Search results for "ISP"
showing 10 items of 10048 documents
Modeling Rain Isotopic Composition under Orographic Control: A Landscape Approach for Hydrogeological Applications
2021
Oxygen isotopic composition is useful for individuating recharge areas of groundwater bodies by the comparison with those of local rainfalls. While on a global scale general relationships, such as the isotopic vertical gradient or continentality effects, efficiently describe spatial variations of the isotopic signature, hydrogeological applications need spatial models that are more focused on the effects of local topographic structures and/or subsoil geology. This work presents a case study in northeastern Sicily (Italy) characterized by complex geological and orographic structures, in which isotopic composition of rainfalls is governed by orographic effects and the varying initial composit…
Dimensionless Stage-Discharge Relationship for a Non-Linear Water Reservoir: Theory and Experiments
2020
In the field of hydrology, stage&ndash
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…
Validation of the Sentinel-3 Ocean and Land Colour Instrument (OLCI) Terrestrial Chlorophyll Index (OTCI): Synergetic Exploitation of the Sentinel-2 …
2018
Continuity to the Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) will be provided by the Sentinel-3 Ocean and Land Colour Instrument (OLCI), and to ensure its utility in a wide range of operational applications, validation efforts are required. In the past, these activities have been constrained by the need for costly airborne hyperspectral data acquisition, but the Sentinel-2 Multispectral Instrument (MSI) now offers a promising alternative. In this paper, we explore the synergetic use of Sentinel-2 MSI data for validation of the Sentinel-3 OLCI Terrestrial Chlorophyll Index (OTCI) over the Valencia Anchor Station, a large agricultural site in the Valen…
Optimized Class-Separability in Hyperspectral Images
2016
International audience; Image visualization techniques are mostly based on three bands as RGB color composite channels for human eye to characterize the scene. This, however, is not effective in case of hyper-spectral images (HSI) because they contain dozens of informative spectral bands. To eliminate redundancy of spectral information among these bands, dimensionality reduction (DR) is applied while at the same trying to retain maximum information. In this paper, we propose a new method of information-preserved hyper-spectral satellite image visualization that is based on fusion of unsupervised band selection techniques and color matching function (CMF) stretching. The results show consist…
Environmental and biological factors are joint drivers of mercury biomagnification in subarctic lake food webs along a climate and productivity gradi…
2021
Subarctic lakes are getting warmer and more productive due to the joint effects of climate change and intensive land-use practices (e.g. forest clear-cutting and peatland ditching), processes that potentially increase leaching of peat- and soil-stored mercury into lake ecosystems. We sampled biotic communities from primary producers (algae) to top consumers (piscivorous fish), in 19 subarctic lakes situated on a latitudinal (69.0-66.5 degrees N), climatic (+3.2 degrees C temperature and +30% precipitation from north to south) and catchment land-use (pristine to intensive forestry areas) gradient. We first tested how the joint effects of climate and productivity influence mercury biomagnific…
Multispectral high resolution sensor fusion for smoothing and gap-filling in the cloud
2020
Remote sensing optical sensors onboard operational satellites cannot have high spectral, spatial and temporal resolutions simultaneously. In addition, clouds and aerosols can adversely affect the signal contaminating the land surface observations. We present a HIghly Scalable Temporal Adaptive Reflectance Fusion Model (HISTARFM) algorithm to combine multispectral images of different sensors to reduce noise and produce monthly gap free high resolution (30 m) observations over land. Our approach uses images from the Landsat (30 m spatial resolution and 16 day revisit cycle) and the MODIS missions, both from Terra and Aqua platforms (500 m spatial resolution and daily revisit cycle). We implem…
Convolutional Neural Networks for Cloud Screening: Transfer Learning from Landsat-8 to Proba-V
2018
Cloud detection is a key issue for exploiting the information from Earth observation satellites multispectral sensors. For Proba-V, cloud detection is challenging due to the limited number of spectral bands. Advanced machine learning methods, such as convolutional neural networks (CNN), have shown to work well on this problem provided enough labeled data. However, simultaneous collocated information about the presence of clouds is usually not available or requires a great amount of manual labor. In this work, we propose to learn from the available Landsat −8 cloud masks datasets and transfer this learning to solve the Proba-V cloud detection problem. CNN are trained with Landsat images adap…
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.
The Influence of Crystal Size Distributions on the Rheology of Magmas: New Insights From Analog Experiments
2017
This study examines the influence of particle size distributions on the rheology of particle suspensions by using analogue experiments with spherical glass beads in silicone oil as magma equivalent. The analyses of 274 individual particle-bearing suspensions of varying modality (uni-, bi- tri- and tetramodality), as well as of polymodal suspensions with specific defined skewness and variance, are the first data set of its kind and provide important insights in the relationship between the solid particles of a suspension and its rheological behaviour. Since the relationship between the rheology of particle bearing suspensions and its maximum packing fraction ϕm is well established by several…