Egidio Arai
According to our database1,
Egidio Arai
authored at least 27 papers
between 2004 and 2024.
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Bibliography
2024
Variation of Water Cover in Amazon Biome During Year 2023 Seen by Remote Sensor Data.
Proceedings of the IGARSS 2024, 2024
Classifying Forest Degradation by Fire and Selective Logging in Mato Grosso State, Brazilian Amazon, Using Sentinel-2 MSI and Landsat OLI Sensor Data.
Proceedings of the IGARSS 2024, 2024
2023
Land use and Land Cover Classification in São Paulo, Brazil, Using Landsat-8 Oli Images and Derived Spectral Indices.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
Fraction Images Derived from Landsat Mss, TM and Oli Images for Monitoring Forest Cover at the Rondônia State, Brazilian Amazon.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023
2022
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Mapping and Monitoring Forest Plantation using Fraction Images Derived from Multi-Annual Landsat TM Datasets.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
2021
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
2020
Discriminating Land Use and Land Cover Classes in Brazil Based on the Annual PROBA-V 100 m Time Series.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2020
Mapping Burned Areas of Mato Grosso State Brazilian Amazon Using Multisensor Datasets.
Remote. Sens., 2020
Vegetation Fraction Images Derived from PROBA-V Data for Rapid Assessment of Annual Croplands in Brazil.
Remote. Sens., 2020
Land Use and Land Cover Mapping Using Fraction Images Derived from Annual VIIRS-NPP Dataset.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
Determining a Threshold to Delimit the Amazonian Forests from the Tree Canopy Cover 2000 GFC Data.
Sensors, 2019
Assessment of Land Use Land Cover in Brazil, South America, Using Fraction Images Derived from Proba-V Datasets.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Detection and Analysis of Forest Degradation by Fire Using Landsat/Oli Images in Google Earth Engine.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
Proceedings of the XX Brazilian Symposium on Geoinformatics, 2019
Spatiotemporal Distribution of Clouds Observed by MODIS Quality Assurance in the Brazilian Northeast.
Proceedings of the XX Brazilian Symposium on Geoinformatics, 2019
2018
Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series.
Int. J. Appl. Earth Obs. Geoinformation, 2018
Metodologia para Classificacao Subpixel de Imagens MODIS Com Base em Classificacao de Imagem de Maior Resolucao.
Proceedings of the XIX Brazilian Symposium on Geoinformatics, 2018
2017
An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon.
Int. J. Appl. Earth Obs. Geoinformation, 2017
Monitoring deforestation and forest degradation using multi-temporal fraction images derived from Landsat sensor data in the Brazilian Amazon.
Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, 2017
2016
Remote. Sens., 2016
2015
A new 500-m resolution map of canopy height for Amazon forest using spaceborne LiDAR and cloud-free MODIS imagery.
Int. J. Appl. Earth Obs. Geoinformation, 2015
2011
A Multi-Resolution Multi-Temporal Technique for Detecting and Mapping Deforestation in the Brazilian Amazon Rainforest.
Remote. Sens., 2011
2010
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010
2009
Mapping and Monitoring Land Cover in Acre State, Brazilian Amazônia, using Multitemporal Remote Sensing Data.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2009
2004
Deforestation detection in Brazilian Amazon region in a near real time using Terra MODIS daily data.
Proceedings of the 2004 IEEE International Geoscience and Remote Sensing Symposium, 2004