Uncertainties in carbon emissions from land use and land cover change in Indonesia
Authors: Brasika Ida Bagus Mandhara , Friedlingstein Pierre , Sitch Stephen , O'Sullivan Michael , Duran-Rojas Maria Carolina , Rosan Thais Michele , Goldewijk Kees Klein , Pongratz Julia , Schwingshackl Clemens , Chini Louise P. , Hurtt George C. 
Published: November 2024

Abstract. Indonesia is currently one of the three largest contributors of carbon emissions from land use and land cover change (LULCC) globally, together with Brazil and the Democratic Republic of the Congo. However, until recently, there was only limited reliable data available on LULCC across Indonesia, leading to a lack of agreement on drivers, magnitude, and trends in carbon emissions between different estimates. Accurate LULCC should improve robustness and reduce the uncertainties of carbon dioxide (CO2) emissions from Land Use Change (ELUC) estimation. Here, we assess several cropland datasets that are used to estimate ELUC in Dynamic Global Vegetation Models (DGVMs) and Bookkeeping models (BKMs). Available cropland datasets are generally categorized as either census-based such as the Food and Agricultural Organization (FAO) annual statistical dataset, or satellite-based such as the Mapbiomas dataset, which is derived from Landsat Satellite images. Our results show that census-based and satellite-based estimates have little agreement on temporal variability and cropland area changes. In some islands, they show spatial similarity, but differences appear in the main islands such as Kalimantan, Sumatra and Java. These differences lead to spatio-temporal uncertainty in carbon emissions. The different land cover forcings (census-based vs satellite-based) in a single model (JULES-ES) result in ELUC uncertainties of about 0.08 [0.06 to 0.11] PgC/yr. Furthermore, we found that uncertainties in ELUC estimates are also due to differences in the carbon cycle models in DGVMs, as DGVMs driven by the same land cover dataset show differences in ELUC estimates of 0.12 ± 0.02 PgC/yr with 95 % confidence level and range [-0.04 to 0.35] PgC/yr. This is consistent with other product such as BKMs that estimates 0.14 [0.12 to 0.15] PgC/yr with both steady trend. We also compare emissions with those from the National Greenhouse Gas Inventory (NGHGI) product. The NGHGI estimates (based on BUR3; periodic official government report on Greenhouses Gas to UNFCCC) have much lower carbon emissions (0.06 ± 0.06 PgC/yr), though with an increasing trend. These numbers double when we include emissions from peat fire and peat drainage: the DGVM ensemble indicates emissions of 0.23 ± 0.05 PgC/yr and BKMs indicate emissions of 0.24 [0.22–0.25] PgC/yr. In contrast, emissions based on the Indonesian NGHGI remain much lower (BUR2: 0.18±0.07 PgC/yr BUR3: 0.13 ± 0.10 PgC/yr). Furthermore, emission peaks occur in year of moderate-to-strong El Nino events. Several improvements might reduce uncertainties in carbon emissions from LULCC in Indonesia, such as: combination of satellite-based dataset with census-based dataset, inclusion of peat-related emissions in DGVMs and potentially explicit inclusion of palm oil in the models as this is a major crop in Indonesia. Overall, the analysis shows that carbon emissions have no decreasing trend in Indonesia, Therefore, deforestation and forest fire prevention remain vital for Indonesia.