Massimo Vincini

Multitemporal evaluation of topographic normalization methods on deciduous forest TM data

Five empirical and nonempirical parametric topographic normalization methods (the cosine, SCS, Minnaert, b correction, and c correction methods) were applied to multitemporal Landsat Thematic Mapper data (bands 1-5 and 7) collected in different periods of the growing season (April, June, and July) of a mixed deciduous forest area (340 ha) in the northern Apennines. The effectiveness of the models at removing topographic control, preserving internal data variability, and consistently normalizing radiance for flat pixels from band to band and image to image was evaluated. The entirely empirical b correction outperformed the other considered methods without relying on any photometric function.

Empirical Estimation of Leaf Chlorophyll Density in Winter Wheat Canopies Using Sentinel-2 Spectral Resolution

A comparison between the sensitivities to leaf chlorophyll density at the canopy scale of several vegetation indices (VIs) obtained at different spectral resolutions was carried out using spectral reflectance collected in winter wheat field trials with different nitrogen fertilization levels. A total of 350 spectra were collected from experimental plots at Feekes growth stages 5, 6, and 9 using a portable spectroradiometer (ASD FieldSpec HH), along with Minolta SPAD measurements of leaf optical thickness as a proxy for leaf chlorophyll density. Indices based on visible and near-infrared (NIR) bands were obtained from average reflectance in spectral ranges corresponding to SPOT HRG and Sentinel-2 (S2) bands. Indices requiring a red-edge band were obtained from reflectance at the originally proposed VI wavelengths using the 1.6-nm nominal spectral resolution bandwidth of the spectroradiometer and from average reflectance in the S2 red-edge bands with the closest spectral position to VI originally proposed wavelengths. Among VIs obtained from Sentinel-2 bands MERIS terrestrial chlorophyll index, red-edge position and triangular chlorophyll index/optimized soil adjusted VI ratio (TCI/OSAVI) indices, obtainable at 20-m spatial resolution from future S2 red-edge bands, and chlorophyll VI (CVI), obtainable at 10 m from visible and NIR bands, were the best estimators of winter wheat leaf chlorophyll density. The sensitivity of the best-performing indices obtained from S2 bands to winter wheat with other conditions was addressed by the analysis of a large synthetic data set obtained using the PROSPECT-SAILH model in the direct mode. Analysis of the synthetic data set using Sentinel-2 spectral resolution indicates that the two leaf area index normalized (TCI/OSAVI and CVI) indices are better leaf chlorophyll estimators.

An empirical topographic normalization method for forest TM data

A new empirical topographic correction method is proposed and applied to multi-temporal Landsat TM data (bands 1-5 and 7) collected in different periods of the growing season (April, June, July), for a mixed deciduous forest area (343 ha) in the northern Apennines. The method is based on the empirical observation that while for near-Lambertian behavior a linear relationship exists between radiance and the cosine of the incidence angle (i), for more anisotropic reflection a linear regression between the radiance logarithm and cos(i) is more effective at modeling topographic dependence.

Portability of leaf chlorophyll empirical estimators obtained at Sentinel-2 spectral resolution

The present work addresses the comparison of the sensitivity of leaf chlorophyll estimators vegetation indices (VI), obtainable from Sentinel-2 (S2) spectral bands, in the 1-4 LAI range and of their portability with different crops/soil/illumination conditions. The comparison is addressed by the analysis of a large PROSPECT-SAILH synthetic dataset. Results indicate that the TCI/OSAVI (Triangular Chlorophyll index / Optimized Soil Adjusted Vegetation Index ratio) and MTCI (MERIS Terrestrial Chlorophyll Index), obtainable at 20 m spatial resolution from future S2 data, are the best leaf chlorophyll estimators. The TCI/OSAVI ratio is the best estimator for erectophile crop canopies whereas for planophile canopies the TCI/OSAVI ratio or the MTCI index are the best estimators depending on modelled leaf structure. The CVI (chlorophyll vegetation index), obtainable at 10 m, is the second best estimator for both planophile and erectophile crops canopies.

Corrections to “Empirical Estimation of Leaf Chlorophyll Density in Winter Wheat Canopies Using Sentinel-2 Spectral Resolution” [Jun 14 3220-3235]

In the above paper (ibid., vol. 52, no. 6, pp. 3220-3235, Jun. 2014), clarification of Equation (2) is needed. The clarification is presented here.

An optimized broad-band leaf chlorophyll estimator

A comparison of the sensitivity of several broad-band and narrow-band vegetation indices (VI) to leaf chlorophyll concentration is conduced by the analysis of a large synthetic dataset obtained by using in the direct mode the coupled PROSPECT+SAILH leaf and canopy reflectance models. The newly proposed broad-band OCVI (Optimized Chlorophyll Vegetation Index) outperformed as a leaf chlorophyll estimator at the canopy scale both broad-band (i.e., Green NDVI, Green Simple Ratio) and narrow-band VI (i.e.: TCARI - Transformed Chlorophyll Absorption in Reflectance Index, TCARI/OSAVI ratio - TCARI/Optimized Soil Adjusted VI - and REIP, Red Edge Inflection Position), specifically proposed as leaf chlorophyll estimators, with the exception of the TCARI/OSAVI ratio for some soil/solar elevation conditions. Changes in sensitivity of a VI over the range of chlorophyll concentration are analysed, in addition to traditional regression-based statistics, by using a sensitivity function obtained according to the method proposed by Ji and Peters (2007).