[1] LIUJ, BOWMAN KW, SCHIMEL DS et al. Contrasting carbon cycle responses of the tropical continents to the 2015-2016 El Niño[J]. Science, 358, 5690(2017).
[2] GUOW, KOGANF. Strong 2015-2016 El Niño and implication to global ecosystems from space data[J]. International Journal of Remote Sensing, 38, 161-178(2017).
[3] BARBER RT, CHAVEZ FP. Biological consequences of El Niño[J]. Science, 222, 1203-1210(1983).
[4] TURNERJ, METELMANNS, CAMINADEC et al. Global risk model for vector-borne transmission of Zika virus reveals the role of El Nino 2015[C]. Proceedings of the National Academy of Sciences of the United States of America, 114, 119-124(2017).
[5] THIRUMALAIK, DINEZIO PN, OKUMURAY et al. Extreme temperatures in Southeast Asia caused by El Niño and worsened by global warming[J]. Nature Communications, 8, 15531(2017).
[6] WANG GW, LIM, 柴旭荣, 王贵文, 李明, CHAI XR et al. Research on meteorological drought in the middle and lower reaches of the Yangtze River[J]. Journal of Natural Resources, 34, 374-384(2019).
[7] 石培礼, 李文华, LI WH, SHI PL. Influence of forest cover change on hydrological process and watershed runoff[J]. Journal of Natural Resources, 16, 481-487(2001).
[8] 邵华, ZHU SH, 朱士华, SHAOH, YANY, 艳燕 et al. The responses of the net primary productivity of the dryland ecosystems in Central Asia to the CO2 and climate changes during the past 35 years[J]. Journal of Natural Resources, 32, 1844-1856(2017).
[9] WANG SP, WANG JS, LIU YP, 王素萍, 王劲松, 柳媛普 et al. Risk assessment of drought disaster in Southwest China under the background of climate warming[J]. Journal of Natural Resources, 33, 325-336(2018).
[10] MORTON DC, CHENY, ANDELAN et al. A pan-tropical cascade of fire driven by El Niño/Southern Oscillation[J]. Nature Climate Change, 7, 906-911(2017).
[11] ANDELAN, VAN DERWERF G R. Recent trends in African fires driven by cropland expansion and El Niño to La Niña transition[J]. Nature Climate Change, 4, 791-795(2014).
[12] FULLER DO, MURPHYK. The enso-fire dynamic in Insular Southeast Asia[J]. Climatic Change, 74, 435-455(2006).
[13] CHENY, MORTON DC, ANDELAN et al. A pan-tropical cascade of fire driven by El Niño/Southern Oscillation[J]. Nature Climate Change, 7, 906-911(2017).
[14] FANINT, FIELD RD, VAN DERWERF G R et al. Indonesian fire activity and smoke pollution in 2015 show persistent nonlinear sensitivity to El Niño-induced drought[J]. PNAS, 113, 9204(2016).
[15] PATRA PK, ICHIIK, KONDOM et al. Land use change and El Niño-Southern Oscillation drive decadal carbon balance shifts in Southeast Asia[J]. Nature Communications, 9, 1-7(2018).
[16] LEE B PY, DAVIES ZG, STRUEBIG MJ. Smoke pollution disrupted biodiversity during the 2015 El Nino fires in Southeast Asia[J]. Environmental Research Letters, 12, 1-7(2017).
[17] VAROTSOS CA, TZANIS CG, SARLIS NV. On the progress of the 2015-2016 El Niño event[J]. Atmospheric Chemistry and Physics, 16, 2007-2011(2016).
[18] COLLATZ GJ, VAN DERWERF G R, RANDERSON JT et al. Continental-scale partitioning of fire emissions during the 1997 to 2001 El Nino/La Nina period[J]. Science, 303, 73-76(2004).
[19] ZHANG HZ, OUYANG ZY, HUANG BR, 欧阳志云, 张慧智, 黄宝荣 et al. A graph-theoretic analysis of relationships among anthropogenic stressors on natural forest in Hainan Island[J]. Journal of Natural Resources, 24, 154-161(2009).
[20] SMITH SC, UBILAVAD. The El Niño Southern Oscillation and economic growth in the developing world[J]. Global Environmental Change, 151-164(2017).
[21] RANDERSON JT, VAN DERWERF G R, GIGLIOL et al. Global estimation of burned area using MODIS active fire observations[J]. Atmospheric Chemistry and Physics, 6, 957-974(2006).
[22] FENG ZM, LIP. Extent and area of swidden in montane mainland Southeast Asia: Estimation by Multi-Step Thresholds with Landsat-8 OLI data[J]. Remote Sensing, 8, 44(2016).
[23] FENG ZM, LIP, XIAOC et al. Detecting and mapping annual newly-burned plots (NBP) of swiddening using historical Landsat data in Montane Mainland Southeast Asia (MMSEA) during 1988-2016[J]. Journal of Geographical Sciences, 28, 1307-1328(2018).
[24] NOOJIPADYP, MORTON DC, SCHROEDERW et al. Managing fire risk during drought: The influence of certification and El Niño on fire-driven forest conversion for oil palm in Southeast Asia[J]. Earth System Dynamics, 8, 749-771(2017).
[25] GIGLIOL, OLIVAP, SCHROEDERW et al. The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment[J]. Remote Sensing of Environment, 143, 85-96(2014).
[26] OLIVAP, SCHROEDERW, GIGLIOL et al. Active fire detection using Landsat-8/OLI data[J]. Remote Sensing of Environment, 185, 210-220(2016).
[27] HEWSON JH, STOCKSB, KASISCHKE ES et al. The use of ATSR active fire counts for estimating relative patterns of biomass burning-a study from the boreal forest region[J]. Geophysical Research Letters, 30, 1-4(2003).
[28] SCHROEDERW, OLIVAP. Assessment of VIIRS 375 m active fire detection product for direct burned area mapping[J]. Remote Sensing of Environment, 160, 144-155(2015).
[29] PALMER PI. The role of satellite observations in understanding the impact of El Niño on the carbon cycle: Current capabilities and future opportunities. Philosophical transactions of the Royal Society of London[J]. Series B, Biological sciences, 373, 1-12(2018).
[30] REICHEJ, VERHOEVENR, VERBESSELTJ et al. Characterizing tropical forest cover loss using Dense Sentinel-1 data and active fire alerts[J]. Remote Sensing, 10, 777(2018).
[31] RANDERSON JT, VAN DERWERF G R, GIGLIOL et al. Global fire emissions estimates during 1997-2016[J]. Earth System Science Data, 9, 697-720(2017).
[32] MORTON DC, LOUISG, ANDELAN et al. The Global Fire Atlas of individual fire size, duration, speed, and direction[J]. Earth Syst Dynam, 11, 529-552(2019).
[33] 封志明, 李鹏, LI WJ, FENG ZM, LIP, 李文君 et al. Spatiotemporal dynamics of active fire frequency in Southeast Asia with the FIRMS Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer (VIIRS) data[J]. Resources Science, 41, 1526-1540(2019).
[34] LIP, LIANG YH, 李鹏, 刘佳, 梁一行, LIUJ et al. Occurrence characteristics and response to El Niño of MODIS-based active fires in Indonesia during 2001-2018[J]. Acta Geographica Sinica, 75, 1907-1920(2020).
[35] LIP, FENG ZM, XIAO CW et al. Occurrence frequencies and regional variations in VIIRS global active fires[J]. Global Change Biology, 26, 2970-2987(2020).
[36] XIAO CW, 刘怡媛, 肖池伟, LIU YY, LIP, 李鹏 et al. Characteristics analyses of major physical geographic elements of Visible Infrared Imaging Radiometer (VIIRS) active fire in Laos[J]. Geographical Research, 39, 749-760(2020).
