Contribution of Chlorophyll Fluorescence to the Apparent Reflectance of Vegetation

Current strategies for monitoring the physiologic status of terrestrial vegetation rely on remote sensing reflectance (R) measurements, whi ch provide estimates of relative vegetation vigor based primarily on chlorophyll content. Vegetation chlorophyll fluorescence (CF) offers a non-destructive alternative and a more direct approach for diagnosis of vegetation stress before a significant reduction in chlorophyll content has occurred. Thus, monitoring of vegetation vigor based on CF may allow earlier stress detection and more accurate carbon sequestra tion estimates, than is possible using R data alone. However, the observed apparent vegetation reflectance (Ra) in reality includes contrib utions from both the reflected and fluoresced radiation. The aim of t his study is to determine the relative R and CF fractions contributing to Ra from the vegetation in the red to near-infrared region of the spectrum. The practical objectives of the study are to: 1) evaluate t he relationship between CF and R at the foliar level for corn, soybean, maple; and 2) for corn, determine if the relationship established f or healthy (optimal N) vegetation changes under N defiiency. To obtai n generally applicable results, experimental measurements were conducted on unrelated crop and tree species (maple, soybean and corn), unde r controlled conditions and a gradient of inorganic N fertilization l evels. Optical R spectra and actively induced CF emissions were obtained on the same foliar samples, in conjunction with measurements of p hotosynthetic function, pigment levels, and C and N content. The comm on spectral trends or similarities were examined. On average, 10-20% of apparent R at 685 nm was actually due to CF. The spectral trends in steady and maximum F varied significantly, with Fs (especially red) showing higher ability for species and treatment separation. The relative contribution of ChF to R varied significantly among species, with maple emitting much higher F amounts, as compared to corn and soybea n. Fs individual red and far-red bands and their ratio exhibited consistent species separations. For corn, the relative CF fraction increased in concert with the nutrient stress levels from 7% for severely nutrient deficient plants. F685s provide d optimal treatment separation. This study confirms the trends in F68 5sE740s associated with N deficiency and vegetation stress, established usmg single narrow band excitation

Scientific and technical challenges in remote sensing of plant canopy reflectance and fluorescence

State-of-the-art optical remote sensing of vegetation canopies is reviewed here to stimulate support from laboratory and field plant research. This overview of recent satellite spectral sensors and the methods used to retrieve remotely quantitative biophysical and biochemical characteristics of vegetation canopies shows that there have been substantial advances in optical remote sensing over the past few decades. Nevertheless, adaptation and transfer of currently available fluorometric methods aboard air- and space-borne platforms can help to eliminate errors and uncertainties in recent remote sensing data interpretation. With this perspective, red and blue-green fluorescence emission as measured in the laboratory and field is reviewed. Remotely sensed plant fluorescence signals have the potential to facilitate a better understanding of vegetation photosynthetic dynamics and primary production on a large scale. The review summarizes several scientific challenges that still need to be resolved to achieve operational fluorescence based remote sensing approache

Remote Sensing of Biophysical Parameters

Vegetation plays an essential role in the study of the environment through plant respiration and photosynthesis. Therefore, the assessment of the current vegetation status is critical to modeling terrestrial ecosystems and energy cycles. Canopy structure (LAI, fCover, plant height, biomass, leaf angle distribution) and biochemical parameters (leaf pigmentation and water content) have been employed to assess vegetation status and its dynamics at scales ranging from kilometric to decametric spatial resolutions thanks to methods based on remote sensing (RS) data.Optical RS retrieval methods are based on the radiative transfer processes of sunlight in vegetation, determining the amount of radiation that is measured by passive sensors in the visible and infrared channels. The increased availability of active RS (radar and LiDAR) data has fostered their use in many applications for the analysis of land surface properties and processes, thanks to their insensitivity to weather conditions and the ability to exploit rich structural and texture information. Optical and radar data fusion and multi-sensor integration approaches are pressing topics, which could fully exploit the information conveyed by both the optical and microwave parts of the electromagnetic spectrum.This Special Issue reprint reviews the state of the art in biophysical parameters retrieval and its usage in a wide variety of applications (e.g., ecology, carbon cycle, agriculture, forestry and food security)

Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science

Remote sensing methods enable detection of solar-induced chlorophyll a fluorescence. However, to unleash the full potential of this signal, intensive cross-disciplinary work is required to harmonize biophysical and ecophysiological studies. For decades, the dynamic nature of chlorophyll a fluorescence (ChlaF) has provided insight into the biophysics and ecophysiology of the light reactions of photosynthesis from the subcellular to leaf scales. Recent advances in remote sensing methods enable detection of ChlaF induced by sunlight across a range of larger scales, from using instruments mounted on towers above plant canopies to Earth-orbiting satellites. This signal is referred to as solar-induced fluorescence (SIF) and its application promises to overcome spatial constraints on studies of photosynthesis, opening new research directions and opportunities in ecology, ecophysiology, biogeochemistry, agriculture and forestry. However, to unleash the full potential of SIF, intensive cross-disciplinary work is required to harmonize these new advances with the rich history of biophysical and ecophysiological studies of ChlaF, fostering the development of next-generation plant physiological and Earth-system models. Here, we introduce the scale-dependent link between SIF and photosynthesis, with an emphasis on seven remaining scientific challenges, and present a roadmap to facilitate future collaborative research towards new applications of SIF.Peer reviewe

Diurnal and Seasonal Variations in Chlorophyll Fluorescence Associated with Photosynthesis at Leaf and Canopy Scales

There is a critical need for sensitive remote sensing approaches to monitor the parameters governing photosynthesis, at the temporal scales relevant to their natural dynamics. The photochemical reflectance index (PRI) and chlorophyll fluorescence (F) offer a strong potential for monitoring photosynthesis at local, regional, and global scales, however the relationships between photosynthesis and solar induced F (SIF) on diurnal and seasonal scales are not fully understood. This study examines how the fine spatial and temporal scale SIF observations relate to leaf level chlorophyll fluorescence metrics (i.e., PSII yield, YII and electron transport rate, ETR), canopy gross primary productivity (GPP), and PRI. The results contribute to enhancing the understanding of how SIF can be used to monitor canopy photosynthesis. This effort captured the seasonal and diurnal variation in GPP, reflectance, F, and SIF in the O2A (SIFA) and O2B (SIFB) atmospheric bands for corn (Zea mays L.) at a study site in Greenbelt, MD. Positive linear relationships of SIF to canopy GPP and to leaf ETR were documented, corroborating published reports. Our findings demonstrate that canopy SIF metrics are able to capture the dynamics in photosynthesis at both leaf and canopy levels, and show that the relationship between GPP and SIF metrics differs depending on the light conditions (i.e., above or below saturation level for photosynthesis). The sum of SIFA and SIFB (SIFA+B), as well as the SIFA+B yield, captured the dynamics in GPP and light use efficiency, suggesting the importance of including SIFB in monitoring photosynthetic function. Further efforts are required to determine if these findings will scale successfully to airborne and satellite levels, and to document the effects of data uncertainties on the scaling

Evaluation of the UAV-Based Multispectral Imagery and Its Application for Crop Intra-Field Nitrogen Monitoring and Yield Prediction in Ontario

Unmanned Aerial Vehicle (UAV) has the capability of acquiring high spatial and temporal resolution images. This new technology fills the data gap between satellite and ground survey in agriculture. In addition, UAV-based crop monitoring and methods are new challenge of remote sensing application in agriculture. First, in my thesis the potential of UAV-based imagery was investigated to monitor spatial and temporal variation of crop status in comparison with RapidEye. The correlation between red-edge indices and LAI and biomass are higher for UAV-based imagery than that of RapidEye. Secondly, the nitrogen weight and yield in wheat was predicted using the UAV-based imagery. The intra-field nitrogen prediction model performs well at wheat early growth stage. Additionally, the best data collection time for yield prediction is at the end of booting stage. The results demonstrate the UAV-based data could be an alternative effective and affordable approach for farmers on intra-field management

The Photochemical Reflectance Index from Directional Cornfield Reflectances: Observations and Simulations

The two-layer Markov chain Analytical Canopy Reflectance Model (ACRM) was linked with in situ hyperspectral leaf optical properties to simulate the Photochemical Reflectance Index (PRI) for a corn crop canopy at three different growth stages. This is an extended study after a successful demonstration of PRI simulations for a cornfield previously conducted at an early vegetative growth stage. Consistent with previous in situ studies, sunlit leaves exhibited lower PRI values than shaded leaves. Since sunlit (shaded) foliage dominates the canopy in the reflectance hotspot (coldspot), the canopy PRI derived from field hyperspectral observations displayed sensitivity to both view zenith angle and relative azimuth angle at all growth stages. Consequently, sunlit and shaded canopy sectors were most differentiated when viewed along the azimuth matching the solar principal plane. These directional PRI responses associated with sunlit/shaded foliage were successfully reproduced by the ACRM. As before, the simulated PRI values from the current study were closer to in situ values when both sunlit and shaded leaves were utilized as model input data in a two-layer mode, instead of a one-layer mode with sunlit leaves only. Model performance as judged by correlation between in situ and simulated values was strongest for the mature corn crop (r = 0.87, RMSE = 0.0048), followed by the early vegetative stage (r = 0.78; RMSE = 0.0051) and the early senescent stage (r = 0.65; RMSE = 0.0104). Since the benefit of including shaded leaves in the scheme varied across different growth stages, a further analysis was conducted to investigate how variable fractions of sunlit/shaded leaves affect the canopy PRI values expected for a cornfield, with implications for 20 remote sensing monitoring options. Simulations of the sunlit to shaded canopy ratio near 50/50 +/- 10 (e.g., 60/40) matching field observations at all growth stages were examined. Our results suggest in the importance of the sunlit/shaded fraction and canopy structure in understanding and interpreting PRI

Assessing the contribution of understory sun-induced chlorophyll fluorescence through 3-D radiative transfer modelling and field data

A major international effort has been made to monitor sun-induced chlorophyll fluorescence (SIF) from space as a proxy for the photosynthetic activity of terrestrial vegetation. However, the effect of spatial heterogeneity on the SIF retrievals from canopy radiance derived from images with medium and low spatial resolution remains uncharacterised. In images from forest and agricultural landscapes, the background comprises a mixture of soil and understory and can generate confounding effects that limit the interpretation of the SIF at the canopy level. This paper aims to improve the understanding of SIF from coarse spatial resolutions in heterogeneous canopies by considering the separated contribution of tree crowns, understory and background components, using a modified version of the FluorFLIGHT radiative transfer model (RTM). The new model is compared with others through the RAMI model intercomparison framework and is validated with airborne data. The airborne campaign includes high-resolution data collected over a tree-grass ecosystem with the HyPlant imaging spectrometer within the FLuorescence EXplorer (FLEX) preparatory missions. Field data measurements were collected from plots with a varying fraction of tree and understory vegetation cover. The relationship between airborne SIF calculated from pure tree crowns and aggregated pixels shows the effect of the understory at different resolutions. For a pixel size smaller than the mean crown size, the impact of the background was low (R2 > 0.99; NRMSE 0.2). This study demonstrates that using a 3D RTM model improves the calculation of SIF significantly (R2 = 0.83, RMSE = 0.03 mW m−2 sr−1 nm−1) when the specific contribution of the soil and understory layers are accounted for, in comparison with the SIF calculated from mixed pixels that considers only one layer as background (R2 = 0.4, RMSE = 0.28 mW m−2 sr−1 nm−1). These results demonstrate the need to account for the contribution of SIF emitted by the understory in the quantification of SIF within tree crowns and within the canopy from aggregated pixels in heterogeneous forest canopies