Michele Meroni

Validation of global moderate-resolution LAI products: a framework proposed within the CEOS land product validation subgroup

Initiated in 1984, the Committee Earth Observing Satellites Working Group on Calibration and Validation (CEOS WGCV) pursues activities to coordinate, standardize and advance calibration and validation of civilian satellites and their data. One subgroup of CEOS WGCV, Land Product Validation (LPV), was established in 2000 to define standard validation guidelines and protocols and to foster data and information exchange relevant to the validation of land products. Since then, a number of leaf area index (LAI) products have become available to the science community at both global and regional extents. Having multiple global LAI products and multiple, disparate validation activities related to these products presents the opportunity to realize efficiency through international collaboration. So the LPV subgroup established an international LAI intercomparison validation activity. This paper describes the main components of this international validation effort. The paper documents the current participants, their ground LAI measurements and scaling techniques, and the metadata and infrastructure established to share data. The paper concludes by describing plans for sharing both field data and high-resolution LAI products from each site. Many considerations of this global LAI intercomparison can apply to other products, and this paper presents a framework for such collaboration

Identification of hyperspectral vegetation indices for Mediterranean pasture characterization

Abstract A field experiment was carried out to assess biomass and nitrogen status in Mediterranean pastures by means of hyperspectral high resolution field radiometric data. Spectral and agronomic measurements were collected at three different pasture growth stages and in grazed–ungrazed plots distributed over an area of 14xa0ha. Reflectance-based vegetation indices such as simple ratio indices (SR[i,j]) and normalized difference vegetation indices (NDVI[i,j]) were calculated using all combinations of two wavelengths i and j in the spectral range 400–1000xa0nm. The performances of these indices in predicting green biomass (GBM, t ha−1), leaf area index (LAI, m2xa0m−2), nitrogen content (N, kgxa0ha−1) and nitrogen concentration (NC, %) were evaluated by linear regression analysis using the cross validated coefficient of determination ( R CV 2 ) and root mean squared error (RMSECV). SR involving bands in near-infrared (ixa0=xa0770–930xa0nm) and in the red edge (jxa0=xa0720–740xa0nm) yielded the best performance for GBM ( R CV 2 = 0.73 , RMSECVxa0=xa02.35xa0txa0ha−1), LAI ( R CV 2 = 0.73 , RMSECVxa0=xa00.37xa0m2xa0m−2), and N ( R CV 2 = 0.73 , RMSECVxa0=xa07.36xa0kgxa0ha−1). The best model performances for NC ( R CV 2 = 0.54 , RMSECVxa0=xa00.35%) were obtained using SR involving near-infrared bands (ixa0=xa0775–820xa0nm) and longer wavelengths of the red edge (jxa0=xa0740–770xa0nm). The defined indices lead to significant improvements in model predictive capability compared to the traditional SR [near-infrared, red] and NDVI [near-infrared, red] and to broad-band indices. The possibility of exploiting these results gathered at field level with high resolution spectral data (FWHM 3.5xa0nm) also at landscape level by means of hyperspectral airborne or satellite sensors was explored. Model performances resulted extremely sensitive to band position, suggesting the importance of using hyperspectral sensors with contiguous spectral bands.

Developments for vegetation fluorescence retrieval from spaceborne high‐resolution spectrometry in the O2‐A and O2‐B absorption bands

[1]xa0Solar-induced chlorophyll fluorescence is a weak electromagnetic signal emitted in the red and far-red spectral regions by vegetation chlorophyll under excitation by solar radiation. Chlorophyll fluorescence has been demonstrated to be a close proxy to vegetation physiological functioning. The basis for fluorescence retrieval from passive space measurements is the exploitation of the O2-A and O2-B atmospheric absorption features to isolate the fluorescence signal from the solar radiation reflected by the surface and the atmosphere. High spectral resolution measurements and a precise modeling of the atmospheric radiative transfer in the visible and near-infrared regions are mandatory. Recent developments for fluorescence retrieval from passive high spectral resolution spaceborne measurements are presented in this work, which has been performed in preparation of the FLuorescence EXplorer (FLEX) mission, which is currently under development by the European Space Agency. A large data set of FLEX-like measurements has been simulated for the purpose of methodology development and testing. Issues related to vegetation chlorophyll fluorescence retrieval from space, a description of the proposed methodology, initial results from simulated test cases, and general guidelines for the specification of fluorescence retrieval instruments are presented and discussed in this work.

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.

Leaf level early assessment of ozone injuries by passive fluorescence and photochemical reflectance index

Excess energy dissipation pathways (heat and fluorescence) were monitored, at leaf level as indicators of plant physiological status, with field spectroscopy techniques on poplar clones subjected to ozone fumigation. Measurements of spectral radiance emerging from a leaf provide a fast, non‐destructive method for the assessment of excess energy dissipation: xanthophyll‐related heat dissipation was estimated with the photochemical reflectance index (PRI) calculated from a traditional field spectrometer, and steady‐state fluorescence (Fs) under natural illumination conditions was estimated by exploiting a variation of the Fraunhofer line‐depth principle, where the radiance collected with very high resolution spectrometers (FWHM = 0.13 nm) was spectrally modelled. Both remotely‐sensed dissipation pathways responded to fumigation. During a 26‐day fumigation experiment, four diurnal cycles of spectral measurements were collected in parallel to meteorological and key physiological variables (active fluorescence, net photosynthesis) and leaf sample collection for pigment extraction. We outline evidence of a link between the remotely‐sensed Fs and PRI and leaf physiological status. These results open up new possibilities for assessment of plant stress by means of hyperspectral remote sensing.

European larch phenology in the Alps: can we grasp the role of ecological factors by combining field observations and inverse modelling?

Vegetation phenology is strongly influenced by climatic factors. Climate changes may cause phenological variations, especially in the Alps which are considered to be extremely vulnerable to global warming. The main goal of our study is to analyze European larch (Larix decidua Mill.) phenology in alpine environments and the role of the ecological factors involved, using an integrated approach based on accurate field observations and modelling techniques. We present 2xa0years of field-collected larch phenological data, obtained following a specifically designed observation protocol. We observed that both spring and autumn larch phenology is strongly influenced by altitude. We propose an approach for the optimization of a spring warming model (SW) and the growing season index model (GSI) consisting of a model inversion technique, based on simulated look-up tables (LUTs), that provides robust parameter estimates. The optimized models showed excellent agreement between modelled and observed data: the SW model predicts the beginning of the growing season (BGS) with a mean RMSE of 4xa0days, while GSI gives a prediction of the growing season length (LGS) with a RMSE of 5xa0days. Moreover, we showed that the original GSI parameters led to consistent errors, while the optimized ones significantly increased model accuracy. Finally, we used GSI to investigate interactions of ecological factors during springtime development and autumn senescence. We found that temperature is the most effective factor during spring recovery while photoperiod plays an important role during autumn senescence: photoperiod shows a contrasting effect with altitude decreasing its influence with increasing altitude.

The hyperspectral irradiometer, a new instrument for long-term and unattended field spectroscopy measurements

Reliable time series of vegetation optical properties are needed to improve the modeling of the terrestrial carbon budget with remote sensing data. This paper describes the development of an automatic spectral system able to collect continuous long-term in-field spectral measurements of spectral down-welling and surface reflected irradiance. The paper addresses the development of the system, named hyperspectral irradiometer (HSI), describes its optical design, the acquisition, and processing operations. Measurements gathered on a vegetated surface by the HSI are shown, discussed and compared with experimental outcomes with independent instruments.

Nitrogen Status Assessment for Variable Rate Fertilization in Maize through Hyperspectral Imagery

This paper presents a method for mapping the nitrogen (N) status in a maize field using hyperspectral remote sensing imagery. An airborne survey was conducted with an AISA Eagle hyperspectral sensor over an experimental farm where maize (Zea mays L.) was grown with two N fertilization levels (0 and 100 kg N ha−1) in four replicates. Leaf and canopy field data were collected during the flight. The nitrogen (N) status has been estimated in this work based on the Nitrogen Nutrition Index (NNI), defined as the ratio between the leaf actual N concentration (%Na) of the crop and the minimum N content required for the maximum biomass production (critical N concentration (%Nc)) calculated through the dry mass at the time of the flight (Wflight). The inputs required to calculate the NNI (i.e., %Na and Wflight) have been estimated through regression analyses between field data and remotely sensed vegetation indices. MCARI/MTVI2 (Modified Chlorophyll Absorption Ratio Index/Modified Triangular Vegetation Index 2) showed the best performances in estimating the %Na (R2 = 0.59) and MTVI2 in estimating the Wflight (R2 = 0.80). The %Na and the Wflight were then mapped and used to compute the NNI map over the entire field. The NNI map agreed with the NNI estimated using field data through traditional destructive measurements (R2 = 0.70) confirming the potential of using remotely sensed indices to assess the crop N condition. Finally, a method to derive a pixel based variable rate N fertilization map was proposed as the difference between the actual N content and the optimal N content. We think that the proposed operational methodology is promising for precision farming since it represents an innovative attempt to derive a variable rate N fertilization map based on the actual crop N status from an aerial hyperspectral image.

A flux-based assessment of the effects of ozone on foliar injury, photosynthesis, and yield of bean (Phaseolus vulgaris L. cv. Borlotto Nano Lingua di Fuoco) in open-top chambers.

Stomatal ozone uptake, determined with the Jarvis approach, was related to photosynthetic efficiency assessed by chlorophyll fluorescence and reflectance measurements in open-top chamber experiments on Phaseolus vulgaris. The effects of O(3) exposure were also evaluated in terms of visible and microscopical leaf injury and plant productivity. Results showed that microscopical leaf symptoms, assessed as cell death and H(2)O(2) accumulation, preceded by 3-4 days the appearance of visible symptoms. An effective dose of ozone stomatal flux for visible leaf damages was found around 1.33 mmol O(3) m(-2). Significant linear dose-response relationships were obtained between accumulated fluxes and optical indices (PRI, NDI, DeltaF/F(m)). The negative effects on photosynthesis reduced plant productivity, affecting the number of pods and seeds, but not seed weight. These results, besides contributing to the development of a flux-based ozone risk assessment for crops in Europe, highlight the potentiality of reflectance measurements for the early detection of ozone stress.

A phenology-based method to derive biomass production anomalies for food security monitoring in the Horn of Africa

Monitoring vegetation conditions is a critical activity for assessing food security in the Horn of Africa. Remote sensing from space offers a unique opportunity to obtain consistent and timely information over large and often inaccessible areas where field observations are scattered, non-homogenous, or frequently unavailable. In this study we outline a method to assess objectively the performance and characteristics of seasonal vegetation development solely on the basis of time series of the fraction of absorbed photosynthetically active radiation (FAPAR) derived from Satellite Pour l’Observation de la Terre SPOT-VEGETATION (SPOT-VGT) imagery. Key phenological indicators such as the start and end of growing periods are derived from a statistical analysis of the time series to characterize the spatial and temporal evolution of successive seasons. These indicators are then utilized to compute a proxy of the seasonal gross primary production (GPP) as the cumulative FAPAR during the growing season. Vegetation condition and associated risk of food deficit for specific seasons and locations are finally derived from the comparison of the seasonal GPP proxy with its average value computed over the whole time series. The impact on vegetation of the severe drought experienced by the Horn of Africa between late 2010 and late 2011 is discussed.