English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/121400
Compartir / Impacto:
Estadísticas
Add this article to your Mendeley library MendeleyBASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Título

CLUAS: Assessment of Trees/ Trees Orchards Characteristic For Precision Agriculture

Otros títulosEl programa informático “Clustering Assessment IDL.IAS.1” para el agrupamiento e integración de píxeles contiguos en imágenes remotas
AutorGarcía Torres, Luis ; Peña Barragán, José Manuel ; López Granados, Francisca ; Jurado-Expósito, Montserrat
Palabras claveCLUAS
Fecha de publicaciónjun-2006
ResumenA research group of the Institute for Sustainable Agriculture (CSIC, Cordoba, Spain) has developed a procedure to spatially assess key agronomic and environmental characteristics of tree orchards from remote sensing images through the software named Clustering Assessment® (CLUAS).
In the attached paper the CLUAS software development and the information generated by for selected olive orchards and its validation with ground-truth data is shown. CLUAS works as an add-on of ENVI®, and operates integrating the digital values (DV) of the neighboring pixels within a defined range of DV. In the orchards plots trees, other vegetation cover and bare soil were the land uses considered and the range of digital values (BDV) which best define each of them determined. CLUAS provides parameters of each tree, such as the geometric centre, the number of pixels or area, and the integrated digital values or relative potential yield. CLUAS also characterizes key parameters of tree groves, such as the total area and the number, area and the relative potential productivity of the whole trees; and similarly for the other land uses such as vegetation cover and bare soil. Remote images with spatial resolution from 0.25 to 1.5m were suitable for olive grove characterization.
CLUAS can contribute to the site-specific management of tree groves, providing quantitative information on each tree, small areas of an orchard, or whole orchards.
DescripciónContiene 7 documentos (1. Objetivos, alcance y publicaciones. 2. Registro y código) y 5 con el software
URIhttp://hdl.handle.net/10261/121400
ReferenciasGarcía Torres, Luis, Peña Barragán, José Manuel, López Granados, Francisca, Jurado-Expósito, Montserrat. Procedimiento para la obtención automática de indicadores agronómicos y ambientales de plantaciones de árboles mediante teledetección. http://hdl.handle.net/10261/121403
García Torres, Luis, Peña Barragán, José Manuel, López Granados, Francisca, Jurado-Expósito, Montserrat. Procedimiento para la obtención automática de indicadores agronómicos y ambientales de plantaciones de árboles mediante teledetección. http://hdl.handle.net/10261/121404
García Torres, Luis, Peña Barragán, José Manuel, López Granados, Francisca, Jurado-Expósito, Montserrat,Fernández-Escobar, R. Automatic assessment of agro-environmental indicators from remotely sensed images of tree orchards and its evaluation using olive plantations. 10.1016/j.compag.2007.11.004. http://hdl.handle.net/10261/121405
Gómez-Candón, David, López Granados, Francisca, Caballero Novella, Juan José, Jurado-Expósito, Montserrat, García Torres, Luis. Caracterización cuantitativa del olivar mediante teledetección. http://hdl.handle.net/10261/121413
García Torres, Luis, Peña Barragán, José Manuel, Gómez-Candón, David, López Granados, Francisca, Jurado-Expósito, Montserrat. CLUAS® : A software for managing remotely sensed imagery of orchard plantations for precision agricultura. http://hdl.handle.net/10261/121424
García Torres, Luis, Peña Barragán, José Manuel, López Granados, Francisca, Jurado-Expósito, Montserrat. CLUAS Software® for managing remote images for precision agricultura. http://hdl.handle.net/10261/121433
Aparece en las colecciones: (IAS) Programas informáticos
Mostrar el registro completo
 


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.