DOI: 10.5061/dryad.msbcc2g1t
title: Discrete fire events, their severity, and their ignitions, as derived from MODIS MCD 14ML active-fire detection data for Indonesia, 2002-2019

description: 1. PUBLICATION CORRESPONDING TO THESE DATA   Sloan, Sean*;
 Locatelli, Bruno; Andela, Niels; Cattau, Megan E.; Gaveau, David; Tacconi,
 Luca. 2022 ‘Declining Severe Fire Activity on Managed Lands in Equatorial
 Asia’. Communications Earth & Environment. DOI:
 10.1038/s43247-022-00522-6.   *Corresponding author email:
 sean.sloan@viu.ca     2. ABSTRACT OF THE DATA  
 The GIS data and corresponding attribute data described here pertain to
 discrete fire events, their severity, and their ignitions, as derived on
 the basis of daily MODIS Collection 6 MCD14ML active-fire detections
 (AFDs).  Data on fire events and their ignitions are provided
 separately, as two data files.  These data files on fire events
 and ignitions may however be linked to each other by the data
 user.  Fire-event severity is quantified per fire event and
 reported in the data file for fire events.   A fire event is a
 cluster of MODIS Collection 6 MCD14ML active-fire detections (AFDs)
 wherein each AFD has a spatial (&lt;=1-km) and temporal
 (&lt;=4-day) proximity to another AFD in the same fire event,
 inferring thus a relational co-occurrence amongst AFDs in time and
 space.  In other words, a fire event is considered a likely
 occasion of burning wherein all constituent AFDs are related to each other
 in time and space, either directly (as for proximate AFDs) or indirectly
 (as in the case of a large area of fire activity that spread progressively
 over time and space from an initial source).   Each fire event
 has a designated ignition AFD, being the AFD of the fire event with the
 earliest detection date.  A given fire event can have more than
 one ignition AFD if the ignitions all share same earliest detection
 date.  The ignition AFD(s) is the nominal initial source of the
 burning described by the corresponding fire event.  All other,
 non-ignition AFDs of a fire event are deemed its ‘propagation’ AFDs, since
 these AFDs follow from the ignitions, temporally and spatially.  
 See Figure 4 in the publication by Sloan et al. for an illustration of the
 geography of fire events and their ignition AFDs.   
 Fire events and their ignitions were derived from standard science-quality
 MODIS Collection 6 MCD 14ML AFD data, commonly referred to as fire
 ‘hotspot’ data.  Data were detected by both the Terra and Aqua
 satellite sensors daily for Indonesia between July 2002 and December 2019.
  Information on these input data are provide by the two citations
 below.  The publication of Sloan et al. provides methodological
 details on how the MODIS Collection 6 MCD 14ML AFD data were processed
 into discrete fire events and ignitions.   EarthData. MODIS
 Collection 6 Active-Fire Detections standard scientific data (MCD14ML),
 NASA EarthData, https://earthdata.nasa.gov/firms (2019).  
 Giglio, L., Schroeder, W. & Justice, C. O. The Collection 6 MODIS
 active fire detection algorithm and fire products. Remote Sensing of
 Environment 178, 31-41, (2016).     3. DATA FILES
   Two data files are distributed here – one for discrete fire
 events, and another for the ignition AFDs of each fire event. 
 The data files are provided in a GIS-compatible format, and also as a
 generic text format, as described below.   3.1 GIS VERSION
   Data files in GIS-compatible format are provided as ‘feature
 classes’ within an ArcGIS file geodatabase
 ‘Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb’.  These data
 files can be viewed and manipulated using either ArcGIS Desktop or ArcGIS
 Pro software.  There is one feature class for fire events, and
 another file for ignitions.  
 Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb\nfire4_all_spatial_fire_2002_2019_joins_sp_LC This file pertains to fire events.  All AFDs of a given fire event are included, without differentiation as to whether the AFDs are ignition AFDs or other (propagation) AFDs.  Fire events are assigned unique ID values and basic attribute data.   Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb\nfire4_all_spatial_fire_2002_2019_igs_sp_LC This file pertains to ignitions. Only ignition AFDs are included for a given fire event.  Fire events corresponding to the ignitions are assigned unique ID values and basic attribute data.   3.2 CSV TEXT VERSION   Both data files are also supplied as comma-separated value (CSV) text files for viewing and manipulation in non-GIS software, such as Excel, text editors, or any statistical software.  The text files can also be read into various GIS software.  CSV-formatted files have the same file name and attribute fields as the corresponding GIS-formatted data files.  These CSV-formatted data files (as well as the GIS-formatted data files) include attribute data on the latitude and the longitude of each AFD.     Attribute field names are included as the first row of values in a CSV file.    No ‘text qualifiers’ like quotations (“ ”) or inverted commas (‘’) are used to designate text/string values within the CSV file.  Text values appear directly between commas in the CSV data file, e.g.,  …,Kalimantan_Southern,…  .   Note two points of caution for working with these CSV data:   i)                    Microsoft Excel may be used for a partial view of the data file nfire4_all_spatial_fire_2002_2019_joins_sp_LC.csv, but it is not recommended for working with this data file.  This is because the number of records/rows in this csv file slightly exceeds that maximum that may be read by Excel, which is just over 1 million.  This limitation does not apply to the other csv file, however.   ii)                  The GIS-formatted data files employ ‘null values’ in their attribute tables, and so the corresponding ‘values’ in the CSV-formatted data files are similarly null.  For null values, no value whatsoever is ascribed, not even 0.  In the syntax of a CSV file (apparent upon opening the file in any text editor like Microsoft Notepad), a null value is denoted by two consecutive commas without any value, text, or space between them.  If a CSV file were opened in Excel, a cell assigned a null value would be blank, not 0 or otherwise.  This denotes the correct transcription of the GIS-formatted data.  This feature will not impede the correct reading of these CSV data by whatever software.  Users are made aware of this feature merely to ensure the proper input of these data into whatever software.     4. DATA STRUCTURE / GEOGRAPHY   The GIS-formatted data files are ‘point data’, i.e., they map the geography of AFDs as individual ‘points’, in keeping with how these MODIS MCD14ML AFD data were originally structured.  For the GIS-formatted data files, each record/row in its corresponding attribute tables corresponds geographically to single AFD ‘point’, regardless of whether that AFD belongs to a fire event comprised of many AFDs.  In the parlance of GIS files, the files depict ‘single-part’ point features.  The unique ID field [nfireID2] serves to denote the fire event to which a given AFD belongs.   Similarly, for the CSV-formatted data files, each record/row of values corresponds to a single AFD.   There are 1,232,377 records for the data file ‘nfire4_all_spatial_fire_2002_2019_joins_sp_LC’. There are 720795 records for the data file ‘nfire4_all_spatial_fire_2002_2019_igs_sp_LC’.     5. ATTRIBUTE FIELDS   In the data files, while some attribute fields pertain to the individual AFD as the unit of observation (e.g., the land-cover class coincident with the AFD), other attribute fields correspond to the larger ‘fire event’ to which the individual AFD belongs (e.g., the total duration of fire activity for the fire event).  Accordingly, for certain attribute fields pertaining to the fire event as a whole, their values will appear ‘duplicated’ in the data file amongst those individual AFDs (records) that constitute the fire event in question.  Whether a given attribute field pertains to the individual AFD or to its constituent fire event is denoted below for each field.    Each AFD is assigned a unique ID field denoting its constituent fire event, [nfireID2].  This field is consistent between both data files, so that attribute data for a given fire event may be ‘matched’ to attribute data for its corresponding ignition AFD(s), and vice versa, on the basis of the common value of the field [nfireID2].   Note that many attributes below are as originally defined/measured by the input MCD 14ML data, or are derived directly thereof.   5.1 DATASET nfire4_all_spatial_fire_2002_2019_joins_sp_LC   Field Name Geography of Attribute Value Definition OID AFD Object ID value. Unique values for each AFD (record) in the GIS-formatted data file when viewed in ArcGIS. Field values are -1 in the CSV-formatted data file. Peat AFD Denotes whether the AFD occurs on peatlands (value=1) as defined in Sloan et al. MIN_CONFIDE Fire Event The minimum detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. MAX_CONFIDE Fire Event The maximum detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. MEAN_CONFIDE Fire Event The mean detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. STD_CONFIDE Fire Event The standard deviation of detection confidence of all AFDs in the fire event, where confidence ranges from 1-100%. SUM_FRP Fire Event The sum total of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MEAN_FRP Fire Event The mean of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MIN_FRP Fire Event The minimum of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MAX_FRP Fire Event The maximum of all fire-radiative power (FRP) measures for all AFDs in the fire event. Units are megawatts. MEAN_LATITUD Fire Event The mean latitude of all AFDs in the fire event. MEAN_LONGITU Fire Event The mean longitude of all AFDs in the fire event. MIN_ACQ_DAT Fire Event The minimum acquisition date of all AFDs in the fire event (i.e., the ignition AFD detection date). MAX_ACQ_DAT Fire Event The maximum acquisition date of all AFDs in the fire event (i.e., the ignition AFD detection date). MIN_acq_yer Fire Event The year in which the earliest AFD of the fire event was detected. MIN_acq_mnt Fire Event The month in which the earliest AFD of the fire event (i.e., ignition AFD) was detected. Months are coded numerically, e.g., 1=January, 12=December. MAX_acq_mnt Fire Event The month in which the latest AFD of the fire event was detected. Months are coded numerically, e.g., 1=January, 12=December. MIN_yday Fire Event The detection day of year of the earliest AFD of the fire event, i.e., ignition AFD. Day of year is denoted numerically, where 1=January 1 and 365=December 31. MAX_yday Fire Event The detection day of year of the latest AFD of the fire event, i.e., ignition AFD. Day of year is denoted numerically, where 1=January 1 and 365=December 31. RANGE_yday Fire Event The number of days of duration of the fire event, defined as [MAX_yday]-[MIN_yday] FIRST_subst_r AFD Text labels denoting the Indonesian island/region of data processing, e.g., Kalimantan, Papua. AF_Count Fire Event Number of AFDs in the fire event. nfireID2 Fire Event The unique ID of the fire event to which the AFD belongs. Island AFD Numerical values coding for major Indonesian islands/region: 1000000=Sumatra; 2000000=Kalimantan; 3000000=Sulawesi; 4000000=Papua. FRP_Days Fire Event The severity of the fire event, as defined by Sloan et al., equal to [Sum_FRP] * ([Range_yday]+1). IG_Count Fire Event Number of ignition AFDs in the fire event CCI_LC2002   The land-cover class coincident with the AFD. The class is coded by a numerical value as per the left-most column in the table in Section 5.3.  The class is that observed for the calendar year in which the AFD occurred, where the year #### is denoted in the field name ‘CCI_LC####’.  The land-cover data source is as described in Section 5.3. CCI_LC2003   CCI_LC2004   CCI_LC2005   CCI_LC2006   CCI_LC2007   CCI_LC2008   CCI_LC2009   CCI_LC2010   CCI_LC2011   CCI_LC2012   CCI_LC2013   CCI_LC2014   CCI_LC2015   CCI_LC2016   CCI_LC2017   CCI_LC2018   CCI_LC2019   Region AFD Text labels denote whether the AFD occurs within one of the two focal regions of Sloan et al.: Southern Kalimantan, or Central South Sumatra. POINT_X AFD Longitude, given as decimal degrees with WGS84 datum. POINT_Y AFD Latitude, given as decimal degrees with WGS84 datum. POINT_Z -- Ignore. POINT_M -- Ignore.           5.2 DATASET nfire4_all_spatial_fire_2002_2019_igs_sp_LC   Field Name Geography of Attribute Value Definition OID AFD Object ID value. Unique values for each AFD (record) in the GIS-formatted data file when viewed in ArcGIS. Field values are -1 in the CSV-formatted data file. IG_Count Fire Event Number of ignition AFDs in the fire event. MIN_acq_yer Fire Event The year in which the earliest AFD of the fire event was detected. MIN_acq_mnt Fire Event The month in which the earliest AFD of the fire event (i.e., ignition AFD) was detected. Months are coded numerically, e.g., 1=January, 12=December. FIRST_subst_r AFD Text labels denoting the Indonesian island/region of data processing, e.g., Kalimantan, Papua. MIN_yday Fire Event The detection day of year of the earliest AFD of the fire event, i.e., ignition AFD. Day of year is denoted numerically, where 1=January 1 and 365=December 31. nfireID2 Fire Event The unique ID of the fire event to which the AFD belongs. CCI_LC2002 AFD The land-cover class coincident with the AFD. The class is coded by a numerical value as per the left-most column in the table in Section 5.3.  The class is that observed for the calendar year in which the AFD occurred, where the year #### is denoted in the field name ‘CCI_LC####’.  The land-cover data source is as described in Section 5.3. CCI_LC2003 AFD CCI_LC2004 AFD CCI_LC2005 AFD CCI_LC2006 AFD CCI_LC2007 AFD CCI_LC2008 AFD CCI_LC2009 AFD CCI_LC2010 AFD CCI_LC2011 AFD CCI_LC2012 AFD CCI_LC2013 AFD CCI_LC2014 AFD CCI_LC2015 AFD CCI_LC2016 AFD CCI_LC2017 AFD CCI_LC2018 AFD CCI_LC2019 AFD Region AFD Text labels denote whether the AFD occurs within one of the two focal regions of Sloan et al.: Southern Kalimantan, or Central South Sumatra. Peat AFD Denotes whether the AFD occurs on peatlands (value=1) as defined in Sloan et al. POINT_X AFD Longitude, given as decimal degrees with WGS84 datum. POINT_Y AFD Latitude, given as decimal degrees with WGS84 datum. POINT_Z -- Ignore. POINT_M -- Ignore.     5.3. LAND-COVER ATTRIBUTE DATA   As noted in Section 5.1 and Section 5.2, the nominal values of the attribute fields ‘CCI_LC####’ correspond to column 1 of the table below.  These hierarchical values, and their corresponding land-cover classes labels in column 2 of the table, pertain to the land-cover classification of the Copernicus Climate Change Initiative Land-Cover Product of the European Space Agency.   This classification has an annual temporal resolution and 300-meter spatial resolution.  Pertinent citations for these land-cover data are below:   ESA. Annual land-cover product, 1992 to 2019/present, based on MERIS 300-m and ancillary SPOT, AVHRR, Sentinel-3 and PROB-V satellite data. European Space Agency (ESA) European Centre for Medium-Range Weather Forecasts (ECMFW) Copernicus Climate Change Service (C3S) Climate Change Initiative (CCI), https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=overview; http://maps.elie.ucl.ac.be/CCI/viewer/download.php; http://www.esa-landcover-cci.org/ (2020).   Pérez-Hoyos, A., Rembold, F., Kerdiles, H. & Gallego, J. Comparison of global land cover datasets for cropland monitoring. Remote Sensing 9, (2017).   Columns 3 and 4 in the table below illustrate how the original land-cover classes of the Copernicus Climate Change Initiative Land-Cover Product were reclassified for analysis in Sloan et al.     1. CCI-LC Class Value 2. CCI-LC Class Label 3. New Class Value for Sloan et al. 4. New Class Label for Sloan et al. 0 No Data 0 No Data 10 Cropland, rainfed 1 Cleared/Cultivated 11 Herbaceous cover 1 Cleared/Cultivated 12 Tree or shrub cover 1 Cleared/Cultivated 20 Cropland, irrigated or post‐flooding 1 Cleared/Cultivated 30 Mosaic cropland (&gt;50%) / natural vegetation (tree, shrub, herbaceous cover) (&lt;50%) 2 Mosaic Cropland 40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (&gt;50%) / cropland (&lt;50%) 3 Mosaic Natural Veg 50 Tree cover, broadleaved, evergreen, closed to open (&gt;15%) 4 Forest 60 Tree cover, broadleaved, deciduous, closed to open (&gt;15%) 4 Forest 61 Tree cover, broadleaved, deciduous, closed (&gt;40%) 4 Forest 62 Tree cover, broadleaved, deciduous, open (15‐40%) 4 Forest 70 Tree cover, needleleaved, evergreen, closed to open (&gt;15%) 4 Forest 71 Tree cover, needleleaved, evergreen, closed (&gt;40%) 4 Forest 72 Tree cover, needleleaved, evergreen, open (15‐40%) 4 Forest 80 Tree cover, needleleaved, deciduous, closed to open (&gt;15%) 4 Forest 81 Tree cover, needleleaved, deciduous, closed (&gt;40%) 4 Forest 82 Tree cover, needleleaved, deciduous, open (15‐40%) 4 Forest 90 Tree cover, mixed leaf type (broadleaved and needleleaved) 4 Forest 100 Mosaic tree and shrub (&gt;50%) / herbaceous cover (&lt;50%) 5 Mosaic Shrubland 110 Mosaic herbaceous cover (&gt;50%) / tree and shrub (&lt;50%) 5 Mosaic Shrubland 120 Shrubland 6 Low/Sparse Vegetation 121 Evergreen shrubland 6 Low/Sparse Vegetation 122 Deciduous shrubland 6 Low/Sparse Vegetation 130 Grassland 6 Low/Sparse Vegetation 140 Lichens and mosses 6 Low/Sparse Vegetation 150 Sparse vegetation (tree, shrub, herbaceous cover) (&lt;15%) 6 Low/Sparse Vegetation 151 Sparse tree (&lt;15%) 6 Low/Sparse Vegetation 152 Sparse shrub (&lt;15%) 6 Low/Sparse Vegetation 153 Sparse herbaceous cover (&lt;15%) 6 Low/Sparse Vegetation 160 Tree cover, flooded, fresh or brakish water 7 Flooded Vegetation 170 Tree cover, flooded, saline water 7 Flooded Vegetation 180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water 7 Flooded Vegetation 190 Urban areas 8 Other 200 Bare areas 8 Other 201 Consolidated bare areas 8 Other 202 Unconsolidated bare areas 8 Other 210 Water bodies 8 Other
description: <strong>6. METHODOLOGICAL SUMMARY </strong>   Full methodological details of how daily MODIS Collection 6 MCD 14ML active-fire detections (AFDs) were rendered as discrete fire events and ignitions are provided in the current publication by Sloan et al., as well as by citations therein to the following earlier sources:   Sloan, S., et al. (2021). "Fire prevention in managed landscapes: Recent successes and challenges in Indonesia." <em>Mitigation and Adaptation Strategies for Global Change</em> 26: Article 32.             Cattau, M. E., et al. (2016). "Sources of anthropogenic fire ignitions on the peat-swamp landscape in Kalimantan, Indonesia." <em>Global Environmental Change</em> 39: 205-219.   The publication by Cattau et al. is the foundational methodological paper of Sloan et al. (2021) and the current publication of Sloan et al.   In summary, the method of defining a discrete fire event was to cluster MODIS Collection 6 MCD 14ML active-fire detections (AFDs) according to the spatial and temporal proximity of AFDs.  Here such a ‘cluster’ of AFDs constitutes a discrete fire event.  AFDs were clustered progressively and exhaustively such that fire events were defined ‘organically’.  An AFD was incorporated into a fire event whenever (i) the AFD occurred within a 1-km<sup>2</sup> grid cell that was the same as or adjacent to a grid cell already hosting at least one AFD already in the fire event, and (ii) the AFD occurred within four days of at least one AFD already incorporated by the fire event and in the same or an adjacent grid cell.  These protocols are those adopted by Sloan et al.(2021) and Cattau et al. (2016).    All AFDs in the MODIS Collection 6 MCD 14ML AFD archive for July 2002-December 2019 were used.  AFD Data were processed into fire events across Indonesia on a per-annum, per island basis.  Hence, no fire events span two calendar years, nor of course do any span more than one island.   Active fires were detectable as MODIS Collection 6 MCD 14ML AFDs at a temporal resolution of up to four time per day, given the MODIS Terra and Aqua satellite revisit rates (i.e., the frequency with which the satellite sensor returns to observe a given locale).  In practice, AFD rates may be less than this, due to cloud or smoke haze, which obscures the detection of active fires.  Of all AFDs clustered to compose a given fire event, those AFD(s) with the earliest detection date were designated as the nominal ignition AFD(s) of the fire event.  A given fire event can have more than one ignition AFD if such ignition AFDs all share same earliest detection date.     
description: <strong>3. DATA FILES</strong>   Two data files are distributed here – one for discrete fire events, and another for the ignition AFDs of each fire event.  The data files are provided in a GIS-compatible format, and also as a generic text format, as described below.   <strong>3.1 GIS VERSION</strong>   Data files in GIS-compatible format are provided as ‘feature classes’ within an ArcGIS file geodatabase ‘Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb’.  These data files can be viewed and manipulated using either ArcGIS Desktop or ArcGIS Pro software.  There is one feature class for fire events, and another file for ignitions.   Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb\nfire4_all_spatial_fire_2002_2019_joins_sp_LC This file pertains to fire events.  All AFDs of a given fire event are included, without differentiation as to whether the AFDs are ignition AFDs or other (propagation) AFDs.  Fire events are assigned unique ID values and basic attribute data.   Sloan_MODIS_FireEvents_Ignitions_2002_2019.gdb\nfire4_all_spatial_fire_2002_2019_igs_sp_LC This file pertains to ignitions. Only ignition AFDs are included for a given fire event.  Fire events corresponding to the ignitions are assigned unique ID values and basic attribute data.   <strong>3.2 CSV TEXT VERSION</strong>   Both data files are also supplied as comma-separated value (CSV) text files for viewing and manipulation in non-GIS software, such as Excel, text editors, or any statistical software.  The text files can also be read into various GIS software.  CSV-formatted files have the same file name and attribute fields as the corresponding GIS-formatted data files.  These CSV-formatted data files (as well as the GIS-formatted data files) include attribute data on the latitude and the longitude of each AFD.     Attribute field names are included as the first row of values in a CSV file.    No ‘text qualifiers’ like quotations (“ ”) or inverted commas (‘’) are used to designate text/string values within the CSV file.  Text values appear directly between commas in the CSV data file, e.g.,  …,Kalimantan_Southern,…  .   Note two points of caution for working with these CSV data:   i)                    Microsoft Excel may be used for a partial view of the data file nfire4_all_spatial_fire_2002_2019_joins_sp_LC.csv, but it is not recommended for working with this data file.  This is because the number of records/rows in this csv file slightly exceeds that maximum that may be read by Excel, which is just over 1 million.  This limitation does not apply to the other csv file, however.   ii)                  The GIS-formatted data files employ ‘null values’ in their attribute tables, and so the corresponding ‘values’ in the CSV-formatted data files are similarly null.  For null values, no value whatsoever is ascribed, not even 0.  In the syntax of a CSV file (apparent upon opening the file in any text editor like Microsoft Notepad), a null value is denoted by two consecutive commas without any value, text, or space between them.  If a CSV file were opened in Excel, a cell assigned a null value would be blank, not 0 or otherwise.  This denotes the correct transcription of the GIS-formatted data.  This feature will not impede the correct reading of these CSV data by whatever software.  Users are made aware of this feature merely to ensure the proper input of these data into whatever software.