Programme

MorningSession

Presentations

MC : Byron Anangwe

DAY 2 Summary

• Current initiative is a 30m resolution landcover to

• Reason why?• For global consistent and locally

relevant• Permits detection of land change

• Method stacking all images and using them to classify and generate LC sa opposed to using onetime imagery

• Validation @ 500*500 & 100*100 km sq• Displayed a number of examples of

classifications done in Kenya-Lodwar, SA- Kwa zulu Natal e.tc

• Showed the new initiatives in close to real time landcover mapping

• Current initiative is a 30m resolution landcover to

• Reason why?• For global consistent and locally

relevant• Permits detection of land change

• Method stacking all images and using them to classify and generate LC sa opposed to using onetime imagery

• Validation @ 500*500 & 100*100 km sq• Displayed a number of examples of

classifications done in Kenya-Lodwar, SA- Kwa zulu Natal e.tc

• Showed the new initiatives in close to real time landcover mapping

The USGS global land cover The USGS global land cover mapping initiativemapping initiative

The USGS global land cover The USGS global land cover mapping initiativemapping initiative

• Has 6 dedicated space resources• Other than satellites the other services are:• Land monitoring services for:

• European Union-urban • Global component- S3 resolution

product, the need for 30m resolution datasets

• There is an action plan for digital observatory to protected areas

• Trend indicate that decline in recovery and regeneration of vegetation is evident

• Sentinel spatial temporal and spectral characteristics provide huge potential for LC /LU user satisfaction

• Has 6 dedicated space resources• Other than satellites the other services are:• Land monitoring services for:

• European Union-urban • Global component- S3 resolution

product, the need for 30m resolution datasets

• There is an action plan for digital observatory to protected areas

• Trend indicate that decline in recovery and regeneration of vegetation is evident

• Sentinel spatial temporal and spectral characteristics provide huge potential for LC /LU user satisfaction

Land use and land cover mapping at the

Joint Research Centre Alan Belward

Land use and land cover mapping at the

Joint Research Centre Alan Belward

Main Activity•Putting information within reach; Sharing policy expertise; Providing a meeting place for nations; Bringing field knowledge Main objectives•improve linkages •standardization, homogenization, compatibility•validation of land cover•use and sharing of remote sensing data•comparable products•capacity development and institution strengthening•operational development and use•FAO GLCN Core activities•Standards and Classification SystemLCCS / LCML / ISO 19144-2:2012•LCCS databases•Mapping Device – Change Analysis Tools (MADCAT)

Main Activity•Putting information within reach; Sharing policy expertise; Providing a meeting place for nations; Bringing field knowledge Main objectives•improve linkages •standardization, homogenization, compatibility•validation of land cover•use and sharing of remote sensing data•comparable products•capacity development and institution strengthening•operational development and use•FAO GLCN Core activities•Standards and Classification SystemLCCS / LCML / ISO 19144-2:2012•LCCS databases•Mapping Device – Change Analysis Tools (MADCAT)

FAO Land Cover Mapping methodology,

tools and standards&

GLC–SHARE databaseRenato Cumani

FAO Land Cover Mapping methodology,

tools and standards&

GLC–SHARE databaseRenato Cumani

MC : Byron Anangwe

Programme

Presentations

Group presentations

HealthBreak Mid

Morning / Early Afternoon session

MC : Byron Anangwe

Lunch

DAY 2 Summary

Countries participating in the project Malawi; Rwanda; Tanzania

Zambia; Namibia; BotswanaOverall Project Aims:•Strengthen the institutional arrangements•Enhance the technical capacity of designated personnel•Improve national methodologies, activity data and emission factors•operational development and useObjectives•To collect ancillary and ground reference data –validate lc.•To develop LC maps from Landsat satellite images using RS sensing techniques for 2000 and 2010 epochs.•Development of replicable and consistent procedures.•To build capacity of the countries through training on Land Cover mapping for GHG Inventory Development in the ESA Region.

Classification schemeScheme I: IPCC defineScheme II: defined by the country

Countries participating in the project Malawi; Rwanda; Tanzania

Zambia; Namibia; BotswanaOverall Project Aims:•Strengthen the institutional arrangements•Enhance the technical capacity of designated personnel•Improve national methodologies, activity data and emission factors•operational development and useObjectives•To collect ancillary and ground reference data –validate lc.•To develop LC maps from Landsat satellite images using RS sensing techniques for 2000 and 2010 epochs.•Development of replicable and consistent procedures.•To build capacity of the countries through training on Land Cover mapping for GHG Inventory Development in the ESA Region.

Classification schemeScheme I: IPCC defineScheme II: defined by the country

General scope of JICA•Development of forest resource inventory system•Basic info for REDD+•Contribution for sustainable forest management

Generation of National biomass amount and inventorisation•Presented a case study of Gabon and how they have mapped out different forest types•He presented the methodology and approach with the utilization of pan-sharpened imagery and extracting training sites for object oriented supervised classification•The data has been utilized to determine areas that have been logged. •Direct (high res)a nd Indirect (constant distance)

General scope of JICA•Development of forest resource inventory system•Basic info for REDD+•Contribution for sustainable forest management

Generation of National biomass amount and inventorisation•Presented a case study of Gabon and how they have mapped out different forest types•He presented the methodology and approach with the utilization of pan-sharpened imagery and extracting training sites for object oriented supervised classification•The data has been utilized to determine areas that have been logged. •Direct (high res)a nd Indirect (constant distance)

• Driven by the Need for Better Cropland Maps

• Spatially incorrect• Need % cropland• Need crop type distribution maps

• Needs more ground validation

• Looking into the future with best available global data

• Working on tools that will help compare a variety of products at various locations

• They have developed a tool to allow some validation on the ground using Crowdsourced geo-wiki points via validation

• Driven by the Need for Better Cropland Maps

• Spatially incorrect• Need % cropland• Need crop type distribution maps

• Needs more ground validation

• Looking into the future with best available global data

• Working on tools that will help compare a variety of products at various locations

• They have developed a tool to allow some validation on the ground using Crowdsourced geo-wiki points via validation

Global and African Crop Land and Crowdsourcing

Steffen Fritz

Global and African Crop Land and Crowdsourcing

Steffen Fritz

JICA National Land Cover Datasets in African Countries

Hiroshi Sasakawa Ph. D.

JICA National Land Cover Datasets in African Countries

Hiroshi Sasakawa Ph. D.

U.S. EPA African activities supporting national GHG inventory Mapping in

six ESA countries Phoebe Oduor

U.S. EPA African activities supporting national GHG inventory Mapping in

six ESA countries Phoebe Oduor

MC : Byron Anangwe / Shuaib Lwasa

• Capacity building remains their core objective

Conclusion

• Land Cover maps produced are envisaged to be used as an input in the ALU tool (Agriculture Land Use tool

•  ALU tool uses an empirical formula to determine the GHG emissions for a country using activity data from different sectors: Agriculture, Transport, Industrial, Energy and Waste. And using Land cover maps as baseline data.

Recommendations

• Extension of GHG land cover mapping to include more countries.

• A reconnaissance exercise which was not supported due to budgetary limitations should be included.

• Extensive field work to ensure that most of the country is covered for more reliable accuracy assessment.

• Development of Scheme III Land use Land cover maps.

DAY 2 Summary

UN-REDD ProgrammeExample from Nigeria, Tanzania

Spatial decision support software for land use planningUsing Marxan for REDD+ Linking the above with economic Global forest watch 2.0

UN-REDD ProgrammeExample from Nigeria, Tanzania

Spatial decision support software for land use planningUsing Marxan for REDD+ Linking the above with economic Global forest watch 2.0

He started off with a background presentation on the size, and demographic dynamics 2% pop growth rateHigh forest cover loss in 1090-2000 4.8% decrease

 Drivers of deforestation pop growth; fuel wood; insecure land tenure; policy implementation

Objectives and progress

ExpectationsCommunity developmentGovernment coordinated activities and initiatives

Short term•Education and awareness•Development of a national lC classification system•Harmonization of existing lc luse data•National forest inventory & MRV

Long term-Empirical review of drivers and development of corresponding emissions and national and sub-national spatial data

-Implementation of NFMS and MRV strategies

He started off with a background presentation on the size, and demographic dynamics 2% pop growth rateHigh forest cover loss in 1090-2000 4.8% decrease

 Drivers of deforestation pop growth; fuel wood; insecure land tenure; policy implementation

Objectives and progress

ExpectationsCommunity developmentGovernment coordinated activities and initiatives

Short term•Education and awareness•Development of a national lC classification system•Harmonization of existing lc luse data•National forest inventory & MRV

Long term-Empirical review of drivers and development of corresponding emissions and national and sub-national spatial data

-Implementation of NFMS and MRV strategies

Malawi REDD+ Readiness Program

John Kerkering

Malawi REDD+ Readiness Program

John Kerkering

MC : Byron Anangwe / Shuaib Lwasa

Programme

MorningSession

Presentations

Presentations

Group presentations

Presentations

Group presentations

Presentations

Your Text

HealthBreak Mid

Morning / Early Afternoon session

MC : Byron Anangwe

Lunch

Afternoon Session

Evening Session

HealthBreak

Dinner@Safari Park

Plenary sessions

Lots of data has been produced by JRC but still there is need forownership by the respective Countries

Outreach and education on how to interpret this information is required.

GLCN is working on a tool to allow integration of LCCS 2 into 3

Capacity building can be done upon the request of the country

The software is provided free to universities and research institutions

Plenary S1 Plenary S2 Plenary S3 Plenary S4

Presenters

There are similar LC mapping initiatives on the ground and it would have been more beneficial toPartner up with the rest

It would be great if other classification

algorithms could be utilized to improve

on the quality of output results other than

depending on single one e.g maximum likelihood

There is merit in change detection if areas of

high probability of change can be prioritized

and areas of low probability change can be ignored.

There are a number of FOSS that are available

for use but to date there has been no forum for

discussions on merits and demerits and

limitation of some of them

Input: Maybe other technologies can be

exploited with respect to data cataloging,

harvesting, and identification;

why should there be lots of expense in

creation of metadata maybe other

technologies like text search being

utilized by google can be of great essence.

There is need to relate and associate

the importance of social economic

uplift of the society with respect to

available landcover of the society.

There are a number of FOSS that are available

for use but to date there has been no forum for

discussions on merits and demerits and

limitation of some of them

Asante Sanya

Strategic Environmental Assessment (SEA) refers to a range of analytical and participatory approaches to integrate environmental consideration into policies, plans, or programs (PPP) and evaluate the interlinkages with economic and social considerations

Thank You

Asante SanyaGabriel Sanya