AN AUTOMATED METHOD FOR NORMALISING LARGE LANDSAT TIME SERIES DATASETS TO LIKE VALUES FOR CHANGE DETECTION

被引：0
|
作者：
Opie, Kimberley [1 ]
Sims, Neil [1 ]
机构：
[1] CSIRO Land & Water, Clayton 3169, Australia
来源：
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词：
Landsat; normalisation; change detection; pseudo-invariant features;
D O I：
10.1109/IGARSS.2013.6723190
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：
The increased availability of Landsat imagery provides the opportunity to monitor changes in the land surface over long time frames. This paper presents an automated method for normalizing satellite images to a calibrated reference image using pseudo invariant features (PIFs). The method is repeatable, objective and fast, and has been used to prepare a large collection of Landsat images for flood inundation detection.
引用
收藏
页码：1956 / 1958
页数：3
相关论文
共 50 条
  • [1] A new time series change detection method for Landsat land use and land cover change
    Lin, Yukun
    Zhang, Lifu
    Wang, Nan
    [J]. 2019 10TH INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTITEMPORAL REMOTE SENSING IMAGES (MULTITEMP), 2019,
  • [2] A New Method for Automated Clearcut Disturbance Detection in Mediterranean Coppice Forests Using Landsat Time Series
    Giannetti, Francesca
    Pegna, Raffaello
    Francini, Saverio
    McRoberts, Ronald E.
    Travaglini, Davide
    Marchetti, Marco
    Mugnozza, Giuseppe Scarascia
    Chirici, Gherardo
    [J]. REMOTE SENSING, 2020, 12 (22) : 1 - 23
  • [3] DDR: an index method for large time-series datasets
    An, JY
    Chen, YPP
    Chen, HX
    [J]. INFORMATION SYSTEMS, 2005, 30 (05) : 333 - 348
  • [4] Clustering of large time series datasets
    Aghabozorgi, Saeed
    Teh, Ying Wah
    [J]. INTELLIGENT DATA ANALYSIS, 2014, 18 (05) : 793 - 817
  • [5] Improving automated detection of land cover change for large areas using Landsat data
    Song, K
    Townshend, JR
    Kim, S
    Davis, P
    Clay, R
    Rodas, O
    [J]. 2005 INTERNATIONAL WORKSHOP ON THE ANALYSIS ON MULTI-TEMPORAL REMOTE SENSING IMAGES, 2005, : 39 - 43
  • [6] Dagu River Channel Extraction and Change Detection Based on Landsat Time Series
    Zhao, Bing
    Cai, Yulin
    Yuan, Huijie
    [J]. 2018 FIFTH INTERNATIONAL WORKSHOP ON EARTH OBSERVATION AND REMOTE SENSING APPLICATIONS (EORSA), 2018, : 410 - 414
  • [7] Patch-Based Forest Change Detection from Landsat Time Series
    Hughes, M. Joseph
    Kaylor, S. Douglas
    Hayes, Daniel J.
    [J]. FORESTS, 2017, 8 (05):
  • [8] Periodicity Detection Method for Small-Sample Time Series Datasets
    Tominaga, Daisuke
    [J]. BIOINFORMATICS AND BIOLOGY INSIGHTS, 2010, 4 : 127 - 136
  • [9] Estimating Afforestation Area Using Landsat Time Series and Photointerpreted Datasets
    Cavalli, Alice
    Francini, Saverio
    McRoberts, Ronald E.
    Falanga, Valentina
    Congedo, Luca
    De Fioravante, Paolo
    Maesano, Mauro
    Munafo, Michele
    Chirici, Gherardo
    Scarascia Mugnozza, Giuseppe
    [J]. REMOTE SENSING, 2023, 15 (04)
  • [10] Integration of Landsat time-series vegetation indices improves consistency of change detection
    Zhou, Mingxing
    Li, Dengqiu
    Liao, Kuo
    Lu, Dengsheng
    [J]. INTERNATIONAL JOURNAL OF DIGITAL EARTH, 2023, 16 (01) : 1276 - 1299
12345