A time-series model for characterizing continuous land cover change

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

Abstract

We propose a time-series model for characterizing land cover change. The model is developed based on a realistic view of land surface transformation - spatially discrete land cover change events are continuous processes over time. The model utilizes a non-linear mathematical function to reconstruct the underlying continuous land change process from temporally discrete satellite observations. Based on the coefficients of the mathematical function, the model simultaneously derives the timing, intensity and duration of land cover change. Moreover, the smoothing feature of the model can also be used to remove random noise in time-series land cover data and hence to re-establish the stable land cover states before and after change. We illustrate the application of the model by showing examples of characterizing deforestation using time-series MODIS data as well as characterizing urban land expansion using time-series Landsat data.

Original languageEnglish
Title of host publication2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3426-3429
Number of pages4
ISBN (Electronic)9781509033324
DOIs
StatePublished - Nov 1 2016
Event36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Beijing, China
Duration: Jul 10 2016Jul 15 2016

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)
Volume2016-November

Conference

Conference36th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016
CountryChina
CityBeijing
Period07/10/1607/15/16

Keywords

  • Land cover
  • change detection
  • time-series

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  • Cite this

    Song, X. P. (2016). A time-series model for characterizing continuous land cover change. In 2016 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2016 - Proceedings (pp. 3426-3429). [7729885] (International Geoscience and Remote Sensing Symposium (IGARSS); Vol. 2016-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IGARSS.2016.7729885