|
|||||
|
|
| 中南半岛旱季VIIRS活跃火的空间特征与国别差异 | |
| 引用本文： | 刘颖,李鹏,肖池伟,刘佳,叶靓俏,施冬.中南半岛旱季VIIRS活跃火的空间特征与国别差异[J].地理科学进展,2021,40(8):1406-1418. |
| 作者姓名： | 刘颖 李鹏 肖池伟 刘佳 叶靓俏 施冬 |
| 作者单位： | 1.长江大学地球科学学院,武汉 430100 2.中国科学院地理科学与资源研究所,北京 100101 3.中国科学院大学,北京 100049 4.西南大学地理科学学院,重庆 400715 |
| 基金项目： | 国家自然科学基金项目(41971242);国家自然科学基金项目(42001226);中国科学院地理科学与资源研究所“秉维”优秀青年人才计划(2018RC201);中国科学院青年创新促进会会员人才专项(CAS2020055) |
| 摘 要： | 热带是全球活跃火(active fire)的集中发生区,客观认识其空间特征、国别差异及其动态变化对评估区域生物质燃烧及其碳排放等具有重要意义。作为热带季风气候典型区,中南半岛旱季活跃火发生发展空间特征及其动态变化仍缺乏清晰认识。为此,论文利用可见光红外成像辐射仪(VIIRS) S-NPP 2012—2019年活跃火矢量数据,基于核密度与空间自相关评价了中南半岛及国别旱季尤其是其特征月份(2—4月)活跃火发生发展的密集程度、集聚特征及其动态变化。结果表明：① 中南半岛活跃火核密度低值区占比最大(79%),高值区最小(4%);柬埔寨、缅甸、老挝等经济落后国家的核密度均值明显高于泰国和越南;2012—2019年核密度高值区具有朝高海拔、向内陆与趋边境等分布特征,且柬埔寨东北部长居高值区。② 活跃火核密度中值区变化集中在1—4月,且多分布在低、高值区周围;高值区变化集中在2—4月,由柬埔寨东北部逐渐向缅甸东/西部、泰国西北部以及老挝北/南部转移。③ 半岛与5国活跃火核密度在旱季具有显著空间正相关性,空间集聚类型以“高—高”型和“低—低”型集聚为主,越南、柬埔寨等国局部自相关性强于泰国和老挝。 |
| 关 键 词： | 活跃火 VIIRS 核密度 空间自相关 空间分布 中南半岛 |
| 收稿时间： | 2020-11-17 |
| 修稿时间： | 2021-02-22 |
Spatial characteristics and national differences of active fires derived from Visible Infrared Imaging Radiometer Suite(VIIRS)in Mainland Southeast Asia in the dry season during 2012-2019 |
|
| LIU Ying,LI Peng,XIAO Chiwei,LIU Jia,YE Jingqiao,SHI Dong.Spatial characteristics and national differences of active fires derived from Visible Infrared Imaging Radiometer Suite(VIIRS)in Mainland Southeast Asia in the dry season during 2012-2019[J].Progress in Geography,2021,40(8):1406-1418. | |
| Authors: | LIU Ying LI Peng XIAO Chiwei LIU Jia YE Jingqiao SHI Dong |
| Institution: | 1. School of Geosciences, Yangtze University, Wuhan 430100, China 2. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China 3. University of Chinese Academy of Sciences, Beijing 100049, China 4. School of Geographic Sciences, Southwest University, Chongqing 400715, China |
| Abstract: | The tropics is the hotspot of global active fires. It is of great significance to reveal the spatial characteristics and dynamic changes of active fires for assessing regional biomass burning and carbon emissions. Based on the active fire vector data (2012-2019) of Visible Infrared Imaging Radiometer Suite (VIIRS) Suomi National Polar-Orbiting Partnership (S-NPP) provided by the NASA's Fire Information for Resource Management System (FIRMS), the occurrence density and agglomeration degree of active fires in Mainland Southeast Asia were quantified and analyzed using kernel density and spatial autocorrelation methods, in order to reveal the spatiotemporal variations in active fire occurrence frequency within the dry season, especially in February and April, during 2012-2019. The results show that: 1) The occurrence of active fires was dominated by low density (79%), and the high density areas had the smallest proportion (4%). Active fires are more likely to occur in economically backward countries (Cambodia, Myanmar, and Laos) and regions (for example, eastern Cambodia and northern Laos). High kernel density areas tend to distribute in high elevation, inland, and border areas in particular. Cambodia, especially its northeastern region, was always an area with high occurrence density of active fires in the study period. 2) The changes in medium density area of active fires were concentrated between January and April, which was mostly distributed around the low and high density areas, while the changes in high density areas were concentrated between February and April, spatially gradually shifted from northeastern Cambodia to western and eastern Myanmar, northwestern Thailand, and northern and southern Laos. 3) The density of active fire occurrence showed significant spatial autocorrelation in Mainland Southeast Asia and the five countries during the dry season. The spatial clustering types of the kernel density of active fires are dominated by "high-high" and "low-low" agglomerations in the dry season, especially between February and April. The local spatial autocorrelation of the kernel density of active fires in Vietnam and Cambodia is stronger than those in Thailand and Laos. |
| Keywords: | active fires VIIRS kernel density spatial autocorrelation spatial distribution Mainland Southeast Asia |
| 本文献已被 CNKI 万方数据 等数据库收录！ | |
| 点击此处可从《地理科学进展》浏览原始摘要信息 | |
| 点击此处可从《地理科学进展》下载免费的PDF全文 | |