993 resultados para Temporal resolution
Resumo:
The importance of intermediate water masses in climate change and ocean circulation has been emphasized recently. In particular, Southern Ocean Intermediate Waters (SOIW), such as Antarctic Intermediate Water and Subantarctic Mode Water, are thought to have acted as active interhemispheric transmitter of climate anomalies. Here we reconstruct changes in SOIW signature and spatial and temporal evolution based on a 40 kyr time series of oxygen and carbon isotopes as well as planktic Mg/Ca based thermometry from Site GeoB12615-4 in the western Indian Ocean. Our data suggest that SOIW transmitted Antarctic temperature trends to the equatorial Indian Ocean via the "oceanic tunnel" mechanism. Moreover, our results reveal that deglacial SOIW carried a signature of aged Southern Ocean deep water. We find no evidence of increased formation of intermediate waters during the deglaciation.
Resumo:
The spatial and temporal dynamics of seagrasses have been studied from the leaf to patch (100 m**2) scales. However, landscape scale (> 100 km**2) seagrass population dynamics are unresolved in seagrass ecology. Previous remote sensing approaches have lacked the temporal or spatial resolution, or ecologically appropriate mapping, to fully address this issue. This paper presents a robust, semi-automated object-based image analysis approach for mapping dominant seagrass species, percentage cover and above ground biomass using a time series of field data and coincident high spatial resolution satellite imagery. The study area was a 142 km**2 shallow, clear water seagrass habitat (the Eastern Banks, Moreton Bay, Australia). Nine data sets acquired between 2004 and 2013 were used to create seagrass species and percentage cover maps through the integration of seagrass photo transect field data, and atmospherically and geometrically corrected high spatial resolution satellite image data (WorldView-2, IKONOS and Quickbird-2) using an object based image analysis approach. Biomass maps were derived using empirical models trained with in-situ above ground biomass data per seagrass species. Maps and summary plots identified inter- and intra-annual variation of seagrass species composition, percentage cover level and above ground biomass. The methods provide a rigorous approach for field and image data collection and pre-processing, a semi-automated approach to extract seagrass species and cover maps and assess accuracy, and the subsequent empirical modelling of seagrass biomass. The resultant maps provide a fundamental data set for understanding landscape scale seagrass dynamics in a shallow water environment. Our findings provide proof of concept for the use of time-series analysis of remotely sensed seagrass products for use in seagrass ecology and management.
Resumo:
This data set provides a high-resolution digital elevation model (DEM) of a thermokarst depression (~7 km²) on ice-complex deposits in the Arctic Lena Delta, Siberia. The DEM based on a geodetic field survey and was used for quantitative land surface analyses and detailed description of the thermokarst depression morphology. Detailed morphometrical analyses, volume calculations, and solar radiation modeling were performed and statistically analyzed by Ulrich et al. (2010) to investigate the asymmetrical thermokarst depression development and directed lake migration previously proposed by Morgenstern et al. (2008). Furthermore, the high-resolution DEM in combination with satellite data allowed detailed analyses of spatial and temporal landscape changes due to thermokarst development (Günther, 2009).
Resumo:
Conventional SAR (Synthetic Aperture Radar) techniques only consider a single reflection of transmitted waveforms from targets. Nevertheless, today?s new applications force SAR systems to work in much more complex scenes such as urban environments. As a result, multiple-bounce returns are additionally superposed to direct echoes. We refer to these as ghost images, since they obscure true target image and lead to poor resolution. By applying Time Reversal concept to SAR imaging (TR-SAR), it is possible to reduce considerably ?or almost mitigate? ghosting artifacts, recovering the lost resolution due to multipath effects. Furthermore, some focusing indicators such as entropy (E), contrast (C) and Rényi entropy (RE) provide us a good focusing criterion when using TR-SAR.
Resumo:
In this paper we propose an innovative approach to tackle the problem of traffic sign detection using a computer vision algorithm and taking into account real-time operation constraints, trying to establish intelligent strategies to simplify as much as possible the algorithm complexity and to speed up the process. Firstly, a set of candidates is generated according to a color segmentation stage, followed by a region analysis strategy, where spatial characteristic of previously detected objects are taken into account. Finally, temporal coherence is introduced by means of a tracking scheme, performed using a Kalman filter for each potential candidate. Taking into consideration time constraints, efficiency is achieved two-fold: on the one side, a multi-resolution strategy is adopted for segmentation, where global operation will be applied only to low-resolution images, increasing the resolution to the maximum only when a potential road sign is being tracked. On the other side, we take advantage of the expected spacing between traffic signs. Namely, the tracking of objects of interest allows to generate inhibition areas, which are those ones where no new traffic signs are expected to appear due to the existence of a TS in the neighborhood. The proposed solution has been tested with real sequences in both urban areas and highways, and proved to achieve higher computational efficiency, especially as a result of the multi-resolution approach.
Resumo:
Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.
Resumo:
This paper shows a system about the recognition of temporal expressions in Spanish and the resolution of their temporal reference. For the identification and recognition of temporal expressions we have based on a temporal expression grammar and for the resolution on an inference engine, where we have the information necessary to do the date operation based on the recognized expressions. For further information treatment, the output is proposed by means of XML tags in order to add standard information of the resolution obtained. Different kinds of annotation of temporal expressions are explained in another articles [WILSON2001][KATZ2001]. In the evaluation of our proposal we have obtained successful results.
Resumo:
This paper tells about the recognition of temporal expressions and the resolution of their temporal reference. A proposal of the units we have used to face up this tasks over a restricted domain is shown. We work with newspapers' articles in Spanish, that is why every reference we use is in Spanish. For the identification and recognition of temporal expressions we base on a temporal expression grammar and for the resolution on a dictionary, where we have the information necessary to do the date operation based on the recognized expressions. In the evaluation of our proposal we have obtained successful results for the examples studied.