Temporal and spatial dynamic characteristics of forest fire in Zhejiang Province of eastern China based on MODIS satellite hot spot data

Zeng Aicong; Guo Xinbin; Zheng Wenxia; Wei Mao; Jin Quanfeng; Guo Futao

doi:10.12171/j.1000-1522.20190483

Journal of Beijing Forestry University > 2020 > 42(11): 39-46. > DOI: 10.12171/j.1000-1522.20190483

Zeng Aicong, Guo Xinbin, Zheng Wenxia, Wei Mao, Jin Quanfeng, Guo Futao. Temporal and spatial dynamic characteristics of forest fire in Zhejiang Province of eastern China based on MODIS satellite hot spot data[J]. Journal of Beijing Forestry University, 2020, 42(11): 39-46. DOI: 10.12171/j.1000-1522.20190483

Citation:

PDF (1355 KB)

Temporal and spatial dynamic characteristics of forest fire in Zhejiang Province of eastern China based on MODIS satellite hot spot data

College of Forestry, Fujian Agriculture and Forestry University, Collaborative Innovation Center of Soil and Water Conservation in Red Soil Region of the Cross-Strait, Fuzhou 350002, Fujian, China

More Information

Received Date: December 30, 2019
Revised Date: February 27, 2020
Available Online: November 06, 2020
Published Date: December 13, 2020

Graphical Abstract

Abstract

Abstract

Objective Studying the spatial and temporal dynamics of forest fire is beneficial for understanding the trend of forest fire, and can provide a scientific basis for the division of fire risks and the rational allocation of fire management resources.
Method Based on MODIS satellite fire point data, the statistics method, Mann-Kendall trend test and sliding t-test were applied to study the characteristics of spatial and temporal distribution of forest fire, the change of fire trend and fire season in Zhejiang Province from 2001 to 2016.
Result (1) On the whole, the forest fire in Zhejiang Province increased during 2001−2016. The forest fire mainly occurred in spring, summer and winter. The number of forest fire in spring and summer had a significant growth; however, the forest fire in autumn and winter increased first and then decreased. The number of forest fire occurred during the traditional fire season was getting fewer, and more forest fire occurred in the summer compared with the past. The traditional fire season (November to the coming April) had changed to January 19 th−September 1st. (2) The forest fire declined spatially from southwestern to northeastern Zhejiang, and Hangzhou, Quzhou, Lishui and Wenzhou were fire prone areas and the fire numbers increased during the fire prevention period, spring and summer.
Conclusion Our findings suggest that the publicity and education of fire prevention should be enhanced in the southwestern Zhejing Province and in the spring and summer, and properly adjusting the definition of fire season and allocation of fire management resources will help curb the growth trend of forest fire in Zhejiang Province.
- forest fire,
- temporal and spatial distribution,
- change trend,
- fire prevention period

FullText(HTML)

References (33)

References

[1]	周生瑞, 何诚, 陈锋, 等. 我国森林火灾危害性评价分析[J]. 森林防火, 2018(2):33−36. doi: 10.3969/j.issn.1002-2511.2018.02.011. Zhou S R, He C, Chen F, et al. Analysis on the hazard assessment of forest fires in China[J]. Forest Fire Prevention, 2018(2): 33−36. doi: 10.3969/j.issn.1002-2511.2018.02.011.
[2]	Clark J S. Effect of climate change on fire regimes in northwestern Minnesota[J]. Nature, 1988, 334: 233−235. doi: 10.1038/334233a0.
[3]	Parisien M, Parks S, Miller C. Contributions of ignitions, fuels, and weather to the spatial patterns of burn probability of a boreal landscape[J]. Ecosystems, 2011, 14(7): 1141−1155. doi: 10.1007/s10021-011-9474-2.
[4]	Jordan G, Fortin M, Lertzman K. Spatial pattern and persistence of historical fire boundaries in southern interior British Columbia[J]. Environmental and Ecological Statistics, 2008, 15(4): 523−535. doi: 10.1007/s10651-007-0063-7.
[5]	Levin N, Heimowitz A. Mapping spatial and temporal patterns of Mediterranean wildfires from MODIS[J]. Remote Sensing of Environment, 2012, 126: 12−26. doi: 10.1016/j.rse.2012.08.003.
[6]	田晓瑞, 舒立福, 王明玉, 等. 西藏森林火灾时空分布规律研究[J]. 火灾科学, 2007, 16(1):10−14. doi: 10.3969/j.issn.1004-5309.2007.01.002. Tian X R, Su L F, Wang M Y, et al. Temporal and spatial distribution of forest fires in Tibet[J]. Fire Safety Science, 2007, 16(1): 10−14. doi: 10.3969/j.issn.1004-5309.2007.01.002.
[7]	张冬有, 邓欧, 李亦秋, 等. 黑龙江省1980—2005年森林火灾时空特征[J]. 林业科学, 2012, 48(2):175−179. doi: 10.11707/j.1001-7488.20120227. Zhang D Y, Deng O, Li Y Q, et al. Temporal and spatial characteristics of forest fires in Heilongjiang Province between 1980 and 2005[J]. Scientla Silvae Sinicae, 2012, 48(2): 175−179. doi: 10.11707/j.1001-7488.20120227.
[8]	萨如拉, 周庆, 刘鑫晔, 等. 1980—2015年内蒙古森林火灾的时空动态[J]. 南京林业大学学报(自然科学版), 2019, 43(2):137−143. Sa R L, Zhou Q, Liu X Y, et al. Studies on the spatial and temporal dynamics of forest fires in Inner Mongolia from 1980 to 2015[J]. Journal of Nanjing Forestry University (Natural Sciences Edition), 2019, 43(2): 137−143.
[9]	黄宝华, 张华, 孙治军, 等. 基于GIS与RS的山东森林火险因子及火险区划[J]. 生态学杂志, 2015, 34(5):1464−1472. Huang B H, Zhang H, Sun Z J, et al. Forest fire danger factors and their division in Shandong based on GIS and RS[J]. Chinese Journal of Ecology, 2015, 34(5): 1464−1472.
[10]	Guo F T, Zhang L J, Jin S, et al. Modeling anthropogenic fire occurrence in the boreal forest of China using logistic regression and random forests[J]. Forests, 2016, 7(250): 1−14.
[11]	沈姣姣, 宋鸿, 曹慧萍, 等. 陕西省林火特征及与关键气候因子的关系[J]. 灾害学, 2016, 31(2):99−105. doi: 10.3969/j.issn.1000-811X.2016.02.020. Shen J J, Song H, Cao H P, et al. Characteristic of forest fires and the relationship between forest fires and key climate factors in Shanxi Province[J]. Journal of Catastrophology, 2016, 31(2): 99−105. doi: 10.3969/j.issn.1000-811X.2016.02.020.
[12]	马楠楠, 张彦雷, 李建, 等. 黑龙江呼玛县森林火灾时空分布特征[J]. 东北林业大学学报, 2016, 44(5):20−23, 56. doi: 10.3969/j.issn.1000-5382.2016.05.005. Ma N N, Zhang Y L, Li J, et al. Spatial and temporal distribution characteristics of forest fire in Huma County of Heilongjiang Province[J]. Journal of Northeast Forestry University, 2016, 44(5): 20−23, 56. doi: 10.3969/j.issn.1000-5382.2016.05.005.
[13]	郑琼, 邸雪颖, 金森. 伊春地区1980—2010年森林火灾时空格局及影响因子[J]. 林业科学, 2013, 49(4):157−163. doi: 10.11707/j.1001-7488.20130424 Zheng Q, Di X Y, Jin S. Temporal and spatial patterns of forest fires in Yichun Area during 1980−2010 and the influence of meteorological factors[J]. Scientla Silvae Sinicae, 2013, 49(4): 157−163. doi: 10.11707/j.1001-7488.20130424
[14]	石晶晶. 浙江省林火发生格局及预测模型研究[D]. 杭州: 浙江农林大学, 2014. Shi J J. Study on occurring space and forecasting model of forest fores in Zhejing Province[D]. Hangzhou: Zhejiang A&F University, 2014.
[15]	田野, 牛树奎, 陈锋, 等. 丽江地区森林火灾的时空分布规律[J]. 西北林学院学报, 2018, 33(5):142−148. doi: 10.3969/j.issn.1001-7461.2018.05.22 Tian Y, Niu S K, Chen F, et al. Temporal and spatial distribution of forest fire in Lijiang Area[J]. Journal of Northwest Forestry University, 2018, 33(5): 142−148. doi: 10.3969/j.issn.1001-7461.2018.05.22
[16]	浙江省林业局. 2018年浙江省森林资源及其生态功能价值公告[EB/OL]. (2019−03−06)[2019−07−06]. http://www.zjly.gov.cn/art/2019/3/6/art_1275964_30743029.html. Zhejiang Province Forestry Bureau. Announcement on the value of forest resources and ecological functions in Zhejiang Province in 2018[EB/OL]. (2019−03−06) [2019−07−06]. http://www.zjly.gov.cn/art/2019/3/6/art_1275964_30743029.html.
[17]	张文楚. 浙江省森林火灾成因分析及其预防对策研究[J]. 浙江农业科学, 2009, 1(4):845−848. doi: 10.3969/j.issn.0528-9017.2009.04.082. Zhang W C. Analysis on the causes of forest fires in Zhejiang Province and its preventive countermeasures[J]. Journal of Zhejiang Agricultural Sciences, 2009, 1(4): 845−848. doi: 10.3969/j.issn.0528-9017.2009.04.082.
[18]	国家林业和草原局. 中国林业统计年鉴[M]. 北京: 中国林业出版社, 2017. National Forestry and Grassland Bureau. China forestry statistical yearbook[M]. Beijing: China Forestry Publishing House, 2017.
[19]	Guo F T, Wang G Y, Su Z W, et al. What drives forest fire in Fujian, China? Evidence from logistic regression and random forests[J]. International Journal of Wildland Fire, 2016, 25(5): 505−519.
[20]	Costafreda A S, Vega G C, Comas C. Improving fire season definition by optimized temporal modelling of daily human-caused ignitions[J]. Journal of Environmental Management, 2018, 217: 90−99.
[21]	张燕, 隋传国, 张瑞瑾, 等. 基于Mann-Kendall法的中国海洋环境质量变化趋势分析[J]. 环境污染与防治, 2019, 41(2):201−205. Zhang Y, Sui C G, Zhang R J, et al. Trend analysis of marine environmental quality in China based on Mann-Kendall method[J]. Environmental Pollution & Control, 2019, 41(2): 201−205.
[22]	田晓瑞, 赵凤君, 舒立福, 等. 1961—2010年中国植被区的气候与林火动态变化[J]. 应用生态学报, 2014, 25(1):53−55. Tian X R, Zhao F J, Su L F, et al. Changes of climate and fire dynamic in China vegetation zone during 1961−2010[J]. Chinese Journal of Applied Ecolog, 2014, 25(1): 53−55.
[23]	张珊, 杨树文, 王恒亮. 顾及黄土滑坡的兰州市不同等级降雨时空变化特征[J]. 水土保持研究, 2019, 26(1):184−191. Zhang S, Yang S W, Wang H L. Spatiotemportal variation of rainfall for different categories in Lanzhou during 1965−2015 considering loess land slide[J]. Research of Soil and Water Conservation, 2019, 26(1): 184−191.
[24]	赵嘉阳, 郭福涛, 梁慧玲, 等. 福建长汀红壤区1965—2013年气温和降水量的变化趋势[J]. 福建农林大学学报(自然科学版), 2016, 45(1):77−83. Zhao J Y, Guo F T, Liang H L, et al. Changes in temperature and precipitation in Changting, Fujian Province during 1965−2013[J]. Journal of Fujian Agriculture and Forestry University (Natural Science Edition), 2016, 45(1): 77−83.
[25]	关山, 单延龙, 孙靖松, 等. 吉林省森林防火期的时空变化[J]. 森林防火, 2015(1):36−40. doi: 10.3969/j.issn.1002-2511.2015.01.012. Guan S, Shan Y L, Sun J S, et al. Temporal and spatial variation of forest fire prevention period in Jilin Province[J]. Forest Fire Prevention, 2015(1): 36−40. doi: 10.3969/j.issn.1002-2511.2015.01.012.
[26]	高颍仪, 杨美和. 吉林省春秋森林防火期划分的研究[J]. 吉林林学院学报, 1987(3):54−58. Gao Y Y, Yang M H. Study on fire prevention division of spring and autumn forest in Jilin Province[J]. Journal of Jilin Forestry University, 1987(3): 54−58.
[27]	田晓瑞, 舒立福, 王明玉, 等. 林火与气候变化研究进展[J]. 世界林业研究, 2006, 19(5):38−42. doi: 10.3969/j.issn.1001-4241.2006.05.007. Tian X R, Shu L F, Wang M Y, et al. Review on the researches of forest fire and climate change[J]. World Forestry Research, 2006, 19(5): 38−42. doi: 10.3969/j.issn.1001-4241.2006.05.007.
[28]	金芃霏, 刘剑刚. 基于EOF的浙江省降水变化时空分析研究[J]. 环境科学与管理, 2015, 40(7):40−45. doi: 10.3969/j.issn.1673-1212.2015.07.011. Jin P F, Liu J G. Analysis on temporal and spatial precipitation changes based on EOF in Zhejiang Province[J]. Environmental Science and Management, 2015, 40(7): 40−45. doi: 10.3969/j.issn.1673-1212.2015.07.011.
[29]	张青. 浙江省近百年气温变化研究[D]. 兰州: 兰州大学, 2015. Zhang Q. Studies on the temperature change in the last 100 years over Zhejiang Province[D]. Lanzhou: Lanzhou University, 2015.
[30]	孙科, 娄伟平, 刘昌杰. 1961—2017年浙江省夏季高温热浪时空变化特征[J]. 科技通报, 2019, 35(7):53−58. Sun K, Lou W P, Liu C J. Temporal-spatial change characteristics of summer heatwaaves in Zhejiang Province during 1961−2017[J]. Bulletin of Science and Technology, 2019, 35(7): 53−58.
[31]	赵凤君, 舒立福. 气候异常对森林火灾发生的影响研究[J]. 森林防火, 2007(1):21−23. doi: 10.3969/j.issn.1002-2511.2007.01.009. Zhao F J, Shu L F. Impact of climate anomalies on forest fires[J]. Forest Fire Prevention, 2007(1): 21−23. doi: 10.3969/j.issn.1002-2511.2007.01.009.
[32]	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(7):159−169. doi: 10.11707/j.1001-7488.20170716. Tian X R, Shu L F, Zhao F J, et al. Impacts of climate change on forest fire danger in China[J]. Scientia Silvae Sinicae, 2017, 53(7): 159−169. doi: 10.11707/j.1001-7488.20170716.
[33]	曾爱聪, 蔡奇均, 苏漳文, 等. 基于MODIS卫星火点的浙江省林火季节变化及驱动因子[J]. 应用生态学报, 2020, 31(2):399−406. Zeng A C, Cai Q J, Su Z W, et al. Seasonal variation and driving factors of forest fire in Zhejiang Province based on MODIS satellite hot spots[J]. Chinese Journal of Applied Ecolog, 2020, 31(2): 399−406.

[1]	Mei Xuesong, Dong Lingbo, Chen Guanmou. Driving factors of carbon sink in natural Larix gmelinii forests based on structural equation models[J]. Journal of Beijing Forestry University, 2024, 46(9): 1-10. DOI: 10.12171/j.1000-1522.20230284
[2]	Wu Yan, Li Xinyu, Zhang Yiting, Ding Bo, Zhang Yunlin, Fu Yuhong, Liu Xun. Litter carbon, nitrogen, and phosphorus stoichiometric characteristics and their influencing factors of Pinus massoniana plantation with different age groups in karst region of southwestern China[J]. Journal of Beijing Forestry University, 2024, 46(2): 87-94. DOI: 10.12171/j.1000-1522.20220052
[3]	Xu Chao, Long Ting, Wu Xinlei, Chen Jie, Liang Yanjun, Li Jingwen. Reintroducing effects and influencing factors of Taxus cuspidata population[J]. Journal of Beijing Forestry University, 2020, 42(8): 34-42. DOI: 10.12171/j.1000-1522.20190423
[4]	Gao Yan, Zhang Yuqing, Qin Shugao, Zhang Jutao, Liu Zhen. Landscape pattern change and its influencing factors of sand-binding vegetation[J]. Journal of Beijing Forestry University, 2020, 42(4): 102-112. DOI: 10.12171/j.1000-1522.20190061
[5]	He Xiao, Cao Lei, Xu Shenglin, Li Haikui. Forest biomass characteristics and influencing factors in different restoration stages in the Daxing’anling forest region of Inner Mongolia, northern China[J]. Journal of Beijing Forestry University, 2019, 41(9): 50-58. DOI: 10.13332/j.1000-1522.20190030
[6]	ZHOU Wen-jun, SHA Li-qing, ZHANG Yi-ping, SONG Qing-hai, LIU Yun-tong, DENG Yun, DENG Xiao-bao. Characteristics and influencing factors of soil dissolved organic carbon and nitrogen in a tropical seasonal rainforest in Xishuangbanna,Southwest China.[J]. Journal of Beijing Forestry University, 2016, 38(9): 34-41. DOI: 10.13332/j.1000-1522.20150238
[7]	LI Ning, CHEN Li-hua, YANG Yuan-jun.. Factors influencing root tensile properties of Pinus tabuliformis and Larix principis-rupprechtii.[J]. Journal of Beijing Forestry University, 2015, 37(12): 77-84. DOI: 10.13332/j.1000-1522.20150131
[8]	CHEN Chong, LI Ji-yue, , WANG Yu- tao. Variation of stem sap flow of Salix matsudana and its impact factors.[J]. Journal of Beijing Forestry University, 2008, 30(4): 82-88.
[9]	GUO Hong-wu, WANG Jin-lin, LI Chun-sheng, YAN Hao-Peng. Light-induced discoloration and influencing factors of dyed veneer after painted.[J]. Journal of Beijing Forestry University, 2008, 30(4): 22-27.
[10]	JIAO Wen-jun, ZHU Qing-ke, ZHANG Yu-qing, WU Xiu-qin, WANG Na. Distribution of biotic crusts and its influencing factors in the grain-for-green land of the loess region, northern Shaanxi Province[J]. Journal of Beijing Forestry University, 2007, 29(1): 102-107. DOI: 10.13332/j.1000-1522.2007.01.018

Cited By

Cited by

Periodical cited type(34)

1.	孙丽，张颖，李文彬，包红光，孙迎坤. 青岛市3种常绿灌木滞尘量与叶微观特征及光合作用等的相关性分析. 西北林学院学报. 2024(04): 232-241 .
2.	裴云霞，洪慧，包美玲，邓俊，陈岷轩，张强. 农业环境损害鉴定中受体植物的损害因素判别及损害程度分析. 中国司法鉴定. 2024(04): 40-48 .
3.	贺丹，李朝梅，华超，李思洁，雷雅凯，张曼. 郑州市10种园林植物叶片滞尘与富集重金属的能力. 西北林学院学报. 2023(01): 230-237 .
4.	张碧媛，李智琦，阮琳，潘勇军，陈国财，代色平，冯娴慧. 2种常用的植物滞纳能力测定方法对比研究. 林业与环境科学. 2023(01): 112-119 .
5.	罗建平，王宁，宋菲菲，魏汉博，原白玉，唐钰鑫. 大庆市6种绿化树种对SO_2、NO_2的消减及滞尘效应. 生态学报. 2023(11): 4561-4569 .
6.	张翠，马瑞，谭立佳，杜婉倩，刘涵科. 兰州市10种常用园林绿化树种叶表面微结构对其滞尘量的影响. 甘肃农业大学学报. 2023(04): 192-200+211 .
7.	廖慧敏，师凤起，李明，朱逸龙. 长沙市典型园林植物叶片的滞尘等级与模式识别研究. 生态环境学报. 2022(01): 110-116 .
8.	贺丹，汪安印，李紫萱，王翼飞，李朝梅，雷雅凯，李永华，董娜琳. 郑州市常绿树种滞尘能力与叶片生理结构的响应. 福建农业学报. 2022(02): 203-212 .
9.	李晓璐，叶锦东，章剑，周毅烈，袁楚阳，于慧，张天然，黄芳，张贵豪，邵锋. 乔木滞留大气颗粒物能力及其与叶表面微结构关系. 中国城市林业. 2022(03): 22-28+120 .
10.	王军梦，汪安印，王翼飞，贺丹，李永华，董娜琳. 不同污染程度下树种滞尘能力与叶表微形态关系研究. 林业调查规划. 2022(05): 16-21+37 .
11.	孟畅，彭洋，赵杨，王秀荣，肖枫. 2种叶型膏桐幼苗的形态结构和光合特性. 林业科学. 2022(12): 32-41 .
12.	岳晨，李广德，席本野，曹治国. 叶片大气颗粒物滞纳能力评估方法的定量对比. 环境科学. 2021(01): 114-126 .
13.	徐立人，刘宠，张军，柳俊明，王立成，李清泉，杨敏生，李彦慧. 单叶刺槐半同胞子代叶片的滞尘能力及叶表SEM特征分析. 西部林业科学. 2021(01): 124-131 .
14.	杨克彤，陈国鹏，李广，汤东，张凯. 兰州市常见阔叶树种对大气颗粒物吸滞能力的评估. 东北林业大学学报. 2021(05): 84-89 .
15.	刘宇，张楠，王晓立，周力行，韩浩章. 冬季苏北8种常绿乔木吸滞颗粒物能力与叶表微结构关系. 西北林学院学报. 2021(03): 80-87+127 .
16.	王薇，张蕾. 基于CiteSpace的城市环境中细颗粒物研究进展的可视化分析. 生态环境学报. 2021(06): 1321-1332 .
17.	谢长坤，郭健康，梁安泽，汪静，姜睿原，车生泉. 园林植物表面对大气颗粒物削减过程研究进展. 世界林业研究. 2021(05): 38-43 .
18.	吴桂香，徐成林，刘杰，杨燕飞. 城市道路植物叶面滞尘的微观效应研究. 昆明理工大学学报(自然科学版). 2021(06): 109-115 .
19.	陈胜楠，陈左司南，张志强. 北京山区油松和元宝槭冠层气孔导度特征及其环境响应. 植物生态学报. 2021(12): 1329-1340 .
20.	王琴，冯晶红，黄奕，王鹏程，谢梦婷，万好，苏泽琳，王仁鹏，王征洋，余刘思. 武汉市15种阔叶乔木滞尘能力与叶表微形态特征. 生态学报. 2020(01): 213-222 .
21.	童凌云，何婉璎，裘璐函，陈健，刘美华. 基于层次分析法的杭州市8种园林植物林分环境质量评价. 浙江林业科技. 2020(01): 56-62 .
22.	苏维，刘苑秋，赖胜男，古新仁，刘青，龚鹏. 南昌市8种乔木叶片性状对叶表滞留颗粒物的影响. 西北林学院学报. 2020(04): 61-67 .
23.	刘开琳，李学敏，万翔，刘淑娟，李菁菁，徐先英，刘虎俊. 民勤植物园3种灌木的叶面微结构及其滞尘能力研究. 中国农学通报. 2020(26): 62-68 .
24.	孙应都，陈奇伯，李艳梅，杨思莹. 昆明市6个绿化树种叶表微结构与滞尘能力的关系研究. 西南林业大学学报(自然科学). 2019(03): 78-85 .
25.	张俊叶，邹明，刘晓东，王林，朱晨晨，俞元春. 南京城市森林植物叶面颗粒物的含量特征. 环境污染与防治. 2019(07): 837-843 .
26.	林星宇，李海梅，李彦华，姜月梅. 八种乔木滞尘效益及其与叶表面特征关系. 北方园艺. 2019(17): 94-101 .
27.	林星宇，李海梅，李彦华，刘志科. 灌木滞尘能力与重金属含量间的关系. 江苏农业科学. 2019(15): 180-183 .
28.	姜霞，侯贻菊，刘延惠，舒德远，崔迎春，李成龙，杨冰，丁访军. 3种木樨科树种叶片滞尘效应动态变化及其与叶片特征的关系. 江苏农业科学. 2019(16): 150-154 .
29.	林星宇，李彦华，李海梅，李士美. 乔木对不同粒径颗粒物吸滞作用研究. 福建农业学报. 2019(08): 912-919 .
30.	阿丽亚·拜都热拉，甄敬，潘存德，张中远，胡梦玲，喀哈尔·扎依木. 乌鲁木齐市河滩快速路林带内颗粒物浓度变化特征. 新疆农业大学学报. 2019(05): 378-384 .
31.	林星宇，李海梅，李彦华，郑茗月. 5种灌木的滞尘效益研究. 现代农业科技. 2018(02): 150-151+155 .
32.	赵文君，侯贻菊，舒德远，刘延惠，崔迎春，丁访军. 贵阳市木兰科树种叶片滞尘效应及影响因素. 贵州林业科技. 2018(02): 19-24 .
33.	李艳梅，陈奇伯，王邵军，孙应都，杨淏舟，杨思莹. 昆明市主要绿化树种叶片滞尘能力的叶表微形态学解释. 林业科学. 2018(05): 18-29 .
34.	朱济友，于强，刘亚培，覃国铭，李金航，徐程扬，何韦均. 植物功能性状及其叶经济谱对城市热环境的响应. 北京林业大学学报. 2018(09): 72-81 . 本站查看

Other cited types(26)

Get Citation

PDF

XML

Article views (2304) PDF downloads (168) Cited by(60)

Turn off MathJax

Article Contents

Abstract

References

Temporal and spatial dynamic characteristics of forest fire in Zhejiang Province of eastern China based on MODIS satellite hot spot data