Integration of sar and optical dense time series for land cover monitoring

R. A. Molijn, L. Iannini, R. F. Hanssen, F. J. Van Leijen, R. Lamparelli, A. Coutinho

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

Abstract

Multi-temporal and multi-sensor solutions are essential to increase timeliness and reliability of land monitoring systems. This paper advocates the exploitation of the temporal contextual information provided by temporally dense SAR and optical data series series through the use of a Hidden Markov model (HMM)-based approach. An efficient strategy to incorporate the C-Band SAR data into the HMM framework, relying so far on Landsat, will be debated and assessed over a dynamic agricultural scenario, i.e. characterized by high temporal and spatial diversity in cropping practices. The site is located in the state of São Paulo (Brazil), where recent ground surveying activities has been conducted.

Original languageEnglish
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 (IEEE)
Pages4330-4333
Number of pages4
Volume2017-July
ISBN (Electronic)9781509049516
DOIs
Publication statusPublished - 1 Dec 2017
Event37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017: IEEE Geoscience and Remote Sensing - Fort Worth, United States
Duration: 23 Jul 201728 Jul 2017
Conference number: 37
http://www.igarss2017.org/

Conference

Conference37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017
Abbreviated titleIGARSS 2017
CountryUnited States
CityFort Worth
Period23/07/1728/07/17
Internet address

Keywords

  • C-band SAR
  • Land cover mapping
  • Landsat
  • Sensor assimilation
  • Time series processing

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