MRV & Climate Reporting

Greenhouse Gas Inventory Inputs

Activity data are the areas of each land-use change per year, from the SLEEK change matrices (see FREL / FRL › Reference Data).

Read gross change with care. The annual gross areas are large compared with Kenya's forest area because dryland forest and wooded grassland are often confused in the maps, and the change maps' own accuracy is only 30–52% (Quality & Transparency › Uncertainty Assessment). Net change and the FRL averages are more robust than single-epoch gross figures.

The FRL executive summary gives deforestation as 103,368 ha/yr and reforestation as 90,477 ha/yr, while Table 8 gives 338,863 and 326,794 ha/yr. The portal shows the table values, which are consistent with the change matrices; the difference has been referred to the FRL team.

Activity data in the national GHG inventory (NID 2024)

Kenya used IPCC Approach 2 (consistent representation of lands) with a sample-based method, Ensemble Sample-Based Area Estimation (eSBAE). A 2 km grid over the whole country gave 149,460 points (the grid size was chosen after testing 500 m to 50 km). Machine-learning time-series analysis flagged probable change, and 7,313 points were interpreted visually in Collect Earth Online as deforestation, degradation, no change, enhancement or other transitions.

Data collected for the second FRL for 2000–2005, 2005–2010, 2013–2017 and 2018–2021 were used to build annual land-use change matrices for 25 land sub-categories. Years without data were held constant (1990–1999 as 2000; 2011, 2012 and 2022 as the previous year).

• See the land-use change matrices as an interactive chart

Carbon stocks per hectare for each stratum and canopy class are the basis of every emission factor. They come from 121 pilot inventory plots (ICFRA 2016, JICA CADEP-SFM 2017), converted with the allometric equations, root:shoot ratios and carbon fraction below.

Emission factors (EF) are the change in CO₂ per hectare between two land classes. Because no full NFI had been completed by 2020, Kenya used country-specific data from the pilot forest inventories of IC-FRA (KFS, 2016) and CADEP-SFM (JICA, 2017).

• Above-ground biomass (AGB) from allometric equations; below-ground biomass (BGB) = AGB × root:shoot ratio
• Carbon stock (tC/ha) = (AGB + BGB) × 0.47 (carbon fraction, IPCC 2006)
• CO₂ (tCO₂/ha) = carbon stock × 44/12
• EF = CO₂ at the start class − CO₂ at the end class

MW = Montane & western rain forests & bamboo; MC = Mangroves & coastal forests; DL = Dryland forests; D / M / O = Dense / Moderate / Open canopy.

Additional factors used in the national GHG inventory (NID 2024)

The inventory uses the same pilot-inventory carbon stocks per stratum and canopy class as shown above. Biomass is converted to carbon with the IPCC default carbon fraction of 0.47, and carbon to CO₂ by multiplying by 44/12. Below-ground biomass comes from these root-to-shoot ratios:

• Wooded grassland: IPCC default stock of 8.7 t carbon per hectare; open grassland is assumed to hold half of that (expert judgement).
• Perennial cropland: country-specific factors from a study of Grevillea agroforestry in Kenya (Owate et al., 2018); annual cropland uses IPCC defaults.
• Soils: Kenya is treated as one tropical dry climate region with high-activity clay mineral soils (Kenya is about 80% arid and semi-arid land); no organic soils.
• Wetlands, settlements and other land: IPCC defaults; land converted to these categories is assumed to hold zero carbon stock.
• Deforestation and degradation: instantaneous oxidation (all carbon lost at once); harvested wood products are not yet included.