Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem). (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem). (Articolo in rivista) (literal)

Anno

• 2001-01-01T00:00:00+01:00 (literal)

Alternative label

• Leone A.P., Escadafal R (2001)
  Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem).
  in International journal of remote sensing (Print)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Leone A.P., Escadafal R (literal)

Pagina inizio

• 2311 (literal)

Pagina fine

• 2328 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 22 (literal)

Rivista

• International journal of remote sensing (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• IF 0,827 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo

• 12 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• Munsell hue, value and chroma of 69 surface soil samples were both visually estimated by four observers under diffuse daylight and computed from laboratory reflectance spectra by applying the CIE 1931 standard method. Significant relationships were found between ‘observed’ and ‘computed’ colour components, and between the latter and some soil properties. Using a correspondence analysis, an important contribution of soil colour on differentiating soil types was then demonstrated. From the original spectra, the visible bands of the MIVIS hyperspectral sensor were simulated and related to the colour components through single and multiple regression analyses. The R2 for hue, value and chroma was 0.58, 0.81 and 0.87, respectively. Results were compared with those obtained using the simulated visible TM bands. For each sample, a curve was fitted to both the MIVIS and TM bands. From these curves, values of colour components were computed and compared with those obtained from the original spectra. Results showed a clear improvement on colour determination. Nevertheless, the complexity and variability of the best fitting curves makes this approaches difficult to apply to the images. Remote sensing of soil colour is expected to improve with the launch in the future of higher resolution hyperspectral sensors. (literal)

Note

• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Antonio.P. Leone, Italian National Research Council (CNR) - Institute for Agro-forestry Systems, Ercolano, Italy. Richard Escadafal, Institut de Recherche pour le Développement, Paris, France, detached scientist at EGEO-SAI, JRC, Ispra, Italy (literal)

Titolo

• Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem). (literal)

Abstract

• Munsell hue, value and chroma of 69 surface soil samples were both visually estimated by four observers under diffuse daylight and computed from laboratory reflectance spectra by applying the CIE 1931 standard method. Significant relationships were found between ‘observed’ and ‘computed’ colour components, and between the latter and some soil properties. Using a correspondence analysis, an important contribution of soil colour on differentiating soil types was then demonstrated. From the original spectra, the visible bands of the MIVIS hyperspectral sensor were simulated and related to the colour components through single and multiple regression analyses. The R2 for hue, value and chroma was 0.58, 0.81 and 0.87, respectively. Results were compared with those obtained using the simulated visible TM bands. For each sample, a curve was fitted to both the MIVIS and TM bands. From these curves, values of colour components were computed and compared with those obtained from the original spectra. Results showed a clear improvement on colour determination. Nevertheless, the complexity and variability of the best fitting curves makes this approaches difficult to apply to the images. Remote sensing of soil colour is expected to improve with the launch in the future of higher resolution hyperspectral sensors. (literal)

Prodotto di

• Institute for Agricultural and Forest Systems in the Mediterranean (ISAFoM) (Istituto)

Autore CNR

• ANTONIO PASQUALE LEONE (Unità di personale interno)

Insieme di parole chiave

• Keywords of "Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem)." (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute for Agricultural and Forest Systems in the Mediterranean (ISAFoM) (Istituto)

Autore CNR di

• ANTONIO PASQUALE LEONE (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• International journal of remote sensing (Rivista)

Insieme di parole chiave di

• Keywords of "Statistical analysis of soil colour and spectroradiometric data for hyperspectral remote sensing of soil properties (example in a southern Italy Mediterranean ecosystem)." (Insieme di parole chiave)