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Doraiswamy, Paul C.; McMurtrey, James E.; Daughtry, Craig S.T.; Perry, Eileen M.; and Akhmedov, Bakhyt, "A visible band index for remote sensing leaf chlorophyll content at the canopy scale" (2013 and soil type at low crop LAI, whereas at high LAI and canopy closure, TGI was only affected by leaf chlorophyll content. Therefore, TGI may be the best spectral index to detect crop nitrogen requirements with low-cost digital cameras mounted on low-altitude airborne platforms.

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A gronomy J our n al • Volu me 10 0 , I s sue 4 • 2 0 0 8 electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher.T here is a growing library of work published on spectral refl ectance measurements in the visible and near infrared wavelengths to assess plant nutrient and water status, which follows decades of work based on the Normalized Diff erence Vegetation Index (NDVI) (Rouse et al., 1974) and related indices. To date, the use of indices that exploit refl ectance measurements in narrow waveband intervals, especially those involving the chlorophyll red-edge, have produced impressive results in characterizing plant nutrient status (e.g., Haboudane et al., 2002;Gitelson et al., 2003;Strachan et al., 2002). Key questions remain about application of these indices to detect crop stress. One is whether it is possible to detect plant stress for areas smaller than the GSD, or nominal sample size, of a given sensor. In the case of imagery, this is oft en referred to as subpixel detection. Surprisingly, while there has been substantial research based on linear mixing models (e.g., Goel et al., 2003;Okin et al., 2001;and Bannari et al., 2006) there has been little evaluation of the ability of vegetation indices to detect stress areas that are smaller than the GSD. Accurate subpixel stress detection would certainly benefi t and extend applications of space-born imaging spectrometers to crop assessment.Another concern in the application of the spectral refl ectance indices is how well they are able to diff erentiate water and nutrient stress. Some research indicates they do this quite well. Barnes et al. (2000) evaluated the use of refl ectance measurements at key wavelengths of 555 nm, 670 nm, 720 nm, and 790 nm. Among their fi ndings, they demonstrated that the use of one chlorophyll red-edge-based index (the Canopy Chlorophyll Content Index [CCCI], Fitzgerald et al., 2006) diff erentiated the low water/high N treatments from the low water/low N and the high water/low N treatments in cotton. Fitzgerald et al. (2006) also demonstrated signifi cant relationships between CCCI and leaf chlorophyll concentration or shoot N concentration in wheat that were independent of water stress. However, other work suggests that the spectral refl ectance indices may not always reliably separate nutrient and water stress. Clay et al. (2006) designed a factorial N and water experiment in corn. Th ey used canopy refl ectance to calculate NDVI, the Normalized Diff erence Water Index (NDWI) (Gao, 1996), and red-edge indices from Gitelson et al. (2005). Th e ANOVA results for the V8-V9 development stage showed that both NDVI and the red-edge indices were signifi cant for N treatment; the red-edge indices were also signifi cant for water. At the later V11-VT growth stage, red-edge indices were less signifi cant than NDVI for N treatment. At both stages, the NDWI was not signifi cant for water, and none of the indices evaluated were signifi ca...

Abstract. Frost damage causes significant production losses and costs to Australian dryland wheat, and frost impacts are not expected to decline in the near future, despite global warming. Rapid estimation of frost damage to crops on a spatial basis would allow for timely management decisions to reduce the economic impact of frost events. In this paper, we take a first step in evaluating the utility of hyperspectral reflectance and active light fluorescence for detecting frost damage to wheat during its reproductive phase. Two experiments were conducted immediately after the first observation of frost damage, (i) in 2006, five plots in an existing trial were opportunistically subdivided to take spectral reflectance measurements on frost damaged plants along with yield measurements, and (ii) in 2015, a transect across 31 rows within a commercial paddock was established to evaluate spectral reflectance, fluorometer measurements, and yield along a gradient from non-frosted to frost damaged plants. The results of the hyperspectral reflectance data appeared variable in response across the two experimental sites where frost was observed in-crop. In 2006, hyperspectral-derived indices showed significant differences (P < 0.05) between measurements of frosted and non-frosted canopies, but this was not the case for observations taken in 2015, where the mean response was reversed between experimental sites for several of the indices. In contrast, fluorometer measurements in the 2015 trial resulted in higher correlations with yield and observed frost damage compared with the reflectance measurements. Seven of the nine fluorometer indices evaluated were correlated with yield (used as an indicator of frost damage) at P < 0.01. An index of compounds which absorbs at 375 nm, FLAV, had the best correlation coefficients of 0.91 and 0.90 for the two dates in 2015. The fluorescence index FLAV was selected to evaluate whether it could be used to classify the canopy as frost affected or not, using discriminant analysis for the 2015 transect data. The overall classification accuracy, defined as the number of correctly classified measurements (57) divided by the total number (62) was 92%. The present study was not able to provide insight into how rapidly the sensors could detect frost damage before detection with the naked eye, as the survey data constituted a transect based on early visual symptoms, however this study does provide important insight into what sensors and/or indices may be sensitive to 'seeing' early frost damage in-crop. The next steps, which build on this work and need to be resolved are (i) what is the nominal scale of measurements required, and for which portions of the plant canopy? (ii) How robust (over space and time) are any relationships between frost damage and index response? (iii) Can frost damage be detected before the onset of visual damage?

Arid and semiarid rangelands comprise a significant portion of the earth's land surface. Yet little is known about the effects of temporal and spatial changes in surface soil moisture on the hydrologic cycle, energy balance, and the feedbacks to the atmosphere via thermal forcing over such environments. Understanding this interrelationship is crucial for evaluating the role of the hydrologic cycle in surface-atmosphere interactions. This study focuses on the utility of remote sensing to provide measurements of surface soil moisture, surface albedo, vegetation biomass, and temperature at different spatial and temporal scales. Remote-sensing measurements may provide the only practical means of estimating some of the more important factors controlling land surface processes over large areas. Consequently, the use of remotely sensed information in biophysical and geophysical models greatly enhances their ability to compute fluxes at catchment and regional scales on a routine basis. However, model calculations for different climates and ecosystems need verification. This requires that the remotely sensed data and model computations be evaluated with ground-truth data collected at the same areal scales. The present study (MONSOON 90) attempts to address this issue for semiarid rangelands. The experimental plan included remotely sensed data in the visible, near-infrared, thermal, and microwave wavelengths from ground and aircraft platforms and, when available, from satellites. Collected concurrently were ground measurements of soil moisture and temperature, energy and water fluxes, and profile data in the atmospheric boundary layer in a hydrologically instrumented semiarid rangeland watershed. Field experiments were conducted in 1990 during the dry and wet or "monsoon season" for the southwestern United States. A detailed description of the field campaigns, including measurements and some preliminary results are given.