Formulation and assessment of narrow-band vegetation indices from EO-1 hyperion imagery for discriminating sugarcane disease - Apan, Armando; Held, Alex; Phinn, Stuart; Markley, John (2003 Spatial Sciences Institute Conference: Spatial Knowledge Without Boundaries (SSC2003), 2003)
The increasing commercial availability of hyperspectral image data promotes growing interests in the development of application-specific narrow-band spectral vegetation indices (SVIs). However, the selection of the optimum SVIs for a particular purpose is not straightforward, due to the wide choice of band combinations and transformations, combined with specific application purposes and conditions. Thus, the aim of this study was to develop an approach for formulating and assessing narrow-band vegetation indices, particularly those from EO-1 Hyperion imagery. The focus of SVI development was for discriminating sugarcane areas affected by 'orange rust' (Puccinia kuehnii) disease in Mackay, Queensland, Australia. After a series of pre-processing and post-atmospheric correction techniques, an empirical-statistical approach to SVI development was designed and implemented. This included the following components: a) selection of sample pixels of diseased and nondiseased areas, b) visual examination of spectral plots to identify bands of maximum spectral separability, c)generation of SVIs, d) use of multiple discriminant function analysis, and e) result interpretation and validation. From the forty existing and newly developed vegetation indices, the output discriminant function (i.e. a linear combination of three indices) attained a classification accuracy of 96.9% for the hold-out sample pixels. The statistical analyses also produced a list of function coefficients and correlation rankings that indicate the predictive potential of each SVI. The newly formulated 'Disease-Water Stress Indices' (DSWI) produced the highest correlations. The approach designed for this study provided a systematic framework in the formulation and assessment of SVIs for sugarcane disease detection.
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Keywords: hyperspectral remote sensing, spectral vegetation indices, sugarcane disease, Hyperion

Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements - le Maire, G.; Francois, C.; Dufrene, E. (Remote Sensing of Environment, 2004)
Fifty-three leaves were randomly sampled on different deciduous tree species, representing a wide range of chlorophyll contents, tree ages, and leaf structural features. Their reflectance was measured between 400 and 800 nm with a 1-nm,step, and their chlorophyll content determined by extraction. A larger simulated database (11,583 spectra) was built using the PROSPECT model, in order to test, calibrate, and obtain universal indices, i.e., indices applicable to a wide range of species and leaf structure. To our knowledge, almost all leaf chlorophyll indices published in the literature since 1973 have been tested on both databases. Fourteen canonical types of indices (published ones and new ones) were identified, and their wavelengths calibrated on the simulated database as well as on the experimental database to determine the best wavelengths and, hence, the best performances in chlorophyll estimation for each index types. These indices go from simple reflectance ratios to more sophisticated indices Using reflectance first derivatives (using the Savitzky and Golay method). We also tested other nondestructive methods to obtain total chlorophyll concentration: SPAD (Minolta Camera, Osaka, Japan) and neural networks. The validity of the actual PROSPECT model is challenged by our results: Important discordances are found when the indices are calculated with PROSPECT compared to experimental data, especially for some indices and wavelengths. The discordance is even greater when the indices are determined with PROSPECT and applied on the experimental database. A new calibration of PROSPECT is therefore necessary for any study aiming at using simulated spectra to determine or to calibrate indices. The "peak jump" and the multiple-peak feature observed on the first derivative of the reflectances (e.g., in the Red-Edge Inflection Point [REIP] index) has been investigated. It was shown that chlorophyll absorption alone can explain this feature. The peak jump disqualifies' the REIP to be a valuable chlorophyll index. A simple modified difference ratio gave the best results among all published indices (cross-validated RMSE = 2.1 mug/cm(2) on the experimental database). After calibration on the experimental database, modified Simple Ratio (mSR) and modified Normalized Difference (mND) indices gave the best 2 performances (RMSECV = 1.8 mug/cm(2) on the experimental database). The new Double Difference (DD) index, although not the best on the 2), 2 experimental database (RMSECV 2.9 mug/cm(2)), has the best results on the larger simulated database (RMSE = 3.7 mug/cm(2)) and is expected to give good results on larger experimental databases. The best reflectance-based indices give better performances than the current commercial nondestructive device SPAD (RMSECV = 4.5 mug/cm(2)). In This leaf-level study, the best indices are very near from each other, so that complex methods are useless: REIP-like, neural networks, and derivative-based indices are not necessary and give worst results than simpler properly chosen indices. These conclusions will certainly be different for. a canopy-level study, where the derivative-based indices may perform significantly better than the other ones. (C) 2003 Elsevier Inc. All rights reserved.
Keywords: universal broad leaf chlorophyll indices. PROSPECT. hyperspectral. reflectance measurements. neural-network classification. radiative-transfer models. remote-sensing. data. red-edge. vegetation indexes. spectral reflectance. optical-properties. bidirectio

An investigation into robust spectral indices for leaf chlorophyll estimation - Main, Russell; Cho, Moses Azong; Mathieu, Renaud; OâKennedy, Martha M.; Ramoelo, Abel; Koch, Susan (ISPRS Journal of Photogrammetry and Remote Sensing, 2011)
Quantifying photosynthetic activity at the regional scale can provide important information to resource managers, planners and global ecosystem modelling efforts. With increasing availability of both hyperspectral and narrow band multispectral remote sensing data, new users are faced with a plethora of options when choosing an optical index to relate to their chosen or canopy parameter. The literature base regarding optical indices (particularly chlorophyll indices) is wide ranging and extensive, however it is without much consensus regarding robust indices. The wider spectral community could benefit from studies that apply a variety of published indices to differing sets of species data. The consistency and robustness of 73 published chlorophyll spectral indices have been assessed, using leaf level hyperspectral data collected from three crop species and a variety of savanna tree species. Linear regression between total leaf chlorophyll content and bootstrapping were used to determine the leafpredictive capabilities of the various indices. The indices were then ranked based on the prediction error (the average root mean square error (RMSE)) derived from the bootstrapping process involving 1000 iterative resampling with replacement. The results show two red-edge derivative based indices (red-edge position via linear extrapolation index and the modified red-edge inflection point index) as the most consistent and robust, and that the majority of the top performing indices (in spite of species variability) were simple ratio or normalised difference indices that are based on off-chlorophyll absorption centre wavebands (690â730 nm).
Keywords: Leaf level reflectance; Leaf chlorophyll; Red-edge; Vegetation indices; Photosynthetic activity

Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages - Sims, Daniel A.; Gamon, John A. (Remote Sensing of Environment, 2002)
Leaf pigment content can provide valuable insight into the physiological performance of leaves. Measurement of spectral reflectance provides a fast, nondestructive method for pigment estimation. A large number of spectral indices have been developed for estimation of leaf pigment content. However, in most cases these indices have been tested for only one or at most a few related species and thus it is not clear whether they can be applied across species with varying leaf structural characteristics. Our objective in this study was to develop spectral indices for prediction of leaf pigment content that are relatively insensitive to species and leaf structure variation and thus could be applied in larger scale remote-sensing studies without extensive calibration. We also quantified the degree of spectral interference between pigments when multiple pigments occur within the same leaf tissue. We found that previously published spectral indices provided relatively poor correlations with leaf chlorophyll content when applied across a wide range of species and plant functional types. Leaf surface reflectance appeared to be the most important factor in this variation. By developing a new spectral index that reduces the effect of differences in leaf surface reflectance, we were able to significantly improve the correlations with chlorophyll content. We also found that an index based on the first derivative of reflectance in the red edge region was insensitive to leaf structural variation. The presence of other pigments did not significantly affect estimation of chlorophyll from spectral reflectance. Previously published carotenoid and anthocyanin indices performed poorly across the whole data set. However, we found that the photochemical reflectance index (PRI, originally developed for estimation of xanthophyll cycle pigment changes) was related to carotenoid/chlorophyll ratios in green leaves. This result has important implications for the interpretation of PRI measured at both large and small scales. Our results demonstrate that spectral indices can be applied across species with widely varying leaf structure without the necessity for extensive calibration for each species. This opens up new possibilities for assessment of vegetation health in heterogeneous natural environments.

The IndexDatabase - Henrich, V.; Krauss, G.; Götze, C.; Sandow, C. (2011)