Seasonal Analysis of the Hotspot Spatial Grid in Indonesia and the Relationship of the Hotspot Grid with the Nino SST Indices

I. Dewa Gede Arya Putra, E. Heriyanto, A. Sopaheluwakan, R. P. Pradana, D. Nuryanto
{"title":"Seasonal Analysis of the Hotspot Spatial Grid in Indonesia and the Relationship of the Hotspot Grid with the Nino SST Indices","authors":"I. Dewa Gede Arya Putra, E. Heriyanto, A. Sopaheluwakan, R. P. Pradana, D. Nuryanto","doi":"10.1109/AGERS51788.2020.9452775","DOIUrl":null,"url":null,"abstract":"Forest fires have caused significant economic losses and environmental damage. The phenomenon of Nino variability in the Pacific region has affected the occurrence of forest fires in Indonesia. The hotspot data gridding in this study aims to change the host data format to make it more universal with other geodata, most of which are already in the grid matrix format in the NetCDF data format to facilitate the need for spatial and temporal analysis and interpretation. The method in this analysis is to add up the daily hotspots with a hotspot confidence level above 80% in a grid area with a spatial resolution of 25 km2 per month, then create a time series from 2001 to 2019 with the research domain of all parts of Indonesia. Based on gridding data, the spatial distribution of the number of dominant hotspots over 100 hotspots occurs during the JJA and SON seasons in Jambi, South Sumatra, West Kalimantan, Central Kalimantan, South Kalimantan, and East Kalimantan. Based on the spatial correlation of hotspots with Nino 1.2, Nino 3, Nino 3.4, and Nino 4, there is a positive correlation with coefficient values ranging from 0.1 to 0.4 for almost all parts of Indonesia except northern Sumatra which is negatively correlated around -0.1.","PeriodicalId":125663,"journal":{"name":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AGERS51788.2020.9452775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Forest fires have caused significant economic losses and environmental damage. The phenomenon of Nino variability in the Pacific region has affected the occurrence of forest fires in Indonesia. The hotspot data gridding in this study aims to change the host data format to make it more universal with other geodata, most of which are already in the grid matrix format in the NetCDF data format to facilitate the need for spatial and temporal analysis and interpretation. The method in this analysis is to add up the daily hotspots with a hotspot confidence level above 80% in a grid area with a spatial resolution of 25 km2 per month, then create a time series from 2001 to 2019 with the research domain of all parts of Indonesia. Based on gridding data, the spatial distribution of the number of dominant hotspots over 100 hotspots occurs during the JJA and SON seasons in Jambi, South Sumatra, West Kalimantan, Central Kalimantan, South Kalimantan, and East Kalimantan. Based on the spatial correlation of hotspots with Nino 1.2, Nino 3, Nino 3.4, and Nino 4, there is a positive correlation with coefficient values ranging from 0.1 to 0.4 for almost all parts of Indonesia except northern Sumatra which is negatively correlated around -0.1.
印度尼西亚热点空间网格的季节分析及热点网格与Nino海温指数的关系
森林火灾造成了重大的经济损失和环境破坏。太平洋地区的尼诺变率现象影响了印度尼西亚森林火灾的发生。本研究的热点数据网格化旨在改变主机数据格式,使其与其他地理数据更加通用,这些地理数据在NetCDF数据格式中大部分已经是网格矩阵格式,以方便时空分析和解释的需要。本文的分析方法是在空间分辨率为25 km2 /月的网格区域内,将热点置信度在80%以上的日热点相加,建立2001 - 2019年印度尼西亚各地研究域的时间序列。在JJA和SON季节,占比、南苏门答腊、西加里曼丹、中加里曼丹、南加里曼丹和东加里曼丹的优势热点数量在100个以上。从热点与Nino 1.2、Nino 3、Nino 3.4和Nino 4的空间相关性来看,除北苏门答腊在-0.1附近呈负相关外,印尼几乎所有地区的热点与Nino 1.2、Nino 3、Nino 4的空间相关性均在0.1 ~ 0.4之间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信