Estimation of dynamic parameters of MODIS NDVI time series nonlinear model using particle filtering

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Normalized Difference Vegetation Index (NDVI) time series is used to study different land cover dynamics such as change, compare vegetation dynamics between years and analyze intra-annual components. A nonlinear cosine model of the NDVI time series with a constant frequency is used to account for the time-varying nature of the land cover parameters due to seasonality or change. The Extended Kalman Filter (EKF) is used to estimate these parameters, which introduces linearization and negatively impacts the state estimation accuracy. This paper proposes using a Particle Filter (PF) for state estimation to better address nonlinearity in the model. The cosine model is modified to capture frequency variations to account for changes in the vegetation growth cycle caused by abrupt phenomenon such as forest fires. PF obtains better state estimates than EKF, capturing the intra-annual components and time-varying frequency of the model accurately.

Original languageEnglish (US)
Title of host publication2017 IEEE International Geoscience and Remote Sensing Symposium
Subtitle of host publicationInternational Cooperation for Global Awareness, IGARSS 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1091-1094
Number of pages4
Volume2017-July
ISBN (Electronic)9781509049516
DOIs
StatePublished - Dec 1 2017
Externally publishedYes
Event37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017 - Fort Worth, United States
Duration: Jul 23 2017Jul 28 2017

Other

Other37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
CountryUnited States
CityFort Worth
Period7/23/177/28/17

Keywords

  • Land cover change detection
  • nonlinear model
  • particle filter

ASJC Scopus subject areas

  • Computer Science Applications
  • Earth and Planetary Sciences(all)

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    Chakraborty, S., Banerjee, A., Gupta, S., Papandreou-Suppappola, A., & Christensen, P. (2017). Estimation of dynamic parameters of MODIS NDVI time series nonlinear model using particle filtering. In 2017 IEEE International Geoscience and Remote Sensing Symposium: International Cooperation for Global Awareness, IGARSS 2017 - Proceedings (Vol. 2017-July, pp. 1091-1094). [8127146] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2017.8127146