The crop growth stage represents essential information for agricultural areas management. In this study we investigate the feasibility of a tool based on remotely sensed satellite (Landsat 8) imagery, capable of automatically classify crop fields and how much resolution enhancement based on pan-sharpening techniques and phenological information extraction, useful to create decision rules that allow to identify semantic class to assign to an object, can effectively support the classification process. Moreover we investigate the opportunity to extract vegetation health status information from remotely sensed assessment of the equivalent water thickness (EWT). Our case study is the Kenya's Great Rift valley, in this area a ground truth campaign was conducted during August 2015 in order to collect crop fields GPS measurements, leaf area index (LAI) and chlorophyll samples

Developing a satellite based automatic system for crop monitoring: Kenya's Great Rift valley, a case study / Luciani, Roberto; Laneve, Giovanni; Jahjah, Munzer; Mito, Collins. - ELETTRONICO. - 740:(2016), pp. 168-171. (Intervento presentato al convegno Living Planet Symposium tenutosi a Praga nel Maggio).

Developing a satellite based automatic system for crop monitoring: Kenya's Great Rift valley, a case study

LUCIANI, ROBERTO;LANEVE, Giovanni;JAHJAH, munzer;
2016

Abstract

The crop growth stage represents essential information for agricultural areas management. In this study we investigate the feasibility of a tool based on remotely sensed satellite (Landsat 8) imagery, capable of automatically classify crop fields and how much resolution enhancement based on pan-sharpening techniques and phenological information extraction, useful to create decision rules that allow to identify semantic class to assign to an object, can effectively support the classification process. Moreover we investigate the opportunity to extract vegetation health status information from remotely sensed assessment of the equivalent water thickness (EWT). Our case study is the Kenya's Great Rift valley, in this area a ground truth campaign was conducted during August 2015 in order to collect crop fields GPS measurements, leaf area index (LAI) and chlorophyll samples
2016
Living Planet Symposium
Landsat 8; agriculture; Great Rift
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Developing a satellite based automatic system for crop monitoring: Kenya's Great Rift valley, a case study / Luciani, Roberto; Laneve, Giovanni; Jahjah, Munzer; Mito, Collins. - ELETTRONICO. - 740:(2016), pp. 168-171. (Intervento presentato al convegno Living Planet Symposium tenutosi a Praga nel Maggio).
File allegati a questo prodotto
File Dimensione Formato  
SP-740_toc.pdf

solo gestori archivio

Note: Lista contenuto pubblicazione ESA SP 740
Tipologia: Altro materiale allegato
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 628.09 kB
Formato Adobe PDF
628.09 kB Adobe PDF   Contatta l'autore
Luciani_developing_2016.pdf

accesso aperto

Tipologia: Documento in Post-print (versione successiva alla peer review e accettata per la pubblicazione)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 553.55 kB
Formato Adobe PDF
553.55 kB Adobe PDF

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/931225
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? ND
social impact