#2021ReSAKSS - Plenary Session I – presentation by Dr. Eliane Ubalijoro, Executive Director, Sustainability in The Digital Age, Global Hub Director, Canada, Future
Earth, and Co-editor of the 2021 Annual Trends and Outlook Report (ATOR)
Johan Swinnen
CONFERENCE
IFIAD Annual Conference 2020
COVID-19 & Sustainable Food Systems - Transforming food systems in times of crises
OCT 21, 2020 - 10:00 AM TO 01:00 PM IST
Christophe Béné (The Alliance Bioversity International – CIAT)
Deborah Bakker and Anne Sonneveld (Wageningen University and Research)
Monica Chavarro, Brice Even and Jenny Melo (The Alliance Bioversity International – CIAT
Food systems lessons from COVID-19: From understanding fragilities to building resilience
Co-Organized by IFPRI and the CGIAR COVID-19 Hub
MAR 2, 2021 - 09:30 AM TO 11:00 AM EST
#2021ReSAKSS - Plenary Session I – presentation by Dr. Eliane Ubalijoro, Executive Director, Sustainability in The Digital Age, Global Hub Director, Canada, Future
Earth, and Co-editor of the 2021 Annual Trends and Outlook Report (ATOR)
Johan Swinnen
CONFERENCE
IFIAD Annual Conference 2020
COVID-19 & Sustainable Food Systems - Transforming food systems in times of crises
OCT 21, 2020 - 10:00 AM TO 01:00 PM IST
Christophe Béné (The Alliance Bioversity International – CIAT)
Deborah Bakker and Anne Sonneveld (Wageningen University and Research)
Monica Chavarro, Brice Even and Jenny Melo (The Alliance Bioversity International – CIAT
Food systems lessons from COVID-19: From understanding fragilities to building resilience
Co-Organized by IFPRI and the CGIAR COVID-19 Hub
MAR 2, 2021 - 09:30 AM TO 11:00 AM EST
Joseph Glauber
POLICY SEMINAR
Virtual Event - The political economy of COVID-19: Impacts on agriculture and food policies
OCT 22, 2020 - 08:30 AM TO 10:00 AM EDT
Danielle Resnick
POLICY SEMINAR
Virtual Event - The political economy of COVID-19: Impacts on agriculture and food policies
OCT 22, 2020 - 08:30 AM TO 10:00 AM EDT
Maximo Torero
The 2021 United Nations Food Systems Summit: How to Incentivize Food Loss and Waste Reduction
Co-Organized by the International Food Policy Research Institute, Embassy of Denmark in Washington D.C., World Resources Institute, and Champions 12.3
MAR 12, 2021 - 09:30 AM TO 11:00 AM EST
GLOBAL FOOD POLICY REPORT
IFPRI South Asia Discussion of the 2020 Global Food Policy Report
Co-Organized by IFPRI, Indian Council of Agricultural Research Johan Swinnen
(ICAR), and Trust for Advancement of Agricultural Sciences (TAAS)
JUL 6, 2020 - 04:30 PM TO 06:00 PM IST
Máximo Torero
POLICY SEMINAR
Making agrifood systems more resilient to shocks and stresses
Co-Organized by IFPRI and FAO North America
JAN 19, 2022 - 9:30 TO 11:00AM EST
This presentation was given on 27 October 2021 by Krystal Crumpler, Climate Change and Agricultural Specialist at FAO, during the webinar "Achieving NDC Ambition in Agriculture" organized by CCAFS, FAO and WRI.
Find the recording and more information here: https://bit.ly/AchievingNDCs
Johan Swinnen
SEMINAR
Virtual Event --Discussion of the 2020 Global Food Policy Report
Co-Organized by the Ministry of Foreign Affairs, Government of the Netherlands, IFPRI, and Food & Business Knowledge Platform
APR 28, 2020 - 10:00 AM TO 11:15 AM EDT
2020 The State of Food Security and Nutrition in the World: Challenges and op...Francois Stepman
“2020 The State of Food Security and Nutrition in the World: Challenges and opportunities for LDCs, LLDCs and SIDs” by Máximo Torero Cullen, FAO Chief Economist
13 July 2020. SOFI: Transforming food systems Hand-in-Hand to deliver affordable healthy diets in Least developed Countries (LDCs), Landlocked Developing Countries (LLDCs) and Small Island Developing States (SIDS)
Rob Vos
POLICY SEMINAR
Retail food prices at the country level and implications for food security
How are rising food prices, further aggravated by the invasion of Ukraine, being transmitted at the country level?
MAR 29, 2022 - 9:30 TO 11:00AM EDT
Rob Vos
SEMINAR
Virtual Event --Discussion of the 2020 Global Food Policy Report
Co-Organized by the Ministry of Foreign Affairs, Government of the Netherlands, IFPRI, and Food & Business Knowledge Platform
APR 28, 2020 - 10:00 AM TO 11:15 AM EDT
Jean Chrysostome Ngabitsinze
POLICY SEMINAR
Retail food prices at the country level and implications for food security
How are rising food prices, further aggravated by the invasion of Ukraine, being transmitted at the country level?
MAR 29, 2022 - 9:30 TO 11:00AM EDT
Christophe Béné
POLICY SEMINAR
UNFSS Science Days Side Event: COVID-19, food systems, and One Health in an urbanizing world: Research responses at a national level
Co-Organized by CGIAR and RUAF
JUL 6, 2021 - 09:30 AM TO 11:00 AM EDT
Impact of COVID 19 on Food and Nutrition SecurityFrancois Stepman
Dr. John Swinnen, Director General, International Food Policy Research Institute.
5 May 2020. Webinar German Agribusiness alliance: Making food systems resilient to Covid 19.
Joseph Glauber
POLICY SEMINAR
Virtual Event - The political economy of COVID-19: Impacts on agriculture and food policies
OCT 22, 2020 - 08:30 AM TO 10:00 AM EDT
Danielle Resnick
POLICY SEMINAR
Virtual Event - The political economy of COVID-19: Impacts on agriculture and food policies
OCT 22, 2020 - 08:30 AM TO 10:00 AM EDT
Maximo Torero
The 2021 United Nations Food Systems Summit: How to Incentivize Food Loss and Waste Reduction
Co-Organized by the International Food Policy Research Institute, Embassy of Denmark in Washington D.C., World Resources Institute, and Champions 12.3
MAR 12, 2021 - 09:30 AM TO 11:00 AM EST
GLOBAL FOOD POLICY REPORT
IFPRI South Asia Discussion of the 2020 Global Food Policy Report
Co-Organized by IFPRI, Indian Council of Agricultural Research Johan Swinnen
(ICAR), and Trust for Advancement of Agricultural Sciences (TAAS)
JUL 6, 2020 - 04:30 PM TO 06:00 PM IST
Máximo Torero
POLICY SEMINAR
Making agrifood systems more resilient to shocks and stresses
Co-Organized by IFPRI and FAO North America
JAN 19, 2022 - 9:30 TO 11:00AM EST
This presentation was given on 27 October 2021 by Krystal Crumpler, Climate Change and Agricultural Specialist at FAO, during the webinar "Achieving NDC Ambition in Agriculture" organized by CCAFS, FAO and WRI.
Find the recording and more information here: https://bit.ly/AchievingNDCs
Johan Swinnen
SEMINAR
Virtual Event --Discussion of the 2020 Global Food Policy Report
Co-Organized by the Ministry of Foreign Affairs, Government of the Netherlands, IFPRI, and Food & Business Knowledge Platform
APR 28, 2020 - 10:00 AM TO 11:15 AM EDT
2020 The State of Food Security and Nutrition in the World: Challenges and op...Francois Stepman
“2020 The State of Food Security and Nutrition in the World: Challenges and opportunities for LDCs, LLDCs and SIDs” by Máximo Torero Cullen, FAO Chief Economist
13 July 2020. SOFI: Transforming food systems Hand-in-Hand to deliver affordable healthy diets in Least developed Countries (LDCs), Landlocked Developing Countries (LLDCs) and Small Island Developing States (SIDS)
Rob Vos
POLICY SEMINAR
Retail food prices at the country level and implications for food security
How are rising food prices, further aggravated by the invasion of Ukraine, being transmitted at the country level?
MAR 29, 2022 - 9:30 TO 11:00AM EDT
Rob Vos
SEMINAR
Virtual Event --Discussion of the 2020 Global Food Policy Report
Co-Organized by the Ministry of Foreign Affairs, Government of the Netherlands, IFPRI, and Food & Business Knowledge Platform
APR 28, 2020 - 10:00 AM TO 11:15 AM EDT
Jean Chrysostome Ngabitsinze
POLICY SEMINAR
Retail food prices at the country level and implications for food security
How are rising food prices, further aggravated by the invasion of Ukraine, being transmitted at the country level?
MAR 29, 2022 - 9:30 TO 11:00AM EDT
Christophe Béné
POLICY SEMINAR
UNFSS Science Days Side Event: COVID-19, food systems, and One Health in an urbanizing world: Research responses at a national level
Co-Organized by CGIAR and RUAF
JUL 6, 2021 - 09:30 AM TO 11:00 AM EDT
Impact of COVID 19 on Food and Nutrition SecurityFrancois Stepman
Dr. John Swinnen, Director General, International Food Policy Research Institute.
5 May 2020. Webinar German Agribusiness alliance: Making food systems resilient to Covid 19.
Geo-spatial analysis for effective technology targetingICRISAT
Mapping and monitoring of biophysical and socio economic characteristics of dryland cereals and grain legumes producing areas is key for developing effective targeting strategies, dissemination of new technologies and sustainable crop management and diversification options.
When we think of agriculture we think of cultivation,
plant life, soil fertility, types of crops, terrestrial environment,
etc. But in today’s world we associate with agriculture terms
like climate change, irrigation facilities, technological
advancements, synthetic seeds, advanced machinery etc. In
short we are interested in how science of today can help us in
the field of agriculture. And so comes into the picture
Precision Agriculture (PA).
The general definition is information and technology
based farm management system to identify, analyze and
manage spatial and temporal variability within fields for
optimum productivity and profitability, sustainability and
protection of the land resource by minimizing the production
costs. Simply put, precision farming is an approach where
inputs are utilized in precise amounts to get increased average
yields compared to traditional cultivation techniques. Hence it
is a comprehensive system designed to optimize production
with minimal adverse impact on our terrestrial system. [1]
The three major components of precision agriculture
are information, technology and management. Precision
farming is information-intense. Precision Agriculture is a
management strategy that uses information technologies to
collect valuable data from multiple sources. This type of analyzing data gives idea what to do in upcoming years to tackle the situations.
kibrom abay ag foresight closing workshop 2022.03.14Ahmed Ali
This Closing Workshop presents the output produced under the project. Modelling, analysis, and training activities’ results will be discussed and presentations will provide a walk-through of the spatial database, including both the modeling work that took place in the background as well as the online platform built to host the data in a user-friendly manner.
GIS Applications for Smart Agriculture-Case Studies & Research Prospects.AdityaAllamraju1
My special webinar talk about 'GIS Applications for Smart Agriculture-Case Studies & Research Prospects’ is a part of the webinar series on October 31st, 2020 organized by the TGISlab, a GIS Consultancy that is an initiative to fill the gap in GIS/Remote Sensing field to aware people about space technology for Earth Science & its applications. TGISLab works on different GIS Applications work and offers training/webinars/workshops to a wider community. It is based at Ahmedabad in Gujarat, India.
Committing to Transform Food Systems: Responsiveness of pledges by African governments to the WHO Priority Food Systems Policies and select CAADP Biennial Review Indicators
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
AKADEMIYA2063-Ecowas Regional Learning event: Food Crop Production during the COVID-19 Pandemic
1. Food Crop Production during the COVID-19 Pandemic
The Case of Six Western African Countries
Côte d’Ivoire, Mali, Burkina Faso, Sierra Leone, The Gambia, and Senegal
ECOWAS Regional Learning Event
February 11th, 2021
Racine Ly, Director Data Management, Digital Products, and Technology
AKADEMIYA2063
2. Outline
1. Introduction & Context
2. Remotely Sensed Data
3. Machine Learning Framework
4. Food Crop Production Model
5. Results
Notice:
The shown boundaries and names, and the designations used on maps do not imply official endorsement or acceptance by AKADEMIYA2063.
3. 1. Introduction & Context
• Measures taken to mitigate the COVID-19 propagation put a heavy strain onto the
agricultural sector.
• Inadequate growing conditions can also push African countries at the blink of a
food crisis.
• From the production side, the interrelationship between food crop production and
the COVID-19 is not well established.
• In periods of uncertainties, forecasts can play an important role to reduce the cost
of bad decisions and allow to plan for the recovery process.
• We combined remotely sensed data and machine learning techniques to provide
maps of food crop production forecasts for several countries in Africa.
4. 1. Introduction & Context (Cont’d)
Better agricultural sector data through remote sensing and artificial intelligence
• The challenge of COVID-19 on food production systems is not only the likely extent
and complexity of the disruptions but also the difficulty to identify and track them
in real time.
• The propagation of the disease can be tracked through testing and tracing, while it
is impossible, even in normal times, to have accurate information on cropping
activities.
• The lack of information about growing conditions can be overcome by using today’s
digital technologies e.g., remote sensing data and machine learning techniques.
• The many weaknesses hampering the access to good quality agricultural statistics
can be overcome using the same digital technologies.
5. 2. Remotely Sensed Data
• Remotely sensed data through sat. images provide a wealth of information about
features on earth.
• Several advantages of using multispectral satellite images
• Vegetation, including crops, have a specific way to respond to light
Figure 1. (left) False RGB color scene of the North of Senegal with agricultural lands, bare soil, and water. (Right) The
same scene after an unsupervised classification with seven clusters using K-means and Landsat 8 spectral bands. Key messages
1. Features on earth react differently
to the electromagnetic spectrum.
2. Features on earth can be identified
from satellite images based on their
reflectance.
6. 2. Remotely Sensed Data (Cont’d)
Application to our Food Crop Production Model
• Vegetation (crops) only absorb specific wavelengths as energy for photosynthesis.
• What is not absorbed is considered as reflected by the leaves.
Figure 2. Reflectance of healthy and stressed plants across the visible
and infrared spectrum filter wavelengths. (McVeagh et al., 2012)
Figure 3. (top-left) 2017 NDVI map; (top-right) 2017 Rainfall
data (CHIRPS); (bottom-left) 2017 Daytime Land Surface
Temperature – Senegal. Source: Ly & Dia, 2020.
The 3 types of maps are
used as inputs.
7. Figure 4. Senegal Millet
Production (left) 2005;
Middle 2010; (Right) 2017).
Data Source: IFPRI, 2020,
Map Source: Ly et al., 2020.
3. Machine Learning Framework
• Machine Learning techniques are draining attention into the research community.
• Two main ways of training a machine learning: (Supervised) Building a relationship
between inputs and their corresponding examples; (Unsupervised) Identify
similarities within the dataset (without examples).
• In our case, we use artificial neural networks which are the supervised type.
Production values as examples
8. 4. Food Crop Production Model
Training Scheme
NDVI
LST
RAIN
2005
2010
2017
2005
2010
2017
2005
2010
2017
Crop Masks
2005
2010
2017
2005
2010
2017
2005
2010
2017
Neural Net.
Raw sat. Images Masked images Labels
(Examples)
Learning Process
12. THANK YOU
AKADEMIYA2063 – Kicukiro / Niboye KK 360 St 8 I P.O. Box 4729 Kigali-Rwanda
FIND MORE COVID-19 RELATED WORK at
https://akademiya2063.org/covid-19.php