Transcript PPT

MRV & Reporting Status
& Related Space Data Needs
Kenya
SDCG-7
Sydney, Australia
March 4th – 6th 2015
Institutional background
• The System for Land-based Emissions Estimation for Kenya
(SLEEK) aims at providing time series information on
emissions associated with land use activities in Kenya for
national planning and international reporting.
• Based on sources of emissions (i.e. Forests, Cropland,
grasslands, soils and associated land use changes) technical
working groups have been formed to provide information on
emission factors
• The state Department of environment in the Ministry of
Environment, Water and Irrigation spearheads this
programme supported by the Clinton Climate Initiative and
the Government of Australia
MGD Session
Sydney, Australia
March 4th – 6th 2015
How will SLEEK support Kenya domestically?
• Support implementation of the Constitution,
Vision 2030, NCCRS and Action Plan, Land Policy,
Forest Policy and State of Environment reporting.
• Develop a National Forest Monitoring System
• Support informed decision making for Sustainable
development and Sustainable land use
How will SLEEK support Kenya Internationally?
• Allow Kenya to meet international treaty
obligations such as UNFCCC
• Support Kenya’s position in the international
climate change negotiations
• Predict future GHG emissions and removals
• Provide the capacity for credible Reference
Emission Level
• Contribution to global climate change goals
• Enable access to International carbon finance
What is the roadmap to deliver SLEEK?
Year 1: Design of the program; setting up the
implementation and management structures, capacity
building & assessment of knowledge/capacity.
Year 2: Development of the technical designs & model
selection, field work to populate models and the
initial system development.
Year 3: Completion of field work, concerted system
development, quality assurance & testing.
How will SLEEK integrate data?
Seven Elements of SLEEK
SLEEK is being delivered through seven Element
Working Groups that will bring institutions together
to collaborate:
• Climate Parameters and Trends
• Crop Growth and Plant Parameters
• Forest Biomass Stock and Growth Increment
• Land Cover Change
• Land Use Change and Management
• Soil Carbon
• System Integration and Modelling
Key institutions involved
• Department of Resource
•
Survey & Remote Sensing
• Kenya Meteorological Service •
• Kenya Agricultural Research •
Institute
• Kenya Forest Service
•
• Kenyatta University
•
Jomo Kenyatta University of
Agriculture and Technology
University of Nairobi
National Environment
Management Agency
National Museums of Kenya
Regional Centre For Mapping
Resource For Development
Relevant History of NFMS
The Kenya Forests Master plan of 1994 is the earliest document
that proposed a national forest monitoring programme
Since then forest monitoring has been done in piece meal de to
costs associated E.g.
1.
2.
3.
4.
5.
Kenya Indigenous forest conservation (KIFCON) supported by ODA 1990 –
1994
NRM programme inventorying all Plantation forests in 2009 – 2012 and
supported by World Bank
Kenya Forest Preservation Programme supported by Japan in 2012 and
piloting biomass in Mau forest
Increasing Capacity in Forest Resource Assessment (Ongoing) supported
by Finland and developing and national forest inventory programme
Mapping Kenya's Forest lands 1990, 2000, 2005 and 2010 supported by
Japan and world bank. Classified forestlands by canopy classes into
open, moderately open and closed
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Sydney, Australia
March 4th – 6th 2015
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Proposed Stratification System
• Based on carbon dynamics e.g.
1. Forestlands
• 1st level – Natural, Plantation bamboo by Remote sensing
• 2nd level by canopy closure by Remote sensing
• 3rd level by climate and altitude (Coastal dryland, montane
and western rain forests) uses ancillary data
• 4th level – Species, age, associations – by ancillary data
2. Grasslands -Wooded grasslands and open grasslands
3. Croplands – Annual herbaceous, agroforestry,
perennial shrubs
SDCG-7
Sydney, Australia
March 4th – 6th 2015
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Status of land cover mapping
• State of knowledge and identification of
relevant stakeholders
• Completion of the process manual
• Land cover mapping
– 2014 and 2010 (March – June 2015)
– 2013, 2012, 2011, 2015 (July – December 2015)
– 1990 – 2009 (January – June 2016)
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2015
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Space Data Needs
– Wall-wall imagery required for the period 2000-2014 or since 1990?
– Preference for Landsat data due to cost, availability on time series
and its moderate resolution that allows categorization of our features
of interest. Landsat will be used for land cover mapping and change
detection
– High resolution imagery (e.g. SPOT) will be used to clarify training
sites
– Images of the dry season and with less clouds have been proposed
i.e. January – March
– We wish to use a semi automated system of land cover mapping
using signatures of known sites
SDCG-7
Sydney, Australia
March 4th – 6th 2015
Required space data types
• Though we are developing a manual that
highlights all stages of data processing, we
request pre-processed images – Level 1T.
GFOI support so far
a) We have received Landsat imagery for 2013 and 2014
b) We have download some data from USGS website to test speed
and practicality based on our internet conditions
c) We have been introduced to the COVE tool to help us identify
which images may be helpful
d) We have been provided with updated summaries of images
available to help us decide our options
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Images provided
2013
2014
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Image downloads Landsat 8 for 2014
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Current challenges & obstacles where GFOI
assistance may be most valuable
• Provision of time series pre-processed images (Annual
Landsat LT1 pre processed for 1990 -2015)
• Provision of high resolution imagery to aid us in ground
confirmation and reduce a lot of ground truthing field
work (for hotspots)
• Training in land cover classification, change detection and
uncertainty analysis
• Training on more efficient ground data collection
methods
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