UGA_2016-2019_NBS_v01_EN_M_v01_A_OCS
National Biomass Study, 2016-2019.
Name | Country code |
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Uganda | UGA |
Forest survey
Three previous phases of the NBS for woody biomass assessment took place in 1989-90 in 7 peri-urban areas, 1990-2002 and 2003-2006 at national level mostly outside protected areas. (see Chapter 1.2 of document "UGANDA NATIONAL FOREST INVENTORY (NFI)"). Also, the Exploratory Inventory (EI) 1990-1995 (not comparable in scope and coverage) was mostly on Central Forest Reserves (protected areas) and was used together with the NBS to compound the National Forest Inventory (NFI) estimates.
National Biomass Survey (NBS) - was designed in 1989 to quantify biomass stock across the landscape in all woody formations including bush and agricultural residues with the purpose to evaluate the biomass energy contributes of Uganda’s total delivered energy. After the REDD+ programme engagement, Uganda used the biomass information from NBS for climate change studies. NBS reports provide very reliable statistics on biomass resources down to Sub- County level.
Sample survey data [ssd]
Plants
BIOMASS: quantify biomass stock across the landscape in all woody formations including bush and agricultural residues
Topic |
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Forest production and carbon stocks |
National Coverage.
Trees = 3 cm DBH. Deadwood pieces = 10 cm diameter
Name | Affiliation |
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National Forest Authority | NFA |
Ministry of Water and Environment | |
District Forest Services |
Name | Role |
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Ministry of Water and Environment | Coordination |
District Forest Services | Support in Field Operation |
Food and Agriculture Organization | Technical Support |
Name | Role |
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Forest Carbon Partnership Facility | |
Austria Development Agency | |
Food and Agriculture Organization | Implementation Agency |
Systematic cluster grid of 5 km by 5 km, stratified by three population intensities of less than 50 people per km, between 50 and 100 people per km and above 100 people per km. Sampling included protected areas. Out of a cluster (PSU) of nine plots (SSU, their plot centers separated 300 m producing a cluster cross shape and 0.25 ha - 50 x 50 m - of area ) on each grid intersection a minimum of three plots are measured. A total of 439 square plots in a sampled area of 110 hectares. Given the unequal geographical representativity of the samples, it is difficult to assign a sampling intensity. The plot selection is made during the planning phase by the field Inventory Supervisor, the Field team leaders are allowed to make alternative selections only if a preselected plot(s) is inaccessible. Selection priority is given to the plot numbers 1, 2 and 3 at the centre although any other plot may be measured as replacement of any of the three key plots. Interest in getting information on certain vegetation types may influence plot selection. Each square plot is subdivided into five strips measuring 10 by 50 metres, running in the east-west direction. Tree measurements are done systematically from one strip to another, and tree numbering is based on the location of the tree in the strip. This is intended to make tree re-identification easier during subsequent visits. NBS has a nested plot approach whereby the minimum measurable DBH in the first strip is 3cm. In the rest of the plot, the DBH threshold is trees of 5cm and above.
The within-cluster plot selection protocol makes a proper probabilistic selection of plots as sampling units impossible. Hence taking cluster as the minimum sampling unit while using an uneven inclusion probability approach is recommendable in the analysis. The unit of analysis, however, was a cluster - weighted by total plot within cluster area.
Response rates are close to 100% due to the within-cluster plot selection protocol (whereby 3 plots out of the possible 9 per cluster, are selected - if one pre-selected plot is inacessible the crew leader will choose another one).
Sample weights were determined according to area expansion factors (in regards to a reference 0.5 ha. total area per SSU). Hence they are given as:
Weight w of trees and deadwood pieces included in whole plot: 0.25 ha/0.25 ha =1
Weight w of strip 1 for trees 3=DBH<5 cm: 0.25 ha/0.05 ha = 5
Reweighting if cluster is statistical unit of analysis: w * 9 plots per cluster/no. plots enumerated in cluster
Start | End | Cycle |
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2016-01 | 2019-07 | 5 |
The reference period for the BS was from 1 January 2016 to 31 December 2019. However, data on trees, deadwoood and forests numbers were recorded as of the time of the visit of the enumerator to the plots.
Data collected by measuring and observing variables in the field and entering data in a tablet with specific software (OpenForis)
Several data quality control procedures too place: 1) 10% of plots in the field were rechecked by peer teams (Number of trees not correctly identified, Number of trees that are supposed to be in a plot but were omitted, Number of trees that were not supposed to be in a plot but were included, DBH error measurements in percent error from the correct measurement, Height error measurement percent error from the correct measurement, Incorrect recording of plot coordinates, Incorrect recording of land use\cove). 2) minimum and maximum limits to DBH and height values (which are mandatory) are built in the mobile device forms and software (Open Foris Collect) to capture data, which automatically val.Data Cleaning ex-post collection has been done by analyzing the species names, heights, DBH, number of trees per hectare. Only errors have been removed but not the outliers.idates data entries according to validation rules. 3) a daily manual supervision of the data enumerated takes place by the field crew leader
Tree heights were measured with hypsometers using the tangent method, which has been observed in other studies to possibly overestimate tree heights, particularly when the distance to the tree was less than its height. This situation is fairly common in a forest inventory, since the forest often masks the vision of individual trees, so crews can only measure from very near the trees.
Is signing of a confidentiality declaration required? | Confidentiality declaration text |
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yes | The users shall not take any action with the purpose of identifying any individual entity (i.e. person, household, enterprise, etc.) in the micro dataset(s). If such a disclosure is made inadvertently, no use will be made of the information, and it will be reported immediately to FAO. |
Micro datasets disseminated by FAO shall only be allowed for research and statistical purposes. Any user which requests access working for a commercial company will not be granted access to any micro dataset regardless of their specified purpose. Users requesting access to any datasets must agree to the following minimal conditions:
(c) UGANDA NFI 2016. Dataset downloaded from https://microdata.fao.org.
Or
NFI Report: UGANDA NATIONAL FOREST INVENTORY (NFI), THE NATIONAL FORESTRY AUTHORITY
MINISTRY OF WATER AND ENVIRONMENT 2019. Dataset downloaded from https://microdata.fao.org.
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Name | Affiliation | |
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Senyonjo Edward | NFA | [email protected] |
John Diisi | NFA | [email protected] |
DDI_UGA_2016-2019_NBS_v01_EN_M_v01_A_OCS_FAO
Name | Affiliation | Role |
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Office of Chief Statistician | Food and Agriculture Organization | Metadata adapted for FAM |
Antonello Salis | Food and Agriculture Organization | Metadata producer |
2019-10-31
UGA_2016-2019_NBS_v01_EN_M_v01_A_OCS_v01