Search results for "Computers in Earth Science"

A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion

2015

article i nfo The focus of the current study is to compare data fusion methods applied to sensors with medium- and high- spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to incorporate prior spectral information.Furthermore, thestrengths of both algorithms arecombined ina novel data fusionmethod: the Spatial and Temporal Reflectance Unmixing Model (STRUM). The potential of each method is demonstrated using simulation imagery and Landsat and MODIS imagery. The theoretical basis of the algorithms causes STARFM and STRUM to produce Landsat-like reflecta…

Conventional and fuzzy comparisons of large scale land cover products: Application to CORINE, GLC2000, MODIS and GlobCover in Europe

2012

One of the major drawbacks of land cover products is the lack of interoperability among them. Since their development was driven by different national or international initiatives, they were developed for different purposes and hold diverse technical characteristics. Thus, comparison among products and quality monitoring is necessary in assessing their usefulness. This paper provides a methodology to compare global land cover maps that allows for differences in legend definitions among products. Two different approaches were considered for map comparison, a Boolean approach and a new methodology based on fuzzy set theory in which the Land Cover Classification System (LCCS) acted as a genera…

Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval

2013

Abstract ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we f…

Retrieval of carbon content and biomass from hyperspectral imagery over cultivated areas

2022

Tropical–extratropical interactions related to upper-level troughs at low latitudes

2007

Abstract Momentum and kinetic energy fluxes associated with low-latitude transient disturbances at upper-levels play an important role in the general circulation of the atmosphere. They are related to eastward and equatorward propagating, positively tilted wave trains from the extratropics. Theoretical, modelling and observational studies show that this particular kind of tropical–extratropical interaction is most common in regions of mean upper-level westerlies at low latitudes, i.e. over the central and eastern Pacific and Atlantic Oceans during boreal winter and spring. The penetration of an upper-level trough into the Tropics is often associated with enhanced convection and the formatio…

Uncertainty analysis of gross primary production upscaling using Random Forests, remote sensing and eddy covariance data

2015

Abstract The accurate quantification of carbon fluxes at continental spatial scale is important for future policy decisions in the context of global climate change. However, many elements contribute to the uncertainty of such estimate. In this study, the uncertainties of eight days gross primary production (GPP) predicted by Random Forest (RF) machine learning models were analysed at the site, ecosystem and European spatial scales. At the site level, the uncertainties caused by the missing of key drivers were evaluated. The most accurate predictions of eight days GPP were obtained when all available drivers were used (Pearson's correlation coefficient, ρ ~ 0.84; Root Mean Square Error (RMSE…

Three-dimensional numerical simulations on wind- and tide-induced currents: The case of Augusta Harbour (Italy)

2014

The hydrodynamic circulation in the coastal area of the Augusta Bay (Italy), located in the eastern part of Sicily, is analysed. Due to the heavy contamination generated by the several chemical and petrochemical industries active in the zone, the harbour was declared a Contaminated Site of National Interest. To mitigate the risks connected with the industrial activities located near the harbour, it is important to analyse the hydrodynamic circulation in the coastal area. To perform such analysis, a parallel 3D numerical model is used to solve the Reynolds-averaged momentum and mass balance, employing the k-e turbulence model for the Reynolds stresses. The numerical model is parallelized usi…

MDA: a MATLAB-based program for morphospace-disparity analysis

2003

A MATLAB® program that examines patterns of state-space occupation is described. Four subroutines are available with which to visualize morphospace patterns: (i) in terms of their features such as dispersion, aggregation and location, thereby allowing users to extract complementary quantitative information about how the state-space is structured, and (ii) in terms of changes in those patterns that can be compared with other biotic (e.g., extinction, origination rates) or abiotic (e.g., environmental proxy) information. The program incorporates many of the latest and most widely used statistical parameters for describing multivariate spaces. The parameters are estimated on the basis of boots…

OpenHVSR - Processing toolkit: Enhanced HVSR processing of distributed microtremor measurements and spatial variation of their informative content

2018

Abstract The investigation of seismic ambient noise (microtremor) in spectral ratio form, known as the Horizontal-to-Vertical Spectral Ratio technique, is extremely popular nowadays both to investigate large areas in a reduced amount of time, and to leverage a wider choice of low cost equipment. In general, measurements at multiple locations are collected to generate multiple, individual spectral ratio curves. Recently, however, there has been an increasing interest in spatially correlating informative content from different locations. Accordingly, we introduce a new computer program, “OpenHVSR – Processing Toolkit”, developed in Matlab (R2015b), specifically engineered to enhance data proc…

Integration of high and low resolution NDVI data for monitoring vegetation in Mediterranean environments

1998

Abstract The integration of the useful features of high and low spatial and temporal resolution satellite data is a major issue in remote sensing studies. The current work presents the development and testing of a procedure based on classification and regression analysis techniques for generating an NDVI data set with the spatial resolution of Landsat TM images and the temporal resolution of NOAA AVHRR maximum-value composites. The procedure begins with a classification of the high resolution TM data which yields land use references. These are degraded to low spatial resolution in order to produce abundance images comparable with the AVHRR data. Linear regressions are then applied between t…