西南地区不同下垫面雷电活动特征与森林雷击火的关系

doi:10.12302/j.issn.1000-2006.202206039

国家林草科技领军期刊
中国精品科技期刊
中国高校百佳科技期刊
江苏省新闻出版政府奖期刊奖
RCCSE林学权威期刊（A+）
CSCD核心期刊
Scopus数据库收录期刊
中文核心期刊
SCD核心期刊

作者加群：102861116

微信公众号：南京林业大学学报

高级检索

南京林业大学学报（自然科学版） ›› 2024, Vol. 48 ›› Issue (3): 219-228.doi: 10.12302/j.issn.1000-2006.202206039

西南地区不同下垫面雷电活动特征与森林雷击火的关系

李岩松¹(), 杨艳蓉¹^,^*(), 张文艺¹, 张乐英¹, 黄傲¹, 张贻荣²

1.南京林业大学生态与环境学院, 南方现代林业协同创新中心,江苏南京 210037
2.武夷山国家公园管理局,福建南平 354300

收稿日期:2022-06-22 修回日期:2022-11-01 出版日期:2024-05-30 发布日期:2024-06-14
作者简介:李岩松(liyansonglyj1997@163.com)。
基金资助:
国家自然科学基金面上项目(31971670);福建省林业科技项目(2022FKJ28)

Relationship between characteristics of lightning activity on different underlying surface and forest lightning fire in southwest China

LI Yansong¹(), YANG Yanrong¹^,^*(), ZHANG Wenyi¹, ZHANG Leying¹, HUANG Ao¹, ZHANG Yirong²

1. College of Ecology and Environment, Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China
2. Wuyi Mountain National Park Administration, Nanping 354300,China

Received:2022-06-22 Revised:2022-11-01 Online:2024-05-30 Published:2024-06-14

1. 西南地区不同下垫面雷电活动特征与森林雷击火的关系.zip(13756KB)

摘要/Abstract

摘要：

【目的】西南地区是我国第二大天然林区,该地生态系统脆弱,森林雷击火灾频发。通过遥感、探测资料分析不同地表覆盖类型、不同海拔下垫面的雷电活动特征,探究雷电活动对森林雷击火的影响。【方法】根据2005—2017年全球闪电定位系统(WWLLN)闪电数据、MCD12Q1土地覆盖数据、SRTM(shuttle radar topography mission)海拔数据以及相应森林雷击火个例,结合Theil-Sen趋势分析、Mann-Kendall趋势检验、相对密度差分析,对我国西南地区雷电活动随下垫面类型、海拔的变化特征及其与森林雷击火的关系进行研究。【结果】 ① 2005—2017年西南地区云地闪频次以每年8.75%的速率增加。四川和云南交界的攀枝花附近区域是最高值核心区。② 海拔500~1 000 m、稀树草原类下垫面年均云地闪频次最多。以相对密度差表征雷电活跃程度,从季节上看,春季最活跃;从昼夜变化尺度上看,昼间最活跃。表现活跃的下垫面集中在海拔0~1 000 m段,以及农用地/自然植被拼接、稀树草原类和城区为主的地表类型。③ 云地闪在不同下垫面均呈增长趋势,其增长面积占比为西南地区的93.48%。其中,海拔3 500 m以上和草地类型下垫面的增长趋势最显著,从海拔和地表类型来看,显著的面积占比均超过80%。④ 年云地闪频次越高,发生森林雷击火的概率越大。海拔0~1 000 m森林雷击火发生与云地闪活动的下垫面特点一致,海拔1 000 m以上雷击火主要受高云地闪频次影响。【结论】西南地区雷电活动与下垫面的海拔、地表类型关系密切,且这一关系随不同时间尺度而变化。作为森林雷击火的起因,结合下垫面特征分析雷电活动,探究森林雷击火,可以为西南山地天然林保护提供科学支撑。

关键词: 森林雷击火, 云地闪, 海拔, 地表覆盖类型, 西南地区

Abstract:

【Objective】 Southwest China is the second largest natural forest region in China, where the ecosystem is fragile and forest lightning fire disasters occur frequently. According to the causal relationship between lightning and forest lightning fire, the characteristics of lightning activities on underlying surfaces with different land cover types and different altitudes, and the influence of lightning activity on forest lightning fire is explored. 【Method】 Based on WWLLN lightning data, land cover data MCD12Q1, altitude data SRTM and corresponding lightning forest fires from 2005 to 2017, combined with Theil-Sen trend analysis, Mann-Kendall trend test, relative density difference analysis. The variation characteristics of lightning activity with underlying surface type and altitude in southwest China and its relationship with forest lightning fire were studied.【Result】 (1) From 2005 to 2017, the cloud-to-ground lightning frequency in southwest China increased at a rate of 8.75% per year. The area near Panzhihua at the border of Sichuan and Yunnan maintains the core area of the highest value in years and seasons. (2) The annual cloud-to-ground lightning frequency was the highest in the underlying surface of savanna at an altitude of 500-1 000 m. The degree of lightning activity is characterized by the relative density difference. It is most active in spring and most active in daytime on a daily scale. The active surface types are concentrated in the 0-1 000 m elevation, Agricultural land/natural vegetation Mosaic, savanna type and urban type. (3) Cloud-to-ground lightning showed an increasing trend in different underlying surfaces, and its area accounted for 93.48% in southwest China. Among them, the growth trend of underlying surface of above 3 500 m altitude and grassland type is the most significant, and the significant area accounts for more than 80% from the elevation and surface type respectively. (4) The higher the annual cloud-to-ground lightning frequency, the greater the probability of lightning fire. The occurrence of forest lightning fire at 0-1 000 m altitude is consistent with the characteristics of the underlying surface of cloud-to-ground lightning distribution, and the lightning fire above 1 000 m altitude is mainly affected by high cloud-to-ground lightning frequency. 【Conclusion】 The lightning activity in southwest China is closely related to the underlying surface altitude and surface type, and the relationship varies with different time scales. As the cause of forest lightning fire, the analysis of lightning activity and forest lightning fire combined with the characteristics of underlying surface can provide scientific support for the protection of natural forest in southwest mountainous area.

Key words: lightning caused forest fire, cloud-to-ground lightning, altitude, land cover type, southwest China

中图分类号:

S762.1

李岩松,杨艳蓉,张文艺,等. 西南地区不同下垫面雷电活动特征与森林雷击火的关系[J]. 南京林业大学学报（自然科学版）, 2024, 48(3): 219-228.

LI Yansong, YANG Yanrong, ZHANG Wenyi, ZHANG Leying, HUANG Ao, ZHANG Yirong. Relationship between characteristics of lightning activity on different underlying surface and forest lightning fire in southwest China[J].Journal of Nanjing Forestry University (Natural Science Edition), 2024, 48(3): 219-228.DOI: 10.12302/j.issn.1000-2006.202206039.

图/表 10

图1

图2

图3

图4

表1

图5

表2

表3

图6

图7

参考文献 46

[1]	MAGNUSSON W E, LIMA L O D. Group lightning mortality of trees in a Neotropical forest[J]. J Trop Ecol, 1996, 12: 899-903. DOI: 10.1017/S0266467400010166.
[2]	PARLATO B P, GORA E M, YANOVIAK S P. Lightning damage facilitates beetle colonization of tropical tree[J]. Ann Entomol Soc Am, 2020, 6(3): 404-410. DOI: 10.1093/aesa/saaa015.
[3]	PRICE C, CRIND D. Possible implications of global climate change on global lightning distributionsand frequencie[J]. J Geophys Res-Atmos, 1994, 99(D5): 10823-10831. DOI: 10.1029/94JD00019.
[4]	SCHUMACHER V, SETZER A, SABA M M F, et al. Characte-ristics of lightning-caused wildfires in central Brazilirelation to cloud-ground and dry lightning[J]. Agr Forest Meteorol, 2022, 312: 108723. DOI: 10.1016/j.agrformet.2021.108723.
[5]	SIMON T, MAYR G J. Daily-resolved lightning climatology of the eastern alpine region at the kilometer scale[J]. Atmos Ocean Phy, 2022: 2201.07294. DOI: 10.1007/s00502-022-01032-1.
[6]	DISSING D, VERBYLA D L. Spatial patterns of lightning strikes in interior Alaska and their relations to elevation and vegetation[J]. Can J Forest Res, 2003, 33(5): 770-782. DOI:10.1139/x02-214.
[7]	赵生昊, 杨磊. 基于MODIS数据的地表覆盖种类与地闪分布特征关系研究[J]. 气象科技, 2016, 44(5): 822-827.
	ZHAO S H, YANG L. Relationship between land cover and cloud-to-ground lightning distribution based on MODIS data[J]. Meteorological Science and Technology, 2016, 44(5): 822-827. DOI: 10.19517/j.1671-6345.2016.05.022.
[8]	吴量, 郭媛, 向清才. 河池市闪电活动与下垫面植被类型关系分析[J]. 气象研究与应用, 2019, 40(1): 62-64.
	WU L, GUO Y, XIANG Q C. Analysis of the relationship between lightning activity and vegetation forms on underlying surface in Hechi[J]. Journal of Meteorological Research and Application, 2019, 40(1): 62-64.
[9]	卢友发, 吴世安. 河南省闪电活动与复杂下垫面之间的相关性分析[J]. 信阳师范学院学报(自然科学版), 2017, 30(1): 87-91.
	LU Y F, WU S A. Analysis about the correlation between lightning activity and the complex underlying surface in Henan Province[J]. Journal of Xinyang Normal University(Natural Science), 2017, 30(1): 87-91. DOI: 10.3969/j.issn.1003-0972.2017.01.019.
[10]	PETROV N I, WATERS R T. Lightning to earthed structures: striking distance variation with stroke polarity, structure geometry and altitude based on a theoretical approach[J]. J Electrostat, 2021, 112(6): 103599. DOI: 10.1016/j.elstat.2021.103599.
[11]	BOCCIPPIO D J, CUMMINS K L, CHRISTIAN H J, et al. Combined satellite and surface-based estimation of the intracloud/cloud-to-ground lightning ratio over the continental United States[J]. Mon Weather Rev, 2000, 129(1): 108-122. DOI: 10.1175/1520-0493(2001)129<0108:CSASBE>2.0.CO;2.
[12]	李政, 肖稳安, 李家启, 等. 区域海拔高度变化对闪电特征影响的初步分析[J]. 湖北大学学报(自然科学版), 2011, 33(2): 197-201.
	LI Z, XIAO W A, LI J Q, et al. The preliminary analysis of the influence of region’s elevation change onlightning characteristics[J]. Journal of Hubei University(Natural Science), 2011, 33(2): 197-201.
[13]	王凯, 周丽雅, 鞠晓雨, 等. 2011—2019年中国长江三角洲区域闪电时空分布特征[J]. 气象与环境学报, 2021, 37(4): 100-106.
	WANG K, ZHOU L Y, JU X Y, et al. Temporal and spatial distribution characteristics of lightning in the Yangtze River Delta of China from 2011 to 2019[J]. Journal of Meteorology and Environment, 2021, 37(4): 100-106. DOI: 10.3969/j.issn.1673-503X.2021.04.014.
[14]	ADHIKARI P B, ADHIKARI A, TIWARI A K. Effects of lightning as a disaster in Himalayan region[J]. Bibechana, 2021, 18(2): 117-129. DOI: 10.3126/bibechana.v18i2.29168.
[15]	RODRIGUES M, GELABERT P J, RESCO DE DIOS V, et al. High-resolution modeling of lightning ignition Likelihood in Spain[J]. Environ Sci Technol, 2022, 17(1): 40. DOI: 10.3390/environsciproc2022017040.
[16]	尹赛男, 王东昶, 单延龙, 等. 黑龙江省3种主要火源引发森林火灾的次数和面积时空分布特征[J]. 林业科学, 2021, 7(6): 115-124.
	YIN S N, WANG D C, SHAN Y L, et al. Spatial and temporal distribution of forest fires (frequency and area) caused by three main fire sources in Heilongjiang Province[J]. Scientia Silvae Sincae, 2021, 7(6): 115-124. DOI: 10.11707/j.1001-7488.20210613.
[17]	PINEDA N, RIGO T. The rainfall factor in lightning-ignited wildfires in Catalonia[J]. Agr Forest Meteorol, 2017, 239: 249-263. DOI: 10.1016/j.agrformet.2017.03.016.
[18]	BARANOVSKIY N. Deterministic-probabilistic approach to predict lightning-caused forest fires in mounting areas[J]. Forecasting, 2021, 3(4): 695-715. DOI: 10.3390/forecast3040043.
[19]	NADEEM K, TAYLOR S W, WOOLFORD D G, et al. Mesoscale spatiotemporal predictive models of daily human-and lightning-caused wildland fire occurrence in British Columbia[J]. Int J Wildland Fire, 2019, 29(1): 11-27. DOI: 10.1071/WF19058.
[20]	MARINA Y B, NIKOLAY V B, ANDREY V K, et al. Assessment of the uncertainty for the spatial distribution of lightning discharge density based on the smoothed bootstrap procedure and wwlln data: a case study[J]. International Journal on Engineering Applications, 2022. DOI: 10.15866/irea.v10i2.20850.
[21]	何诚, 舒立福, 刘柯珍. 大兴安岭地区夏季森林火灾环境因子特征分析[J]. 西南林业大学学报(自然科学), 2021, 41(3): 87-93.
	HE C, SHU L F, LIU K Z. Analysis on environmental factors’ characteristics of summer forest fire in Daxing’an Mountains[J]. Journal of Southwest Forestry University, 2021, 41(3): 87-93. DOI: 10.11929/j.swfu.202008039.
[22]	杨少斌, 曹萌, 祝鑫海, 等. 2001—2019年内蒙古大兴安岭北部原始林区森林火灾发生规律研究[J]. 灾害学, 2022, 37 (3): 122-128.
	YANG S B, CAO M, ZHU X H, et al. Research on occurrence law of forest fire in the northern primitive forest area of Greater Khingan range, Inner Mongolia from 2001 to 2019[J]. Journal of Catastrophology, 2022, 37(3): 122-128. DOI: 10.3969/j.issn.1000-811X.2022.03.020.
[23]	杜野. 内蒙古北部原始林区的雷击火分布规律研究[J]. 森林防火, 2017(4): 28-31.
	DU Y. Study on distribution law of lightning fire in primitive forest area in northern Inner Mongolia[J]. Forest Fire Prevention, 2017(4): 28-31.
[24]	靖娟利, 和彩霞, 王永锋, 等. 西南地区1902-2018年干旱时空演变特征分析[J]. 水土保持研究, 2022, 29(3): 220-227.
	JING J L, HE C X, WANGY F, et al. Spatiotemporal evolution characteristics of meteorological drought in southwest China from 1902 to 2018[J]. Research of Soil and Water Conservation, 2022, 29(3): 220-227. DOI: 10.13869/j.cnki.rswc.2022.03.007.
[25]	田晓瑞, 舒立福, 赵凤君, 等. 气候变化对中国森林火险的影响[J]. 林业科学, 2017, 53(3): 159-169.
	TIAN X R, SHU L F, ZHAO F J, et al. Impacts of climate change on forest fire danger in China[J]. Scientia Silvae Sincae, 2017, 53(3): 159-169. DOI: 10.11707/j.1001-7488.20170716.
[26]	刘晔, 李鹏, 许玥, 等. 中国西南干旱河谷植物群落的数量分类和排序分析[J]. 生物多样性, 2016, 24(4): 378-388.
	LIU Y, LI P, XU Y, et al. Quantitative classification and ordination for plant communities in dry valleys of Southwest China[J]. Biodiverdity Science, 2016, 24(4): 378-388. DOI: 10.17520/biods.2015241.
[27]	杨艳蓉, 侯召朕, 张增信. 2001—2018年西南地区NDVI变化特征及影响因素[J]. 水土保持通报, 2021, 41(2): 337-344.
	YANG Y R, HOU Z Z, ZHANG Z X. NDVI Changes and driving factors in southwest China from 2001 to 2018[J]. Bulletin of Soil and Water Conservation, 2021, 41(2): 337-344. DOI: 10.13961/j.cnki.stbctb.2021.02.044.
[28]	舒洋, 孙子瑜, 张恒. 世界森林雷击火研究现状和展望[J]. 世界林业研究, 2022, 35(2):34-40.
	SHU Y, SUN Z Y, ZHANG H. Research on lightning fire in forest: current status and outlook[J]. World Forestry Research, 2022, 35(2): 34-40. DOI: 10.13348/j.cnki.sjlyyj.2021.0070.y.
[29]	MORIS J V, CONEDERA M, NISI L, et al. Lightning-caused fires in the Alps: identifying the igniting strokes[J]. Agricultural and Forest Meteorology, 2020, 290(107990): 1-11. DOI: 10.1016/j.agrformet.2020.107990.
[30]	马金福, 冯志伟. 雷击地闪密度与雷暴日数的关系分析[J]. 气象科学, 2009, 29(5): 674-678.
	MA J F, FENG Z W. The analysis the relationship between density of ground lightning strokes and the number of thunderstorm days[J]. Scientia Meteorologica Sinica, 2009, 29(5): 674-678.
[31]	李洪广, 周旭, 肖杨, 等. 基于SRP模型的西南喀斯特山区生态脆弱性时空变化特征[J]. 生态科学, 2021, 40(3): 238-246.
	LI H G, ZHOU X, XIAO Y, et al. Temporal and spatial changes of ecological vulnerability in southwestern Karst mountains based on SRP model[J]. Ecological Science, 2021, 40(3): 238-246. DOI: 10.14108/j.cnki.1008-8873.2021.03.028.
[32]	杨宗凯, 刘平英, 胡颖, 等. 云南省雷电活动分布特征及对农村地区的影响分析[J]. 中国农业资源与区划, 2018, 39(9): 262-267.
	YANG Z K, LIU P Y, HU Y, et al. Analysis of distribution characteristic of lightning activity and its influence on rural areas in Yunnan[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2018, 39(9): 262-267. DOI: 10.7621/cjarrp.1005-9121.20180935.
[33]	杨水泉, 熊晓洪. 利用LIS/OTD格点资料分析西南地区闪电活动的气候分布特征[J]. 广西气象, 2006(S3): 60-66.
	YANG S Q, XIONG X H. Climate distribution characteristics of lightning activity in southwest China were analyzed using LIS/OTD grid data[J]. Journal of Guangxi Meteorology, 2006(S3): 60-66.
[34]	KARANINA S Y, KARANIN A V, KOCHEEVA N A, et al. The distribution of lightning discharges across the altitude of the territory in the Altai-Sayan region[J]. Journal of Physics: Conference Series, 2020, 1604(1): 12009.
[35]	王学良, 张科杰, 余田野, 等. 湖北地区云地闪电频次及雷电流幅值时间分布特征[J]. 电瓷避雷器, 2017(3): 1-9.
	WANG X L, ZHANG K J, YU T Y, et al. The time distribution characteristics on frequency and peak current of cloud-to-ground lightning in Hubei Province[J]. Insulators and Surge Arresters, 2017(3): 1-9. DOI: 10.16188/j.isa.1003-8337.2017.03.001.
[36]	GALANAKI E, LAGOUVARDOS K, KOTRONI V, et al. Thunderstorm climatology in the Mediterranean using cloud-to-ground lightning observations[J]. Atmospheric Research, 2018, 207(15): 136-144. DOI: 10.1016/j.atmosres.2018.03.004.
[37]	王义耕, 刘洁, 王介君, 等. 卫星观测的西南地区闪电的时空分布[J]. 大气科学学报, 2010, 33(4): 489-495.
	WANG Y G, LIU J, WANG J J, et al. Temporal and spatial distributions of lightning activity in southwest China based on satellite observations[J]. Transactions of Atmospheric Sciences, 2010, 33(4): 489-495. DOI: 10.13878/j.cnki.dqkxxb.2010.04.010.
[38]	成鹏伟, 周筠珺, 赵鹏国, 等. 北京与成都城市下垫面闪电时空分布特征对比研究[J]. 成都信息工程大学学报, 2018, 33(3): 326-334.
	CHENG P W, ZHOU Y J, ZHAO P G, et al. A comparative study on space-time distribution characteristics of lightning flashes in Beijing and Chengdu cities[J]. Journal of Chengdu University of Information Technology, 2018, 33(3): 326-334. DOI: 10.16836/j.cnki.jcuit.2018.03.016.
[39]	许洪泽, 周梅. ADTD异常对闪电定位资料影响分析[J]. 气象科技进展, 2018, 8(1): 33-37.
	XU H Z, ZHOU M. An analysis of the effect of ADTD abnormality on lightning location Data[J]. Advances in Meteorological Science and Technology, 2018, 8(1): 33-37. DOI: 10.3969/j.issn.2095-1973.2018.01.005.
[40]	邓雨荣, 李涵, 朱时阳, 等. 基于卫星资料的全球闪电定位系统探测效率评估[J]. 气象科学, 2015, 35(5): 599-604.
	DENG Y R, LI H, ZHU S Y, et al. Detection efficiency of the WWLLN based on OTD/LIS data[J]. Journal of the Meteorological Science, 2015, 35(5): 599-604. DOI: 10.3969/2014jms.0051.
[41]	KAPLAN J O, LAU K H K. The WGLC global gridded lightning climatology and time series[J]. Earth System Science Data, 2021, 13(7): 3219-3237.
[42]	LIAO W L, LIU X P, XU X Y, et al. Projections of land use changes under the plant functional type classificationin different SSP-RCP scenarios in China[J]. Science Bulletin, 2020, 65(22): 1935-1947. DOI: 10.1016/j.scib.2020.07.014.
[43]	ZHU Y, DENG X Q, NEWSAM S. Fine-grained land use classification at the city scale using ground-level images[J]. IEEE Transactions on Multimedia, 2018, 21(7): 1825-1838. DOI: 10.1109/TMM.2019.2891999.
[44]	岳超, 罗彩访, 舒立福, 等. 全球变化背景下野火研究进展[J]. 生态学报, 2020, 40(2): 385-401.
	YUE C, LUO C F, SHU L F, et al. A review on wildfire studies in the context of global change[J]. Acta Ecologica Sinica, 2020, 40(2): 385-401. DOI: 10.5846/stxb201812202762.
[45]	孙龙, 窦旭, 胡同欣. 林火对森林生态系统碳氮磷生态化学计量特征影响研究进展[J]. 南京林业大学学报(自然科学版), 2021, 45(2): 1-9.
	SUN L, DOU X, HU T. Research progress on the effects of forest fire on forest ecosystem C-N-P ecological stoichiometry characteristics[J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2021, 45(2): 1-9. DOI: 10.12302/j.issn.1000-2006.202003037.
[46]	张宏民, 乔艺骞, 唐珑坪, 等. 模拟雷击明火点燃松针燃料的实验研究[J]. 工程热物理学报, 2022, 43(3): 840-845.
	ZHANG H M, QIAO Y Q, TANG L P, et al. Experimental study on sustainable flaming lgnition of dead pine needles by simulated lightning discharge[J]. Journal of Engineering Thermophysics, 2022, 43(3): 840-845.

海拔/m altitude section	春 spring	夏 summer	秋 autumn	昼 day	夜 night
[0,200)	38.01^*	-37.97	-45.49	32.44^*	-35.69
[200,500)	10.64^*	39.14^*	-21.54	98.10^*	-24.72
[500,1 000)	43.05^*	12.99^*	-1.65	29.18^*	8.48^*
[1 000,3 500)	-22.34	-9.17	16.77^*	-25.05	4.37^*
≥3 500	-63.63	-34.23	-9.46	-81.78	-10.98

土地覆盖类型 land cover type	春 spring	夏 summer	秋 autumn	昼 day	夜 night
森林 forest	-4.57	-10.62	3.91^*	-10.84	-4.11
多树型稀树草原 multi-tree savanna	8.53^*	1.33^*	-6.14	4.83^*	0.31^*
稀树草原 savanna	27.05^*	20.93^*	15.67^*	27.18^*	16.57^*
草地 grass	-60.42	-36.83	-15.97	-77.76	-16.90
农用地 agricultural land	-5.49	2.38^*	12.24^*	-8.07	7.66^*
城市和建筑区 urban and built areas	10.41^*	39.15^*	-0.09	64.48^*	-2.99
水体 waters	-30.11	21.22^*	-6.05	-28.66	-2.55
农用地/自然植被拼接 agricultural land/natural vegetation mosaic	33.03^*	31.13^*	-6.73	85.57^*	-5.67

下垫面类型 underlying surface type		变化面积占比/% proportion of change area
下垫面类型 underlying surface type		显著增加 significant increase	不显著增加 insignificant increase	不显著减少 insignificant reduction
按海拔分类 classification by altitude	[0, 200)m	7.69	84.62	7.69
	[200, 500)m	8.38	65.24	26.38
	[500, 1 000)m	35.98	57.13	6.89
	[1 000, 3 500)m	44.63	51.72	3.61
	≥3 500 m	85.21^*	14.64	0.15
按土地类型分类 classification by land type	森林 forest	57.21^*	37.46	5.28
	多树型稀树草原 multi-tree savanna	42.21	52.03	5.76
	稀树草原 savanna	34.49	57.97	7.55
	草地 grass	80.61^*	18.62	0.77
	农用地 agricultural land	28.43	62.88	8.70
	城市和建筑区 urban and built areas	33.33	40.40	26.26
	水体 waters	60.00^*	30.00	10.00
	农用地/自然植被拼接 agricultural land/natural vegetation mosaic	8.92	1.96	19.12

西南地区不同下垫面雷电活动特征与森林雷击火的关系

Relationship between characteristics of lightning activity on different underlying surface and forest lightning fire in southwest China

RichHTML

PDF

详细数据

可视化

摘要/Abstract

引用本文

使用本文

图/表 10

参考文献 46

相关文章 15

编辑推荐

Metrics

本文评价

作者

读者

审稿

[1]	陆其伟, 脱云飞, 郑阳, 骆伟, 代勤龙, 何霞红. 栗子坪自然保护区不同海拔梯度土壤入渗特性研究[J]. 南京林业大学学报（自然科学版）, 2025, 49(2): 143-152.
[2]	高羽, 李静, 刘洋, 乌雅瀚, 巩家星, 辛启睿. 结构方程模型在兴安落叶松林生长中的应用[J]. 南京林业大学学报（自然科学版）, 2023, 47(1): 38-46.
[3]	邓小军, 唐健, 王会利, 宋贤冲, 曹继钊, 覃祚玉, 宋光桃. 猫儿山自然保护区沿海拔分布植被带土壤硝化-反硝化和呼吸作用分析[J]. 南京林业大学学报（自然科学版）, 2020, 44(1): 81-88.
[4]	陈禹衡, 吕一维, 殷晓洁. 气候变化下西南地区12种常见针叶树种适宜分布区预测[J]. 南京林业大学学报（自然科学版）, 2019, 43(6): 113-120.
[5]	张雨峰, 代丽, 谢寅峰, 马迎莉, 汤文华, 袁婷婷. 不同海拔金佛山方竹出笋及幼竹生长特性[J]. 南京林业大学学报（自然科学版）, 2019, 43(5): 199-203.
[6]	孟苗婧,张金池,郭晓平,吴家森,赵有朋,叶立新,刘胜龙. 海拔变化对黄山松阔叶混交林土壤有机碳组分的影响[J]. 南京林业大学学报（自然科学版）, 2018, 42(06): 106-112.
[7]	刘明慧,孙雪,于文杰,秦立武,冯富娟1. 长白山不同海拔原始红松林土壤活性有机碳含量的生长季动态[J]. 南京林业大学学报（自然科学版）, 2018, 42(02): 67-74.
[8]	孟苗婧,张金池,郭晓平,吴家森,赵有朋,叶立新,刘胜龙. 海拔对黄山松阔叶混交林土壤微生物功能多样性的影响[J]. 南京林业大学学报（自然科学版）, 2017, 41(04): 209-214.
[9]	谢静,朱万泽,周鹏,赵广. 贡嘎山木本植物碳同位素沿海拔梯度的变化[J]. 南京林业大学学报（自然科学版）, 2014, 38(06): 33-37.
[10]	李蒙，严邦祥，赵昌高，徐洪峰，李少欣，伊贤贵，王贤荣*. 大仰山高山湿地山樱花种群数量结构特征[J]. 南京林业大学学报（自然科学版）, 2013, 37(05): 40-44.
[11]	渠纪腾，阎毛毛，戴晓港，李淑娴*. 马尾松、黄山松及其杂种域球果形态和种子性状变异[J]. 南京林业大学学报（自然科学版）, 2012, 36(06): 143-146.
[12]	姜艳，王兵，汪玉如. 江西大岗山毛竹林土壤呼吸时空变异及模型模拟[J]. 南京林业大学学报（自然科学版）, 2010, 34(06): 47-52.
[13]	韩勇，徐宪根，阮宏华*，王邵军，汪家社，徐自坤. 武夷山黄山松凋落叶在不同植物群落中的分解动态[J]. 南京林业大学学报（自然科学版）, 2010, 34(03): 141-145.
[14]	周焱1，徐宪根1，阮宏华1*，汪家社2，方燕鸿2，吴焰玉2，徐自坤2. 武夷山不同海拔土壤水溶性有机碳的含量特征[J]. 南京林业大学学报（自然科学版）, 2009, 33(04): 48-52.
[15]	徐侠1,3，权伟1，汪家社2，方燕鸿2，阮宏华1*，叶镜中1. 武夷山不同海拔植被带土壤活性有机碳的季节变化[J]. 南京林业大学学报（自然科学版）, 2009, 33(03): 55-59.