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Mário Cunha
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- affiliation: University of Porto, Portugal
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2020 – today
- 2024
- [j19]Manuel F. Silva, C. Queirós, M. Pereira, Tatiana M. Pinho, Teresa Barroso, Sandro Magalhães, J. Boaventura, Filipe Santos
, Mário Cunha
Precision Fertilization: A critical review analysis on sensing technologies for nitrogen, phosphorous and potassium quantification. Comput. Electron. Agric. 224: 109220 (2024) - 2023
- [j18]Marcos Norberto, Neftalí Sillero
Filling the maize yield gap based on precision agriculture - A MaxEnt approach. Comput. Electron. Agric. 211: 107970 (2023) - [c8]Daniel Queirós da Silva
Assessing Soil Ripping Depth for Precision Forestry with a Cost-Effective Contactless Sensing System. ROBOT (2) 2023: 297-310 - 2022
- [j17]Rui Costa Martins, Teresa Barroso
Unscrambling spectral interference and matrix effects in Vitis vinifera Vis-NIR spectroscopy: Towards analytical grade 'in vivo' sugars and acids quantification. Comput. Electron. Agric. 194: 106710 (2022) - [j16]Yahui Guo
Machine Learning-Based Approaches for Predicting SPAD Values of Maize Using Multi-Spectral Images. Remote. Sens. 14(6): 1337 (2022) - 2021
- [j15]Patrícia Lourenço, Ana C. Teodoro
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 95: 102263 (2021) - [j14]Bruno Marcos
A Framework for Multi-Dimensional Assessment of Wildfire Disturbance Severity from Remotely Sensed Ecosystem Functioning Attributes. Remote. Sens. 13(4): 780 (2021) - [j13]Yahui Guo
Integrating Spectral and Textural Information for Monitoring the Growth of Pear Trees Using Optical Images from the UAV Platform. Remote. Sens. 13(9): 1795 (2021) - [j12]Sandro Augusto Magalhães
Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse. Sensors 21(10): 3569 (2021) - [c7]Tiago Cerveira Padilha
Tomato Detection Using Deep Learning for Robotics Application. EPIA 2021: 27-38 - [c6]Pedro Moreira, Lia Duarte
Modeling Spatial-Temporal Wine Yield Based on Land Surface Temperature, Vegetation Indices and GIS - The Case of the Douro Wine Region. IGARSS 2021: 6431-6434 - [i1]Sandro Augusto Magalhães, Luís Castro, Germano Moreira, Filipe Neves dos Santos, Mário Cunha, Jorge Dias, António Paulo Moreira:
Evaluating the Single-Shot MultiBox Detector and YOLO Deep Learning Models for the Detection of Tomatoes in a Greenhouse. CoRR abs/2109.00810 (2021) - 2020
- [j11]Sosdito Mananze, Isabel Pôças
Mapping and Assessing the Dynamics of Shifting Agricultural Landscapes Using Google Earth Engine Cloud Computing, a Case Study in Mozambique. Remote. Sens. 12(8): 1279 (2020)
2010 – 2019
- 2019
- [j10]Bruno Marcos
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 78: 77-85 (2019) - [j9]André R. S. Marçal, Mario Cunha
Development of an image-based system to assess agricultural fertilizer spreader pattern. Comput. Electron. Agric. 162: 380-388 (2019) - [c5]Pedro Moura
Estimation of Vineyard Productivity Map Considering a Cost-Effective LIDAR-Based Sensor. EPIA (1) 2019: 121-133 - 2018
- [j8]Lia Duarte
QPhenoMetrics: An open source software application to assess vegetation phenology metrics. Comput. Electron. Agric. 148: 82-94 (2018) - [j7]Sosdito Mananze
Retrieval of Maize Leaf Area Index Using Hyperspectral and Multispectral Data. Remote. Sens. 10(12): 1942 (2018) - 2017
- [j6]Isabel Pôças
Hyperspectral-based predictive modelling of grapevine water status in the Portuguese Douro wine region. Int. J. Appl. Earth Obs. Geoinformation 58: 177-190 (2017) - 2015
- [j5]Isabel Pôças
Estimation of Actual Crop Coefficients Using Remotely Sensed Vegetation Indices and Soil Water Balance Modelled Data. Remote. Sens. 7(3): 2373-2400 (2015) - [j4]Isabel Pôças
Predicting Grapevine Water Status Based on Hyperspectral Reflectance Vegetation Indices. Remote. Sens. 7(12): 16460-16479 (2015) - 2014
- [j3]Mario Cunha
A Time-Frequency Analysis on the Impact of Climate Variability on Semi-Natural Mountain Meadows. IEEE Trans. Geosci. Remote. Sens. 52(10): 6156-6164 (2014) - 2013
- [j2]Isabel Pocas
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 21: 159-172 (2013) - [j1]Arlete Rodrigues
Monitoring Vegetation Dynamics Inferred by Satellite Data Using the PhenoSat Tool. IEEE Trans. Geosci. Remote. Sens. 51(4-1): 2096-2104 (2013) - 2012
- [c4]Arlete Rodrigues
Phenology parameter extraction from time-series of satellite vegetation index data using phenosat. IGARSS 2012: 4926-4929 - 2010
- [c3]Mario Cunha
Evaluating MODIS vegetation indices using ground based measurements in mountain semi-natural meadows of Northeast Portugal. IGARSS 2010: 1525-1528 - [c2]André R. S. Marçal, Arlete Rodrigues
Evaluation of satellite image segmentation using synthetic images. IGARSS 2010: 2210-2213
2000 – 2009
- 2009
- [c1]André R. S. Marçal, Arlete Rodrigues
The Synthetic Image Testing Framework (SITEF) for the Evaluation of Multi-spectral Image Segmentation Algorithms. IGARSS (4) 2009: 236-239
Coauthor Index
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