Search results for "computers"
showing 10 items of 3243 documents
FAME: Software for analysing rock microstructures
2016
Determination of rock microstructures leads to a better understanding of the formation and deformation of polycrystalline solids. Here, we present FAME (Fabric Analyser based Microstructure Evaluation), an easy-to-use MATLAB®-based software for processing datasets recorded by an automated fabric analyser microscope. FAME is provided as a MATLAB®-independent Windows® executable with an intuitive graphical user interface. Raw data from the fabric analyser microscope can be automatically loaded, filtered and cropped before analysis. Accurate and efficient rock microstructure analysis is based on an advanced user-controlled grain labelling algorithm. The preview and testing environments simplif…
Comparison of gap-filling techniques applied to the CCI soil moisture database in Southern Europe
2021
Abstract Soil moisture (SM) is a key variable that plays an important role in land-atmosphere interactions. Monitoring SM is crucial for many applications and can help to determine the impact of climate change. Therefore, it is essential to have continuous and long-term databases for this variable. Satellite missions have contributed to this; however, the continuity of the series is compromised due to the data gaps derived by different factors, including revisit time, presence of seasonal ice or Radio Frequency Interference (RFI) contamination. In this work, the applicability of different gap-filling techniques is evaluated on the ESA Climate Change Initiative (CCI) SM combined product, whi…
Linking photosynthesis and sun-induced fluorescence at sub-daily to seasonal scales
2018
Abstract Due to its close link to the photosynthetic process, sun-induced chlorophyll fluorescence (F) opens new possibilities to study dynamics of photosynthetic light reactions and to quantify CO2 assimilation rates. Although recent studies show that F is linearly related to gross primary production (GPP) on coarse spatial and temporal scales, it is argued that this relationship may be mainly driven by seasonal changes in absorbed photochemical active radiation (APAR) and less by the plant light use efficiency (LUE). In this work a high-resolution spectrometer was used to continuously measure red and far-red fluorescence and different reflectance indices within a sugar beet field during t…
Transferring deep learning models for cloud detection between Landsat-8 and Proba-V
2020
Abstract Accurate cloud detection algorithms are mandatory to analyze the large streams of data coming from the different optical Earth observation satellites. Deep learning (DL) based cloud detection schemes provide very accurate cloud detection models. However, training these models for a given sensor requires large datasets of manually labeled samples, which are very costly or even impossible to create when the satellite has not been launched yet. In this work, we present an approach that exploits manually labeled datasets from one satellite to train deep learning models for cloud detection that can be applied (or transferred) to other satellites. We take into account the physical proper…
Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress
2019
Remote sensing of solar-induced chlorophyll fluorescence (SIF) is a rapidly advancing front in terrestrial vegetation science, with emerging capability in space-based methodologies and diverse application prospects. Although remote sensing of SIF – especially from space – is seen as a contemporary new specialty for terrestrial plants, it is founded upon a multi-decadal history of research, applications, and sensor developments in active and passive sensing of chlorophyll fluorescence. Current technical capabilities allow SIF to be measured across a range of biological, spatial, and temporal scales. As an optical signal, SIF may be assessed remotely using high-resolution spectral sensors in …
Spectral alignment of multi-temporal cross-sensor images with automated kernel canonical correlation analysis
2015
In this paper we present an approach to perform relative spectral alignment between optical cross-sensor acquisitions. The proposed method aims at projecting the images from two different and possibly disjoint input spaces into a common latent space, in which standard change detection algorithms can be applied. The system relies on the regularized kernel canonical correlation analysis transformation (kCCA), which can accommodate nonlinear dependencies between pixels by means of kernel functions. To learn the projections, the method employs a subset of samples belonging to the unchanged areas or to uninteresting radiometric differences. Since the availability of ground truth information to p…
Validation of HF radar sea surface currents in the Malta-Sicily Channel
2019
Abstract A network of High-Frequency radar (HFR) stations runs operationally in the Malta-Sicily Channel (MSC), Central Mediterranean Sea, providing sea surface current maps with high temporal (1 h) and spatial (3 × 3 km) resolutions since August 2012. Comparisons with surface drifter data and near-surface Acoustic Doppler Current Profiler (ADCP) observations, as well as radar site-to-site baseline analyses, provide quantitative assessments of HFR velocities accuracy. Twenty-two drifters were deployed within the HFR domain of coverage between December 2012 and October 2013. Additionally, six ADCP vertical current profiles were collected at selected positions during a dedicated field survey.…
Synergistic use of MERIS and AATSR as a proxy for estimating Land Surface Temperature from Sentinel-3 data
2016
Land Surface Temperature (LST) is one of the key parameters in the physics of land-surface processes on regional and global scales, combining the results of all surface-atmosphere interactions and energy fluxes between the surface and the atmosphere. With the advent of the ESA's Sentinel 3 (S3) satellite, accurate LST retrieval methodologies exploiting the synergy between OLCI and SLSTR instruments can be developed. In this paper we propose a candidate methodology for retrieving LST from data acquired with the forthcoming S3 instruments. The LST algorithm is based on the Split-Window (SW) technique with an explicit dependence on surface emissivity, in contrast to the AATSR level 2 algorithm…
Estimating high resolution evapotranspiration from disaggregated thermal images
2016
Abstract Accurate evapotranspiration (ET) estimations based on surface energy balance from remote sensing require information in the thermal infrared (TIR) domain, normally provided with an insufficient spatial resolution. In order to estimate ET in heterogeneous agricultural areas, we inspect in this paper the use of disaggregation techniques applied to two different sensors, such as MODIS (daily revisit cycle and 1 km spatial resolution in the TIR domain) and Spot 5 (5 days revisit cycle and 10 m spatial resolution in the VNIR bands but no TIR band). Spot 5 images were used as a proxy for upcoming Sentinel-2. The Simplified Two-Source Energy Balance (STSEB) model was used for the estimati…
Half a century of forest cover change along the Latvian-Russian border captured by object-based image analysis of Corona and Landsat TM/OLI data
2020
Abstract After 1991, major events, such as the collapse of socialism and the transition to market economies, caused land use change across the former USSR and affected forests in particular. However, major land use changes may have occurred already during Soviet rule, but those are largely unknown and difficult to map for large areas because 30-m Landsat data is not available prior to the 1980s. Our goal was to analyze the rates and determinants of forest cover change from 1967 to 2015 along the Latvian-Russian border, and to develop an object-based image analysis approach to compare forest cover based on declassified Corona spy satellite images from 1967 with that derived from Landsat 5 TM…