Comparative study of three satellite image time-series decomposition methods for vegetation change detection-Reference-Cited by-同舟云学术

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Comparative study of three satellite image time-series decomposition methods for vegetation change detection

Published:2018-01-01 Issue:1 Volume:51 Page:607-615
ISSN:2279-7254
Container-title:European Journal of Remote Sensing
language:en
Short-container-title:European Journal of Remote Sensing

Author:

Ben Abbes Ali¹,Bounouh Oumayma¹,Farah Imed Riadh¹²,de Jong Rogier³,Martínez Beatriz⁴

Affiliation:

1. Laboratoire RIADI, Ecole Nationale des Sciences de l’Informatique, Manouba, Tunisia

2. Laboratoire ITI, TELECOM-Bretagne, Technopôle Brest Iroise, Brest Cedex, France

3. Department of Geography, University of Zurich, Zurich, Switzerland

4. Departament de Física de la Terra i Termodinàmica, Universitat de València, Valencia, Spain

Publisher

Informa UK Limited

Subject

Applied Mathematics,Atmospheric Science,Computers in Earth Sciences,General Environmental Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/22797254.2018.1465360

Reference44 articles.

1. Mapping vegetation-soil-climate complexes in southern Africa using temporal Fourier analysis of NOAA-AVHRR NDVI data

2. Computation and analysis of multiple structural change models

3. A Framework for Automatic and Unsupervised Detection of Multiple Changes in Multitemporal Images

4. Local Vegetation Trends in the Sahel of Mali and Senegal Using Long Time Series FAPAR Satellite Products and Field Measurement (1982–2010)

5. Breaks in MODIS time series portend vegetation change: verification using long-term data in an arid grassland ecosystem

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