Wenru Xu Hong S. He Todd J. Hawbaker Zhiliang Zhu Paul D. Henne 20200304 Raster Digital Data Set https://doi.org/10.5066/P913N38G Wenru Xu Hong S. He Todd J. Hawbaker Zhiliang Zhu Paul D. Henne 2020 Publication (Journal) Science of the Total Environment 716 Amsterdam, Netherlands Elsevier https://doi.org/10.1016/j.scitotenv.2020.136534 Geospatial data were developed to characterize pre-fire biomass, burn severity, and biomass consumed for the Black Dragon Fire that burned in northern China in 1987. Pre-fire aboveground tree biomass (Mh/ha) raster data were derived by relating plot-level forest inventory data with pre-fire Landsat imagery from 1986 and 1987. Biomass data were generated for individual species: Dahurian larch (Larix gmelinii Rupr. Kuzen), white birch (Betula platyphylla Suk), aspen (Populus davidiana Dode and Populus suaveolens Fischer), and Mongolian Scots pine (Pinus sylvestris var. mongolica Litvinov). A raster layer of total aboveground tree biomass was also generated. Burned area was manually delineated using the normalized burn ratio (NBR) calculated from post-fire Landsat imagery. Burn severity categories include unburned, low, moderate, and high, and were mapped using established relationships between NBR and the composite burn index (CBI). Aboveground biomass consumption (Mg/ha) was calculated using biomass consumption rates specific to individual species and burn severity categories. Based on these data, the Black Dragon Fire burned 1.3 million ha and consumed 36.99 Tg of aboveground biomass. These data were generated to map the extent and severity of the Black Dragon Fire that burned in 1987 in northern China, and to estimate biomass consumption and carbon emissions. 19860612 19900902 observed Complete None planned 121.174009066 125.211072294 53.600194089 52.120356204 None Boreal forest Wildfire Carbon and greenhouse gas emissions USGS Metadata Identifier USGS:5d77e92de4b0c4f70d020b19 Common geographic areas China None. Unless otherwise stated, all data, metadata, and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. Todd J. Hawbaker U.S. Geological Survey Mailing and Physical

Denver Federal Center, P.O. Box 25046, MS 980

Lakewood CO 80225-0046 USA 303-236-1371 tjhawbaker@usgs.gov Environment as of Metadata Creation: Microsoft [Unknown] Version 6.2 (Build 9200) ; Esri ArcGIS 10.6.1 (Build 9270) Service Pack N/A (Build N/A) No formal attribute accuracy tests were conducted. No formal logical accuracy tests were conducted. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details. A formal accuracy assessment of the horizontal positional information in the data set has not been conducted. A formal accuracy assessment of the vertical positional information in the data set has either not been conducted, or is not applicable. US Geological Survey 20180909 Raster Digital Data (Aerial Imagery) Sioux Falls, SD, USA Earth Resources Observation Science Center https://earthexplorer.usgs.gov/ Digital and/or Hardcopy Resources 19860612 199009902 observed Source Input 1 Source information used in support of the development of the data set. 1. Acquisition of Landsat data Pre- and post-fire Landsat images from the U.S. Geological Survey (http://earthexplorer.usgs.gov) were used to cover the 1987 Black Dragon fire to estimate aboveground biomass and burn severity. The images were chosen primarily from June to August (growing season) shortly before and after the fire (June 26, 1986 and June 24, 1987 for path 121, row 23; June 12, 1986 and June 15, 1987 for path 122, row 23; August 6, 1986 for path 123, row 23; June 15, 1987 for path 122, row 24) to ensure the trees were in the same phenological phase. Because of a gap in the data, however, we chose April 26, 1989 and September 2, 1990 for path 123, row 23, and September 14, 1988 for path 121, row 24. The images were processed by United States Geological Survey to convert from DN (digital numbers) to surface-reflectance using the LEDAPS algorithm (Landsat ecosystem disturbance adaptive processing system, Masek et al. 2006). Clouds, cloud shadows, and snow pixels were masked using the function of mask algorithm (FMASK) (Zhu and Woodcock 2012). Masek, JG (2006) Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). Zhu Z, Woodcock CE (2012) Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 118, 83-94. 2. Pre-fire biomass mapping Zhang et al. (2018) combined 2000s forest inventory data and remote sensing data to map species-level biomass in the boreal forests of China. The pre-fire aboveground biomass density maps by species in this study were produced using pre-fire Landsat data, according to the AGB estimation model developed by Zhang et al. (2018). We calibrated and validated the results with post-fire forest inventory data. We subtracted biomass gained from succession based on stand-age specific annually biomass increases estimated from 2000s (1997-2001) and 2010s (2010-2015) forest inventory data. We assumed that the forest species composition did not change within the 20-year period. Zhang Q, He HS, Liang Y, Hawbaker TJ, Henne PD, Liu J, Huang S, Wu Z, Huang C (2018) Integrating forest inventory data and MODIS data to map species-level biomass in Chinese boreal forests. Canadian Journal of Forest Research 48, 1-19. 3. Burn severity mapping Chang et al. (2016) explored relationships between remote sensing indices and the composite burn index (CBI) based on 85 CBI plots within 16 fires in this area. They found that normalized burn ratio (NBR) was highly correlated with the field-based CBI (R2=0.63, p<0.0001). Here, we used the developed relationship of CBI and NBR by Chang et al. (2016) to assess burn severity using the historical post-fire Landsat imagery for the Black Dragon Fire, including four classes: no effect (unburned), low severity, moderate severity, and high severity. From the above relationship, we assigned tree mortality levels Chang Y, Zhu ZL, Feng YT, Li YH, Bu RC, Hu YM (2016) The spatial variation in forest burn severity in Heilongjiang Province, China. Natural Hazards 81, 981-1001 4. Perimeter mapping The outermost fire perimeter was manually interpreted based on Landsat NBR values, because valleys and low-elevation areas in the south were not burned, but also characterized with low NBR values, which could be misclassified as low-severity burned areas using the NBR thresholds. Raster Grid Cell 5111 8850 1 Beijing 1954 3 Degree GK CM 120E (ESRI Full Name: Beijing_1954_3_Degree_GK_CM_120E) 500000.00000000 0 0 120.0 1.0 row and column 30.0 30.0 Meter D_Beijing_1954 Krasovsky_1940 6378245.0 298.3 Attribute Table Aspen.tif Producer defined Value Aspen aboveground tree biomass (Mg/ha) Producer defined 0 54.7958 Mg/ha Attribute Table burnseverity.tif Producer defined Value Burn severity Producer defined 1 Unburned Producer defined 2 Low severity Producer defined 3 Moderate severity Producer defined 4 High severity Producer defined Count Count of pixels Producer defined 437397 7476186 Attribute Table consumed_biomass.tif Producer defined Value Total aboveground tree biomass consumed in the Black Dragon Fire (Mg/ha) Producer defined 0 106.646 Mg/ha Attribute Table FirePerimeter.shp Producer defined Id Unique identifier for polygons. Producer defined 0 0 Attribute Table larch.tif Producer defined Value Dahurian larch aboveground tree biomass (Mg/ha) Producer defined 0 118.829 Mg/ha Attribute Table pine.tif Producer defined Value Mongolian Scots pine aboveground tree biomass (Mg/ha) Producer defined 0 107.186 Mg/ha Attribute Table TotalAGB.tif Producer defined Value Total aboveground tree biomass (Mg/ha) Producer defined 0 174.434 Mg/ha Attribute Table wbirch.tif Producer defined Value White birch aboveground tree biomass (Mg/ha) Producer defined 0 102.753 Mg/ha aspen.tif: Estimated aboveground pre-fire biomass for aspen (Mg/ha). burn_severity.tif: Estimated burn severity categories (1=unburned, 2=low severity, 3=moderate severity, 4=high severity). consumed_biomass.tif: Estimated amount of aboveground tree biomass consumed in the Black Dragon Fire (Mg/ha). fire_perimeter.shp: Polygon of the Black Dragon Fire perimeter. larch.tif: Estimated aboveground pre-fire biomass for larch (Mg/ha). pine.tif: Estimated aboveground pre-fire biomass for pine (Mg/ha). total_abg.tif: Estimated aboveground pre-fire biomass for all species (Mg/ha). wbirch.tif: Estimated aboveground pre-fire biomass for white birch (Mg/ha). 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Lakewood CO 80225-0046 United States 888-275-8747 sciencebase@usgs.gov Any use of trade, product or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Geological Survey. Although this information product, for the most part, is in the public domain, it also contains copyrighted materials as noted in the text. Permission to reproduce copyrighted items for other than personal use must be secured from the copyright owner. This database has been approved for release and publication by the Director of the USGS. Although this database has been subjected to rigorous review and is substantially complete, the USGS reserves the right to revise the data pursuant to further analysis and review. Furthermore, it is released on condition that neither the USGS nor the United States Government may be held liable for any damages resulting from its authorized or unauthorized use. Although these data have been processed successfully on a computer system at the U.S. Geological Survey, no warranty expressed or implied is made regarding the display or utility of the data on any other system, or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. The U.S. Geological Survey shall not be held liable for improper or incorrect use of the data described and/or contained herein. Raster Digital Data Sets and Vector Digital Data Set (Polygon) https://doi.org/10.5066/P913N38G None. No fees are applicable for obtaining the data set. 20200820 Todd J Hawbaker U.S. Geological Survey mailing address

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Lakewood CO 80225-0046 United States 303-236-1371 tjhawbaker@usgs.gov FGDC Content Standard for Digital Geospatial Metadata FGDC-STD-001-1998