Search results for " Planetary"

2021

Nitrogen (N) is one of the key nutrients supplied in agricultural production worldwide. Over-fertilization can have negative influences on the field and the regional level (e.g., agro-ecosystems). Remote sensing of the plant N of field crops presents a valuable tool for the monitoring of N flows in agro-ecosystems. Available data for validation of satellite-based remote sensing of N is scarce. Therefore, in this study, field spectrometer measurements were used to simulate data of the Sentinel-2 (S2) satellites developed for vegetation monitoring by the ESA. The prediction performance of normalized ratio indices (NRIs), random forest regression (RFR) and Gaussian processes regression (GPR) f…

Spatio-temporal soil drying in southeastern South America: the importance of effective sampling frequency and observational errors on drydown time sc…

2020

The study of the spatio-temporal dynamics of surface soil moisture (SSM) drydowns integrates the soil response to climatic conditions, drainage and land cover and is key to advances in our knowledg...

Transition vers des systèmes agricole et agroalimentaire durables : quelle place et qualification pour les légumineuses à graines ?

2017

Cet article propose une analyse historique du processus de verrouillage du système agroalimentaire en défaveur des légumineuses à graines, à l’aune des théories évolutionnistes. Plusieurs mécanismes d’autorenforcement permettent de comprendre pourquoi ces espèces sont de moins en moins cultivées en France face à un système agro-industriel qui s’est spécialisé en faveur des céréales, favorisant à l’amont l’usage d’engrais azotés de synthèse et limitant à l’aval les investissements pour les légumineuses en alimentation humaine. Cet article s’interroge alors sur les perspectives de déverrouillage.

Satellite Observations of the Contrasting Response of Trees and Grasses to Variations in Water Availability

2019

Interannual variations in ecosystem primary productivity are dominated by water availability. Until recently, characterizing the photosynthetic response of different ecosystems to soil moisture anomalies was hampered by observational limitations. Here, we use a number of satellite-based proxies for productivity, including spectral indices, sun-induced chlorophyll fluorescence, and data-driven estimates of gross primary production, to reevaluate the relationship between terrestrial photosynthesis and water. In contrast to nonwoody vegetation, we find a resilience of forested ecosystems to reduced soil moisture. Sun-induced chlorophyll fluorescence and data-driven gross primary production ind…

Retrieval of canopy water content of different crop types with two new hyperspectral indices: Water Absorption Area Index and Depth Water Index

2018

Crop canopy water content (CWC) is an essential indicator of the crop’s physiological state. While a diverse range of vegetation indices have earlier been developed for the remote estimation of CWC, most of them are defined for specific crop types and areas, making them less universally applicable. We propose two new water content indices applicable to a wide variety of crop types, allowing to derive CWC maps at a large spatial scale. These indices were developed based on PROSAIL simulations and then optimized with an experimental dataset (SPARC03; Barrax, Spain). This dataset consists of water content and other biophysical variables for five common crop types (lucerne, corn, potato, sugar …

Scenario-based discrimination of common grapevine varieties using in-field hyperspectral data in the western of Iran

2019

Abstract Field spectroscopy is an accurate, rapid and nondestructive technique for monitoring of agricultural plant characteristics. Among these, identification of grapevine varieties is one of the most important factors in viticulture and wine industry. This study evaluated the discriminatory ability of field hyperspectral data and statistical techniques in case of five common grapevine varieties in the western of Iran. A total of 3000 spectral samples were acquired at leaf and canopy levels. Then, in order to identify the best approach, two types of hyperspectral data (wavelengths from 350 to 2500 nm and 32 spectral indices), two data reduction methods (PLSR and ANOVA-PCA) and two classif…

Land use intensification increasingly drives the spatiotemporal patterns of the global human appropriation of net primary production in the last cent…

2021

Land use has greatly transformed Earth's surface. While spatial reconstructions of how the extent of land cover and land-use types have changed during the last century are available, much less information exists about changes in land-use intensity. In particular, global reconstructions that consistently cover land-use intensity across land-use types and ecosystems are missing. We, therefore, lack understanding of how changes in land-use intensity interfere with the natural processes in land systems. To address this research gap, we map land-cover and land-use intensity changes between 1910 and 2010 for 9 points in time. We rely on the indicator framework of human appropriation of net primar…

Land use classification from multitemporal Landsat imagery using the Yearly Land Cover Dynamics (YLCD) method

2011

Abstract Several previous studies have shown that the inclusion of the LST (Land Surface Temperature) parameter to a NDVI (Normalized Difference Vegetation Index) based classification procedure is beneficial to classification accuracy. In this work, the Yearly Land Cover Dynamics (YLCD) approach, which is based on annual behavior of LST and NDVI, has been used to classify an agricultural area into crop types. To this end, a time series of Landsat-5 images for year 2009 of the Barrax (Spain) area has been processed: georeferenciation, destriping and atmospheric correction have been carried out to estimate NDVI and LST time series for year 2009, from which YLCD parameters were estimated. Then…

Information nutritionnelle, choix et caractéristiques des consommateurs

2012

Consumers’ food decisions are based on the information they receive and on their own individual characteristics. This paper is based on an experiment using experimental economics and sensory evaluation to measure individual characteristics of participants and to analyze the impact of nutritional information relative to orange juice. The aim is to explore the potential link between specific characteristics (risk aversion, time preference) and the reactions of consumers to nutritional information. The results show that participants react significantly to this information supplied, positively for the pure orange juice and a negatively for orange nectars. In addition, “risk averse” individuals …

Monitoring Cropland Phenology on Google Earth Engine Using Gaussian Process Regression

2021

Monitoring cropland phenology from optical satellite data remains a challenging task due to the influence of clouds and atmospheric artifacts. Therefore, measures need to be taken to overcome these challenges and gain better knowledge of crop dynamics. The arrival of cloud computing platforms such as Google Earth Engine (GEE) has enabled us to propose a Sentinel-2 (S2) phenology end-to-end processing chain. To achieve this, the following pipeline was implemented: (1) the building of hybrid Gaussian Process Regression (GPR) retrieval models of crop traits optimized with active learning, (2) implementation of these models on GEE (3) generation of spatiotemporally continuous maps and time seri…