Search results for "oftware"

A Survey on Gaussian Processes for Earth-Observation Data Analysis: A Comprehensive Investigation

2016

Gaussian processes (GPs) have experienced tremendous success in biogeophysical parameter retrieval in the last few years. GPs constitute a solid Bayesian framework to consistently formulate many function approximation problems. This article reviews the main theoretical GP developments in the field, considering new algorithms that respect signal and noise characteristics, extract knowledge via automatic relevance kernels to yield feature rankings automatically, and allow applicability of associated uncertainty intervals to transport GP models in space and time that can be used to uncover causal relations between variables and can encode physically meaningful prior knowledge via radiative tra…

Alg: a Toolbox for the Generation of Look-Up tables Based on Atmospheric Radiative Transfer Models

2018

Atmospheric radiative transfer models (RTMs) are software tools describing the radiation processes occurring on the Earth’s atmosphere. While the evolution of these tools have achieved better representations of the light-atmosphere interactions, the increase of complexity, interpretability and computation time bears implications towards practical applications in Earth observation. Despite of existing RTM-specific graphical user interfaces, none of these tools allow common streamlining model setup for a wide variety of atmospheric RTMs. In addition, the automatic generation of atmospheric look-up tables (LUTs) can hardly be done with the use of these graphical tools. This paper presents the …

Batch Methods for Resolution Enhancement of TIR Image Sequences

2015

Thermal infrared (TIR) time series are exploited by many methods based on Earth observation (EO), for such applications as agriculture, forest management, and meteorology. However, due to physical limitations, data acquired by a single sensor are often unsatisfactory in terms of spatial or temporal resolution. This issue can be tackled by using remotely sensed data acquired by multiple sensors with complementary features. When nonreal-time functioning or at least near real-time functioning is admitted, the measurements can be profitably fed to a sequential Bayesian algorithm, which allows to account for the correlation embedded in the successive acquisitions. In this work, we focus on appli…

Statistical biophysical parameter retrieval and emulation with Gaussian processes

2019

Abstract Earth observation from satellites poses challenging problems where machine learning is being widely adopted as a key player. Perhaps the most challenging scenario that we are facing nowadays is to provide accurate estimates of particular variables of interest characterizing the Earth's surface. This chapter introduces some recent advances in statistical bio-geophysical parameter retrieval from satellite data. In particular, we will focus on Gaussian process regression (GPR) that has excelled in parameter estimation as well as in modeling complex radiative transfer processes. GPR is based on solid Bayesian statistics and generally yields efficient and accurate parameter estimates, a…

Assessing forest landscape structure using geographic windows.

2001

Landscape structure, interpreted as indicator of functional processes, has become a main attribute of multiresource forest inventories, enhancing its value with respect to society needs. This approach implies effective use of earth observation techniques and geographic information systems to obtain a global view of the inventoried landscapes and to understand the ecological functions of large spatially-heterogeneous landscape mosaics. Landscape structure often reveal extremely complex patterns that can only be very roughly characterized by methods of Euclidean geometry. Conversely, fractals can be applied to adequately describe many of the irregular, fragmented patterns found in nature. In …

Advances in Kernel Machines for Image Classification and Biophysical Parameter Retrieval

2017

Remote sensing data analysis is knowing an unprecedented upswing fostered by the activities of the public and private sectors of geospatial and environmental data analysis. Modern imaging sensors offer the necessary spatial and spectral information to tackle a wide range problems through Earth Observation, such as land cover and use updating, urban dynamics, or vegetation and crop monitoring. In the upcoming years even richer information will be available: more sophisticated hyperspectral sensors with high spectral resolution, multispectral sensors with sub-metric spatial detail or drones that can be deployed in very short time lapses. Besides such opportunities, these new and wealthy infor…

Green LAI Mapping and Cloud Gap-Filling Using Gaussian Process Regression in Google Earth Engine

2021

For the last decade, Gaussian process regression (GPR) proved to be a competitive machine learning regression algorithm for Earth observation applications, with attractive unique properties such as band relevance ranking and uncertainty estimates. More recently, GPR also proved to be a proficient time series processor to fill up gaps in optical imagery, typically due to cloud cover. This makes GPR perfectly suited for large-scale spatiotemporal processing of satellite imageries into cloud-free products of biophysical variables. With the advent of the Google Earth Engine (GEE) cloud platform, new opportunities emerged to process local-to-planetary scale satellite data using advanced machine …

Empirical evidence for musical syntax processing? Computer simulations reveal the contribution of auditory short-term memory

2014

During the last decade, it has been argued that (1) music processing involves syntactic representations similar to those observed in language, and (2) that music and language share similar syntactic-like processes and neural resources. This claim is important for understanding the origin of music and language abilities and, furthermore, it has clinical implications. The Western musical system, however, is rooted in psychoacoustic properties of sound, and this is not the case for linguistic syntax. Accordingly, musical syntax processing could be parsimoniously understood as an emergent property of auditory memory rather than a property of abstract processing similar to linguistic processing.…

Introduction

1998

2015

The manner in which populations of inhibitory (INH) and excitatory (EXC) neocortical neurons collectively encode stimulus-related information is a fundamental, yet still unresolved question. Here we address this question by simultaneously recording with large-scale multi-electrode arrays (of up to 128 channels) the activity of cell ensembles (of up to 74 neurons) distributed along all layers of 3–4 neighboring cortical columns in the anesthetized adult rat somatosensory barrel cortex in vivo. Using two different whisker stimulus modalities (location and frequency) we show that individual INH neurons – classified as such according to their distinct extracellular spike waveforms – discriminat…