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A HMM-based approach for historic and up-to-date land cover mapping through Landsat time-series in the state of Sao Paulo, Brazil.

, , , , and . IGARSS, page 5457-5460. IEEE, (2016)

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Monitoring LULC dynamics in the Sao Paulo region through landsat and C-band SAR time series., , , and . IGARSS, page 90-93. IEEE, (2015)Sugarcane Productivity Mapping through C-Band and L-Band SAR and Optical Satellite Imagery., , , and . Remote. Sens., 11 (9): 1109 (2019)On the Value of Sentinel-1 InSAR Coherence Time-Series for Vegetation Classification., , , and . Remote. Sens., 13 (16): 3300 (2021)Crop Monitoring Using Sentinel-1 Data: A Case Study from The Netherlands., , , , , , , , , and . Remote. Sens., 11 (16): 1887 (2019)A HMM-based approach for historic and up-to-date land cover mapping through Landsat time-series in the state of Sao Paulo, Brazil., , , , and . IGARSS, page 5457-5460. IEEE, (2016)The Effects of Sugarcane Productivity Anomalies on L-Band and C-Band SAR Signals., , , , , and . IGARSS, page 5371-5374. IEEE, (2018)Erratum: Ramses A.M. et al. Vegetation Characterization through the Use of Precipitation-Affected SAR Signals. Remote Sens. 2018 10 1647., , , , and . Remote. Sens., 10 (11): 1854 (2018)Timely Mapping of Crop Stage and Watering Events Through Sentinel-L Time-Series., , , , and . IGARSS, page 196-199. IEEE, (2018)Sugarcane growth monitoring through spatial cluster and temporal trend analysis of radar and optical remote sensing images., , , and . IGARSS, page 7141-7144. IEEE, (2016)Integration of sar and optical dense time series for land cover monitoring., , , , , and . IGARSS, page 4330-4333. IEEE, (2017)