Ieda Del'Arco Sanches
Orcid: 0000-0003-1296-0933
According to our database1,
Ieda Del'Arco Sanches
authored at least 26 papers
between 2008 and 2024.
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Bibliography
2024
A Method for Estimating Soybean Sowing, Beginning Seed, and Harvesting Dates in Brazil Using NDVI-MODIS Data.
Remote. Sens., July, 2024
Sugarcane Yield Estimation Using Satellite Remote Sensing Data in Empirical or Mechanistic Modeling: A Systematic Review.
Remote. Sens., March, 2024
2023
Estimating Crop Sowing and Harvesting Dates Using Satellite Vegetation Index: A Comparative Analysis.
Remote. Sens., November, 2023
Mapping Agricultural Intensification in the Brazilian Savanna: A Machine Learning Approach Using Harmonized Data from Landsat Sentinel-2.
ISPRS Int. J. Geo Inf., July, 2023
Detecting Irrigated Croplands: A Comparative Study With Segment Anything Model And Region-Growing Algorithm.
Proceedings of the XXIV Brazilian Symposium on Geoinformatics, 2023
Assessing The Influence Of Borders And Roads On The Segmentation Of Rice Fields: A Case Study.
Proceedings of the XXIV Brazilian Symposium on Geoinformatics, 2023
2022
Hierarchical Classification of Soybean in the Brazilian Savanna Based on Harmonized Landsat Sentinel Data.
Remote. Sens., 2022
Leaf Spectra Changes of Plants Grown in Soils Pre- and Post-Contaminated with Petroleum Hydrocarbons.
Remote. Sens., 2022
2020
Recent Applications of Landsat 8/OLI and Sentinel-2/MSI for Land Use and Land Cover Mapping: A Systematic Review.
Remote. Sens., 2020
SAR Data for Land Use Land Cover Classification in a Tropical Region with Frequent Cloud Cover.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
Applying A Phenological Object-Based Image Analysis (Phenobia) for Agricultural Land Classification: A Study Case in the Brazilian Cerrado.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
Combining Deep Learning and Prior Knowledge for Crop Mapping in Tropical Regions from Multitemporal SAR Image Sequences.
Remote. Sens., 2019
Detailed agricultural land classification in the Brazilian cerrado based on phenological information from dense satellite image time series.
Int. J. Appl. Earth Obs. Geoinformation, 2019
Comparing Phenometrics Extracted From Dense Landsat-Like Image Time Series for Crop Classification.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Proceedings of the Computational Science and Its Applications - ICCSA 2019, 2019
2018
Campo Verde Database: Seeking to Improve Agricultural Remote Sensing of Tropical Areas.
IEEE Geosci. Remote. Sens. Lett., 2018
Use of MSI/Sentinel-2 and airborne LiDAR data for mapping vegetation and studying the relationships with soil attributes in the Brazilian semi-arid region.
Int. J. Appl. Earth Obs. Geoinformation, 2018
Int. J. Appl. Earth Obs. Geoinformation, 2018
2017
A Comparative Analysis of Deep Learning Techniques for Sub-Tropical Crop Types Recognition from Multitemporal Optical/SAR Image Sequences.
Proceedings of the 30th SIBGRAPI Conference on Graphics, Patterns and Images, 2017
Spatial-temporal conditional random field based model for crop recognition in tropical regions.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017
2016
Remote. Sens., 2016
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.
Proceedings of the XVII Brazilian Symposium on Geoinformatics, 2016
2015
Self-Guided Segmentation and Classification of Multi-Temporal Landsat 8 Images for Crop Type Mapping in Southeastern Brazil.
Remote. Sens., 2015
2011
Pattern Recognit. Lett., 2011
2008
Proceedings of the SIBGRAPI 2008, 2008