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2017-2018
UNCCD Reporting
Regional Workshops on UNCCD reporting for countries (March – May 2018)
S0 1.2
Trends in Land
Productivity
Dr Hakki Erdogan
Date
S0 1.2 Trends in Land Productivity
Content
1) What is Land Productivity ? (concept and main drivers)
2) UNCCD Default data for PRAIS 3
3) Interpretation of UNCCD default data
4) Conclusions and references
Date
1. What is Land Productivity ?
• Land productivity is the biological
productive capacity of the land
• Signals long-term changes in the health
and productive capacity of the land and
reflects the net effects of changes in
ecosystem functioning on plant and
biomass growth.
• Measured across large areas from
remotely sensed Net Primary
Productivity (NPP), such as the
Normalised Difference Vegetation Index
(NDVI)
Date
1. What is Land Productivity ?
• Because NDVI is strongly related to the absorption of energy for photosynthesis by green
plants, it can be used as a proxy for the amount of green biomass (& NPP).
https://eros.usgs.gov/westafrica/
Date
• Rainfall decreases— so does land productivity. LPD follows
the climatic gradient and rainfall is a major constraining factor
in most of the areas.
• It varies not only in space, but also in time. This variability in
land productivity occurs at different time scales, from
seasonal to interannual, in response to the variability in
rainfall.
• BUT Climate is not the only driver; Soils, topography, and
management have important roles in land productivity at finer
scales.
• Close association with land use/land cover and their changes
1. What is Land Productivity ? (main drivers)
JRC, 2014
Date
• Land productivity is measured at local to global scales using time-series satellite remote
sensing with image transformation.
• The remotely sensed data identifies changes in plant productivity and is correlated with
plant Annual Net Primary Production (ANPP).
• It is not necessary to quantify the magnitude of change in productivity of ANPP
(kg/ha/year).
• We only need to know whether productivity is increasing (positive), decreasing
(negative), or stable for the reporting time period.
1. What is Land Productivity ?
For the reporting on SDG Indicator 15.3.1
Date
Default data comes from:
The World Atlas of Desertification,
Europen Commission - Joint Research
Center
http://wad.jrc.ec.europa.eu/
2. UNCCD Default data for PRAIS 3
Date
2. UNCCD Default data for PRAIS 3
JRC LPD Dataset
Date
2. UNCCD Default data for PRAIS 3
JRC, 2013
Trend (the trajectory of
productivity over time)
State, ( compares the
current productivity
level in a given area to
historical observations
of productivity in that
same area )
Performance, (local
productivity relative to other
similar LC, vegetation, soil,
bioclimatic regions)
Date
2. UNCCD Default data for PRAIS 3
Date
UNCCD – LPD product for SIDS
MODISsensors 250 m spatial resolution,
Daily-Weekly intervals from 2001 to 2015
UNCCD Default data for PRAIS 3
Date
2. UNCCD Default data for PRAIS 3
Data processing for country default data for reporting
(Tier 1 level)
LPD classes is broken down to land cover (LC) categories at
national levels based on the information contained in the
ESA_CCI (2000-2015) land cover datasets.
2. UNCCD Default data for PRAIS
3Country_Reporting table ready to use
in PRAIS3 system.
Date
3. Interpretation of UNCCD default data
Date
Date
e.g. In Madagascar, referring to the
observation period from 1999 to 2013
approximately 32% of the territory’s vegetated
land surface shows persistent declining trends
or stressed on land productivity.
However, 54% of the territory is stable and
10% of total areas shows increasing in land
productivity trend.
3. Interpretation of UNCCD default data
In Tree-Covered Area:
• 52% of tree-covered areas (126,998 km2)
shows stable productivity trend.
• 14% (33,427 km2) shows an increasing in
land productivity trend.
• 34% (83,892 km2) shows a declining trend
(Declining+ Moderate Decline + Stressed)
3. Interpretation of UNCCD default data
Date
# During 2000-2013, 5,024km2
areas coverted from tree-
covered areas to cropland.
# 20% of these converted areas
show an increasing land
productivity trend.
# 25% of these converted areas
show a persistent declining
trend (Declining + Moderate
Decline + Stressed)
3. Interpretation of UNCCD default data
Date
① Increasing land-productivity ≠ Land improvement
e.g. intensive agriculture may increase biomass grown in the short-term,
but reduce environmental quality in the long-term
② Land degradation = Declining land-productivity
degraded land will always perform worse than its unaffected counterpart
3. Interpretation of UNCCD default data
Date
① Land productivity is complex and agreed field measurement protocols don’t yet exist
② Land-productivity dynamics are a proxy for land degradation, not a measure of land
degradation
③ Long-term satellite-based observations offer much potential as a source of information
on land-productivity dynamics
④ Complex social, economic and biophysical processes drive both positive and negative
changes in land-productivity dynamics
⑤ Systematic validation is needed, including further analysis of the causes, statistics and
economics behind the observed changes
4. Conclusions
Date
4. Reference documents
- Good Practices Guidance, 2017
http://www2.unccd.int/sites/default/files/relevant-links/2017-
10/Good%20Practice%20Guidance_SDG%20Indicator%2015.3.1_Version%201.0.pdf
- The Global Land Outlook, 2017
http://www2.unccd.int/actions/global-land-outlook-glo
- EC- JRC Technical Report on Land-Productivity Dynamics Towards integrated assessment
of land degradation at global scales, 2013
http://publications.jrc.ec.europa.eu/repository/bitstream/JRC80541/lb-na-26052-en-
n%20.pdf
Thank you

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So1.2. LDN indicator Land Productivity - Hakki Emrah Erdogan

  • 1. 2017-2018 UNCCD Reporting Regional Workshops on UNCCD reporting for countries (March – May 2018)
  • 2. S0 1.2 Trends in Land Productivity Dr Hakki Erdogan
  • 3. Date S0 1.2 Trends in Land Productivity Content 1) What is Land Productivity ? (concept and main drivers) 2) UNCCD Default data for PRAIS 3 3) Interpretation of UNCCD default data 4) Conclusions and references
  • 4. Date 1. What is Land Productivity ? • Land productivity is the biological productive capacity of the land • Signals long-term changes in the health and productive capacity of the land and reflects the net effects of changes in ecosystem functioning on plant and biomass growth. • Measured across large areas from remotely sensed Net Primary Productivity (NPP), such as the Normalised Difference Vegetation Index (NDVI)
  • 5. Date 1. What is Land Productivity ? • Because NDVI is strongly related to the absorption of energy for photosynthesis by green plants, it can be used as a proxy for the amount of green biomass (& NPP). https://eros.usgs.gov/westafrica/
  • 6. Date • Rainfall decreases— so does land productivity. LPD follows the climatic gradient and rainfall is a major constraining factor in most of the areas. • It varies not only in space, but also in time. This variability in land productivity occurs at different time scales, from seasonal to interannual, in response to the variability in rainfall. • BUT Climate is not the only driver; Soils, topography, and management have important roles in land productivity at finer scales. • Close association with land use/land cover and their changes 1. What is Land Productivity ? (main drivers) JRC, 2014
  • 7. Date • Land productivity is measured at local to global scales using time-series satellite remote sensing with image transformation. • The remotely sensed data identifies changes in plant productivity and is correlated with plant Annual Net Primary Production (ANPP). • It is not necessary to quantify the magnitude of change in productivity of ANPP (kg/ha/year). • We only need to know whether productivity is increasing (positive), decreasing (negative), or stable for the reporting time period. 1. What is Land Productivity ? For the reporting on SDG Indicator 15.3.1
  • 8. Date Default data comes from: The World Atlas of Desertification, Europen Commission - Joint Research Center http://wad.jrc.ec.europa.eu/ 2. UNCCD Default data for PRAIS 3
  • 9. Date 2. UNCCD Default data for PRAIS 3 JRC LPD Dataset
  • 10. Date 2. UNCCD Default data for PRAIS 3 JRC, 2013 Trend (the trajectory of productivity over time) State, ( compares the current productivity level in a given area to historical observations of productivity in that same area ) Performance, (local productivity relative to other similar LC, vegetation, soil, bioclimatic regions)
  • 11. Date 2. UNCCD Default data for PRAIS 3
  • 12. Date UNCCD – LPD product for SIDS MODISsensors 250 m spatial resolution, Daily-Weekly intervals from 2001 to 2015 UNCCD Default data for PRAIS 3
  • 13. Date 2. UNCCD Default data for PRAIS 3 Data processing for country default data for reporting (Tier 1 level) LPD classes is broken down to land cover (LC) categories at national levels based on the information contained in the ESA_CCI (2000-2015) land cover datasets.
  • 14. 2. UNCCD Default data for PRAIS 3Country_Reporting table ready to use in PRAIS3 system.
  • 15. Date 3. Interpretation of UNCCD default data Date
  • 16. Date e.g. In Madagascar, referring to the observation period from 1999 to 2013 approximately 32% of the territory’s vegetated land surface shows persistent declining trends or stressed on land productivity. However, 54% of the territory is stable and 10% of total areas shows increasing in land productivity trend. 3. Interpretation of UNCCD default data
  • 17. In Tree-Covered Area: • 52% of tree-covered areas (126,998 km2) shows stable productivity trend. • 14% (33,427 km2) shows an increasing in land productivity trend. • 34% (83,892 km2) shows a declining trend (Declining+ Moderate Decline + Stressed) 3. Interpretation of UNCCD default data
  • 18. Date # During 2000-2013, 5,024km2 areas coverted from tree- covered areas to cropland. # 20% of these converted areas show an increasing land productivity trend. # 25% of these converted areas show a persistent declining trend (Declining + Moderate Decline + Stressed) 3. Interpretation of UNCCD default data
  • 19. Date ① Increasing land-productivity ≠ Land improvement e.g. intensive agriculture may increase biomass grown in the short-term, but reduce environmental quality in the long-term ② Land degradation = Declining land-productivity degraded land will always perform worse than its unaffected counterpart 3. Interpretation of UNCCD default data
  • 20. Date ① Land productivity is complex and agreed field measurement protocols don’t yet exist ② Land-productivity dynamics are a proxy for land degradation, not a measure of land degradation ③ Long-term satellite-based observations offer much potential as a source of information on land-productivity dynamics ④ Complex social, economic and biophysical processes drive both positive and negative changes in land-productivity dynamics ⑤ Systematic validation is needed, including further analysis of the causes, statistics and economics behind the observed changes 4. Conclusions
  • 21. Date 4. Reference documents - Good Practices Guidance, 2017 http://www2.unccd.int/sites/default/files/relevant-links/2017- 10/Good%20Practice%20Guidance_SDG%20Indicator%2015.3.1_Version%201.0.pdf - The Global Land Outlook, 2017 http://www2.unccd.int/actions/global-land-outlook-glo - EC- JRC Technical Report on Land-Productivity Dynamics Towards integrated assessment of land degradation at global scales, 2013 http://publications.jrc.ec.europa.eu/repository/bitstream/JRC80541/lb-na-26052-en- n%20.pdf