Yu Chenglong, Liu Dan, He Feng, et al. Dynamic Characteristics of Natural Vegetation Fires and Their Response to Drought in Northeast China[J]. Bulletin of Soiland Water Conservation, 2019, 39(4): 9-16.
DOI:
Yu Chenglong, Liu Dan, He Feng, et al. Dynamic Characteristics of Natural Vegetation Fires and Their Response to Drought in Northeast China[J]. Bulletin of Soiland Water Conservation, 2019, 39(4): 9-16. DOI: 10.13961/j.cnki.stbctb.2019.04.002.
Dynamic Characteristics of Natural Vegetation Fires and Their Response to Drought in Northeast China
[Objective] The development law of natural vegetation fires and their response to drought in Northeast China during 2002-2017 was studied
so as to provide scientific basis for regional fire management
fire risk level prediction and forest resources protection.[Methods] Based on the published available Moderate Resolution Imaging Spectroradiometer(MODIS) satellite products and the self-calibrating Palmer drought severity index(scPDSI)data
the seasonal and interannual characteristics of fire dynamics of natural vegetation in Northeast China were analyzed by using statistical methods
and the response law of fire dynamics to dry-wet conditions was explored.[Results] On seasonal scale
most forest and grassland fires occurred in spring and autumn
and grassland fire occurrence increased significantly in these two seasons. On inter-annual scale
forest fire occurrence decreased significantly at the rate of 18 times per year and their average burnt area increased faintly. Grassland fire occurrence showed an extremely significant upward trend at the rate of 36 times per year
and their average burnt area decreased faintly. There were linear and negative correlations between fire occurrence and scPDSI. But burnt area appeared exponential and negative correlations with scPDSI. Both average fire occurrence and average burnt area per individual fire showed an increasing trend with the deepening of drought.[Conclusion] Fire occurrence and burnt area per individual fire of natural vegetation could be increased under the condition of drought.
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Malone S L, Kobziar L N, Staudhammer C L, et al. Modeling relationships among 217 fires using remote sensing of burn severity in southern pine forests[J]. Remote Sensing, 2011,3(9):2005-2028.
Brazhnik K, Hanley C, Shugar H H. Simulating changes in fires and ecology of the 21 st century Eurasian boreal forests of Siberia[J]. Forests, 2017,8(2):49-63.
Martín M L, Gonzalez-Vila F J, Knicker H. Distribution of black carbon and black nitrogen in physical soil fractions from soils seven years after an intense forest fire and their role as C sink[J]. Science of The Total Environment, 2018,637:1187-1196.
Saranya K R L, Reddya C S, Prasada-Rao P V V. Estimating carbon emissions from forest fires over a decade in Similipal Biosphere Reserve, India[J]. Remote Sensing Applications Society and Environment, 2016,4:61-67.
Tansey K, Gregoire J M, Defourny P, et al. A new, global, multi-annual(2000-2007) burnt area product at 1 km resolution[J]. Geophysical Research Letters,2008,35(1):L011401.
Plummer S, Arino O, Simon M, et al. Establishing a earth observation product service for the terrestrial carbon community:The globcarbon initiative[J]. Mitigation and Adaptation Strategies for Global Change, 2006,11(1):97-111.
Chuvieco E, Yue C, Heil A, et al. A new global burned area product for climate assessment of fire impacts[J]. Global Ecology and Biogeography, 2016,25(5):619-629.
Andela N, Morton D C, Giglio L, et al. A human-driven decline in global burned area[J]. Science, 2017,356(6345):1356-1362.
Hantson S, Pueyo S, Chuvieco E. Global fire size distribution is driven by human impact and climate[J]. Global Ecology and Biogeography, 2015,24(1):77-86.
Shi Y S, Sasai T, Yamaguchi Y. Spatio-temporal evaluation of carbon emissions from biomass burning in Southeast Asia during the period 2001-2010[J]. Ecological Modelling, 2014,272(24):958-115.
Van der W G R, Randerson J T, Giglio L, et al. Global fire emissions estimates during 1997-2016[J]. Earth System Science Data, 2017,9(2):697-720.
Caccamo G, Chisholm L A, Bradstock R A, et al. Using remotely-sensed fuel connectivity patterns as a tool for fire danger monitoring[J]. Geophysical Research Letters Banner, 2012,39(1):L01302.
Spessa A C, Field R D, Pappenberger F, et al. Seasonal forecasting of fire over Kalimantan, Indonesia[J]. Natural Hazards and Earth System Sciences, 2015,15(3):5079-5111.
Sholihah R I, Trisasongko B H, Shiddiq D, et al. Identification of agricultural drought extent based on vegetation health indices of Landsat data:Case of Subang and Karawang, Indonesia[J]. Procedia Environmental Sciences, 2016,33:14-20.
王士君,宋飏.中国东北地区城市地理基本框架[J].地理学报,2006,61(6):574-584.
Liu Dan, Yu Chenglong, Zhao Fang. Response of the water use efficiency of natural vegetation to drought in Northeast China[J]. Journal of Geographical Sciences, 2018,28(5):611-628.
Fusco E J, Abatzoglou J T, Balch J K, et al. Quantifying the human influence on fire ignition across the western USA[J]. Ecological Applications, 2016,26(8):2390-2401.
Pereira A A, Pereira J M C, Libonati R, et al. Burned area mapping in the Brazilian Savanna using a one-class support vector machine trained by active fires[J]. Remote Sensing, 2017,9(11):1161-1182.
Guindos-Rojas F, Arbelo M, García-Lázaro J R, et al. Evaluation of a bayesian algorithm to detect burned areas in the canary islands' dry woodlands and forests ecoregion using MODIS data[J]. Remote Sensing, 2018,10(5):789-810.
Giglioa L, Boschettib L, Roy D P, et al. The Collection6 MODIS burned area mapping algorithm and product[J]. Remote Sensing of Environment,2018,217:72-85.
Schrier V D G, Barichivich J, Briffa K R, et al. A scPDSI-based global data set of dry and wet spells for 1901-2009[J]. Journal of Geophysical Research:Atmospheres, 2013,118(10):4025-4048.