Gleyce Kelly Dantas Araújo Figueiredo

Orcid: 0000-0002-5017-8320

According to our database1, Gleyce Kelly Dantas Araújo Figueiredo authored at least 11 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Mapping Integrated Crop-Livestock Systems Using Fused Sentinel-2 and PlanetScope Time Series and Deep Learning.
Remote. Sens., April, 2024

2023
SAR and Optical Data Applied to Early-Season Mapping of Integrated Crop-Livestock Systems Using Deep and Machine Learning Algorithms.
Remote. Sens., February, 2023

Imputation of Missing Parts in UAV Orthomosaics Using PlanetScope and Sentinel-2 Data: A Case Study in a Grass-Dominated Area.
ISPRS Int. J. Geo Inf., 2023

2022
Nitrogen variability assessment of pasture fields under an integrated crop-livestock system using UAV, PlanetScope, and Sentinel-2 data.
Comput. Electron. Agric., 2022

Estimating pasture aboveground biomass under an integrated crop-livestock system based on spectral and texture measures derived from UAV images.
Comput. Electron. Agric., 2022

2021
Evaluation of Time Series Gap-Filling of Venµs Satellite for Land Use Classification.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

Deep Neural Networks for Mapping Integrated Crop-Livestock Systems Using Planetscope Time Series.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021

2020
Monitoring Pasture Aboveground Biomass and Canopy Height in an Integrated Crop-Livestock System Using Textural Information from PlanetScope Imagery.
Remote. Sens., 2020

Choosing pasture maps: An assessment of pasture land classification definitions and a case study of Brazil.
Int. J. Appl. Earth Obs. Geoinformation, 2020

2019
Classification of Crops, Pastures, and Tree Plantations along the Season with Multi-Sensor Image Time Series in a Subtropical Agricultural Region.
Remote. Sens., 2019

Comparison of Pasture Areas Over Brazil Biomes Using Global And National Land Cover Maps.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019


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