Search results for "Gaussian process"
showing 10 items of 128 documents
Intelligent Sampling for Vegetation Nitrogen Mapping Based on Hybrid Machine Learning Algorithms
2021
Upcoming satellite imaging spectroscopy missions will deliver spatiotemporal explicit data streams to be exploited for mapping vegetation properties, such as nitrogen (N) content. Within retrieval workflows for real-time mapping over agricultural regions, such crop-specific information products need to be derived precisely and rapidly. To allow fast processing, intelligent sampling schemes for training databases should be incorporated to establish efficient machine learning (ML) models. In this study, we implemented active learning (AL) heuristics using kernel ridge regression (KRR) to minimize and optimize a training database for variational heteroscedastic Gaussian processes regression (V…
Quantifying Fundamental Vegetation Traits over Europe Using the Sentinel-3 OLCI Catalogue in Google Earth Engine
2022
Thanks to the emergence of cloud-computing platforms and the ability of machine learning methods to solve prediction problems efficiently, this work presents a workflow to automate spatiotemporal mapping of essential vegetation traits from Sentinel-3 (S3) imagery. The traits included leaf chlorophyll content (LCC), leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and fractional vegetation cover (FVC), being fundamental for assessing photosynthetic activity on Earth. The workflow involved Gaussian process regression (GPR) algorithms trained on top-of-atmosphere (TOA) radiance simulations generated by the coupled canopy radiative transfer model (RTM) SC…
Parabolic pulse generation through passive reshaping of gaussian pulses in a normally dispersive fiber
2007
We numerically and experimentally demonstrate that a Gaussian pulse can be reshaped into a pulse with a stable parabolic intensity profile during propagation in normally dispersive nonlinear fibers.
Pulsating Dissipative Light Bullets
2009
Finding domains of existence for (3+1)D spatio-temporal dissipative solitons, also called “dissipative light bullets”, by direct numerical solving of a cubic-quintic Ginzburg-Landau equation (CGLE) is a lengthy procedure [1,2]. Variational approaches pave the way for quicker soliton solution mapping, as long as tractable trial functions remain suitable approximations for exact solutions [3,4].
A Hybrid Algorithm Based on WiFi for Robust and Effective Indoor Positioning
2019
Indoor positioning based on the Wireless Fidelity (WiFi) protocol and the Pedestrian Dead Reckoning (PDR) approach is widely exploited because of the existing WiFi infrastructure in buildings and the advancement of built-in smartphone sensors. In this work, a hybrid algorithm that combines WiFi fingerprinting and PDR to both exploit their advantages as well as limiting the impact of their disadvantages is proposed. Specifically, to build a probability map from noisy Received Signal Strength (RSS), a Gaussian Process (GP) regression is deployed to estimate and construct the RSS fingerprints with incomplete data. Mean and variance of generated points are used to estimate WiFi fingerprinting p…
Machine Learning Methods for Spatial and Temporal Parameter Estimation
2020
Monitoring vegetation with satellite remote sensing is of paramount relevance to understand the status and health of our planet. Accurate and constant monitoring of the biosphere has large societal, economical, and environmental implications, given the increasing demand of biofuels and food by the world population. The current democratization of machine learning, big data, and high processing capabilities allow us to take such endeavor in a decisive manner. This chapter proposes three novel machine learning approaches to exploit spatial, temporal, multi-sensor, and large-scale data characteristics. We show (1) the application of multi-output Gaussian processes for gap-filling time series of…
Estudio integral de humedales altoandinos (andean peatlands) con Teledetección y SIG
2022
La Reserva de Producción de Fauna Chimborazo (RPFCH) es un ecosistema de alto valor situado en los andes ecuatorianos, ocupado en su mayor parte por turberas, también llamados bofedales o peatlands. El objetivo de esta tesis es el estudio de dichos ecosistemas a partir de una extensa base de datos de campo obtenida en 2016 y usando datos de teledetección óptica y radar y variables topográficas, ambientales y climáticas con SIG. Para ello se analizaron los mejores métodos para el cartografiado de los peatlands en la RPFCH, la estimación del carbono bajo el suelo (COS) en la capa 0-30 cm y la estimación del carbono almacenado en la vegetación calculado a partir de la biomasa. Como resultado s…
Evaluation of Hybrid Models to Estimate Chlorophyll and Nitrogen Content of Maize Crops in the Framework of the Future CHIME Mission
2022
In the next few years, the new Copernicus Hyperspectral Imaging Mission (CHIME) is foreseen to be launched by the European Space Agency (ESA). This mission 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. In this work, the hybrid approach (HYB) and its variant, featuring sampling dimensionality reduction through active learning heuristics (HAL), were applied to CHIME-like data to evaluate the…
Data Compensation with Gaussian Processes Regression: Application in Smart Building's Sensor Network
2022
Data play an essential role in the optimal control of smart buildings’ operation, especially in building energy-management for the target of nearly zero buildings. The building monitoring system is in charge of collecting and managing building data. However, device imperfections and failures of the monitoring system are likely to produce low-quality data, such as data loss and inconsistent data, which then seriously affect the control quality of the buildings. This paper proposes a new approach based on Gaussian process regression for data-quality monitoring and sensor network data compensation in smart buildings. The proposed method is proven to effectively detect and compensate for low-qu…
Distributed spatial prediction for radio environment maps reconstruction in heterogeneous wireless networks
2017
Las previsiones indican que el tráfico de datos móviles se multiplicará por siete en el periodo de 2016 a 2021, creciendo con una tasa agregada anual del 47%. Para satisfacer esta demanda, tanto la industria como la academia se están centrando en las redes de quinta generación o 5G. Las redes 5G se espera que constituyan un entorno complejo e interconectado, que además proporciones múltiples servicios y aplicaciones a un número masivo de usuarios y máquinas. En este concepto se incluye la necesidad de dar soporte o de crear servicios para el paradigma conocido como el Internet de las Cosas (IoT), donde la visión es la de crear un entorno de todo conectado con todo en todo momento, con aplic…