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Fire-activity trends remain particularly uncertain for the equatorial and broader Southeast Asian regions due to discrepancies amongst studies. Reported regional trends are variously decreasing but non-significant, controlling for precipitation1; increasing-to-decreasing, depending on period, absent any reporting of statistical significance7,10; and non-significant6,16, including for Indonesia, which dominates regional trends16. Discrepancies centre on fire data sensitivity, observation period, whether the confounding effects of drought are observed, and whether trends are tested for significance. Crucially, reported trends invariably reflect aggregate fire activity that conflate large fire events with less destructive but ubiquitous smaller-scale agricultural burning17,18,19, potentially masking shifts to fire regimes driven by changing economic, political, or climatic factors.
Previously, fire abatement driven by intensifying land management in the developing world was observed virtually exclusively in naturally fire-prone savannah biomes, such as northern Africa1,11. We extend such abatement dynamics to the humid tropics for the first time upon disaggregating overall fire activity into discrete fire events and quantifying their severity for Equatorial Asia, describing ultimately an attenuation of the severe fire activity that has arisen largely since ca.1970. We report significant declines in the rate of severe fire events across Indonesia and its fire-affected regions over the last two decades (Fig. 1), as well as significant declines in the severity of seasonal fire activity, particularly in Sumatra (Fig. 3).
Drought reoccurred throughout our time series (Fig. 1c) and was accounted for, both as a variable in our models and by variations to our time-series observations. Therefore, non-climatic factors, namely land management, must underlie the attenuation of severe fire activity. Conceptually, land management has been characterised as progressive agricultural capitalisation1, typified by agricultural investment, intensification, modernisation, and commercialisation. Capitalisation doubtless plays a role in fire abatement, as for instance amongst Indonesian smallholders, who progressively replaced swidden practices with oil-palm permaculture since the 1990s54,55. Yet capitalisation is ultimately a crude determinant of fire abatement and has an uncertain, seemingly nuanced role here. Consistent with the expected role of capitalisation, fire activity declined widely across mosaic cropland, but not the less cultivated and capitalised mosaic vegetation (Table 2). On the other hand, the literature is clear that the relatively capitalised Indonesian agro-industrial sector has a relatively high association with the extensive burning of disused lands, compared to less capitalised land users17; that Indonesian agro-industrial investment has been declining56, as described below; and that the vast majority of such investment has occurred prior to or during agricultural establishment57, which has been ongoing decades. Some clarity of the role of capitalisation may be offered by the fact that fire activity declined rarely and relatively moderately across intensively-farmed cleared/cultivated lands (Table 2), which also have a relatively high fire-occurrence rate (Table 1). Conceptually, therefore, transitioning from mosaic vegetation to mosaic cropland to cleared/cultivated lands as per the presumed course of progressive land management would perversely increase overall fire activity, likely due to more frequent agricultural fires, while simultaneously reducing severe fire activity generally, as per our observations.
The preceding characterises attenuation via land management as an active, if serendipitous, convergence of political forces and economic trends where and when fire prevention becomes feasible and urgent. Such a dynamic complements and extends conceptualisations of passive fire abatement via agricultural capitalisation. Initial capitalisation typically foments additional agricultural development and burning2 and, in time, degraded-land conversion (item i above), greater monitoring and regulation (item ii), and greater political and economic costs for uncontrolled burning (items ii & iii), all of which gradually tip towards attenuation in semi-cultivated mosaic lands. Such a nuanced linkage between attenuation and capitalisation would resolve the apparent contraction whereby fire abatement proceeds from capitalised lands to less capitalised peripheries while attenuation proceeds from the most severe burning to the least.
After Sloan et al.17. A Fire Events 1 and 4 are distinct, regardless of any similarity of their respective active-fire detection (AFD) dates, because their AFDs are separated by at least one 1-km2 grid cell. B Multiple AFDs of the same earliest date per fire event are all considered ignition AFDs. C For fire events defined by a single AFD, the AFD is always an ignition AFD. D The 500-m buffer surrounding an AFD is relevant only for comparisons with burned area maps in Supplementary Note 4. E AFDs of adjacent cells must be detected within four days of each other to belong to the same fire event, regardless of the total duration of the fire event, which may be up to many weeks. F Spatially proximate AFDs belong to different fire events when they are separated from each other by more than four days. G For analysis of fire activity by land-management intensity (Table 2), the incidence of a land-use/cover class amongst a given set of fire activity is given by the overlap of the class and eligible AFDs, not the whole fire event.
Various factors recommend describing fire-activity severity as per Eq. (1) based on MODIS AFD-derived fire events (Supplementary Note 5). Compared to an analogous fire-event severity index defined for Global Fire Atlas fire events83,84 based on MODIS MCD64a1 500-m BA data79 (Eqn. S2), being the only alternative fire-event data for our region and most like it, Eq. (1) represents the scale of large, intense fire events more comprehensively while capturing relatively greater extremes of fire activity amongst individual events. Significant differences in the extremes of fire-event severity frequency distributions between our study and the analogous severity index for the Global Fire Atlas support this view (Supplementary Fig. 9, Supplementary Note 5).
Models were bootstrapped and weighted as above. Complementing bootstrapping, we tested models for sensitivity to widespread burning late in our time series by experimentally omitting all observations for 2019 or 2015. Models for the two resultant partial time series were largely consistent with those for the full time series in Table 2 (Supplementary Note 2), affirming the progressive and robust nature of the observed land-use/cover shifts underlying fire abatement.
All data used in this paper are available via their respective cited online repositories or otherwise via request to the corresponding author. The unique fire-event data created for this study, including fire-event severity and ignitions, are available at
Communications Earth & Environment thanks Yuyun Fu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editors: Gerald Forkuor and Clare Davis.
The Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire 8-Day (MYD14A2) Version 6 data are generated at 1 kilometer (km) spatial resolution as a Level 3 product. The MYD14A2 gridded composite contains maximum value of individual fire pixel classes detected during the eight days of acquisition.
Validation at stage 3 has been achieved for all MODIS Thermal Anomalies and Fire products. Further details regarding MODIS land product validation for the MYD14 data product is available from the MODIS land team validation site.
The Quality Assurance (QA) layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the QA layer.
Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.
Known issues are described on the MODIS Land Quality Assessment website and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.
Download active fire products from the Moderate Resolution Imaging Spectroradiometer (MODIS) (MCD14DL) and Visible Infrared Imaging Radiometer Suite (VIIRS) 375 m (VNP14IMGTDL_NRT, VJ114IMGTDL_NRT, and VJ214IMGTDL_NRT) for the last 24 and 48 hours and for the last 7 days in shapefile, KML, WMS, or text file formats. VIIRS data complement MODIS fire detections, but the improved spatial resolution of the 375 m data provides a greater response over fires covering relatively small areas. Read more about VIIRS.
Data older than seven days can be obtained using the Archive Download Tool. Near real-time (NRT) data are replaced with data extracted from the standard MODIS and VIIRS active fire products. Users intending to perform scientific analysis are advised to download the standard (science quality) data.
ALOHA (Areal Locations of Hazardous Atmospheres) is the hazard modeling program for the CAMEO software suite (Computer-Aided Management of Emergency Operations), which is used widely to plan for and respond to chemical emergencies.
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