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• Select the language that you would like to hear this webinar with the
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• This webinar is in English with simultaneous interpretation to Spanish,
French and Portuguese.
• Enter questions or comments through the “Q&A” button. We will
have a Q&A at the end of the webinar.
SPEAKERS
Fred Stolle
Deputy Director
Land & Carbon Lab
Jessica Ertel
Data Scientist
Global Restoration
Initiative
Gabrielle Nussbaum
Senior Manager
Sustainable Landscapes &
Nature-Based Solutions
MODERATOR
Katie Reytar
Senior Research Associate
Land & Carbon Lab
Eric Lawrence Ng'ang'a
AFR100 Restoration
Monitoring Associate WRI
Africa
Karla Posada
Environmental Economics
Specialist
MARN, El Salvador
Erick Ortiz
Environmental Planning
Technician
MARNM El Salvador
Webinar goals:
• Introduce tree
cover data on GFW
• Lean about the
challenges and
new frontiers in
restoration
monitoring
• Hear from users of
tree cover data
• Q&A
Photo: World Resources Institute
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
GLOBAL FOREST WATCH
• GFW offers a suite of forest
monitoring tools designed to:
• Increase knowledge and
transparency about forest
landscapes
• Advance private sector action
to stop commodity-driven
deforestation and manage
forests sustainably
• Harness information to
mobilize local action by
governments and civil society
• Tropical Tree Cover (WRI)
• Tree Cover Gain & Net Change (UMD)
Poll!
Photo: World Resources Institute
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
RESTORATION
MONITORING
FRED STOLLE, WORLD RESOURCES INSTITUTE
Monitoring restoration is HARD!
• Tree growth is slow & often sparse
• “Restored” means different things to
different people
• No globally-consistent
methods/protocols
Restoration Monitoring: The Challenge
Investment
in pledges
Investment
In monitoring
350 Million
hectares
A Tale of Three Scales
Global
Landscape
Project
• Scale matters !
• Objectives and data needs
are different depending on
scale
• They are all important and
ideally “speak” to each
other to build a picture of
progress
Use globally-consistent data to
compare progress across
countries and landscapes
Project specific data, contribute
to and developed for specific
goal
Project Scale
• Well-defined boundary of intervention area
• Specific objectives related to intervention (e.g., plant 100
trees of x species)
• Requires fine-resolution data
• Usually requires field-based data collection complemented
with satellite data
• Dataset-
• Field data
• Drones
• Visual interpretation on Google Earth, Planet ... Sampling
• Tropical Tree Cover 10m
Source: CI & WRI, TREE RESTORATION MONITORING FRAMEWORK
Project-Scale Monitoring
Landscape -Scale
• Contain multiple intervention
• Broader objectives related to progress
on ecosystem services (e.g., increased
food security)
• Better suited for monitoring via satellite
(or field-based data collection using
sampling approach)
• GFW dataset-
• Tropical Tree Cover 10 m
• 30 m gain and loss (GLAD lab at UMD)
Source: Zamora, et al. Sustainability Index for Landscape Restoration
Landscape-Scale Monitoring
Global Scale
• Targets progress on national and
international agreements (e.g.,
Bonn Challenge)
• Requires globally-consistent data,
definitions, and objectives
• Requires monitoring via satellite
• GFW dataset-
• 30 m gain and loss (GLAD lab at
UMD)
• Tropical Tree cover 10 m
Source: Global Forest Review Targets Tracker, 2023
Global-Scale Monitoring
Summary
• Restoration monitoring has different challenges
as Deforestation monitoring.
• Restoration monitoring is still developing. But
we do have good datasets for all scales
• Scale is always important, but even more so for
Restoration
• Restoration on projects scale can be very
successful, while at national scale the forest
change can be negative
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
TROPICAL TREE COVER
JESSICA ERTEL, WORLD RESOURCES INSTITUTE
TREES OUTSIDE DENSE FORESTS ARE NOT REPRESENTED
DATA SPECIFICATIONS
SPATIAL AND TEMPORAL RESOLUTION
10m resolution, 2020
GEOGRAPHIC COVERAGE
4.35b hectares of land in the tropics
IMAGERY
Sentinel-1 and Sentinel-2 images
ALGORITHM
Multi-temporal convolutional neural network
ACCURACY
97% user’s accuracy, 96% producer’s accuracy
TREE: Woody vegetation >5m or
between 3-5m with a 5m crown.
NOT TREE: Woody vegetation
shorter <3m. Monoculture crops
such as tea, coffee, sugar, banana
and cacti.
TREE DEFINITION
TRAINING AND VALIDATION
• Training and validation data were
labeled using Collect Earth
online.
• 18,100 training samples and
1,417 testing samples were used.
• Validation data was gathered
using a stratified random sample
scheme applied to each
subregion.
Locations of testing sample plots.
Locations of training sample plots.
MANUSCRIPT
Wall-to-wall mapping of tree extent in the
tropics with Sentinel-1 and Sentinel-2
• Improved detection of trees outside of
forests, especially in cropland, urban areas
and drylands.
• 2.7 billion hectares of tropical land had
≥10% tree cover.
• 680 million hectares of tropical drylands
had ≥10% tree cover.
• 52% of tropical cropland and 46% of
tropical cities had ≥10% tree cover.
• Extensive comparisons with existing maps
demonstrate the value of this approach.
IMPROVED TREE DETECTION
• Help stakeholders understand where to
prioritize restoration efforts or increase
connectivity in fragmented agricultural
landscapes.
• Help inform our understanding of the role
and management of trees in densely
populated areas.
• Support decision-making and monitoring
efforts across scales.
DERIVE INSIGHTS
TO INFORM TARGETS AND REPORTING
NOW AVAILABLE ON GLOBAL FOREST WATCH
SUPPORTING MATERIALS
WHICH DATA SET IS BEST FOR MY NEEDS?
UPDATES & NEW RESEARCH
Tropical Tree Cover (TTC)
• Year: 2020
• Resolution: 10m
• Geographic coverage: Tropics
Carbon Estimates
• Year: 2020
• Resolution: 0.5ha
• Geographic coverage: Restoration projects
Plantation Cover
• Year: 2020
• Resolution: 10m
• Geographic coverage: Tropics
TTC Annual Change Detection
• Year: 2017-2022
• Resolution: 10m
• Geographic coverage: Tropics
IMPROVED SPATIAL COVERAGE AND QUALITY
2020 2022
Thank you!
Jessica Ertel
Jessica.Ertel@wri.org
on behalf of WRI’s Global Restoration
Initiative, Monitoring Team
CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, infographics and images by Freepik.
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
MALAWI NATIONAL
MONITORING
LAWRENCE ERIC NG’ANG’A, WORLD RESOURCES INSTITUTE
Africa has 750+ million hectares of land suitable for
restoration, the largest opportunity in the world
AFR100 was endorsed1 at the 2015 African Union heads-of-
state summit with a goal to restore 100 million hectares of
degraded African landscapes
1 – AFR100 partnership subsequently launched by founding members
AUDA-NEPAD, BMZ and WRI at COP21 in Paris
AFR100 contributes to the
Bonn Challenge, the African
Resilient Landscapes Initiative
(ARLI), the African Union
Agenda 2063, the Sustainable
Development Goals and other
targets
Monitoring
progress
Financing
implementation
Brokering
technical assistance
Deepening
national ownership
Phase II delivers the missing pieces of the AFR100
architecture
AFR100 Registries
Vetted catalog of TA and financing
needs of government agencies and
restoration implementers to bring
alignment and coherence while
allowing flexible fund flows
Coalitions of TA providers
Growing network of 60+ NGOs,
development agencies, and
consultants to provide TA services
AFR100 Grant Facility
Providing grants to community
projects that deliver public goods
Matchmaking
TerraMatch platform connects
needs expressed in AFR100
Registries with TA providers and
funders
AFR100 Investment Facility
Privately investing in restoration
companies (Southbridge)
* Powered by data generated by the Land & Carbon Lab
Policy Accelerator
Peer-to-peer platform to convene
national & subnational government
leaders to improve plans & policies
AFR100 Financing Facility
34 African countries
129 million hectares committed to restoration by 2030
Monitoring Accelerator
Peer-to-peer platform to support
African country representatives in
monitoring their landscapes,
resulting in biannual assessment of
progress on enabling conditions
and implementation
Global Forest Watch
A satellite-based system* for
monitoring and verifying tree
regrowth across the continent
AFR100 Risk Mitigation Facility
De-risking through investment
readiness support & guarantees
TROPICAL TREE COVER - AFR100
MALAWI -NATIONALMONITORING UNIT
2017 Launch Forest and Landscape
Restoration Strategy.
MALAWI -MODERN COOKINGHEALTHYFORESTS
Improved GoM capacity to
utilize systems, tools, and
technologies to manage
and monitor forest
landscapes
Tracking of forest cover
for several GoM
initiatives
• REDD+ MRV,
• National FLR goals,
and
• National determined
contributions(NDCs) to
climate mitigation.
MALAWI -MCHF
• 2017 baseline crop mask
• Track progress by 2020
• Track trends at sub national
level
MALAWI -MCHF
QGIS Analysis
Data access
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
Planificación del paisaje
en ecosistemas de El
Salvador
Unidad de Valoración Ambiental Integral
Dirección de Evaluación y Cumplimiento Ambiental
Noviembre 2023
Antecedentes e hitos
De la métrica para la valoración de
ecosistemas naturales y agroecosistemas
Programa de Incentivos y Desincentivos Ambientales
El programa de incentivos y desincentivos tiene como finalidad facilitar la transformación de procesos,
actividades, proyectos y productos amigables con el medio ambiente o que apoyen la
conservación de los recursos naturales (Art. 32 Ley de Medio Ambiente).
Objetivo General
Impulsar la reconversión de
actividades y procesos
contaminantes o que hagan
uso excesivo o ineficiente de
los recursos naturales;
Implementar los instrumentos
del programa de incentivos y
desincentivos ambientales,
los cuales pueden ser de
mercado, de naturaleza fiscal,
crediticia, voluntarios, de
servicios ambientales y otros
afines a la materia.
Estimular a los empresarios a
incorporar en sus actividades
productivas, procesos,
servicios y tecnologías menos
contaminantes, mediante la
gestión preventiva de la
contaminación hacia procesos
de producción más limpia;
Crear mecanismos de
financiamiento especiales
para el medio ambiente, para
cubrir los costos de
readecuación, con recursos
privados, de cooperación
internacional y con fondos
propios;
Establecer mecanismos
financieros (de mercados u
otra índole), que faciliten las
actividades de reforestación y
restauración de ecosistemas
bajo un enfoque de cuenca
hidrográfica.
Apoyar a los gobiernos
municipales, a los sectores
gubernamentales y no
gubernamentales en la
gestión de recursos, a través
de las cooperaciones técnica
y financiera, nacional e
internacional, para ser
destinada a actividades y
proyectos de conservación,
recuperación y producción
más limpia;
Posibilitar la información
sobre nuevos procesos de
producción limpia y de nuevos
mercados ecológicos;
Establecer acuerdos o
convenios con entidades del
sector público encaminados a
lograr compromisos que
tengan por finalidad la
cooperación de cada una de
estas instituciones de
acuerdo a sus competencias
legales.
Programa de Incentivos y Desincentivos Ambientales
Programa nacional
de incentivos y
desincentivos
ambientales
Incentivos
Económicos
Incentivos para la reforestación
y restauración de ecosistemas
Sello verde y certificaciones
Incentivos No
Económicos
Premio Nacional de Medio
Ambiente
Incentivos para la reforestación
y restauración de ecosistemas
Desincentivos
Cargos y desincentivos a las
actividades que degradan los
recursos naturales
Incentivos financieros
Incentivos de gestión
Incentivos mixtos
Mecanismo de apoyo para facilitar financiamiento de acciones tendientes a
mejorar el uso del suelo actual y la restauración. Implementado a través del
Protocolo Verde establecido entre la Banca Nacional y MARN
Incentivos económicos y no económicos. Facilita la regularización de
actividades, obras o proyectos en función de un mejor uso del suelo.
Proceso de gestión del permiso ambiental y reorientación del monto y
actividades de las compensaciones ambientales para asegurar que
contribuyan a la restauración
Incentivos económicos y no económicos. Programa de reconocimiento-
compensa- ción-retribución de beneficios y servicios ecosistémicos (recarga
hídrica entre otros), generados en sistemas de producción agropecuaria. PSA
Métrica para la valoración de
Ecosistemas Naturales y
Agroecosistemas
para la priorización de acciones de restauración
Remanencia de los
ecosistemas
Zonas priorizadas por
recarga hídrica
Significancia
estratégica
Condición de los
ecosistemas
Métrica de
Unidades de Biodiversidad
Planificación del paisaje mediante
la deconstrucción ecosistémica
Área
(Ha)
Calidad
(4 variables)
Componente de riesgo
(2 variables descuento)
Unidades de
biodiversidad
(UB)
Planificación del paisaje mediante la deconstrucción ecosistémica
Clasificación UNESCO Aptitud PSA Índice de Significancia Ambiental Clasificación por ecosistemas
Conectividad y MSPA Categorías de protección PREP 2017
La métrica de UB en el proceso de evaluación ambiental
Iniciativa / Idea / Intervención
Categorización de la
AOP en el SEA
Planificación del
paisaje
Incentivos y
Desincentivos
• El usuario podrá utilizar la información publicada por parte del Ministerio
• Análisis del paisaje con insumos e instrumentos geoespaciales nacionales y globales
• Desarrollo de investigaciones y validaciones para bajar análisis a escala local
Definición de acciones de
restauración e intervenciones
MRV del paisaje
Indicadores de restauración y
biodiversidad del paisaje
Resultados
favorables
Análisis escala local retroalimenta sistema MRV
Restauración de los ecosistemas
naturales y agroecosistemas
Aplicación del TTM para seguimiento
de cambios en el paisaje
Sistema de monitoreo local para
indicadores de biodiversidad
Resultados
desfavorables
Nota:
Las intervenciones en el territorio deberán estar
enfocadas en lograr sostenibilidad mediante:
• Participación de los actores
• Acción sin daño
• Costo-efectividad
• Complementariedad
Ganancia neta y
adicionalidad de UB
Jerarquía de la mitigación
Reformulación /
Corrección
Aplicativos y usos
Insumos WRI+GFW
Tropical Tree Cover
Tropical Tree Cover en la métrica de UB de forma proactiva
Mapa de Regiones para la Restauración de
Ecosistemas Naturales y Agroecosistemas
1:200,00
0
1:100,00
0
1:50,000
1:25,000
2017
2018
2019
2020
2021
2022
2017
2018
2019
2020
2021
2022
Lecciones
aprendidas
• Información global de utilidad y profesionales y expertos con la disposición de ayudar.
• Recoger experiencias y compartir conocimientos entre pares.
• Los análisis multidisciplinarios son enriquecedores.
• Los resultados siempre tienen que verse como un proceso de mejora continua.
GRACIAS
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
TREE COVER GAIN AND
NET CHANGE
KATIE REYTAR, WORLD RESOURCES INSTITUTE
The Data: Forest Height Dynamics 2000-2020
• Mapped height of woody vegetation for years 2000 and 2020 using GEDI
lidar forest structure measurements and collection 1 Landsat time-series
imagery
• “Tree cover extent” defined as tree height ≥ 5m for a 30-m pixel (to match
FAO definition)
• Comparison of tree cover extent in 2000 and 2020 yields results on
gained, lost, and stable forest area
• Two products on Global Forest Watch derived from this data:
• Tree cover gain 2000-2020
• Net change in tree cover 2000-2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
On Global Forest Watch: Tree Cover Gain 2000-2020
• 30x30 m pixels of cumulative tree cover gain from 2000 to 2020
• “Gain” defined as pixels where tree height was <5m in 2000 and
>=5m in 2020
• Primary use case: Areas of no tree cover in 2000 that became
dense tree cover (>=5m and >=20% canopy) by 2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
On Global Forest Watch: Tree Cover Gain 2000-2020
GFW Dashboard: Tree Cover Gain Summarized at
Global, National, or Subnational Levels
Source: Global Forest Watch Dashboard, 2023. Available at: https://www.globalforestwatch.org/dashboards/global/
Global Forest Review: Tracking Global Forest Gain
Source: Targets Tracker (beta), Global Forest Review, 2023. Available at: https://research.wri.org/gfr/forest-targets-tracker
• Compares the difference in tree cover extent (using a threshold
of height >= 5m) between 2000 and 2020
• Percent net change summarized at Admin 1 (Country), Admin 2
(Province/State), and Admin 3 (District/municipality) levels
• Shows what administrative area had a net gain, net loss, or
neutral change in tree cover extent from 2000 to 2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
On Global Forest Watch: Net Change in Tree Cover 2000-2020
On Global Forest Watch: Net Change in Tree Cover 2000-2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
On Global Forest Watch: Net Change in Tree Cover 2000-2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
On Global Forest Watch: Net Change in Tree Cover 2000-2020
Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the
Landsat Archive: First Results. Front. Remote Sens. Available
at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
GFW Dashboard: Net Change in Tree Cover Summarized at
Global, National, or Subnational Levels
Source: Global Forest Watch Dashboard, 2023. Available at: https://www.globalforestwatch.org/dashboards/global/
Caveats
• Tree cover gain is best-available proxy for restoration, but they
are not definitionally equivalent
• Picks up fast-growing species of industrial tree plantations
• Does not pick up sparse tree cover (where canopy cover
threshold is <20%)
• Lag-time between planting/regeneration and detection for
natural forest growth is 5-10 years
Related Forthcoming Products on Global Forest Watch
• Near-term
• 5-year interval for gain (2000, 2005, 2010, 2015, 2020)
• Longer-term:
• Global annual tree cover loss & gain with two variables: canopy cover
and tree height
AGENDA
• Global Forest Watch
Overview
• Introduction to
Restoration Monitoring
• Tropical Tree Cover Data
Set
• Use Case Presentations
• Tree Cover Gain and Net
Change
• Q&A
• Conclusion
Photo: World Resources Institute
Thank you! Questions?
Fred Stolle
Deputy Director
Land & Carbon Lab
Jessica Ertel
Data Scientist
Global Restoration
Initiative
Gabrielle Nussbaum
Senior Manager
Sustainable Landscapes &
Nature-Based Solutions
MODERATOR
Katie Reytar
Senior Research Associate
Land & Carbon Lab
Eric Lawrence Ng'ang'a
AFR100 Restoration
Monitoring Associate WRI
Africa
Karla Posada
Environmental Economics
Specialist
MARN, El Salvador
Erick Ortiz
Environmental Planning
Technician
MARNM El Salvador
Conclusion
Global Forest Watch Resources
• Help Center
• Tutorials, key definitions, webinars,
and FAQs
• Ask questions, provide feedback, or
report bugs
• Contact Us: gfw@wri.org
• Community Forum
• Learn more on the Global Forest
Review
• Deforestation and Restoration
Targets Tracker
Don't forget to complete our webinar survey
to share your feedback!

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world-environment-day-2024-240601103559-14f4c0b4.pptx
world-environment-day-2024-240601103559-14f4c0b4.pptxworld-environment-day-2024-240601103559-14f4c0b4.pptx
world-environment-day-2024-240601103559-14f4c0b4.pptx
 

GFW Datasets for Restoration_November 9 2023.pptx

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  • 2. Webinar Instructions • Select the language that you would like to hear this webinar with the globe icon. • This webinar is in English with simultaneous interpretation to Spanish, French and Portuguese. • Enter questions or comments through the “Q&A” button. We will have a Q&A at the end of the webinar.
  • 3. SPEAKERS Fred Stolle Deputy Director Land & Carbon Lab Jessica Ertel Data Scientist Global Restoration Initiative Gabrielle Nussbaum Senior Manager Sustainable Landscapes & Nature-Based Solutions MODERATOR Katie Reytar Senior Research Associate Land & Carbon Lab Eric Lawrence Ng'ang'a AFR100 Restoration Monitoring Associate WRI Africa Karla Posada Environmental Economics Specialist MARN, El Salvador Erick Ortiz Environmental Planning Technician MARNM El Salvador
  • 4. Webinar goals: • Introduce tree cover data on GFW • Lean about the challenges and new frontiers in restoration monitoring • Hear from users of tree cover data • Q&A Photo: World Resources Institute
  • 5. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 6. GLOBAL FOREST WATCH • GFW offers a suite of forest monitoring tools designed to: • Increase knowledge and transparency about forest landscapes • Advance private sector action to stop commodity-driven deforestation and manage forests sustainably • Harness information to mobilize local action by governments and civil society
  • 7. • Tropical Tree Cover (WRI) • Tree Cover Gain & Net Change (UMD)
  • 9. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 11. Monitoring restoration is HARD! • Tree growth is slow & often sparse • “Restored” means different things to different people • No globally-consistent methods/protocols Restoration Monitoring: The Challenge Investment in pledges Investment In monitoring 350 Million hectares
  • 12. A Tale of Three Scales Global Landscape Project • Scale matters ! • Objectives and data needs are different depending on scale • They are all important and ideally “speak” to each other to build a picture of progress Use globally-consistent data to compare progress across countries and landscapes Project specific data, contribute to and developed for specific goal
  • 14. • Well-defined boundary of intervention area • Specific objectives related to intervention (e.g., plant 100 trees of x species) • Requires fine-resolution data • Usually requires field-based data collection complemented with satellite data • Dataset- • Field data • Drones • Visual interpretation on Google Earth, Planet ... Sampling • Tropical Tree Cover 10m Source: CI & WRI, TREE RESTORATION MONITORING FRAMEWORK Project-Scale Monitoring
  • 16. • Contain multiple intervention • Broader objectives related to progress on ecosystem services (e.g., increased food security) • Better suited for monitoring via satellite (or field-based data collection using sampling approach) • GFW dataset- • Tropical Tree Cover 10 m • 30 m gain and loss (GLAD lab at UMD) Source: Zamora, et al. Sustainability Index for Landscape Restoration Landscape-Scale Monitoring
  • 18. • Targets progress on national and international agreements (e.g., Bonn Challenge) • Requires globally-consistent data, definitions, and objectives • Requires monitoring via satellite • GFW dataset- • 30 m gain and loss (GLAD lab at UMD) • Tropical Tree cover 10 m Source: Global Forest Review Targets Tracker, 2023 Global-Scale Monitoring
  • 19. Summary • Restoration monitoring has different challenges as Deforestation monitoring. • Restoration monitoring is still developing. But we do have good datasets for all scales • Scale is always important, but even more so for Restoration • Restoration on projects scale can be very successful, while at national scale the forest change can be negative
  • 20. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 21. TROPICAL TREE COVER JESSICA ERTEL, WORLD RESOURCES INSTITUTE
  • 22. TREES OUTSIDE DENSE FORESTS ARE NOT REPRESENTED
  • 23. DATA SPECIFICATIONS SPATIAL AND TEMPORAL RESOLUTION 10m resolution, 2020 GEOGRAPHIC COVERAGE 4.35b hectares of land in the tropics IMAGERY Sentinel-1 and Sentinel-2 images ALGORITHM Multi-temporal convolutional neural network ACCURACY 97% user’s accuracy, 96% producer’s accuracy TREE: Woody vegetation >5m or between 3-5m with a 5m crown. NOT TREE: Woody vegetation shorter <3m. Monoculture crops such as tea, coffee, sugar, banana and cacti. TREE DEFINITION
  • 24. TRAINING AND VALIDATION • Training and validation data were labeled using Collect Earth online. • 18,100 training samples and 1,417 testing samples were used. • Validation data was gathered using a stratified random sample scheme applied to each subregion. Locations of testing sample plots. Locations of training sample plots.
  • 25. MANUSCRIPT Wall-to-wall mapping of tree extent in the tropics with Sentinel-1 and Sentinel-2 • Improved detection of trees outside of forests, especially in cropland, urban areas and drylands. • 2.7 billion hectares of tropical land had ≥10% tree cover. • 680 million hectares of tropical drylands had ≥10% tree cover. • 52% of tropical cropland and 46% of tropical cities had ≥10% tree cover. • Extensive comparisons with existing maps demonstrate the value of this approach.
  • 27. • Help stakeholders understand where to prioritize restoration efforts or increase connectivity in fragmented agricultural landscapes. • Help inform our understanding of the role and management of trees in densely populated areas. • Support decision-making and monitoring efforts across scales. DERIVE INSIGHTS
  • 28. TO INFORM TARGETS AND REPORTING
  • 29. NOW AVAILABLE ON GLOBAL FOREST WATCH
  • 31. WHICH DATA SET IS BEST FOR MY NEEDS?
  • 32. UPDATES & NEW RESEARCH
  • 33. Tropical Tree Cover (TTC) • Year: 2020 • Resolution: 10m • Geographic coverage: Tropics Carbon Estimates • Year: 2020 • Resolution: 0.5ha • Geographic coverage: Restoration projects Plantation Cover • Year: 2020 • Resolution: 10m • Geographic coverage: Tropics TTC Annual Change Detection • Year: 2017-2022 • Resolution: 10m • Geographic coverage: Tropics
  • 34. IMPROVED SPATIAL COVERAGE AND QUALITY 2020 2022
  • 35. Thank you! Jessica Ertel Jessica.Ertel@wri.org on behalf of WRI’s Global Restoration Initiative, Monitoring Team CREDITS: This presentation template was created by Slidesgo, including icons by Flaticon, infographics and images by Freepik.
  • 36. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 37. MALAWI NATIONAL MONITORING LAWRENCE ERIC NG’ANG’A, WORLD RESOURCES INSTITUTE
  • 38. Africa has 750+ million hectares of land suitable for restoration, the largest opportunity in the world
  • 39. AFR100 was endorsed1 at the 2015 African Union heads-of- state summit with a goal to restore 100 million hectares of degraded African landscapes 1 – AFR100 partnership subsequently launched by founding members AUDA-NEPAD, BMZ and WRI at COP21 in Paris
  • 40. AFR100 contributes to the Bonn Challenge, the African Resilient Landscapes Initiative (ARLI), the African Union Agenda 2063, the Sustainable Development Goals and other targets
  • 41. Monitoring progress Financing implementation Brokering technical assistance Deepening national ownership Phase II delivers the missing pieces of the AFR100 architecture AFR100 Registries Vetted catalog of TA and financing needs of government agencies and restoration implementers to bring alignment and coherence while allowing flexible fund flows Coalitions of TA providers Growing network of 60+ NGOs, development agencies, and consultants to provide TA services AFR100 Grant Facility Providing grants to community projects that deliver public goods Matchmaking TerraMatch platform connects needs expressed in AFR100 Registries with TA providers and funders AFR100 Investment Facility Privately investing in restoration companies (Southbridge) * Powered by data generated by the Land & Carbon Lab Policy Accelerator Peer-to-peer platform to convene national & subnational government leaders to improve plans & policies AFR100 Financing Facility 34 African countries 129 million hectares committed to restoration by 2030 Monitoring Accelerator Peer-to-peer platform to support African country representatives in monitoring their landscapes, resulting in biannual assessment of progress on enabling conditions and implementation Global Forest Watch A satellite-based system* for monitoring and verifying tree regrowth across the continent AFR100 Risk Mitigation Facility De-risking through investment readiness support & guarantees
  • 43. MALAWI -NATIONALMONITORING UNIT 2017 Launch Forest and Landscape Restoration Strategy.
  • 44. MALAWI -MODERN COOKINGHEALTHYFORESTS Improved GoM capacity to utilize systems, tools, and technologies to manage and monitor forest landscapes Tracking of forest cover for several GoM initiatives • REDD+ MRV, • National FLR goals, and • National determined contributions(NDCs) to climate mitigation.
  • 45. MALAWI -MCHF • 2017 baseline crop mask • Track progress by 2020 • Track trends at sub national level
  • 47. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 48.
  • 49. Planificación del paisaje en ecosistemas de El Salvador Unidad de Valoración Ambiental Integral Dirección de Evaluación y Cumplimiento Ambiental Noviembre 2023
  • 50. Antecedentes e hitos De la métrica para la valoración de ecosistemas naturales y agroecosistemas
  • 51. Programa de Incentivos y Desincentivos Ambientales El programa de incentivos y desincentivos tiene como finalidad facilitar la transformación de procesos, actividades, proyectos y productos amigables con el medio ambiente o que apoyen la conservación de los recursos naturales (Art. 32 Ley de Medio Ambiente). Objetivo General Impulsar la reconversión de actividades y procesos contaminantes o que hagan uso excesivo o ineficiente de los recursos naturales; Implementar los instrumentos del programa de incentivos y desincentivos ambientales, los cuales pueden ser de mercado, de naturaleza fiscal, crediticia, voluntarios, de servicios ambientales y otros afines a la materia. Estimular a los empresarios a incorporar en sus actividades productivas, procesos, servicios y tecnologías menos contaminantes, mediante la gestión preventiva de la contaminación hacia procesos de producción más limpia; Crear mecanismos de financiamiento especiales para el medio ambiente, para cubrir los costos de readecuación, con recursos privados, de cooperación internacional y con fondos propios; Establecer mecanismos financieros (de mercados u otra índole), que faciliten las actividades de reforestación y restauración de ecosistemas bajo un enfoque de cuenca hidrográfica. Apoyar a los gobiernos municipales, a los sectores gubernamentales y no gubernamentales en la gestión de recursos, a través de las cooperaciones técnica y financiera, nacional e internacional, para ser destinada a actividades y proyectos de conservación, recuperación y producción más limpia; Posibilitar la información sobre nuevos procesos de producción limpia y de nuevos mercados ecológicos; Establecer acuerdos o convenios con entidades del sector público encaminados a lograr compromisos que tengan por finalidad la cooperación de cada una de estas instituciones de acuerdo a sus competencias legales.
  • 52. Programa de Incentivos y Desincentivos Ambientales Programa nacional de incentivos y desincentivos ambientales Incentivos Económicos Incentivos para la reforestación y restauración de ecosistemas Sello verde y certificaciones Incentivos No Económicos Premio Nacional de Medio Ambiente Incentivos para la reforestación y restauración de ecosistemas Desincentivos Cargos y desincentivos a las actividades que degradan los recursos naturales Incentivos financieros Incentivos de gestión Incentivos mixtos Mecanismo de apoyo para facilitar financiamiento de acciones tendientes a mejorar el uso del suelo actual y la restauración. Implementado a través del Protocolo Verde establecido entre la Banca Nacional y MARN Incentivos económicos y no económicos. Facilita la regularización de actividades, obras o proyectos en función de un mejor uso del suelo. Proceso de gestión del permiso ambiental y reorientación del monto y actividades de las compensaciones ambientales para asegurar que contribuyan a la restauración Incentivos económicos y no económicos. Programa de reconocimiento- compensa- ción-retribución de beneficios y servicios ecosistémicos (recarga hídrica entre otros), generados en sistemas de producción agropecuaria. PSA
  • 53. Métrica para la valoración de Ecosistemas Naturales y Agroecosistemas para la priorización de acciones de restauración
  • 54. Remanencia de los ecosistemas Zonas priorizadas por recarga hídrica Significancia estratégica Condición de los ecosistemas Métrica de Unidades de Biodiversidad Planificación del paisaje mediante la deconstrucción ecosistémica Área (Ha) Calidad (4 variables) Componente de riesgo (2 variables descuento) Unidades de biodiversidad (UB)
  • 55. Planificación del paisaje mediante la deconstrucción ecosistémica Clasificación UNESCO Aptitud PSA Índice de Significancia Ambiental Clasificación por ecosistemas Conectividad y MSPA Categorías de protección PREP 2017
  • 56. La métrica de UB en el proceso de evaluación ambiental Iniciativa / Idea / Intervención Categorización de la AOP en el SEA Planificación del paisaje Incentivos y Desincentivos • El usuario podrá utilizar la información publicada por parte del Ministerio • Análisis del paisaje con insumos e instrumentos geoespaciales nacionales y globales • Desarrollo de investigaciones y validaciones para bajar análisis a escala local Definición de acciones de restauración e intervenciones MRV del paisaje Indicadores de restauración y biodiversidad del paisaje Resultados favorables Análisis escala local retroalimenta sistema MRV Restauración de los ecosistemas naturales y agroecosistemas Aplicación del TTM para seguimiento de cambios en el paisaje Sistema de monitoreo local para indicadores de biodiversidad Resultados desfavorables Nota: Las intervenciones en el territorio deberán estar enfocadas en lograr sostenibilidad mediante: • Participación de los actores • Acción sin daño • Costo-efectividad • Complementariedad Ganancia neta y adicionalidad de UB Jerarquía de la mitigación Reformulación / Corrección
  • 57. Aplicativos y usos Insumos WRI+GFW Tropical Tree Cover
  • 58. Tropical Tree Cover en la métrica de UB de forma proactiva Mapa de Regiones para la Restauración de Ecosistemas Naturales y Agroecosistemas
  • 62. Lecciones aprendidas • Información global de utilidad y profesionales y expertos con la disposición de ayudar. • Recoger experiencias y compartir conocimientos entre pares. • Los análisis multidisciplinarios son enriquecedores. • Los resultados siempre tienen que verse como un proceso de mejora continua.
  • 64. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 65. TREE COVER GAIN AND NET CHANGE KATIE REYTAR, WORLD RESOURCES INSTITUTE
  • 66. The Data: Forest Height Dynamics 2000-2020 • Mapped height of woody vegetation for years 2000 and 2020 using GEDI lidar forest structure measurements and collection 1 Landsat time-series imagery • “Tree cover extent” defined as tree height ≥ 5m for a 30-m pixel (to match FAO definition) • Comparison of tree cover extent in 2000 and 2020 yields results on gained, lost, and stable forest area • Two products on Global Forest Watch derived from this data: • Tree cover gain 2000-2020 • Net change in tree cover 2000-2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
  • 67. On Global Forest Watch: Tree Cover Gain 2000-2020 • 30x30 m pixels of cumulative tree cover gain from 2000 to 2020 • “Gain” defined as pixels where tree height was <5m in 2000 and >=5m in 2020 • Primary use case: Areas of no tree cover in 2000 that became dense tree cover (>=5m and >=20% canopy) by 2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
  • 68. On Global Forest Watch: Tree Cover Gain 2000-2020
  • 69. GFW Dashboard: Tree Cover Gain Summarized at Global, National, or Subnational Levels Source: Global Forest Watch Dashboard, 2023. Available at: https://www.globalforestwatch.org/dashboards/global/
  • 70. Global Forest Review: Tracking Global Forest Gain Source: Targets Tracker (beta), Global Forest Review, 2023. Available at: https://research.wri.org/gfr/forest-targets-tracker
  • 71. • Compares the difference in tree cover extent (using a threshold of height >= 5m) between 2000 and 2020 • Percent net change summarized at Admin 1 (Country), Admin 2 (Province/State), and Admin 3 (District/municipality) levels • Shows what administrative area had a net gain, net loss, or neutral change in tree cover extent from 2000 to 2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full On Global Forest Watch: Net Change in Tree Cover 2000-2020
  • 72. On Global Forest Watch: Net Change in Tree Cover 2000-2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
  • 73. On Global Forest Watch: Net Change in Tree Cover 2000-2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
  • 74. On Global Forest Watch: Net Change in Tree Cover 2000-2020 Source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
  • 75. GFW Dashboard: Net Change in Tree Cover Summarized at Global, National, or Subnational Levels Source: Global Forest Watch Dashboard, 2023. Available at: https://www.globalforestwatch.org/dashboards/global/
  • 76. Caveats • Tree cover gain is best-available proxy for restoration, but they are not definitionally equivalent • Picks up fast-growing species of industrial tree plantations • Does not pick up sparse tree cover (where canopy cover threshold is <20%) • Lag-time between planting/regeneration and detection for natural forest growth is 5-10 years
  • 77. Related Forthcoming Products on Global Forest Watch • Near-term • 5-year interval for gain (2000, 2005, 2010, 2015, 2020) • Longer-term: • Global annual tree cover loss & gain with two variables: canopy cover and tree height
  • 78. AGENDA • Global Forest Watch Overview • Introduction to Restoration Monitoring • Tropical Tree Cover Data Set • Use Case Presentations • Tree Cover Gain and Net Change • Q&A • Conclusion Photo: World Resources Institute
  • 79. Thank you! Questions? Fred Stolle Deputy Director Land & Carbon Lab Jessica Ertel Data Scientist Global Restoration Initiative Gabrielle Nussbaum Senior Manager Sustainable Landscapes & Nature-Based Solutions MODERATOR Katie Reytar Senior Research Associate Land & Carbon Lab Eric Lawrence Ng'ang'a AFR100 Restoration Monitoring Associate WRI Africa Karla Posada Environmental Economics Specialist MARN, El Salvador Erick Ortiz Environmental Planning Technician MARNM El Salvador
  • 80. Conclusion Global Forest Watch Resources • Help Center • Tutorials, key definitions, webinars, and FAQs • Ask questions, provide feedback, or report bugs • Contact Us: gfw@wri.org • Community Forum • Learn more on the Global Forest Review • Deforestation and Restoration Targets Tracker Don't forget to complete our webinar survey to share your feedback!

Editor's Notes

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  8. Gabby Zoom poll questions:  Are you new to Global Forest Watch? Yes No Are you familiar with the restoration data sets on GFW? Yes No How do you use Global Forest Watch? Deforestation monitoring Restoration monitoring  Both deforestation and restoration monitoring  Other New to Global Forest Watch
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  12. Tree cover statistics on cropland and urban areas are derived by geographic region
  13. As a part of this process, we have improved the spatial coverage of the dataset along coast linies and ini very cloudy areas, such as the mountains in Costa Rica.
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  16. La métrica es el proceso que estima las unidades de biodiversidad presentes en los ecosistemas a partir de los atributos establecidos por el ministerio. Utiliza los ecosistemas como un proxy para describir la biodiversidad generando Unidades de Biodiversidad (UB) por tipo de ecosistema, a partir del producto del área y su calidad.
  17. Antes Trees in Mosaic Landscape
  18. Análisis de presiones urbanas
  19. Evolución del paisaje agroforestal
  20. Monitoreo de los bosques riberanos
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  22. Data source: Potapov, P., et al. (2022). The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results. Front. Remote Sens. 3:856903. doi: 10.3389/frsen.2022.856903. Available at: https://www.frontiersin.org/articles/10.3389/frsen.2022.856903/full
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  25. Gabby Mention the survey
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  27. Data and methods are still under development but we’re making progress. Today’s webinar will focus on two datasets that are currently available on Global Forest Watch, with future improvements and iterations to get us closer to a comprehensive forest landscape restoration monitoring system.