Search results for "Remote Sensing"
showing 10 items of 1262 documents
Environment-sensitivity functions for gross primary productivity in light use efficiency models
2022
International audience; The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full fact…
Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory
2018
International audience; Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types.…
Chlorophyll fluorescence as a tool for management of plant resources
1994
Abstract Light-induced chlorophyll fluorescence has become a tool which has ever-increasing potential application to experimental plant physiology. The effects of frost, heat, and drought have been analyzed using the kinetics of individual leaves of two representative types of life form: an evergreen tree (holm oak) dominant in the Mediterranean Basin and an annual cultivated legume (soybean). Various indices were used to quantify their response to environmental stress. Canopy fluorescence for the two types of plants was simulated. For two levels of measurement, leaf or canopy, light-induced fluorescence appears to be helpful for forest or crop management in the Mediterranean area.
Seguimiento del fenómeno blanco de la laguna de la Cruz (Cuenca, España)
2020
[EN] In the present study, a five-year follow-up was performed by remote sensing of the calcium carbonate precipitation in La Gitana karstic lake also known as La Cruz (located on the province of Cuenca, Spain). The important role that calcium carbonate precipitation plays in the ecology of the lake is well known for its influence on the vertical migrations of phytoplankton, the concentration of bioavailable phosphorus and, therefore, the eutrophication and quality of the waters. Whiting take place between the months of July and August, and it can be studied at this time through its optical properties, with the main objective of offering updated data on a phenomenon traditionally studied an…
Chlorophyll fluorescence emission spectrum inside a leaf
2008
International audience; Chlorophyll a fluorescence can be used as an early stress indicator. Fluorescence is also connected to photosynthesis so it can be proposed for global monitoring of vegetation status from a satellite platform. Nevertheless, the correct interpretation of fluorescence requires accurate physical models. The spectral shape of the leaf fluorescence free of any re-absorption effect plays a key role in the models and is difficult to measure. We present a vegetation fluorescence emission spectrum free of re-absorption based on a combination of measurements and modelling. The suggested spectrum takes into account the photosystem I and II spectra and their relative contributio…
Advanced methods of plant disease detection. A review
2014
International audience; Plant diseases are responsible for major economic losses in the agricultural industry worldwide. Monitoring plant health and detecting pathogen early are essential to reduce disease spread and facilitate effective management practices. DNA-based and serological methods now provide essential tools for accurate plant disease diagnosis, in addition to the traditional visual scouting for symptoms. Although DNA-based and serological methods have revolutionized plant disease detection, they are not very reliable at asymptomatic stage, especially in case of pathogen with systemic diffusion. They need at least 1–2 days for sample harvest, processing, and analysis. Here, we d…
A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data
2018
This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database (> 45% of missing entries) and maximizes the global representativeness of the trait dataset. Plant species are then a…
Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea)
2021
This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200 kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. Th…
Synthetic cartography for mapping biodiversity in the Mediterranean region: Sicily as a case study
2018
This paper proposes a new hierarchical land classification system for the mapping of species distribution at national or regional scales. Our integrative framework incorporates two hierarchical levels inferred from historical, climatic, geomorphological and geological attributes. The feasibility of this proposal is based on the use of historical collections and literature data, as well as on its ability to combine old low-precision data with more recent records of higher resolution. The system is set up for vascular plants, but it can also be used for other taxonomic groups. Furthermore, it has the potential for application to the whole Mediterranean region because it is based on informatio…
Tracking marine alien macroalgae in the mediterranean sea: The contribution of citizen science and remote sensing
2021
The accelerating rate of the introduction of non-indigenous species (NIS) and the magnitude of shipping traffic make the Mediterranean Sea a hotspot of biological invasions. For the effective management of NIS, early detection and intensive monitoring over time and space are essential. Here, we present an overview of possible applications of citizen science and remote sensing in monitoring alien seaweeds in the Mediterranean Sea. Citizen science activities, involving the public (e.g., tourists, fishermen, divers) in the collection of data, have great potential for monitoring NIS. The innovative methodologies, based on remote sensing techniques coupled with in situ/laboratory advanced sampli…