Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloA Comparison of Algorithms for Retrieving Soil Moisture From ENVISAT/ASAR Images
Anno di pubblicazione2008
Formato
  • Elettronico
  • Cartaceo
Autore/iPaloscia S.; P.Pampaloni; S.Pettinato; E.Santi
Affiliazioni autoriCNR-IFAC
Autori CNR e affiliazioni
  • SIMONE PETTINATO
  • EMANUELE SANTI
  • SIMONETTA PALOSCIA
  • PAOLO PAMPALONI
Lingua/e
  • inglese
AbstractIn this paper, we present an intercomparison of algorithms for retrieving soil moisture content (SMC) from ENVIronmental SATtellite (ENVISAT)/Advanced Synthetic Aperture Radar images. The algorithms taken into consideration were a feedforward artificial neural network (ANN) with two hidden layers, a statistical approach based on Bayes' theorem, and an iterative algorithm based on the nelder-mead direct-search method. The comparison was carried out by using both simulated and experimental data. Simulated data were obtained by means of the integral equation model (IEM). Experimental data were collected in an agricultural area in Northern Italy during 2003-2005; they included backscattering coefficient at HH and HV polarizations and at an incidence angle of thetas = 23deg, as well as detailed ground truth measurements of SMC, surface roughness, and vegetation parameters. HH-polarized data were related to SMC, whereas the information of the cross-polarized channel was used to correct the backscatter for the effects of surface roughness. A comparison of the algorithms with experimental data showed that all the tested approaches produced SMC values that are very close to the measured ones. However, the predictions of the ANN were slightly more suitable than the other methods for generating maps in reasonable time. The production of moisture maps carried out at different dates using this algorithm pointed out the feasibility of separating up to six levels of spatial/temporal variations of SMC in the range of 10%-35%.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da3274
Pagine a3284
Pagine totali11
RivistaIEEE transactions on geoscience and remote sensing
Attiva dal 1980
Editore: Institute of Electrical and Electronics Engineers, - New York, N.Y.
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 0196-2892
Titolo chiave: IEEE transactions on geoscience and remote sensing
Titolo proprio: IEEE transactions on geoscience and remote sensing
Titolo abbreviato: IEEE trans. geosci. remote sens.
Titoli alternativi:
  • Institute of Electrical and Electronics Engineers transactions on geoscience and remote sensing
  • I.E.E.E. transactions on geoscience and remote sensing
  • Transactions on geoscience and remote sensing
Numero volume della rivista46/10
Fascicolo della rivista-
DOI-
Verificato da refereeSì: Internazionale
Stato della pubblicazione-
Indicizzazione (in banche dati controllate)-
Parole chiaveENVISAT/ASAR, soil moisture maps, retrieval algorithms
Link (URL, URI)-
Titolo parallelo-
Licenza-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioni-
Strutture CNR
  • IFAC — Istituto di fisica applicata "Nello Carrara"
Moduli/Attività/Sottoprogetti CNR
  • TA.P06.007.001 : Telerilevamento a microonde con sensori attivi e passivi
Progetti Europei-
Allegati
Paloscia_2008 (documento privato )
Descrizione: pdf
Tipo documento: application/pdf

Dati associati a vecchie tipologie
I dati associati a vecchie tipologie non sono modificabili, derivano dal cambiamento della tipologia di prodotto e hanno solo valore storico.
Editore
  • IEEE-Institute Of Electrical And Electronics Engineers Inc., Piscataway (Stati Uniti d'America)

Dati storici
I dati storici non sono modificabili, sono stati ereditati da altri sistemi (es. Gestione Istituti, PUMA, ...) e hanno solo valore storico.
Area disciplinareEarth Sciences
Area valutazione CIVRScienze della Terra
Rivista ISIIEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING [03091J0]