08/01 09/01 10/01
0.8
1.2
1.6
Red/Green
Grasses Shrubs Salt Bush Soil Biological Crust Soil
Understory camera
19. 04/01 05/01 06/01 07/01 08/01 09/01 10/01 11/01
0.8
1.2
1.6
Red/GreenPhenocams
1
1.3
1.6
Red/GreenMODIS
04/01 05/01 06/01 07/01 08/01 09/01 10/01 11/01
0.95
1.1
1.25
Red/GreenPhenocams
1.2
1.4
1.6
Red/GreenMODIS
Calperum-Chowilla (CHO) RGB understory camera
MODIS reflectances (Bi-directional Reflectance Distribution Function, BRDF model MCD43A4)
Grasses Shrubs Salt Bush Soil Biological Crust Soil
MODIS All image (green) Mean Grass, Shrubs, Salt Bush
1.2 1.3 1.4 1.5 1.6
1.1
1.15
1.2
1.25
1.3
R/G
MODIS
=0.09195 R/G
cam
+1.06
p=0.0048 r2=0.24
R/GMODIS
R/Gcam
1.2 1.3 1.4 1.5 1.6
0.9
1
1.1
R/G
MODIS
=0.25 R/G
cam green
+0.704
p=0.0014 r2=0.3
R/GMODIS
R/Gcamgreen
20. 04/01 05/01 06/01 07/01 08/01 09/01 10/01 11/01
0.8
0.925
1.05
Green/RedPhenocams
0.1
0.2
0.3
EVIMODIS
04/01 05/01 06/01 07/01 08/01 09/01 10/01 11/01
0.8
0.925
1.05
Green/RedPhenocams
0.2
0.4
0.6
NDVIMODIS
All image (green) Mean Grass, Shrubs, Salt Bush
MODIS
Calperum-Chowilla (CHO) RGB understory camera
MODIS vegetation indices (MOD13) 16-day product linearly resampled to 8-day
0.1 0.15 0.2 0.25 0.3
1.1
1.15
1.2
1.25
1.3
R/G
MODIS
=-0.3744 R/G
cam
+1.26
p=0.0011 r2=0.31
EVIMODIS
R/Gcam
0.1 0.15 0.2 0.25 0.3
0.9
1
1.1
R/G
MODIS
=-1.403 R/G
cam
+1.33
p=0.00062 r2=0.34
EVIMODIS
R/Gcamgreen
0.3 0.4 0.5 0.6
1.1
1.15
1.2
1.25
1.3
R/G
MODIS
=-0.0956 R/G
cam green
+1.23
p=0.019 r2=0.18
NDVIMODIS
R/Gcam
0.3 0.4 0.5 0.6
0.9
1
1.1
R/G
MODIS
=-0.272 R/G
cam green
+1.16
p=0.0099 r2=0.21
NDVIMODIS
R/Gcamgreen
Dropinactivity
Riseinactivity
Green/Red (instead of Red/Green)
21. 0
0.5
1
1.5
Rainfall(mm)
0
20
04/01 07/01 10/01 01/01
1.1
1.2
1.3
Red/Green
--- WindowSE--- WindowW--- WindowS
Calperum-Chowilla Flux Tower Site
06-Mar-2013 10:00:00 Red/Green
0
0.5
1
1.5
2
ainfall(mm)
20
1.2
1.3
ed/Green
--- WindowSE--- WindowW--- WindowS
2012 2013
Tower nadir camera
23. 0.1 0.15 0.2 0.25 0.3
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=-0.4369 R/G
cam
+1.35
p=0.0016 r2=0.21
EVIMODIS
R/Gcam
0.3 0.4 0.5 0.6
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=-0.1372 R/G
cam green
+1.32
p=0.00042 r2=0.25
NDVIMODIS
R/Gcam
1.2 1.3 1.4 1.5 1.6
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=0.07184 R/G
cam
+1.17
p=0.01 r2=0.14
R/GMODIS
R/Gcam
F M A M J J A S O N D J F M
1.1
1.3
1.5
Red/GreenPhenocams
1.2
1.4
1.6
Red/GreenMODIS
F M A M J J A S O N D J F M
0.75
0.8
0.85
Green/RedPhenocams
0.1
0.2
0.3
EVIMODIS
F M A M J J A S O N D J F M
0.75
0.8
0.85
Green/RedPhenocams
0.2
0.4
0.6
NDVIMODIS
Window E
Window S
Window W
MODIS
Mean all windows
MODIS
Mean all windows
MODIS
24. 0.1 0.15 0.2 0.25 0.3
1
1.05
1.1
1.15
1.2
R/G
MODIS
=-0.6335 R/G
cam
+1.21
p=1.5e-05 r2=0.36
EVIMODIS
R/Gcamgreen
0.3 0.4 0.5 0.6
1
1.05
1.1
1.15
1.2
R/G
MODIS
=-0.1914 R/G
cam green
+1.16
p=7.6e-06 r2=0.38
NDVIMODIS
R/Gcamgreen
0.1 0.15 0.2 0.25 0.3
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=-0.4369 R/G
cam
+1.35
p=0.0016 r2=0.21
EVIMODIS
R/Gcam
0.3 0.4 0.5 0.6
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=-0.1372 R/G
cam green
+1.32
p=0.00042 r2=0.25
NDVIMODIS
R/Gcam
F M A M J J A S O N D J F M
0.85
0.925
1
Green/RedPhenocams
0.1
0.2
0.3
EVIMODIS
F M A M J J A S O N D J F M
0.85
0.925
1
Green/RedPhenocams
0.2
0.4
0.6
NDVIMODIS
Green vegetation window
Red/Green
Eucalyptus window
MODIS
Green/Red (instead of Red/Green)
25. 1.2 1.3 1.4 1.5 1.6
1.2
1.25
1.3
1.35
1.4
R/G
MODIS
=0.07184 R/G
cam
+1.17
p=0.01 r2=0.14
R/GMODIS
R/Gcam
1.2 1.3 1.4 1.5 1.6
1
1.05
1.1
1.15
1.2
R/G
MODIS
=0.1291 R/G
cam green
+0.903
p=1.6e-05 r2=0.36
R/GMODIS
R/Gcamgreen
F M A M J J A S O N D J F M
1.15
1.275
1.4
Red/GreenPhenocams
1.2
1.4
1.6
Red/GreenMODIS
F M A M J J A S O N D J F M
1.03
1.08
1.13
Red/GreenPhenocams
1.2
1.4
1.6
Red/GreenMODIS
Window E
Window S
Window W
MODIS
Eucalyptus
window
MODIS
27. 0.9 0.95 1 1.05 1.1
0.7
0.8
0.9
1
R/G
MODIS
=0.9572 R/G
cam
+-0.0733
p=0.00091 r2=0.37
R/GMODIS
R/Gcam
0.9 0.95 1 1.05 1.1
0.4
0.5
0.6
0.7
0.8
R/G
MODIS
=2.32 R/G
cam green
+-1.64
p=0.0001 r2=0.47
R/GMODIS
R/Gcamgreen
All image
(green) Mean Banskia01, Banskia01, Shrubs
MODIS
Jun Jul Aug Sep Oct Nov
0
0.5
1Red/GreenPhenocams
0.8
0.95
1.1
Red/GreenMODIS
Jun Jul Aug Sep Oct Nov
0.4
0.7
1
Red/GreenPhenocams
0.9
1
1.1
Red/GreenMODIS
28. Green/Red (instead of Red/Green)
0.2 0.25 0.3
0.7
0.8
0.9
1
R/G
MODIS
=-3.54 R/G
cam
+1.78
p=5.9e-05 r2=0.5
EVIMODIS
R/Gcam
0.2 0.25 0.3
0.4
0.5
0.6
0.7
0.8
R/G
MODIS
=-6.757 R/G
cam
+2.37
p=2e-05 r2=0.54
EVIMODIS
R/Gcamgreen
0.4 0.5 0.6
0.7
0.8
0.9
1
R/G
MODIS
=-0.645 R/G
cam green
+1.24
p=1.3e-05 r2=0.55
NDVIMODIS
R/Gcam
0.4 0.5 0.6
0.4
0.5
0.6
0.7
0.8
R/G
MODIS
=-1.507 R/G
cam green
+1.51
p=1.6e-05 r2=0.55
NDVIMODIS
R/Gcamgreen
Jun Jul Aug Sep Oct Nov
1
1.6
2.2
Green/RedPhenocams
0.2
0.25
0.3
EVIMODIS
Jun Jul Aug Sep Oct Nov
1
1.6
2.2
Green/RedPhenocams
0.4
0.6
0.8
NDVIMODISAll image
(green) Mean Banskia01, Banskia01, Shrubs
MODIS
29. 2012 2013
Understory camera
Low density
Alice Springs Mulga Flux Tower Site
15-Oct-2012 14:00:00 Red/Green
0
0.5
1
1.5
2
Rainfall(mm)
0
11
22
S N D J F M A M J J A S O
1
1.4
1.8
Red/Green
--- Grass01
--- Grass02 --- Acacia
--- Litter
--- Crust