NOISE REDUCTION IN MODIS NDVI TIME SERIES DATA BASED ON SPATIAL-TEMPORAL ANALYSIS

被引：5
|
作者：
de Oliveira, Julio Cesar [1 ]
Neves Epiphanio, Jose Carlos [1 ]
机构：
[1] INPE, Div Sensoriamento Remoto, BR-12245970 Sao Jose Dos Campos, SP, Brazil
来源：
2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2012年
关键词：
MODIS NDVI; Time series; Quality Assessment; Spatial-temporal analysis; SOFTWARE TOOL;
D O I：
10.1109/IGARSS.2012.6350807
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Normalized Difference Vegetation Index is a vegetation index widely applied in research. However, noise induced by cloud contamination and atmospheric variability affect the data quality. We propose the reconstruction of time series of MODIS NDVI data based on a quality assessment of the science data sets and on a spatial-temporal analysis of the low quality pixels. The MOD13Q1 product was analyzed over a period of one year. The first task was to identify the pixels with the lowest guarantee of quality. The next step was to recalculate the NDVI values based on spatial and temporal correlations. The results indicate that the spatial-temporal information, combined with pixel quality assessment, is a promising method for reconstructing high-quality MODIS NDVI time series.
引用
收藏
页码：2372 / 2375
页数：4
相关论文
共 50 条
  • [21] SPATIAL AND TEMPORAL CHANGES OF VEGETATION COVER IN CHINA BASED ON MODIS NDVI
    Kasoro, F. R.
    Yan, L.
    Zhang, W.
    ASANTE-BADU, B.
    [J]. APPLIED ECOLOGY AND ENVIRONMENTAL RESEARCH, 2021, 19 (02): : 1371 - 1390
  • [22] A Time Series based Study of MODIS NDVI for Vegetation Cover
    Srivastava, Harsh
    Pant, Triloki
    [J]. 2020 IEEE INDIA GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (INGARSS), 2020, : 21 - 24
  • [23] Fractal Feature Analysis and Information Extraction of Woodlands Based on MODIS NDVI Time Series
    Dong, Shiwei
    Li, Hong
    Sun, Danfeng
    [J]. SUSTAINABILITY, 2017, 9 (07)
  • [24] The global spatial-temporal distribution and EOF analysis of AOD based on MODIS data during 2003-2021
    Tian, Xiaomin
    Tang, Chaoli
    Wu, Xin
    Yang, Jie
    Zhao, Fengmei
    Liu, Dong
    [J]. ATMOSPHERIC ENVIRONMENT, 2023, 302
  • [25] A Noise Detection Method for NDVI Time Series Data Based on Dixon Test
    Gu, Jianyu
    Fan, Deqin
    Jiang, Nan
    Liu, Jianhong
    [J]. 2012 FIRST INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS), 2012, : 547 - 551
  • [26] An Improved Method for Producing High Spatial-Resolution NDVI Time Series Datasets with Multi-Temporal MODIS NDVI Data and Landsat TM/ETM plus Images
    Rao, Yuhan
    Zhu, Xiaolin
    Chen, Jin
    Wang, Jianmin
    [J]. REMOTE SENSING, 2015, 7 (06): : 7865 - 7891
  • [27] Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data
    Guo Wei
    Ni Xiangnan
    Jing Duanyang
    Li Shuheng
    [J]. JOURNAL OF GEOGRAPHICAL SCIENCES, 2014, 24 (06) : 1009 - 1021
  • [28] Remotely Sensed Diagnosing Temporal and Spatial Variation of Vegetation Coverage in Guangxi Based on MODIS NDVI Data
    Zhang, Min
    Cao, Chunxiang
    Chen, Wei
    [J]. Linye Kexue/Scientia Silvae Sinicae, 2019, 55 (10): : 27 - 37
  • [29] Spatial-temporal patterns of vegetation dynamics and their relationships to climate variations in Qinghai Lake Basin using MODIS time-series data
    Wei Guo
    Xiangnan Ni
    Duanyang Jing
    Shuheng Li
    [J]. Journal of Geographical Sciences, 2014, 24 : 1009 - 1021
  • [30] Spatial-temporal Attention Model Based on Transformer Architecture for Anomaly Detection in Multivariate Time Series Data
    Zeng, Lai
    Yang, Xiaomei
    [J]. Journal of Computers (Taiwan), 2024, 35 (03) : 193 - 207
12345