Search results for "algorithm"
showing 10 items of 4887 documents
Crop specific algorithms trained over ground measurements provide the best performance for GAI and fAPAR estimates from Landsat-8 observations
2021
Abstract Estimation of Green Area Index (GAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR) from decametric satellites was investigated in this study using a large database of ground measurements over croplands. It covers six main crop types including rice, corn, wheat and barley, sunflower, soybean and other types of crops. Ground measurements were completed using either digital hemispherical cameras, LAI-2000 or AccuPAR devices over sites representative of a decametric pixel. Sites were spread over the globe and the data collected at several growth stages concurrently to the acquisition of Landsat-8 images. Several machine learning techniques were investigated to re…
Vicarious Calibration of the Landsat 7 Thermal Infrared Band and LST Algorithm Validation of the ETM+ Instrument Using Three Global Atmospheric Profi…
2017
Due to problems in the thermal infrared sensor on-board the Landsat-8 satellite, Landsat-7 (L7) can be an interesting alternative source of thermal data because it is the only source of well-calibrated, free, high-resolution data. To contribute to the quality of thermal data, a vicarious calibration (VC) of the enhanced thematic mapper instrument and a validation of the single-channel general equation and the water vapor approach algorithm in conjunction with an inversion of the radiative transfer equation (RTE) have been performed during 2013–2015 over two Spanish test sites. For this purpose, three global atmospheric profile data sets were used to better characterize the error due to atmo…
A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data
2017
Abstract To determine aerosol optical thickness, AOT, and other geophysical parameters describing conditions in the atmosphere and at the earth's surface by inversion of remote sensing measurements from space based instrumentation, it is necessary to separate ground scenes into cloud free and cloudy or cloud contaminated. Identifying the presence of cloud in a ground scene and establishing an accurate and adequate cloud mask is a challenging task. In this study, measurements by the European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS) have been used to develop a cloud identification and cloud mask algorithm for preprocessing prior to application of the new algorithm cal…
Determination of water speciation in hydrous haplogranitic glasses with partial Raman spectra
2020
Abstract We use a mathematical approach to decompose the Raman water band at 3000 cm−1 to 3750 cm−1 into two partial Raman spectra corresponding to the individual Raman activity of the two water species, i.e., molecular water (H2Om) and OH-groups, present in hydrous rhyolitic glasses. The approach is based on a least-squares optimization algorithm and the assumption that the water band can be expressed as a linear combination of two partial Raman spectra. Our model makes no assumptions regarding the shape of the partial Raman spectra. The model input consists of about 700 Raman spectra from hydrous haplogranitic (HPG8) compositions with total water contents from 0.6 to 3.1 wt% and with know…
Evaluation of deep learning algorithms for national scale landslide susceptibility mapping of Iran
2021
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then d…
Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review
2020
Abstract Green fractional vegetation cover ( f c ) is an important phenotypic factor in the fields of agriculture, forestry, and ecology. Spatially explicit monitoring of f c via relative vegetation abundance (RA) algorithms, especially those based on scaled maximum/minimum vegetation index (VI) values, has been widely investigated in remote sensing research. Although many studies have explored the effectiveness of RA algorithms over the past 30 years, a literature review summarizing the corresponding theoretical background, issues, current state-of-the-art techniques, challenges, and prospects has not yet been published. The overall objective of the present study was to accomplish a compre…
Modelling Complex Volume Shape Using Ellipsoid: Application to Pore Space Representation
2017
Natural shapes have complex volume forms that are usually difficult to model using simple analytical equations. The complexity of the representation is due to the heterogeneity of the physical environment and the variety of phenomena involved. In this study we consider the representation of the porous media. Thanks to the technological advances in Computed Topography scanners, the acquisition of images of complex shapes becomes possible. However, and unfortunately, the image data is not directly usable for simulation purposes. In this paper, we investigate the modeling of such shapes using a piece wise approximation of image data by ellipsoids. We propose to use a split-merge strategy and a…
Vicarious Calibration of Landsat-8 Thermal Data Collections and its Influence on Split-Window Algorithm Validation
2018
Landsat 8 (L8) satellite was launched on February 11, 2013 with two thermal bands located in the atmospheric window between $10-12\ \mu \mathrm{m}$ . Continuous monitoring of the Thermal Infrared Sensor (TIRS) onboard of L8 was performed over two Spanish test sites – Barrax and Donana – in order to contribute to the quality of TIRS data. In this work, a Vicarious Calibration (VC) of the TIRS bands was performed between years 2013–2016 in order to assess the new Stray Light (SL) data correction. The results of VC show us that band 10 and 11 provide accurate results (bias near to zero, and precision around 0.8 K) which is an improvement – especially for band 11 – in comparison to preprocessed…
Performance analysis of Alamouti-coded OFDM systems over spatio-temporally correlated underwater acoustic channels
2017
In this paper, we analyze the performance of Alamouti-coded orthogonal frequency division multiplexing (OFDM) systems over time-varying underwater acoustic (UWA) channels. A realistic UWA channel model has been considered, which can be correlated in either time or space or simultaneously in both domains. An exact analytical expression for the bit error probability (BEP) is necessary to analyze accurately the performance of Alamouti-coded OFDM systems over the spatio-temporally correlated UWA channel model. Hence, by using this UWA channel model, an expression has been derived for the BEP of Alamouti-coded OFDM systems assuming that the receiver knows perfectly the channel state information.…
The ecogenetic link between demography and evolution: can we bridge the gap between theory and data?
2007
Calls to understand the links between ecology and evolution have been common for decades. Population dynamics, i.e. the demographic changes in populations, arise from life history decisions of individuals and thus are a product of selection, and selection, on the contrary, can be modified by such dynamical properties of the population as density and stability. It follows that generating predictions and testing them correctly requires considering this ecogenetic feedback loop whenever traits have demographic consequences, mediated via density dependence (or frequency dependence). This is not an easy challenge, and arguably theory has advanced at a greater pace than empirical research. Howeve…