Veraldo Liesenberg
Orcid: 0000-0003-0564-7818
According to our database1,
Veraldo Liesenberg
authored at least 34 papers
between 2009 and 2023.
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Bibliography
2023
Application of Hydro-Based Morphological Models for Environmental Assessment of Watersheds.
ISPRS Int. J. Geo Inf., July, 2023
Insights for Estimating and Predicting Reservoir Sedimentation Using the RUSLE-SDR Approach: A Case of Darbandikhan Lake Basin, Iraq-Iran.
Remote. Sens., February, 2023
2022
Active Fire Mapping on Brazilian Pantanal Based on Deep Learning and CBERS 04A Imagery.
Remote. Sens., 2022
Characterizing Biophysical Attributes in Tropical Secondary Forest Environments with Multitemporal Hyperspectral Images.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2022
2021
Semantic Segmentation of Tree-Canopy in Urban Environment with Pixel-Wise Deep Learning.
Remote. Sens., 2021
Benefits of Combining ALOS/PALSAR-2 and Sentinel-2A Data in the Classification of Land Cover Classes in the Santa Catarina Southern Plateau.
Remote. Sens., 2021
New Insight on Soil Loss Estimation in the Northwestern Region of the Zagros Fold and Thrust Belt.
ISPRS Int. J. Geo Inf., 2021
Ecol. Informatics, 2021
Average-DInSAR method for unstable escarpments detection induced by underground coal mining.
Int. J. Appl. Earth Obs. Geoinformation, 2021
2020
Applying Fully Convolutional Architectures for Semantic Segmentation of a Single Tree Species in Urban Environment on High Resolution UAV Optical Imagery.
Sensors, 2020
Discriminating Forest Successional Stages, Forest Degradation, and Land Use in Central Amazon Using ALOS/PALSAR-2 Full-Polarimetric Data.
Remote. Sens., 2020
A Machine Learning Framework to Predict Nutrient Content in Valencia-Orange Leaf Hyperspectral Measurements.
Remote. Sens., 2020
A Machine Learning Approach for Mapping Forest Vegetation in Riparian Zones in an Atlantic Biome Environment Using Sentinel-2 Imagery.
Remote. Sens., 2020
ISPRS Int. J. Geo Inf., 2020
A CNN Approach to Simultaneously Count Plants and Detect Plantation-Rows from UAV Imagery.
CoRR, 2020
2019
Assessment of CNN-Based Methods for Individual Tree Detection on Images Captured by RGB Cameras Attached to UAVs.
Sensors, 2019
Tree Species Classification in a Highly Diverse Subtropical Forest Integrating UAV-Based Photogrammetric Point Cloud and Hyperspectral Data.
Remote. Sens., 2019
Application of DInSAR-PSI Technology for Deformation Monitoring of the Mosul Dam, Iraq.
Remote. Sens., 2019
Predicting Canopy Nitrogen Content in Citrus-Trees Using Random Forest Algorithm Associated to Spectral Vegetation Indices from UAV-Imagery.
Remote. Sens., 2019
Modeling Hyperspectral Response of Water-Stress Induced Lettuce Plants Using Artificial Neural Networks.
Remote. Sens., 2019
Optical and SAR Remote Sensing Synergism for Mapping Vegetation Types in the Endangered Cerrado/Amazon Ecotone of Nova Mutum - Mato Grosso.
Remote. Sens., 2019
Estimating Pasture Biomass and Canopy Height in Brazilian Savanna Using UAV Photogrammetry.
Remote. Sens., 2019
Machine Learning Applied to Uav Imagery in Precision Agriculture and Forest Monitoring in Brazililian Savanah.
Proceedings of the 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019
2018
Multifrequency and Full-Polarimetric SAR Assessment for Estimating Above Ground Biomass and Leaf Area Index in the Amazon Várzea Wetlands.
Remote. Sens., 2018
Integration of Worldview-2 and Lidar Data to MAP a Subtropical Forest Area: Comparison of Machine Learning Algorithms.
Proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018
2017
Evaluating Sentinel-2 and Landsat-8 Data to Map Sucessional Forest Stages in a Subtropical Forest in Southern Brazil.
Remote. Sens., 2017
2016
Evaluating Moisture and Geometry Effects on L-Band SAR Classification Performance Over a Tropical Rain Forest Environment.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2016
2013
Multi-Temporal Airborne LiDAR-Survey and Field Measurements of Tropical Peat Swamp Forest to Monitor Changes.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2013
Evaluating SAR polarization modes at L-band for forest classification purposes in Eastern Amazon, Brazil.
Int. J. Appl. Earth Obs. Geoinformation, 2013
Optical and SAR sensor synergies for forest and land cover mapping in a tropical site in West Africa.
Int. J. Appl. Earth Obs. Geoinformation, 2013
2009
Possibilities of discriminating tropical secondary succession in Amazônia using hyperspectral and multiangular CHRIS/PROBA data.
Int. J. Appl. Earth Obs. Geoinformation, 2009
The Contribution of CHRIS/PROBA Data for Tropical Peat Swamp Landscape Discrimination Purposes.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2009