Search results for " mining"
showing 10 items of 1548 documents
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…
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 …
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 …
Working in a boom-town: Female perspectives on gold-mining in Burkina Faso
2009
Abstract In Burkina Faso, informal mining camps attract girls and women from rural areas because they offer a variety of income generating activities and access to urban consumer goods. Moreover, migration to the mines also allows for a different life-style and greater personal freedom. On the other hand, by going to the mining camps, girls and women risk acquiring a bad reputation in their communities because they are suspected of having illicit sexual relationships. In fact, relationships with gold miners and the material benefits connected with them are among the lures of the gold mines. Thus, from a female perspective migration to the gold mines is fraught with ambivalence, which is exp…
Paradigms on landfill mining: From dump site scavenging to ecosystem services revitalization
2017
For the next century to come, one of the biggest challenges is to provide the mankind with relevant and sufficient resources. Recovery of secondary resources plays a significant role. Industrial processes developed to regain minerals for commodity production in a circular economy become ever more important in the European Union and worldwide. Landfill mining (LFM) constitutes an important technological toolset of processes that regain resources and redistribute them with an accompanying reduction of hazardous influence of environmental contamination and other threats for human health hidden in former dump sites and landfills. This review paper is devoted to LFM problems, historical developm…
Forecasting the pulse
2013
Purpose – The steady increase of data on human behavior collected online holds significant research potential for social scientists. The purpose of this paper is to add a systematic discussion of different online services, their data generating processes, the offline phenomena connected to these data, and by demonstrating, in a proof of concept, a new approach for the detection of extraordinary offline phenomena by the analysis of online data. Design/methodology/approach – To detect traces of extraordinary offline phenomena in online data, the paper determines the normal state of the respective communication environment by measuring the regular dynamics of specific variables in data documen…
Experimental investigation of low-frequency pulsed Lorentz force influence on the motion of Galinstan melt
2016
Abstract The paper presents the results of the numerical and physical experiments, aimed at assessing the influence of pulsed force of electromagnetic field on the melt motion and the fluid velocities. The experiment was performed on the eutectic alloy Galinstan in the cylindrical volume, where an ultrasonic Doppler velocimeter was employed for velocity measurements under conditions of pulsed and steady EM field application. A numerical simulation of the melt flow, forced by the steady EM force, involved a 2D axisymmetric model. The k-e turbulence model was used to obtain the information about the melt velocities. The verification of the numerical model was carried out for the steady case. …
A Web Application for Interactive Visualization of European Basketball Data
2020
The statistical analysis of basketball games is a fast-growing field. Certainly, basketball data are scientifically relevant because an appropriate analysis provides a great deal of information about the performance of both players and teams. The number of games played each season generates a large amount of data worth analyzing. Basketball analytics is well established in U.S. leagues. In Europe, however, it has not been duly developed. This study focuses on the top three European team competitions: the EuroLeague, the EuroCup, and the Spanish ACB (Association of Basketball Clubs, acronym in Spanish) league. Their official websites provide access to game data for anyone who is interested, …