Mário Manuel de Miranda Furtado Campos Cunha


AuthID: R-000-CYC

Confirmed Publications: 149



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TITLE: Remote sensing for estimating and mapping single and basal crop coefficientes: A review on spectral vegetation indices approaches  Full Text
AUTHORS: Pocas, I; Calera, A; Campos, I; Cunha, M ;
PUBLISHED: 2020, SOURCE: AGRICULTURAL WATER MANAGEMENT, VOLUME: 233
INDEXED IN: Scopus WOS CrossRef: 125
IN MY: ORCID | CIÊNCIAVITAE
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TITLE: Toward a generalized predictive model of grapevine water status in Douro region from hyperspectral data  Full Text
AUTHORS: Pocas, I; Tosin, R ; Goncalves, I; Cunha, M ;
PUBLISHED: 2020, SOURCE: AGRICULTURAL AND FOREST METEOROLOGY, VOLUME: 280
INDEXED IN: Scopus WOS CrossRef: 29
IN MY: ORCID | CIÊNCIAVITAE
65
TITLE: A semi-automatic approach to derive land cover classification in soil loss models
AUTHORS: Duarte, L ; Teodoro, A ; Cunha, M ;
PUBLISHED: 2019, SOURCE: SPIE Conference on Earth Resources and Environmental Remote Sensing/GIS Applications X held at SPIE Remote Sensing Conference in EARTH RESOURCES AND ENVIRONMENTAL REMOTE SENSING/GIS APPLICATIONS X, VOLUME: 11156
INDEXED IN: Scopus WOS CrossRef: 1
IN MY: ORCID | CIÊNCIAVITAE
66
TITLE: Agricultural drought monitoring based on soil moisture derived from the optical trapezoid model in Mozambique
AUTHORS: Sosdito Mananze; Isabel Pocas ; Mario Cunha ;
PUBLISHED: 2019, SOURCE: JOURNAL OF APPLIED REMOTE SENSING, VOLUME: 13, ISSUE: 2
INDEXED IN: Scopus WOS CrossRef: 31
IN MY: ORCID | CIÊNCIAVITAE
67
TITLE: Development of an image-based system to assess agricultural fertilizer spreader pattern  Full Text
AUTHORS: MARCAL, ANDRE R.S. ; Cunha, M ;
PUBLISHED: 2019, SOURCE: COMPUTERS AND ELECTRONICS IN AGRICULTURE, VOLUME: 162
INDEXED IN: Scopus WOS DBLP CrossRef
IN MY: ORCID | CIÊNCIAVITAE
68
TITLE: Estimation of Vineyard Productivity Map Considering a Cost-Effective LIDAR-Based Sensor
AUTHORS: Moura, P ; Ribeiro, D; dos Santos, FN ; Gomes, A. ; Baptista, R ; Cunha, M ;
PUBLISHED: 2019, SOURCE: 19th EPIA Conference on Artificial Intelligence, EPIA 2019 in PROGRESS IN ARTIFICIAL INTELLIGENCE, EPIA 2019, PT I, VOLUME: 11804
INDEXED IN: Scopus WOS DBLP CrossRef: 1
IN MY: ORCID | CIÊNCIAVITAE
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TITLE: Machine Learning predictive model of grapevine yield based on agroclimatic patterns
AUTHORS: Sirsat, MS; Mendes Moreira, J ; Ferreira, C ; Cunha, M ;
PUBLISHED: 2019, SOURCE: Engineering in Agriculture, Environment and Food, VOLUME: 12, ISSUE: 4
INDEXED IN: Scopus CrossRef: 24
IN MY: ORCID | CIÊNCIAVITAE
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