Search results for "sif"
showing 10 items of 30916 documents
Influence of Wind on Suspended Matter in the Water of the Albufera of Valencia (Spain)
2021
Wind is one of the factors that has a great influence on suspended matter in lakes, especially in shallow lagoons. In order to know how wind affects the water in Albufera of Valencia, a shallow coastal lagoon, the measured variables of turbidity and transparency have been correlated with the estimates by processing Sentinel-2 satellite images with the Sen2Cor processor. Data from four years of study show that most of them are light to gentle easterly breezes and moderate to fresh westerly breezes. The results obtained show significant correlations between the measured variables and those obtained from the satellite images for total suspended matter and water transparency and with the averag…
An Ecohydrological Cellular Automata Model Investigation of Juniper Tree Encroachment in a Western North American Landscape
2016
Woody plant encroachment over the past 140 years has substantially changed grasslands in western North American. We studied encroachment of western juniper (Juniperus occidentalis var. occidentalis) into a previously mixed shrubâgrassland site in central Oregon (USA) using a modified version of Cellular Automata TreeâGrassâShrub Simulator (CATGraSS) ecohydrological model. We developed simple algorithms to simulate three encroachment factors (grazing, fire frequency reduction, and seed dispersal by herbivores) in CATGraSS. Local ecohydrological dynamics represented by the model were first evaluated using satellite-derived leaf area index and measured evapotranspiration data. Reconstruc…
X-ray emission from young brown dwarfs in the Orion Nebula Cluster
2005
We use the sensitive X-ray data from the Chandra Orion Ultradeep Project (COUP) to study the X-ray properties of 34 spectroscopically-identified brown dwarfs with near-infrared spectral types between M6 and M9 in the core of the Orion Nebula Cluster. Nine of the 34 objects are clearly detected as X-ray sources. The apparently low detection rate is in many cases related to the substantial extinction of these brown dwarfs; considering only the BDs with $A_V \leq 5$ mag, nearly half of the objects (7 out of 16) are detected in X-rays. Our 10-day long X-ray lightcurves of these objects exhibit strong variability, including numerous flares. While one of the objects was only detected during a sho…
Recent Advances in Techniques for Hyperspectral Image Processing
2009
International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging
2017
Made available in DSpace on 2018-12-11T17:11:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2017-03-01 Suomen Akatemia Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees repr…
Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks
2020
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown superior results when comparing with conventional machine learning methods such as multi-layer perceptron (MLP) in cases of huge input data. The objective of this research is to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were emp…
Changements environnementaux survenant à la limite Oligocène/Miocène du bassin des Limagnes (Massif central, France).
2018
16 pages; International audience; Continental environments are very sensitive to climatic variations. A unique opportunity to study the climate changes around the Oligocene/Miocene boundary is offered by the Limagne graben Basin (France) where this stage boundary is well constrained by fossils. Indeed, some localities of the Limagne Graben Basin are so rich in mammal remains that they have become a European reference for mammal biostratigraphy. The dominant sedimentary facies of the lacustrine deposits in the northern part of the Limagne Graben Basin are composed of poorly cemented marls and calcarenites containing various plants and animals remains (e.g. algae, fish bones and teeth, gastro…
Efficient remote sensing image classification with Gaussian processes and Fourier features
2017
This paper presents an efficient methodology for approximating kernel functions in Gaussian process classification (GPC). Two models are introduced. We first include the standard random Fourier features (RFF) approximation into GPC, which largely improves the computational efficiency and permits large scale remote sensing data classification. In addition, we develop a novel approach which avoids randomly sampling a number of Fourier frequencies, and alternatively learns the optimal ones using a variational Bayes approach. The performance of the proposed methods is illustrated in complex problems of cloud detection from multispectral imagery.
SVM-based classification of High resolution Urban Satellites Images using Dense SURF and Spectral Information
2018
Remote-sensing focusing on image classification knows a large progress and receives the attention of the remote-sensing community day by day. Combining many kinds of extracted features has been successfully applied to High resolution urban satellite images using support vector machine (SVM). In this paper, we present a methodology that is promoting a performed classification by using pixel-wise SURF description features combined with spectral information in Cielab space for the first time on common scenes of urban imagery. The proposed method gives a promising classification accuracy when compared with the two types of features used separately.
SAR Image Classification Combining Structural and Statistical Methods
2011
The main objective of this paper is to develop a new technique of SAR image classification. This technique combines structural parameters, including the Sill, the slope, the fractal dimension and the range, with statistical methods in a supervised image classification. Thanks to the range parameter, we define the suitable size of the image window used in the proposed approach of supervised image classification. This approach is based on a new way of characterising different classes identified on the image. The first step consists in determining relevant area of interest. The second step consists in characterising each area identified, by a matrix. The last step consists in automating the pr…