Hybrid retrieval of crop traits from multi-temporal PRISMA hyperspectral imagery.

The recently launched and upcoming hyperspectral satellite missions, featuring contiguous visible-to-shortwave infrared spectral information, are opening unprecedented opportunities for the retrieval of a broad set of vegetation traits with enhanced accuracy through novel retrieval schemes. In this framework, we exploited hyperspectral data cubes collected by the new-generation PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite of the Italian Space Agency to develop and test a hybrid retrieval workflow for crop trait mapping. Crop traits were mapped over an agricultural area in north-east Italy (Jolanda di Savoia, FE) using PRISMA images collected during the 2020 and 2021 vegetative seasons.

Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission.

In the next few years, the new Copernicus Hyperspectral Imaging Mission (CHIME) is foreseen to be launched by the European Space Agency (ESA). This missions will provide an unprecedented amount of hyperspectral data, enabling new research possibilities within several fields of natural resources, including the "agriculture and food security" domain. In order to efficiently exploit this upcoming hyperspectral data stream, new processing methods and techniques need to be studied and implemented.

Assessment of maize nitrogen uptake from PRISMA hyperspectral data through hybrid modelling.

The spaceborne imaging spectroscopy mission (PRISMA), launched on 22 March 2019 by the Italian Space Agency, opens new opportunities in many scientific domains, including precision farming and sustainable agriculture. This new Earth Observation (EO) data stream requires new-generation approaches for the estimation of important biophysical crop variables (BVs). In this framework, this study evaluated a hybrid approach, combining the radiative transfer model PROSAIL-PRO and several machine learning (ML) regression algorithms, for the retrieval of canopy chlorophyll content (CCC) and canopy nitrogen content (CNC) from synthetic PRISMA data.

UAV RGB, thermal infrared and multispectral imagery used to investigate the control of terrain on the spatial distribution of dryland biocrust.

Biocrusts (topsoil communities formed by mosses, lichens, bacteria, fungi, algae, and cyanobacteria) are a key biotic component of dryland ecosystems. Whilst climate patterns control the distribution of biocrusts in drylands worldwide, terrain and soil attributes can influence biocrust distribution at landscape scale. Multi-source unmanned aerial vehicle (UAV) imagery was used to map and study biocrust ecology in a typical dryland ecosystem in central Spain.

The three major axes of terrestrial ecosystem function.

The leaf economics spectrum and the global spectrum of plant forms and functions revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability.

Mapping landscape canopy nitrogen content from space using PRISMA data.

Satellite imaging spectroscopy for terrestrial applications is reaching maturity with recently launched and upcoming science-driven missions, e.g. PRecursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP), respectively.

Dynamics of sun-induced chlorophyll fluorescence and reflectance to detect stress-induced variations in canopy photosynthesis.

Passive measurement of sun-induced chlorophyll fluorescence (F) represents the most promising tool to quantify changes in photosynthetic functioning on a large scale. However, the complex relationship between this signal and other photosynthesis-related processes restricts its interpretation under stress conditions. To address this issue, we conducted a field campaign by combining daily airborne and ground-based measurements of F (normalized to photosynthetically active radiation), reflectance and surface temperature and related the observed changes to stress-induced variations in photosynthesis.

Exploring the spatial relationship between airborne-derived red and far-red sun-induced fluorescence and process-based GPP estimates in a forest ecosystem.

Terrestrial gross primary productivity (GPP) plays an essential role in the global carbon cycle, but the quantification of the spatial and temporal variations in photosynthesis is still largely uncertain. Our work aimed to investigate the potential of remote sensing to provide new insights into plant photosynthesis at a fine spatial resolution. This goal was achieved by exploiting high-resolution images acquired with the FLuorescence EXplorer (FLEX) airborne demonstrator .

Leaf and canopy photosynthesis of a chlorophyll deficient soybean mutant.

The photosynthetic, optical, and morphological characteristics of a chlorophyll-deficient (Chl-deficient) "yellow" soybean mutant (MinnGold) were examined in comparison with 2 green varieties (MN0095 and Eiko). Despite the large difference in Chl content, similar leaf photosynthesis rates were maintained in the Chl-deficient mutant by offsetting the reduced absorption of red photons by a small increase in photochemical efficiency and lower non-photochemical quenching. When grown in the field, at full canopy cover, the mutants reflected a significantly larger proportion of incoming shortwave radiation, but the total canopy light absorption was only slightly reduced, most likely due to a deeper penetration of light into the canopy space.

Sun-induced chlorophyll fluorescence from high-resolution imaging spectroscopy data to quantify spatio-temporal patterns of photosynthetic function in crop canopies.

Passive detection of sun-induced chlorophyll fluorescence (SIF) using spectroscopy has been proposed as a proxy to quantify changes in photochemical efficiency at canopy level under natural light conditions. In this study, we explored the use of imaging spectroscopy to quantify spatio-temporal dynamics of SIF within crop canopies and its sensitivity to track patterns of photosynthetic activity originating from the interaction between vegetation structure and incoming radiation as well as variations in plant function. SIF was retrieved using the Fraunhofer Line Depth (FLD) principle from imaging spectroscopy data acquired at different time scales a few metres above several crop canopies growing under natural illumination.

Early drought stress detection in cereals: simplex volume maximisation for hyperspectral image analysis.

Early water stress recognition is of great relevance in precision plant breeding and production. Hyperspectral imaging sensors can be a valuable tool for early stress detection with high spatio-temporal resolution. They gather large, high dimensional data cubes posing a significant challenge to data analysis.

Characterization of fine resolution field spectrometers using solar Fraunhofer lines and atmospheric absorption features.

The accurate spectral characterization of high-resolution spectrometers is required for correctly computing, interpreting, and comparing radiance and reflectance spectra acquired at different times or by different instruments. In this paper, we describe an algorithm for the spectral characterization of field spectrometer data using sharp atmospheric or solar absorption features present in the measured data. The algorithm retrieves systematic shifts in channel position and actual full width at half-maximum (FWHM) of the instrument by comparing data acquired during standard field spectroscopy measurement operations with a reference irradiance spectrum modeled with the MODTRAN4 radiative transfer code.

Nutritional traits of bean ( Phaseolus vulgaris ) seeds from plants chronically exposed to ozone pollution.

The effect of chronic exposure to ozone pollution on nutritional traits of bean ( Phaseolus vulgaris L. cv. Borlotto Nano Lingua di Fuoco) seeds from plants grown in filtered and nonfiltered open-top chambers (OTCs) has been investigated.

Using optical remote sensing techniques to track the development of ozone-induced stress.

In this paper, a literature review about optical remote sensing (RS) of O(3) stress is presented. Studies on O(3)-induced effects on vegetation reflectance have been conducted since late '70s based on the analysis of optical RS data. Literature review reveals that traditional RS techniques were able to detect changes in leaf and canopy reflectance related to O(3)-induced stress when visible symptoms already occurred.

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.

Assessment of oak forest condition based on leaf biochemical variables and chlorophyll fluorescence.

Pedunculate oak forests (Quercus robur L.) in the Ticino Regional Park, Italy, are declining as a result of insect attacks, summer droughts and air pollution. The assessment and monitoring of forest condition can provide a basis for managing and conserving forest ecosystems and thereby avoid loss of valuable natural resources.