AGRIC-LASERUAV

Precision agricultural crop monitoring using laser scanning and unmanned aerial vehicles

 Coordinatore AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS 

 Organization address address: CALLE SERRANO 117
city: MADRID
postcode: 28006

contact info
Titolo: Mr.
Nome: Carlos Manuel
Cognome: Abad Ruiz
Email: send email
Telefono: -9475
Fax: -9536

 Nazionalità Coordinatore Spain [ES]
 Totale costo 154˙417 €
 EC contributo 154˙417 €
 Programma FP7-PEOPLE
Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call FP7-PEOPLE-2009-IIF
 Funding Scheme MC-IIF
 Anno di inizio 2011
 Periodo (anno-mese-giorno) 2011-02-01   -   2013-01-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS

 Organization address address: CALLE SERRANO 117
city: MADRID
postcode: 28006

contact info
Titolo: Mr.
Nome: Carlos Manuel
Cognome: Abad Ruiz
Email: send email
Telefono: -9475
Fax: -9536

ES (MADRID) coordinator 154˙417.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

forestry    detection    ground    time    uav    radiative    spatial    community    remote    imagery    sensing    vegetation    lidar    sustainable    agricultural    transfer   

 Obiettivo del progetto (Objective)

'Currently the science of the remote sensing community does not meet the stringent requirements of sustainable agriculture and forestry practices, where quasi-real-time decision making of irrigation management, fertilizer application and disease detection is needed. The two highlighted obstacles that the remote sensing community needs to overcome are: a) the high cost and operational limitations of airborne remote sensing for short turnaround time needed for agricultural applications, and b) the lack of detailed vegetation canopy structural information that can be used to bridge the gap between spectroscopic methods with 3D radiative transfer models. Recent remote sensing advancements have addressed these challenges using two recently-available, high-potential technological developments: a) Unmanned Aerial Vehicles (UAV) coupled with microsensors, and b) Ground-based Light Detection and Ranging (LiDAR) systems. The introduction of cost-effective UAV-based systems allows us to characterize individual trees within forested and agricultural ecosystems thereby highlighting novel scientific issues at new spatial scales. Such issues can potentially be addressed with terrestrial LiDAR systems that allow the characterization of spatial organization of tree crown elements from a ground-level perspective. As such, this project aims to couple the use of UAV-based imagery with ground-level LiDAR data to characterize important biophysical processes at unprecedented spatial and temporal resolutions, suitable for precision, and sustainable forestry/agricultural monitoring. The project will investigate the impact of vegetation architectural parameters, retrieved using a ground-based LiDAR scanner, on the quantitative estimation of physiological indicators of stress (i.e. evapotranspiration, and leaf chlorophyll content) using UAV-based spectral imagery and 3D radiative transfer modeling.'

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Determinants and dynamics of the obesity epidemic

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STRAINMAP (2008)

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