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Integration of sar and optical dense time series for land cover monitoring
- Source :
- IGARSS
- Publication Year :
- 2017
- Publisher :
- IEEE, 2017.
-
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 Sao Paulo (Brazil), where recent ground surveying activities has been conducted.
- Subjects :
- Synthetic aperture radar
Computer science
Reliability (computer networking)
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION
04 agricultural and veterinary sciences
Land cover
010501 environmental sciences
Antenna diversity
01 natural sciences
Remote sensing (archaeology)
040103 agronomy & agriculture
0401 agriculture, forestry, and fisheries
Time series
Hidden Markov model
Cropping
0105 earth and related environmental sciences
Remote sensing
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)
- Accession number :
- edsair.doi...........f0132fbb13f40de2daccdde51adb2b02