贵州省2011~2023年山火时空分布及气象条件影响分析
Spatiotemporal Distribution and Meteorological Influence Analysis of Forest Fires in Guizhou Province from 2011 to 2023
DOI: 10.12677/ccrl.2024.135129, PDF,    科研立项经费支持
作者: 王 瑶, 向 楠:贵州省山地气象科学研究所,贵州 贵阳;罗雪纯*:昆明市气象局,云南 昆明;皮义均:贵州省丹寨县气象局,贵州 丹寨;王健颖:贵州省气象台,贵州 贵阳
关键词: 贵州MODIS山火气象要素时空分布Guizhou MODIS Forest Fire Meteorological Elements Spatiotemporal Distribution
摘要: 基于MODIS火点资料和区域站气象数据对2011~2023年贵州省山火特征分析及气象因子的影响分析。结果表明:在2011年至2023年期间,MODIS监测到的贵州山火总数为20,866个,其中,山火数量在2013年、2014年、2015年和2023年均超过2000个,尤其是2023年达到2542个,为最高点。从空间分布来看,主要集中在黔西南、黔南和安顺市,火点数量分别为4982个、4399个和2572个。贵州省山火在春季高发,特别是2月、3月和4月,占比达61%,与春季气候干燥、风力大、农业和林业活动密切相关。夏季和秋季山火数量较少,冬季有所回升。山火数量在不同地区、不同月份之间表现出显著的差异,贵阳、遵义、铜仁在2、3、8月时易发生山火,六盘水、安顺、黔东南、黔南、黔西南在2、3、4月时易发生山火,而毕节在1、2、3月易发生山火。黔西南、六盘水及安顺市区域相较于其他地区,呈现出更高的火点温度与更低的相对湿度特征,火点温度主要集中在15℃至22℃的范围内,55%至75%的相对湿度区间为火点分布的高峰范围。
Abstract: Analysis of Forest Fire Characteristics and Meteorological Factors in Guizhou Province from 2011 to 2023 Based on MODIS Fire Data and Regional Meteorological Data. The results show that from 2011 to 2023, a total of 20,866 forest fires were detected by MODIS in Guizhou. Notably, the number of fires exceeded 2000 in 2013, 2014, 2015, and 2023, with the highest count of 2542 occurring in 2023. Spatially, the fires were primarily concentrated in the prefectures of Qianxinan, Qiannan, and Anshun, with 4982, 4399, and 2572 fires, respectively. Forest fires in Guizhou were most frequent in spring, particularly in February, March, and April, accounting for 61% of the total. This high incidence is closely related to the dry climate, strong winds, and intensive agricultural and forestry activities during spring. In contrast, the number of fires in summer and autumn was lower, with a slight increase in winter. The distribution of forest fires varied significantly across different regions and months. Fires were more likely to occur in Guiyang, Zunyi, and Tongren in February, March, and August; in Liupanshui, Anshun, Qiandongnan, Qiannan, and Qianxinan in February, March, and April; and in Bijie in January, February, and March. Compared to other regions, Qiannan, Liupanshui, and Anshun areas exhibit higher ignition temperature and lower relative humidity. The ignition temperature is mainly concentrated in the range of 15°C to 22°C, and the peak range of ignition distribution is between 55% and 75% relative humidity.
文章引用:王瑶, 罗雪纯, 向楠, 皮义均, 王健颖. 贵州省2011~2023年山火时空分布及气象条件影响分析[J]. 气候变化研究快报, 2024, 13(5): 1138-1146. https://doi.org/10.12677/ccrl.2024.135129

参考文献

[1] 苏立娟, 何友均, 陈绍志. 1950-2010年中国森林火灾时空特征及风险分析[J]. 林业科学, 2015, 51(1): 88-96.
[2] 舒立福, 王明玉, 赵凤君, 等. 几种卫星系统监测林火技术的比较与应用[J]. 世界林业研究, 2005, 18(6): 49-53.
[3] 陈京弘, 田晓瑞, 舒立福. 2005-2007年西南地区卫星监测热点分析[J]. 森林防火, 2009(4): 33-35.
[4] Huesca, M., Litago, J., Palacios-Orueta, A., Montes, F., Sebastián-López, A. and Escribano, P. (2009) Assessment of Forest Fire Seasonality Using MODIS Fire Potential: A Time Series Approach. Agricultural and Forest Meteorology, 149, 1946-1955. [Google Scholar] [CrossRef
[5] Tian, L., Wang, J., Zhou, H. and Wang, J. (2018) Automatic Detection of Forest Fire Disturbance Based on Dynamic Modelling from MODIS Time-Series Observations. International Journal of Remote Sensing, 39, 3801-3815. [Google Scholar] [CrossRef
[6] Bisquert, M., Caselles, E., Sánchez, J.M. and Caselles, V. (2012) Application of Artificial Neural Networks and Logistic Regression to the Prediction of Forest Fire Danger in Galicia Using MODIS Data. International Journal of Wildland Fire, 21, 1025-1029. [Google Scholar] [CrossRef
[7] 刘海新, 钱以临, 孔俊杰, 等. 2003~2019年内蒙古FIRMS_MODIS植被火点时空变化[J]. 林业科技情报, 2023, 55(1): 1-8.
[8] 任静, 沈才明, 刘芳, 等. 2011~2020年云南西双版纳MODIS火点的时空动态特征[J]. 生态学杂志, 2023, 42(8): 1953-1962.
[9] 李鹏, 李文君, 封志明, 等. 基于FIRMS MODIS与VIIRS的东南亚活跃火频次时空动态分析[J]. 资源科学, 2019, 41(8): 1526-1540.
[10] 赵文化, 单海滨, 钟儒祥. 基于MODIS火点指数监测森林火灾[J]. 自然灾害学报, 2008, 17(3): 152-157.
[11] 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.
[12] 曾爱聪, 郭新彬, 郑文霞, 等. 基于MODIS卫星火点数据的浙江省林火时空动态变化特征[J]. 北京林业大学学报, 2020, 42(11): 39-46.
[13] Kumari, B. and Pandey, A.C. (2019) MODIS Based Forest Fire Hotspot Analysis and Its Relationship with Climatic Variables. Spatial Information Research, 28, 87-99. [Google Scholar] [CrossRef
[14] Albar, I., Jaya, I.N.S., Saharjo, B.H., Kuncahyo, B. and Vadrevu, K.P. (2018) Spatio-Temporal Analysis of Land and Forest Fires in Indonesia Using MODIS Active Fire Dataset. In: Vadrevu, K.P., Ohara, T. and Justice, C., Eds., Land-Atmospheric Research Applications in South and Southeast Asia, Springer International Publishing, Berlin, 105-127. [Google Scholar] [CrossRef
[15] 贾旭, 高永, 齐呼格金, 等. 基于MODIS数据的内蒙古野火时空变化特征[J]. 中国生态农业学报, 2017, 25(1): 127-135.
[16] 杨青青, 陈小花, 陈宗铸, 等. 基于MODIS数据的海南岛森林火灾时空分布特征分析[J]. 林业科技通讯, 2024(1): 22-26.
[17] Guangmeng, G. and Mei, Z. (2004) Using MODIS Land Surface Temperature to Evaluate Forest Fire Risk of Northeast China. IEEE Geoscience and Remote Sensing Letters, 1, 98-100. [Google Scholar] [CrossRef
[18] Maeda, E.E., Formaggio, A.R., Shimabukuro, Y.E., Arcoverde, G.F.B. and Hansen, M.C. (2009) Predicting Forest Fire in the Brazilian Amazon Using MODIS Imagery and Artificial Neural Networks. International Journal of Applied Earth Observation and Geoinformation, 11, 265-272. [Google Scholar] [CrossRef
[19] 田鹏举, 龙俐, 郑小波, 等. EOS/MODIS卫星资料在贵州省林火监测中的应用[J]. 贵州气象, 2008, 32(2): 20-22.
[20] 罗宇翔, 康为民, 陈娟. GIS和遥感技术在贵州火险监测中的应用[J]. 贵州气象, 2007, 31(3): 19-21.
[21] 黄红. 贵州省森林火灾特征分析[J]. 贵州气象, 2009, 33(S1): 62-64.
[22] 徐盛基. 贵州林火发生时间卫星监测动态分析[J]. 西部林业科学, 2011, 40(2): 98-100.
[23] 张运林, 田玲玲, 丁波, 等. 贵州省林火发生驱动因子及预测模型[J]. 生态学杂志, 2024, 43(1): 282-289.
[24] 张运林, 罗华, 罗爱霞, 等. 贵州喀斯特生态系统典型针叶林地表火蔓延速度影响因子及预测模型[J]. 北京林业大学学报, 2024, 46(5): 37-45.
[25] 郭福涛, 苏漳文, 王光玉, 等. 我国北方针叶林人为火发生的预测模型[J]. 应用生态学报, 2015, 26(7): 2099-2106.
[26] 朱政, 赵璠, 王秋华, 等. 林火发生预报模型研究进展[J]. 世界林业研究, 2022, 35(3): 26-31.
[27] Zhang, Y. and Sun, P. (2020) Study on the Diurnal Dynamic Changes and Prediction Models of the Moisture Contents of Two Litters. Forests, 11, Article No. 95. [Google Scholar] [CrossRef