Search results for "regres"

Comparison between SMOS Vegetation Optical Depth products and MODIS vegetation indices over crop zones of the USA

2014

The Soil Moisture and Ocean Salinity (SMOS) mission provides multi-angular, dual-polarised brightness temperatures at 1.4 GHz, from which global soil moisture and vegetation optical depth (tau) products are retrieved. This paper presents a study of SMOS' tau product in 2010 and 2011 for crop zones of the USA. Retrieved tau values for 504 crop nodes were compared to optical/IR vegetation indices from the MODES (Moderate Resolution Imaging Spectroradiometer) satellite sensor, including the Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVE), Leaf Area Index (LAI), and a Normalised Difference Water Index (NOW!) product. tau values were observed to increase during the…

Towards Quantifying Non-Photosynthetic Vegetation for Agriculture Using Spaceborne Imaging Spectroscopy

2021

Non-photosynthetic vegetation (NPV) has been identified as priority variable in the context of new spaceborne imaging spectroscopy missions. In this study we provide a first attempt to quantify NPV biomass from these unprecedented data streams to be provided by multiple recently launched or planned instruments. A hybrid workflow is proposed including Gaussian process regression (GPR) trained over radiative transfer model (RTM) simulations and applying active learning strategies. A soybean field data set including two dates with NPV measurements on yellow and senescent (brown) plant organs was used for model validation, resulting in relative errors of 13.4%. This prototype retrieval model wa…

Multitemporal and multiresolution leaf area index retrieval for operational local rice crop monitoring

2016

Abstract This paper presents an operational chain for high-resolution leaf area index (LAI) retrieval from multiresolution satellite data specifically developed for Mediterranean rice areas. The proposed methodology is based on the inversion of the PROSAIL radiative transfer model through the state-of-the-art nonlinear Gaussian process regression (GPR) method. Landsat and SPOT5 data were used for multitemporal LAI retrievals at high-resolution. LAI estimates were validated using time series of in situ LAI measurements collected during the rice season in Spain and Italy. Ground LAI data were collected with smartphones using PocketLAI, a specific phone application for LAI estimation. Temporal…

Crop Phenology Retrieval Through Gaussian Process Regression

2021

Monitoring crop phenology significantly assists agricultural managing practices and plays an important role in crop yield predictions. Multi-temporal satellite-based observations allow analyzing vegetation seasonal dynamics over large areas by using vegetation indices or deriving biophysical variables. This study presents a framework for automatic corn phenology characterization based on high spatial and temporal resolution time series. By using the Difference Vegetation Index (DVI) estimated from Sentinel-2 data over Iowa (US), independent phenological models were optimized using Gaussian Processes regression. Their respective performances were assessed based on simulated phenological indi…

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…

2020

Sleep problems reported by parents affect 20% to 30% of infants. Few studies focused on the longitudinal association between infant feeding practices and sleep, especially in France. Analyses were based on 8,696 infants from the French national birth cohort ELFE. Collection of feeding practices from birth to 10 months allowed for the identification of trajectories of use of baby cereals and thickened formula by group‐based trajectory modelling and calculation of duration of any breastfeeding (BF) and age at complementary feeding introduction (CFI) excluding baby cereals. Total sleep duration (TSD), night waking (NW) and sleep onset difficulties (SOD) were reported at age 1. Associations bet…

Polygenic score for physical activity provides odds for multiple common diseases

2021

ABSTRACTPurposeIt has been suggested that genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. However, the evidence about pleiotropy from human studies is limited. This study investigated associations between PA polygenic risk scores (PRSs) and cardiometabolic diseases among the Finnish population.MethodsPRSs for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genome-wide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index (BMI),…

Crop nitrogen monitoring: Recent progress and principal developments in the context of imaging spectroscopy missions

2020

Abstract Nitrogen (N) is considered as one of the most important plant macronutrients and proper management of N therefore is a pre-requisite for modern agriculture. Continuous satellite-based monitoring of this key plant trait would help to understand individual crop N use efficiency and thus would enable site-specific N management. Since hyperspectral imaging sensors could provide detailed measurements of spectral signatures corresponding to the optical activity of chemical constituents, they have a theoretical advantage over multi-spectral sensing for the detection of crop N. The current study aims to provide a state-of-the-art overview of crop N retrieval methods from hyperspectral data…

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…

Menstrual problems and lifestyle among Spanish university women

2020

Menstrual problems affect many young women worldwide, conditioning both their academic performance and quality of life. This study sought to analyse the prevalence of menstrual problems and their possible relationship with lifestyle among Spanish university women, as part of a research project (UniHcos Project) involving a cohort of 11 Spanish universities with 7208 university students. A descriptive analysis was performed using the bivariate chi-square test and the Student&rsquo