• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

受野火影响地区的中分辨率成像光谱仪（MODIS）Aqua和Terra卫星归一化植被指数及增强植被指数时间序列的多重分形分析

Multifractal Analysis of MODIS Aqua and Terra Satellite Time Series of Normalized Difference Vegetation Index and Enhanced Vegetation Index of Sites Affected by Wildfires.

作者信息

Ba Rui, Lovallo Michele, Song Weiguo, Zhang Hui, Telesca Luciano

机构信息

School of National Security, People's Public Security University of China, Beijing 100038, China.

ARPAB, 85100 Potenza, Italy.

出版信息

Entropy (Basel). 2022 Nov 29;24(12):1748. doi: 10.3390/e24121748.

DOI:10.3390/e24121748
PMID:36554153
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9777580/
Abstract

The MODIS Aqua and Terra Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) time series acquired during nearly two decades (2000 to 2020) covering the area burned by the Camp Fire (California) in 2018 is investigated in this study by using the multifractal detrended fluctuation analysis in relation to the recovery process of vegetation after fire. In 2008, the same area was partially burned by two wildfires, the BTU Lightning Complex Fire and the Humboldt Fire. Our results indicate that all vegetation index time series are featured by six- and twelve-month modulating periodicities, with a larger spectral content at longer periods for two-fire-affected sites. Furthermore, two fires cause an increase of the persistence of the NDVI and EVI time series and an increase of the complexity, suggesting that the recovery process of vegetation dynamics of fire-affected sites is characterized by positive feedback mechanisms, driving the growth-generating phenomena, which become even more effective in those sites affected by two fires.

摘要

本研究利用多重分形去趋势波动分析方法，对2000年至2020年近二十年间获取的、覆盖2018年坎普大火（加利福尼亚州）烧毁区域的中分辨率成像光谱仪（MODIS）Aqua和Terra的归一化植被指数（NDVI）及增强植被指数（EVI）时间序列进行了研究，以探讨火灾后植被的恢复过程。2008年，同一区域曾遭受两场野火（BTU闪电复合火灾和洪堡火灾）的部分烧毁。我们的研究结果表明，所有植被指数时间序列均具有6个月和12个月的调制周期，且对于受两场火灾影响的区域，较长周期的光谱含量更大。此外，两场火灾导致NDVI和EVI时间序列的持续性增加以及复杂性提高，这表明受火灾影响区域的植被动态恢复过程具有正反馈机制，推动了生长生成现象，在受两场火灾影响的区域这种机制更为有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/5b253a34f8ec/entropy-24-01748-g018a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/c03b51c518c6/entropy-24-01748-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/99ec5b355671/entropy-24-01748-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/6ee2ae78211d/entropy-24-01748-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/4aee8b279e1e/entropy-24-01748-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/e752a0315f7e/entropy-24-01748-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d2bf541f9aa5/entropy-24-01748-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/208ab7dfa245/entropy-24-01748-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/8d07827ee689/entropy-24-01748-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d53f8a6d2dda/entropy-24-01748-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d15c61cfe0d2/entropy-24-01748-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/c4801b8484c0/entropy-24-01748-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/01aff97be2a3/entropy-24-01748-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/a6a2eb3d4193/entropy-24-01748-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/e75ac719f86d/entropy-24-01748-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/2ae88464e501/entropy-24-01748-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/0d67e55e796e/entropy-24-01748-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/9a11cf497241/entropy-24-01748-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/5b253a34f8ec/entropy-24-01748-g018a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/c03b51c518c6/entropy-24-01748-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/99ec5b355671/entropy-24-01748-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/6ee2ae78211d/entropy-24-01748-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/4aee8b279e1e/entropy-24-01748-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/e752a0315f7e/entropy-24-01748-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d2bf541f9aa5/entropy-24-01748-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/208ab7dfa245/entropy-24-01748-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/8d07827ee689/entropy-24-01748-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d53f8a6d2dda/entropy-24-01748-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/d15c61cfe0d2/entropy-24-01748-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/c4801b8484c0/entropy-24-01748-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/01aff97be2a3/entropy-24-01748-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/a6a2eb3d4193/entropy-24-01748-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/e75ac719f86d/entropy-24-01748-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/2ae88464e501/entropy-24-01748-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/0d67e55e796e/entropy-24-01748-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/9a11cf497241/entropy-24-01748-g017a.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c4a0/9777580/5b253a34f8ec/entropy-24-01748-g018a.jpg

相似文献

1
Multifractal Analysis of MODIS Aqua and Terra Satellite Time Series of Normalized Difference Vegetation Index and Enhanced Vegetation Index of Sites Affected by Wildfires.受野火影响地区的中分辨率成像光谱仪（MODIS）Aqua和Terra卫星归一化植被指数及增强植被指数时间序列的多重分形分析
Entropy (Basel). 2022 Nov 29;24(12):1748. doi: 10.3390/e24121748.
2
Analysis of Multifractal and Organization/Order Structure in Suomi-NPP VIIRS Normalized Difference Vegetation Index Series of Wildfire Affected and Unaffected Sites by Using the Multifractal Detrended Fluctuation Analysis and the Fisher-Shannon Analysis.利用多重分形去趋势波动分析和费舍尔-香农分析对受野火影响和未受影响地区的苏米国家极地轨道伙伴计划可见光红外成像辐射仪组归一化植被指数系列中的多重分形和组织/秩序结构进行分析。
Entropy (Basel). 2020 Apr 7;22(4):415. doi: 10.3390/e22040415.
3
Remote sensing of vegetation conditions after post-fire mulch treatments.火灾后覆盖物处理后植被状况的遥感。
J Environ Manage. 2020 Apr 15;260:109993. doi: 10.1016/j.jenvman.2019.109993. Epub 2020 Jan 21.
4
Biogeographic variability in wildfire severity and post-fire vegetation recovery across the European forests via remote sensing-derived spectral metrics.通过遥感衍生光谱指标分析欧洲森林野火严重程度和火灾后植被恢复的生物地理变异性。
Sci Total Environ. 2022 Jun 1;823:153807. doi: 10.1016/j.scitotenv.2022.153807. Epub 2022 Feb 9.
5
Multitemporal Mapping of Post-Fire Land Cover Using Multiplatform PRISMA Hyperspectral and Sentinel-UAV Multispectral Data: Insights from Case Studies in Portugal and Italy.基于多平台 PRISMA 高光谱和哨兵-UAV 多光谱数据的火灾后土地覆盖多时相制图：来自葡萄牙和意大利案例研究的见解。
Sensors (Basel). 2021 Jun 9;21(12):3982. doi: 10.3390/s21123982.
6
Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada.卫星微波探测阿拉斯加和加拿大 2004 年特大森林火灾后的北方森林恢复情况。
Glob Chang Biol. 2013 Oct;19(10):3111-22. doi: 10.1111/gcb.12288. Epub 2013 Aug 18.
7
Monitoring the Effects of Forest Restoration Treatments on Post-Fire Vegetation Recovery with MODIS Multitemporal Data.利用中分辨率成像光谱仪多时态数据监测森林恢复措施对火灾后植被恢复的影响
Sensors (Basel). 2008 Mar 25;8(3):2017-2042. doi: 10.3390/s8032017.
8
[Comparison of GIMMS and MODIS normalized vegetation index composite data for Qing-Hai-Tibet Plateau].[青藏高原GIMMS和MODIS归一化植被指数合成数据比较]
Ying Yong Sheng Tai Xue Bao. 2014 Feb;25(2):533-44.
9
Reconstructing pre-fire vegetation condition in the wildland urban interface (WUI) using artificial neural network.利用人工神经网络重建城市与森林交界地区（WUI）的火灾前植被状况。
J Environ Manage. 2019 May 15;238:224-234. doi: 10.1016/j.jenvman.2019.02.091. Epub 2019 Mar 7.
10
Does short-interval fire inhibit postfire recovery of chaparral across southern California?短间隔火灾是否会抑制南加州灌丛植被的林火后恢复？
Sci Total Environ. 2021 Jan 10;751:142271. doi: 10.1016/j.scitotenv.2020.142271. Epub 2020 Sep 11.

本文引用的文献

1
Deriving forest fire ignition risk with biogeochemical process modelling.通过生物地球化学过程建模推导森林火灾点火风险。
Environ Model Softw. 2014 May;55:132-142. doi: 10.1016/j.envsoft.2014.01.018.
2
Detecting and interpreting distortions in hierarchical organization of complex time series.检测并解读复杂时间序列层次组织中的失真情况。
Phys Rev E Stat Nonlin Soft Matter Phys. 2015 Mar;91(3):030902. doi: 10.1103/PhysRevE.91.030902. Epub 2015 Mar 20.