Mário Cunha
Orcid: 0000-0002-8299-324XAffiliations:
- University of Porto, Portugal
According to our database1,
Mário Cunha
authored at least 25 papers
between 2009 and 2023.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2023
Comput. Electron. Agric., August, 2023
2022
Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images.
Remote. Sens., 2022
Unscrambling spectral interference and matrix effects in <i>Vitis vinifera</i> Vis-NIR spectroscopy: Towards analytical grade 'in vivo' sugars and acids quantification.
Comput. Electron. Agric., 2022
2021
Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse.
Sensors, 2021
A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes.
Remote. Sens., 2021
Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform.
Remote. Sens., 2021
Assessing the performance of different OBIA software approaches for mapping invasive alien plants along roads with remote sensing data.
Int. J. Appl. Earth Obs. Geoinformation, 2021
Modeling Spatial-Temporal Wine Yield Based on Land Surface Temperature, Vegetation Indices and GIS - The Case of the Douro Wine Region.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2021
Proceedings of the Progress in Artificial Intelligence, 2021
2020
Mapping and Assessing the Dynamics of Shifting Agricultural Landscapes Using Google Earth Engine Cloud Computing, a Case Study in Mozambique.
Remote. Sens., 2020
2019
Development of an image-based system to assess agricultural fertilizer spreader pattern.
Comput. Electron. Agric., 2019
Improving the detection of wildfire disturbances in space and time based on indicators extracted from MODIS data: a case study in northern Portugal.
Int. J. Appl. Earth Obs. Geoinformation, 2019
Estimation of Vineyard Productivity Map Considering a Cost-Effective LIDAR-Based Sensor.
Proceedings of the Progress in Artificial Intelligence, 2019
2018
Remote. Sens., 2018
QPhenoMetrics: An open source software application to assess vegetation phenology metrics.
Comput. Electron. Agric., 2018
2017
Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region.
Int. J. Appl. Earth Obs. Geoinformation, 2017
2015
Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices.
Remote. Sens., 2015
Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data.
Remote. Sens., 2015
2014
A Time-Frequency Analysis on the Impact of Climate Variability on Semi-Natural Mountain Meadows.
IEEE Trans. Geosci. Remote. Sens., 2014
2013
IEEE Trans. Geosci. Remote. Sens., 2013
Using remote sensing energy balance and evapotranspiration to characterize montane landscape vegetation with focus on grass and pasture lands.
Int. J. Appl. Earth Obs. Geoinformation, 2013
2012
Phenology parameter extraction from time-series of satellite vegetation index data using phenosat.
Proceedings of the 2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
2010
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010
Evaluating MODIS vegetation indices using ground based measurements in mountain semi-natural meadows of Northeast Portugal.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2010
2009
The Synthetic Image Testing Framework (SITEF) for the Evaluation of Multi-spectral Image Segmentation Algorithms.
Proceedings of the IEEE International Geoscience & Remote Sensing Symposium, 2009