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Visible and near-infrared (0.4–1.1 μm) analysis of arid and semiarid soils

Ben-Dor, E. ; Banin, A.

Remote sensing of environment, 1994-06, Vol.48 (3), p.261-274 [Periódico revisado por pares]

New York, NY: Elsevier Inc

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Título:
Visible and near-infrared (0.4–1.1 μm) analysis of arid and semiarid soils
Autor: Ben-Dor, E. ; Banin, A.
Assuntos: Agronomy. Soil science and plant productions ; ANALISIS DEL SUELO ; ANALYSE DE SOL ; ARID SOILS ; Biological and medical sciences ; Chemical, physicochemical, biochemical and biological properties ; CHIMIE DU SOL ; CONSTITUENTS ; Earth sciences ; Earth, ocean, space ; EQUATIONS ; ESPECTROMETRIA ; Exact sciences and technology ; FORECASTING ; FOTOGRAFIA ; Fundamental and applied biological sciences. Psychology ; INFRARED IMAGERY ; ISRAEL ; MATEMATICAS ; MATHEMATICS ; MATHEMATIQUE ; Mineral components. Ionic and exchange properties ; Mineralogy ; Mineralogy: general, methodology, regional studies ; PHOTOGRAPHIE ; PHOTOGRAPHY ; Physics, chemistry, biochemistry and biology of agricultural and forest soils ; PREDICTION ; QUIMICA DEL SUELO ; REFLECTANCE ; REFLECTANCIA ; REMOTE SENSING ; SOIL ANALYSIS ; SOIL CHEMISTRY ; Soil science ; SOIL TESTING ; SOL DE ZONE ARIDE ; SPECTRAL DATA ; SPECTROMETRIE ; SPECTROMETRY ; SUELO ARIDO ; TECHNIQUE DE PREVISION ; TECNICAS DE PREDICCION ; TELEDETECCION ; TELEDETECTION
É parte de: Remote sensing of environment, 1994-06, Vol.48 (3), p.261-274
Notas: 9452713
P33
Descrição: Near-infrared analysis (NIRA) methodology was applied to the reflectance spectra of arid and semiarid soils in the visible and near infrared (VIS-NIR; 0.4–1.1 μm) spectral region. The method is termed visible and near-infrared analysis (VNIRA). Although the spectra of the soils were characterized as monotonous and featureless, the methodology has yielded a prediction equation for estimating several soil constituents from the reflectance curves. The constituents were: CaCO 3, Fe 2O 3, Al 2O 3, SiO 2, LOI (lost-on-ignition), Fed (free iron oxides), and K 2O. Several mathematic manipulations were applied to the raw data in order to derive the optimal prediction equation. Spectral compression into 6, 8, 15, 71, and 350 spectral bands and a spectral derivation technique were applied to four separate soil groups, which were selected on the basis of their chemical characteristics. The wavelengths selected by the method for the optimal prediction equation were assigned to constituents that consisted of spectral features within the VIS-NIR region. An intercorrelation between spectrally featureless constituents and constituents with special features was found to be the major mechanism by which to predict constituents that had no spectral features within this part of the spectrum. It was shown that low spectral resolution is not necessarily a limiting factor in obtaining quantitative information about the chemistry of soil samples. All the examined soil constituents except Fed (which needed 700 spectral bands) required between 15 and 350 spectral bands for optimal prediction. It was concluded that the VIS-NIR (0.4–1.1 μm) is a suitable spectral region for obtaining quantitative information about soil chemistry. Although the VNIRA performance is not as precise as the chemical performance, the precision obtained is likely to be useful for rapid soil characterization and remote-sensing applications. We strongly recommend the use of both the VNIRA and the NIRA methods to better interpret high resolution remote-sensing data.
Editor: New York, NY: Elsevier Inc
Idioma: Inglês

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Visible and near-infrared (0.4–1.1 μm) analysis of arid and semiarid soils

Ben-Dor, E. ; Banin, A.

New York, NY: Elsevier Inc

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