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Applying A Phenological Object-Based Image Analysis (Phenobia) for Agricultural Land Classification: A Study Case in the Brazilian Cerrado.

, , , , , , , , , , and . IGARSS, page 1078-1081. IEEE, (2020)

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Assessing The Influence Of Borders And Roads On The Segmentation Of Rice Fields: A Case Study., , , and . GEOINFO, page 1-12. MCTI/INPE, (2023)Crop Type Recognition Based on Hidden Markov Models of Plant Phenology., , , , , and . SIBGRAPI, page 27-34. IEEE Computer Society, (2008)Hidden Markov Models for crop recognition in remote sensing image sequences., , , , , and . Pattern Recognit. Lett., 32 (1): 19-26 (2011)Assessment of a multi-sensor approach for noise removal on Landsat-8 OLI time series using CBERS-4 MUX data to improve crop classification based on phenological features., , , , , and . GEOINFO, page 240-251. MCTIC/INPE, (2016)Mapping croplands, cropping patterns, and crop types using MODIS time-series data., , , , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2018)Potential of Using Sentinel-1 Data to Distinguish Targets in Remote Sensing Images., , , , , , and . ICCSA (4), volume 11622 of Lecture Notes in Computer Science, page 563-576. Springer, (2019)Detecting Irrigated Croplands: A Comparative Study With Segment Anything Model And Region-Growing Algorithm., , , , , , and . GEOINFO, page 199-209. MCTI/INPE, (2023)Comparing Phenometrics Extracted From Dense Landsat-Like Image Time Series for Crop Classification., , , , , , , and . IGARSS, page 469-472. IEEE, (2019)Estimating Crop Sowing and Harvesting Dates Using Satellite Vegetation Index: A Comparative Analysis., , , , , , and . Remote. Sens., 15 (22): 5366 (November 2023)Detailed agricultural land classification in the Brazilian cerrado based on phenological information from dense satellite image time series., , , , , , , and . Int. J. Appl. Earth Obs. Geoinformation, (2019)