module 2.4 incorporating cbm in national (or sub-national/ jurisdictional) redd+ monitoring redd+...

Module 2.4 Incorporating CBM in national (or sub-national/ jurisdictional) REDD+ monitoringREDD+ training materials by GOFC-GOLD, Wageningen University, World Bank FCPF

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Module 2.4 Incorporating community based monitoring in national (or jurisdictional) REDD+ monitoring

Module developer:

Margaret Skutsch, Universidad Nacional Autónoma de Mexico

Arturo Balderas, Universidad Nacional Autónoma de Mexico

Country example: VIETNAM

V1, May 2015

Creative Commons License


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Country examples: VIETNAM

Vietnam is one of the few countries in which there has been experience in the integration of community generated data into larger information systems (though not yet at the national scale)

Here we present an overview of 3 different projects:

●The Sumernet project

●A research project led by Wageningen University

●A pilot project assisted by SNV


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Locations of the three projects described in this module

Map courtesy of Wikipedia


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The Sumernet project

The Sumernet project (which also has sites in Thailand and Laos) is trying to promote integration of local level and national/regional level data systems

The goal of this project is to research, develop and test methods to integrate community-based participatory carbon measurement and monitoring of above-ground biotic carbon with remote sensing, GIS and web-enabled reporting tools as a Measurement, Reporting and Verification (MRV) System for REDD+ and agroforestry carbon sequestration activities


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Field activities in Vietnam are taking place in Na Muc village, Van Minh Commune and in Tu Dooc village, Lang San Commune, which are both in Na Ri District, Bac Kan Province, about 200 km north of Hanoi

These villages are located close to Kim Hy Forest Reserve; an 18,555 ha protected area established in 1997

Tu Dooc village is in the Reserve’s official buffer zone

Both communities have “Red Book” documentation (i.e. tenure rights) for managing community forests:

●Na Muc village – 118.3 ha

●Dooc Village – 45.1 ha


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An “MRV Guidebook for Integrating Participatory Community Carbon Measurement and Monitoring with Satellite Remote Sensing and GIS” will be developed as an output from this project See also European Tropical Forest Research Network News issue 55 for project results: http://www.etfrn.org/index.php?id=1

Activities have involved training local people to establish permanent sampling plots:

● A total 32 plots in evergreen forest and 8 in other types of forest were set up in the two communities, in forest parcels which belong to individual members of the community

● Biometric measurements were carried out by 5 community members; Handheld devices were not used in this exercise

http://www.etfrn.org/index.php?id=1


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Taking DBH measurements in Vietman


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The data was then entered into a secure on-line Forest MRV tool at http:/mrv.carbon2markets.org, for which a password is required (see website for instructions)

It includes a carbon stock calculator that estimates the carbon stock at project or stratum level, based on the plot measurements

●A default allometric equation for tropical moist forest was used, rather than individual allometric equations for each species type

●The default shoot-root ratio (0.20) was used


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Remote sensing data from landsat TM and ETM+ (raster data) is used to create a vegetation index which approximates tree density; threshold values are used to determine forest and non-forest areas

Linear regression is used to calibrate the community gathered plot data with the index, enabling maps of carbon density to be prepared


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Wageningen University research project

Another project in Vietnam with similar aims (i.e. to combine community gathered data with remotely sensed data at larger scales) used Android based handheld devices for community members to record tree measurements, similar to the system described in the main part of this module

The project was led by researchers from Wageningen University in the Netherlands, and was located in Quang Nam province in central Vietnam, in the forest of Tra Bui commune


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Plots of 10m radius were laid out in an area of relatively homogeneous forest, and local monitors were trained to take DBH (using tapes) and height measurements (using clinometers), identifying the species in each case

They entered the data in the handheld device (Samsung Galaxy tab 7.0) but also on a paper form (so that their capacity to accurately input data into the handheld could be assessed)

It was found that more than 60% of the local people use mobile phones so this technology is well known to them


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A major problem was the lack of internet connectivity within the forest, so data had to be stored on the handhelds during the day

Later, data from the handhelds could be uploaded to a local data base using USB connections or SMS, MMS or Bluetooth

The handheld devices have limited battery power, but this was solved using solar chargers


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Accuracy of measurements was checked by experts in a sample of the plots measured, and carbon stock was calculated using local allometric equations

There was close agreement in local peoples´ and experts´ measurements, but local people took longer to make them

It was found that accuracy of text data by community monitors was higher if the screen displayed a choice of options (rather than self-typed responses), although numerical data was accurately typed in

The cost of data collection by community members was $1.2 per ha, $3.2 per ha for local experts and $ 6.4 per ha for national (university) experts


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A time series of SPOT 5 images (2007-2011) was used to determine areas that had been subject to disturbance in this period: This enabled a comparison of community data on disturbance areas

There was very high correlation between community reports on incidence and timing of small and medium sized forest disturbances with that shown on the SPOT images, but communities tended to underestimate the area of large forest disturbances

In addition, communities were able to identify areas of selective logging disturbance which does not show up in the remote sensing


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An important finding of this study is that even high resolution imagery (SPOT 5) does not pick up all disturbances; for this, local, on the ground information is essential

This underlines the need for information systems which combine locally gathered data with remote sensing

More information on this project can be found in:Pratihast et al. (2013) Mobile devices for community-based REDD+ monitoring: a case study for Central Vietnam. Sensors 13, 21-38 (open access, available at http://www.mdpi.com/1424-8220/13/1/21)


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A pilot project assisted by SNV

SNV has been collaborating with local partners in Vietnam in developing a pilot participatory REDD+ monitoring. These include:

● The Department of Agricultural and Rural Development

● the Cat Tien National Park

● The Loc Bac Forestry Company

● The Bao Lam Forestry Company

● The Bao Lam District Forest Protection Unit

● The Loc Lam, Loc Bac, Loc Bao communes of Bao Lam district

● and The Quoc Oai commune of Da Teh district


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The pilot project started in 2012

11 local monitoring teams and one provincial technical team were established

Each team consists of one technical staff of a state-owned forest company, the Cat Tien National Park, the District SFPD or the Commune People’s Committees and local people.

The teams cover four communes in two different districts in Lam Dong, a province in the Central Highlands of Vietnam


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A monitoring team


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The local monitoring teams were trained to use necessary equipment, to identify sampling plots, and to measure and record data

Each team is provided with data sheets, forest cover map, GPS receiver, clinometer, diameter tape, plot-setting cords, hammer and nails, tags, hammock, back bags, knife, etc., and a PCM manual which was especially written for the exercise and can be accessed at: http://www.snvworld.org/en/redd/publications/participatory-carbon-monitoring-manual-for-local-people

● NOTE that this project did not use handheld electronic devices for data capture, in contrast with the others.

● NOTE also that it did not attempt to link local data to data at higher levels through remote sensing

http://www.snvworld.org/en/redd/publications/participatory-carbon-monitoring-manual-for-local-people




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Main findings of the pilot project

Sufficient training with practical, in-field exercises for all team members are always necessary

Participatory Carbon Management manuals are necessary and helpful for the team leaders

A team of 5 people (one team leader--technical person; and four team members—local people) is suitable in terms of workload and task allocation for plot data collection activities

Local people know the geogaphical settings of forest areas well, making movement through the forests faster and easier

The teams can independently manage to fulfil the task of identifying plots and collecting data on the plots; but it is too early to draw conclusions about the reliability of the data collected


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Main findings of the pilot project

Local people in the team, who usually have low educational levels and poor reading and writing skills, find it hard to use the GPS receiver and clinometer, to read maps, and to fill data sheets

Local people more suitable for manual work such as plot set-up, measuring of trees’ diameter; logistic preparation

The technical work of using GPS receivers, recording data using data sheets, are carried out by the team leader who has a technical background

Tough and large geographical conditions mean that the team has to stay overnight in the forests sometimes

Identifying trees species is difficult for most teams

module 2.4 incorporating cbm in national (or sub-national/ jurisdictional) redd+ monitoring redd+...

Documents

national scale

wageningen university

research project

world bank fcpf

community based monitoring

project results

pilot project

ha slide