Time Series of Remote Sensing Data for Interaction Analysis of the Vegetation Coverage and Dust Activity in the Middle East

被引:11
|
作者
Namdari, Soodabeh [1 ]
Alnasrawi, Ali Ibrahim Zghair [2 ]
Ghorbanzadeh, Omid [3 ]
Sorooshian, Armin [4 ,5 ]
Kamran, Khalil Valizadeh [1 ]
Ghamisi, Pedram [3 ]
机构
[1] Univ Tabriz, Dept Remote Sensing & GIS, Tabriz 5166616471, Iran
[2] Minist Educ, Gen Directorate Educ, Maysan 62003, Iraq
[3] Inst Adv Res Artificial Intelligence IARAI, Landstr Hauptstr 5, A-1030 Vienna, Austria
[4] Univ Arizona, Dept Chem & Environm Engn, POB 210011, Tucson, AZ 85721 USA
[5] Univ Arizona, Dept Hydrol & Atmospher Sci, POB 210011, Tucson, AZ 85721 USA
关键词
time series analysis; remote sensing; dust storm; vegetation monitoring; MODIS Terra; STORM FREQUENCY; NORTHERN CHINA; AIR-POLLUTION; CLIMATE; PRECIPITATION; EMISSION; REGIONS; AERONET; SCALE; MODIS;
D O I
10.3390/rs14132963
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Motivated by the lack of research on land cover and dust activity in the Middle East, this study seeks to increase the understanding of the sensitivity of dust centers to climatic and surface conditions in this specific region. In this regard, we explore vegetation cover and dust emission interactions using 16-day long-term Normalized Difference Vegetation Index (NDVI) data and daily Aerosol Optical Depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS) and conduct spatiotemporal and statistical analyses. Eight major dust hotspots were identified based on long-term AOD data (2000-2019). Despite the relatively uniform climate conditions prevailing throughout the region during the study period, there is considerable spatial variability in interannual relationships between AOD and NDVI. Three subsets of periods (2000-2006, 2007-2013, 2014-2019) were examined to assess periodic spatiotemporal changes. In the second period (2007-2013), AOD increased significantly (6% to 32%) across the studied hotspots, simultaneously with a decrease in NDVI (-0.9% to -14.3%) except in Yemen-Oman. Interannual changes over 20 years showed a strong relationship between reduced vegetation cover and increased dust intensity. The correlation between NDVI and AOD (-0.63) for the cumulative region confirms the significant effect of vegetation canopy on annual dust fluctuations. According to the results, changes in vegetation cover have an essential role in dust storm fluctuations. Therefore, this factor must be regarded along with wind speed and other climate factors in Middle East dust hotspots related to research and management efforts.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] THE ANALYSIS OF EAST DONGTING LAKE WATER CHANGE BASED ON TIME SERIES OF REMOTE SENSING DATA
    Ma Caihong
    Dai Qin
    Li Xinpeng
    Liu Shibin
    [J]. 2014 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING (ICSP), 2014, : 718 - 722
  • [2] Remote Sensing and Time Series Data Fused Multimodal Prediction Model Based on Interaction Analysis
    Zhang, Zhiwei
    Wang, Dong
    [J]. ICVIP 2019: PROCEEDINGS OF 2019 3RD INTERNATIONAL CONFERENCE ON VIDEO AND IMAGE PROCESSING, 2019, : 190 - 194
  • [3] Study on the Vegetation Dynamic Change Using Long Time Series of Remote Sensing Data
    Fan Jinlong
    Zhang Xiaoyu
    [J]. REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XII, 2010, 7824
  • [4] Analysis on Terrain Effects to Vegetation Coverage by Quantitative Remote Sensing
    Yu, Zhengzheng
    Zhu, Junge
    Qian, Yuelei
    [J]. ADVANCES IN ENVIRONMENTAL SCIENCE AND ENGINEERING, PTS 1-6, 2012, 518-523 : 5673 - 5677
  • [5] Contribution of time-series data cubes to classify urban vegetation types by remote sensing
    Adorno, Bruno Vargas
    Korting, Thales Sehn
    Amaral, Silvana
    [J]. URBAN FORESTRY & URBAN GREENING, 2023, 79
  • [6] Monitoring the photosynthetic activity of vegetation from remote sensing data
    Gobron, N.
    Pinty, B.
    Taberner, M.
    Melin, F.
    Verstraete, M. M.
    Widlowski, J. -L.
    [J]. ADVANCES IN SPACE RESEARCH, 2006, 38 (10) : 2196 - 2202
  • [7] Monitoring the photosynthetic activity of vegetation from remote sensing data
    Gobron, N.
    Pinty, B.
    Taberner, M.
    Melin, F.
    Verstraete, M. M.
    Widlowski, J. -L.
    [J]. REMOTE SENSING OF OCEANOGRAPHIC PROCESSES AND LAND SURFACES; SPACE SCIENCE EDUCATION AND OUTREACH, 2006, 38 (10): : 2196 - +
  • [8] Monitoring vegetation using remote sensing time series data: a review of the period 1996-2017
    Manuel Zuniga-Vasquez, Jose
    Arturo Aguirre-Salado, Carlos
    Pompa-Garcia, Marin
    [J]. REVISTA DE LA FACULTAD DE CIENCIAS AGRARIAS, 2020, 52 (01) : 175 - 189
  • [9] Remote sensing and modelling analysis of the extreme dust storm hitting the Middle East and eastern Mediterranean in September 2015
    Solomos, Stavros
    Ansmann, Albert
    Mamouri, Rodanthi-Elisavet
    Binietoglou, Ioannis
    Patlakas, Platon
    Marinou, Eleni
    Amiridis, Vassilis
    [J]. ATMOSPHERIC CHEMISTRY AND PHYSICS, 2017, 17 (06) : 4063 - 4079
  • [10] Vegetation Change of Ecotone in West of Northeast China Plain Using Time-series Remote Sensing Data
    Huang Fang
    Wang Ping
    [J]. CHINESE GEOGRAPHICAL SCIENCE, 2010, 20 (02) : 167 - 175