Spectral features associated with nitrogen, phosphorus, and potassium deficiencies in Eucalyptus saligna seedling leaves

Ponzoni, Flávio Jorge; Gonçalves, José Leonardo de Moraes

doi:10.1080/014311699212236

Cited by 66 publications

(25 citation statements)

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“…4(b) shows the percent reflectance of In most cases, an increase in reflectance from 440 to 560 nm and a sharp increase from 675 to 755 nm (red shift) were observed for all deficiency treatments in the greenhouse, however, in the growth chamber a decrease in reflectance in the VI range (P) and in the IR range (K and Ca) was observed. Ponzoni and Goncalves (1999) reported that reflectance values for K and P were significantly lower in the visible range. The results of nutrient deficiencies increasing wheat reflectance are consistent with earlier reports by Masoni et al (1996).…”

Section: Reflectancementioning

confidence: 97%

Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency

Ayala-Silva

Beyl

2005

Advances in Space Research

120

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Section: Reflectancementioning

confidence: 97%

Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency

Ayala-Silva

Beyl

2005

Advances in Space Research

120

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“…The majority of studies have utilized field spectroradiometers to predict P in agricultural fields [23,24] and P and K in the foliage of giant sequoia and eucalyptus trees [25,26]. P, K, Mg and Ca concentrations have been examined in savannah grasses [27] as well as for willow, olive, grass and heather foliage [28].…”

Section: Introductionmentioning

confidence: 99%

Prediction of Macronutrients at the Canopy Level Using Spaceborne Imaging Spectroscopy and LiDAR Data in a Mixedwood Boreal Forest

et al. 2015

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Information on foliar macronutrients is required in order to understand plant physiological and ecosystem processes such as photosynthesis, nutrient cycling, respiration and cell wall formation. The ability to measure, model and map foliar macronutrients (nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg)) at the forest canopy level provides information on the spatial patterns of ecosystem processes (e.g., carbon exchange) and provides insight on forest condition and stress. Imaging spectroscopy (IS) has been used particularly for modeling N, using airborne and satellite imagery mostly in temperate and tropical forests. However, there has been very little research conducted at these scales to model P, K, Ca, and Mg and few studies have focused on boreal forests. We report results of a study of macronutrient modeling using spaceborne IS and airborne light OPEN ACCESSRemote Sens. 2015, 7 9046 detection and ranging (LiDAR) data for a mixedwood boreal forest canopy in northern Ontario, Canada. Models incorporating Hyperion data explained approximately 90% of the variation in canopy concentrations of N, P, and Mg; whereas the inclusion of LiDAR data significantly improved the prediction of canopy concentration of Ca (R 2 = 0.80). The combined used of IS and LiDAR data significantly improved the prediction accuracy of canopy Ca and K concentration but decreased the prediction accuracy of canopy P concentration. The results indicate that the variability of macronutrient concentration due to interspecific and functional type differences at the site provides the basis for the relationship observed between the remote sensing measurements (i.e., IS and LiDAR) and macronutrient concentration. Crown closure and canopy height are the structural metrics that establish the connection between macronutrient concentration and IS and LiDAR data, respectively. The spatial distribution of macronutrient concentration at the canopy scale mimics functional type distribution at the site. The ability to predict canopy N, P, K, Ca and Mg in this study using only IS, only LiDAR or their combination demonstrates the excellent potential for mapping these macronutrients at canopy scales across larger geographic areas into the next decade with the launch of new IS satellite missions and by using spaceborne LiDAR data.

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“…The reflectance of the leaf water content is measured by the wavelengths of 1.45-1.93 µm (Thomas et al 1971) and it was not discussed in this paper. In spite of Ponzoni and Gonçalves (1999) having recommended the usage of larger spectral bands, it should be interesting to consider the possibility to obtain orbital hyperspectral (Hyperion data, for instance) from mangrove areas. Considering the greater amount of mangroves spectra that could be extracted from the hyperspectral images, statistical procedures like those utilized by Galvão et al (2005), for example, could be applied in the entire spectral range data in order to identify differences or similarities between mangroves canopies.…”

mentioning

confidence: 99%

“…It was determined averages from each of those 42 repetitions, for each species, in each of these four spectral bands. The option of large spectral bands in spite of the fine SPECTRON SE-590 spectral resolution was based on Ponzoni and Gonçalves (1999) that compared the results achieved using large spectral bands and SPEC-TRON SE-590 fine ones in DHRF of Eucalyptus saligna detached leaves. The authors found no differences using both spectral resolutions on an ANOVA statistical procedure.…”

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confidence: 99%

Spectral characterization of mangrove leaves in the Brazilian Amazonian Coast: Turiaçu Bay, Maranhão State

Rebelo-Mochel

Ponzoni

2007

An. Acad. Bras. Ciênc.

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Mangrove communities are tropical systems which have fewer species than tropical forests, especially in Latin America and display a single architecture, usually lacking the various strata commonly found in other forest ecosystems. The identification of mangrove communities by orbital data is not a difficult task but the most interesting challenge is to identify themselves by the dominant species. The first step toward that floristic identification is the spectral characterization of detached leaves. Leaves from four species of mangrove trees were spectrally characterized considering the Directional Hemispherical Reflectance Factor (DHRF) determined through radiometric measurements using an integrating sphere LICOR 1800 attached to a spectroradiometer SPECTRON SE-590. In the visible bands (0.45-0.69 µm) the button-shaped mangrove Conocarpus erectus was brighter and the red mangrove Rhizophora mangle was darker than the other two species which shows very close DHRF values. Otherwise the black mangrove Avicennia germinans and the white mangrove Laguncularia racemosa can be distinguished from one another in the Near Infra Red (NIR) region (0.76-0.90 µm and in this region of the spectrum the DHRF of C. erectus and R. mangle become very close.

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Spectral features associated with nitrogen, phosphorus, and potassium deficiencies in Eucalyptus saligna seedling leaves

Cited by 66 publications

References 0 publications

Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency

Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency

Prediction of Macronutrients at the Canopy Level Using Spaceborne Imaging Spectroscopy and LiDAR Data in a Mixedwood Boreal Forest

Spectral characterization of mangrove leaves in the Brazilian Amazonian Coast: Turiaçu Bay, Maranhão State

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