Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages

https://www.calmit.unl.edu/people/agitelson2/pdf/06_JPP-2003.pdf

Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves

Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV) Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface In the real-world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed This paper reviews more than 100 VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas

/pdf/significant-remote-sensing-vegetation-indices-a-review-of-4szax6zlwz.pdf

Significant remote sensing vegetation indices: A review of developments and applications

Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics

Two critical limitations for using current satellite sensors in real-time crop management are the lack of imagery with optimum spatial and spectral resolutions and an unfavorable revisit time for most crop stress-detection applications. Alternatives based on manned airborne platforms are lacking due to their high operational costs. A fundamental requirement for providing useful remote sensing products in agriculture is the capacity to combine high spatial resolution and quick turnaround times. Remote sensing sensors placed on unmanned aerial vehicles (UAVs) could fill this gap, providing low-cost approaches to meet the critical requirements of spatial, spectral, and temporal resolutions. This paper demonstrates the ability to generate quantitative remote sensing products by means of a helicopter-based UAV equipped with inexpensive thermal and narrowband multispectral imaging sensors. During summer of 2007, the platform was flown over agricultural fields, obtaining thermal imagery in the 7.5-13-mum region (40-cm resolution) and narrowband multispectral imagery in the 400-800-nm spectral region (20-cm resolution). Surface reflectance and temperature imagery were obtained, after atmospheric corrections with MODTRAN. Biophysical parameters were estimated using vegetation indices, namely, normalized difference vegetation index, transformed chlorophyll absorption in reflectance index/optimized soil-adjusted vegetation index, and photochemical reflectance index (PRI), coupled with SAILH and FLIGHT models. As a result, the image products of leaf area index, chlorophyll content (C ab), and water stress detection from PRI index and canopy temperature were produced and successfully validated. This paper demonstrates that results obtained with a low-cost UAV system for agricultural applications yielded comparable estimations, if not better, than those obtained by traditional manned airborne sensors.

/pdf/thermal-and-narrowband-multispectral-remote-sensing-for-42l8xtel9f.pdf

Thermal and Narrowband Multispectral Remote Sensing for Vegetation Monitoring From an Unmanned Aerial Vehicle

The photochemical reflectance index (PRI), derived from narrow-band reflectance at 531 and 570 nm, was explored as an indicator of photosynthetic radiation use efficiency for 20 species representing three functional types: annual, deciduous perennial, and evergreen perennial. Across species, top-canopy leaves in full sun at midday exhibited a strong correlation between PRI and ΔF/Fm′, a fluorescence-based index of photosystem II (PSII) photochemical efficiency. PRI was also significantly correlated with both net CO2 uptake and radiation use efficiency measured by gas exchange. When species were examined by functional type, evergreens exhibited significantly reduced midday photosynthetic rates relative to annual and deciduous species. This midday reduction was associated with reduced radiation use efficiency, detectable as reduced net CO2 uptake, PRI, and ΔF/Fm′ values, and increased levels of the photoprotective xanthophyll cycle pigment zeaxanthin. For each functional type, nutrient deficiency led to reductions in both PRI and ΔF/Fm′ relative to fertilized controls. Laboratory experiments exposing leaves to diurnal courses of radiation and simulated midday stomatal closure demonstrated that PRI changed rapidly with both irradiance and leaf physiological state. In these studies, PRI was closely correlated with both ΔF/Fm' and radiation use efficiency determined from gas exchange at all but the lowest light levels. Examination of the difference spectra upon exposure to increasing light levels revealed that the 531 nm Δ reflectance signal was composed of two spectral components. At low irradiance, this signal was dominated by a 545-nm component, which was not closely related to radiation use efficiency. At progressively higher light levels above 100 μmol m−2 s−1, the 531-nm signal was increasingly dominated by a 526-nm component, which was correlated with light use efficiency and with the conversion of the xanthophyll pigment violaxanthin to antheraxanthin and zeaxanthin. Further consideration of the two components composing the 531-nm signal could lead to an index of photosynthetic function applicable over a wide range of illumination. The results of this study support the use of PRI as an interspecific index of photosynthetic radiation use efficiency for leaves and canopies in full sun, but not across wide ranges in illumination from deep shade to full sun. The discovery of a consistent relationship between PRI and photosynthetic radiation use efficiency for top-canopy leaves across species, functional types, and nutrient treatments suggests that relative photosynthetic rates could be derived with the “view from above” provided by remote reflectance measurements if issues of canopy and stand structure can be resolved.

The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels.

We present new remote sensing indices of plant water status: the ratio between the reflectance at 970 nm, one of the water absorption bands, and the reflectance at a reference wavelength, 900 nm (R970/R9000; the first derivative minimum in this near-infrared region (dNIRminimum ) and the wavelength where this minimum is found ( λNIRminimum). In order to evaluate them, we carried out three experiments. Daily irrigated gerbera plants were allowed to dry until almost wilting and then daily irrigation was restarted; pepper and bean plants were grown for four months submitted to two different irrigation treatments; and bean detached leaves were submitted to progressive dehydration whereas pressure-volume curves were being carried out. In gerbera plants, the trough about 950–970 nm decreased as the drought was increasing. Therefore, the R970/R900 index and the dNIRminimum closely tracked the changes in relative water content (RWC), leaf water potential, stomatal conductance and the foliage-air temperat...

The reflectance at the 950-970 nm region as an indicator of plant water status

Nitrogen deficiencies can seriously reduce yield and economic returns for farmers. Remote sensing could provide inexpensive, large-area estimates of N status and be used to monitor N status since leaf chlorophyll (Chl) A content is mainly determined by N availability. The objective was to determine if remote sensing of wheat (Triticum aestivum L.) Chl A content would provide a rapid estimation of wheat N status. We measured the reflectance of a wheat crop submitted to five different fertilization treatments throughout the growth cycle. We tested several empirical reflectance indices of pigment content: reflectance at 550 nm (R550), reflectance at 680 nm (R680), three parameters of the red edge [wavelength (λ re ), amplitude in the first derivative of the reflectance spectra (dR re ), and sum of amplitudes between 680 and 780 nm in the first derivative of the reflectance spectra (ΣdR 680-780nm )], and pigment simple ratio (PSR) and normalized pigment chlorophyll index (NPCI) (indices of carotenoid/Chl ratio). We also measured leaf Chl A and N content, and leaf area index. There were significant correlations between canopy Chl A content and R550, R680, and all the red edge parameters. The NPCI and PSR followed phenological evolution of the carotenoids/Chl A ratio and separated the different treatments. By discriminant analysis based on the pigment indices reflectance at 430 nm (R430), R550, R680, λ re , dR re , and NPCI, each reflectance spectrum can be assigned to a different N status class. Thus, the use of these optical techniques offers a potential for assessing N status of wheat.

Evaluating Wheat Nitrogen Status with Canopy Reflectance Indices and Discriminant Analysis

Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: Decomposing biochemical from structural signals

Vegetation indices derived from reflectance data are related to canopy variables such as aboveground biomass, leaf area index (LAI), and the fraction of intercepted photosynthetically active radiation (fIPAR). However, under N stress the relationships between vegetation indices (VI) and these canopy variables might be confounded due to plant chlorosis. We studied the relationships between reflectance-based VI and canopy variables (aboveground biomass, LAI canopy chlorophyll A content [LAI X Chl A], and fIPAR) for a wheat (Triticum aestivum L.) crop growing under different N supplies. Nitrogen fertilization promoted significant increases in radiation interception (plant growth) and, to a lesser extent, in radiation use efficiency (RUE). The VI vs. LAI relationships varied significantly among treatments, rendering the VI-based equations unreliable to estimate LAI under contrasting N conditions. However, a single relationship emerged when LAI X Chl A was considered. Moreover, VI were robust indicators of fIPAR by green canopy components independently of N treatment and phenology. Aboveground biomass was poorly correlated with grain yield, whereas cumulative VI simple ratio (SR) was a good predictor of grain yield, probably because cumulative SR closely tracked the duration and intensity of the canopy photosynthetic capacity.

Lydia Serrano

Papers

The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels.

The reflectance at the 950-970 nm region as an indicator of plant water status

Evaluating Wheat Nitrogen Status with Canopy Reflectance Indices and Discriminant Analysis

Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: Decomposing biochemical from structural signals

Remote sensing of biomass and yield of winter wheat under different nitrogen supplies