Quantifying the Effect of Registration Error on Spatio-Temporal Fusion

It is challenging to acquire satellite sensor data with both fine spatial and fine temporal resolution, especially for monitoring at global scales. Among the widely used global monitoring satellite sensors, Landsat data have a coarse temporal resolution, but fine spatial resolution, while moderate resolution imaging spectroradiometer (MODIS) data have fine temporal resolution, but coarse spatial resolution. One solution to this problem is to blend the two types of data using spatio-temporal fusion, creating images with both fine temporal and fine spatial resolution. However, reliable geometric registration of images acquired by different sensors is a prerequisite of spatio-temporal fusion. Due to the potentially large differences between the spatial resolutions of the images to be fused, the geometric registration process always contains some degree of uncertainty. This article analyzes quantitatively the influence of geometric registration error on spatio-temporal fusion. The relationship between registration error and the accuracy of fusion was investigated under the influence of different temporal distances between images, different spatial patterns within the images and using different methods (i.e., spatial and temporal adaptive reflectance fusion model (STARFM), and Fit-FC; two typical spatio-temporal fusion methods). The results show that registration error has a significant impact on the accuracy of spatio-temporal fusion; as the registration error increased, the accuracy decreased monotonically. The effect of registration error in a heterogeneous region was greater than that in a homogeneous region. Moreover, the accuracy of fusion was not dependent on the temporal distance between images to be fused, but rather on their statistical correlation. Finally, the Fit-FC method was found to be more accurate than the STARFM method, under all registration error scenarios. © 2008-2012 IEEE

Anterior Hippocampus and Goal-Directed Spatial Decision Making

Contains fulltext : 115487.pdf (publisher's version ) (Open Access

The effect of the point spread function on downscaling continua

The point spread function (PSF) is ubiquitous in remote sensing. This paper investigated the effect of the PSF on the downscaling of continua. Geostatistical approaches were adopted to incorporate explicitly, and reduce the influence of, the PSF effect in downscaling. Two general cases were considered: univariate and multivariate. In the univariate case, the input coarse spatial resolution image is the only image available for downscaling. Area-to-point kriging was demonstrated to be a suitable solution in this case. For the multivariate case, a finer spatial resolution image (or images) observed under different conditions (e.g., at a different wavelength) is available as auxiliary data for downscaling. Area-to-point regression kriging was shown to be a suitable solution for this case. Moreover, a new solution was developed for estimating the PSF in image scale transformation. The experiments show that the PSF effect influences downscaling greatly and that downscaling can be enhanced obviously by considering the PSF effect through the geostatistical approaches and the PSF estimation solution proposed

Virtual image pair-based spatio-temporal fusion

Spatio-temporal fusion is a technique used to produce images with both fine spatial and temporal resolution. Generally, the principle of existing spatio-temporal fusion methods can be characterized by a unified framework of prediction based on two parts: (i) the known fine spatial resolution images (e.g., Landsat images), and (ii) the fine spatial resolution increment predicted from the available coarse spatial resolution increment (i.e., a downscaling process), that is, the difference between the coarse spatial resolution images (e.g., MODIS images) acquired at the known and prediction times. Owing to seasonal changes and land cover changes, there always exist large differences between images acquired at different times, resulting in a large increment and, further, great uncertainty in downscaling. In this paper, a virtual image pair-based spatio-temporal fusion (VIPSTF) approach was proposed to deal with this problem. VIPSTF is based on the concept of a virtual image pair (VIP), which is produced based on the available, known MODIS-Landsat image pairs. We demonstrate theoretically that compared to the known image pairs, the VIP is closer to the data at the prediction time. The VIP can capture more fine spatial resolution information directly from known images and reduce the challenge in downscaling. VIPSTF is a flexible framework suitable for existing spatial weighting- and spatial unmixing-based methods, and two versions VIPSTF-SW and VIPSTF-SU are, thus, developed. Experimental results on a heterogeneous site and a site experiencing land cover type changes show that both spatial weighting- and spatial unmixing-based methods can be enhanced by VIPSTF, and the advantage is particularly noticeable when the observed image pairs are temporally far from the prediction time. Moreover, VIPSTF is free of the need for image pair selection and robust to the use of multiple image pairs. VIPSTF is also computationally faster than the original methods when using multiple image pairs. The concept of VIP provides a new insight to enhance spatio-temporal fusion by making fuller use of the observed image pairs and reducing the uncertainty of estimating the fine spatial resolution increment. © 2020 Elsevier Inc

Geographically Weighted Spatial Unmixing for Spatiotemporal Fusion

Spatiotemporal fusion is a technique applied to create images with both fine spatial and temporal resolutions by blending images with different spatial and temporal resolutions. Spatial unmixing (SU) is a widely used approach for spatiotemporal fusion, which requires only the minimum number of input images. However, ignorance of spatial variation in land cover between pixels is a common issue in existing SU methods. For example, all coarse neighbors in a local window are treated equally in the unmixing model, which is inappropriate. Moreover, the determination of the appropriate number of clusters in the known fine spatial resolution image remains a challenge. In this article, a geographically weighted SU (SU-GW) method was proposed to address the spatial variation in land cover and increase the accuracy of spatiotemporal fusion. SU-GW is a general model suitable for any SU method. Specifically, the existing regularized version and soft classification-based version were extended with the proposed geographically weighted scheme, producing 24 versions (i.e., 12 existing versions were extended to 12 corresponding geographically weighted versions) for SU. Furthermore, the cluster validity index of Xie and Beni (XB) was introduced to determine automatically the number of clusters. A systematic comparison between the experimental results of the 24 versions indicated that SU-GW was effective in increasing the prediction accuracy. Importantly, all 12 existing methods were enhanced by integrating the SU-GW scheme. Moreover, the identified most accurate SU-GW enhanced version was demonstrated to outperform two prevailing spatiotemporal fusion approaches in a benchmark comparison. Therefore, it can be concluded that SU-GW provides a general solution for enhancing spatiotemporal fusion, which can be used to update existing methods and future potential versions

Genetic and bioinformatic analyses of the expression and function of PI3K regulatory subunit PIK3R3 in an Asian patient gastric cancer library

10.1186/1755-8794-5-34BMC Medical Genomics5

Change in angina symptom status after acute myocardial infarction and its association with readmission risk: An analysis of the translational research investigating underlying disparities in acute myocardial infarction patients' health status (TRIUMPH) registry

Angina is common both before and after myocardial infarction (MI). Whether the change in angina status within the first 30 days after MI is associated with subsequent readmission and angina persistence is unknown.We studied 2915 MI patients enrolled at 24 hospitals in the Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) registry. Angina before and 30 days after MI was assessed with the Seattle Angina Questionnaire. Patients were divided into angina-free pre- and post-MI (-/-), resolved angina (+/-), new angina (-/+), and persistent angina (+/+) groups. Multivariable proportional hazards and hierarchical modified Poisson models were performed to assess the association of each group with all-cause readmission, readmission for MI or unplanned revascularization, and angina persistence at 1 year. Overall, 1293 patients (44%) had angina before their MI and 849 (29%) reported angina within 30 days of discharge. Patients with post-MI angina were more likely to be younger, nonwhite, and uninsured. Compared with patients who were angina-free pre- and post-MI, 1-year all-cause readmission risks were significantly higher for patients with persistent angina (hazard ratio [HR], 1.35; 95% CI 1.06-1.71) or new angina (HR, 1.40; 95% CI, 1.08-1.82). At 1 year, angina was present in 22% of patients and was more likely if angina was persistent (HR, 3.55; 95% CI, 3.05-4.13) or new (HR, 3.38; 95% CI, 2.59-4.42) at 30 days compared with patients who were angina-free pre- and post-MI.Post-MI angina, whether new or persistent, is associated with higher likelihood of readmission. Prioritizing post-MI angina management is a potential means of improving 1-year outcomes.Jacob A. Doll, Fengming Tang, Sharon Cresci, P. Michael Ho, Thomas M. Maddox, John A. Spertus and Tracy Y. Wan

Universal features of the order-parameter fluctuations : reversible and irreversible aggregation

We discuss the universal scaling laws of order parameter fluctuations in any system in which the second-order critical behaviour can be identified. These scaling laws can be derived rigorously for equilibrium systems when combined with the finite-size scaling analysis. The relation between order parameter, criticality and scaling law of fluctuations has been established and the connexion between the scaling function and the critical exponents has been found. We give examples in out-of-equilibrium aggregation models such as the Smoluchowski kinetic equations, or of at-equilibrium Ising and percolation models.Comment: 19 pages, 10 figure

Charged pion form factor between Q^2=0.60 and 2.45 GeV^2. II. Determination of, and results for, the pion form factor

The charged pion form factor, Fpi(Q^2), is an important quantity which can be used to advance our knowledge of hadronic structure. However, the extraction of Fpi from data requires a model of the 1H(e,e'pi+)n reaction, and thus is inherently model dependent. Therefore, a detailed description of the extraction of the charged pion form factor from electroproduction data obtained recently at Jefferson Lab is presented, with particular focus given to the dominant uncertainties in this procedure. Results for Fpi are presented for Q^2=0.60-2.45 GeV^2. Above Q^2=1.5 GeV^2, the Fpi values are systematically below the monopole parameterization that describes the low Q^2 data used to determine the pion charge radius. The pion form factor can be calculated in a wide variety of theoretical approaches, and the experimental results are compared to a number of calculations. This comparison is helpful in understanding the role of soft versus hard contributions to hadronic structure in the intermediate Q^2 regime.Comment: 18 pages, 11 figure

Flux Phase as a Dynamic Jahn-Teller Phase: Berryonic Matter in the Cuprates?

There is considerable evidence for some form of charge ordering on the hole-doped stripes in the cuprates, mainly associated with the low-temperature tetragonal phase, but with some evidence for either charge density waves or a flux phase, which is a form of dynamic charge-density wave. These three states form a pseudospin triplet, demonstrating a close connection with the E X e dynamic Jahn-Teller effect, suggesting that the cuprates constitute a form of Berryonic matter. This in turn suggests a new model for the dynamic Jahn-Teller effect as a form of flux phase. A simple model of the Cu-O bond stretching phonons allows an estimate of electron-phonon coupling for these modes, explaining why the half breathing mode softens so much more than the full oxygen breathing mode. The anomalous properties of $O^{2-}$ provide a coupling (correlated hopping) which acts to stabilize density wave phases.Comment: Major Revisions: includes comparisons with specific cuprate phonon modes, 16 eps figures, revte