An ASIFT-based local registration method for satellite imagery

Imagery registration is a fundamental step, which greatly affects later processes in image mosaic, multi-spectral image fusion, digital surface modelling, etc., where the final solution needs blending of pixel information from more than one images. It is highly desired to find a way to identify registration regions among input stereo image pairs with high accuracy, particularly in remote sensing applications in which ground control points (GCPs) are not always available, such as in selecting a landing zone on an outer space planet. In this paper, a framework for localization in image registration is developed. It strengthened the local registration accuracy from two aspects: less reprojection error and better feature point distribution. Affine scale-invariant feature transform (ASIFT) was used for acquiring feature points and correspondences on the input images. Then, a homography matrix was estimated as the transformation model by an improved random sample consensus (IM-RANSAC) algorithm. In order to identify a registration region with a better spatial distribution of feature points, the Euclidean distance between the feature points is applied (named the S criterion). Finally, the parameters of the homography matrix were optimized by the Levenberg–Marquardt (LM) algorithm with selective feature points from the chosen registration region. In the experiment section, the Chang’E-2 satellite remote sensing imagery was used for evaluating the performance of the proposed method. The experiment result demonstrates that the proposed method can automatically locate a specific region with high registration accuracy between input images by achieving lower root mean square error (RMSE) and better distribution of feature points.

Representing the Arctic in global surface temperature time series of recent climate change

The Arctic is an important region in the study of climate change, but monitoring surface temperatures in this region is challenging, particularly in areas covered by sea ice. Here in situ, satellite and reanalysis data were utilised to investigate whether global warming over recent decades could be better estimated by changing the way the Arctic is treated in calculating global mean temperature. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques. Kriging techniques provided the smallest errors in anomaly estimates. Similar accuracies were found for anomalies estimated from in situ meteorological station SAT records using a kriging technique. Whether additional data sources, which are not currently utilised in temperature anomaly datasets, would improve estimates of Arctic surface air temperature anomalies was investigated within the reanalysis testbed and using in situ data. For the reanalysis study, the additional input anomalies were reanalysis data sampled at certain supplementary data source locations over Arctic land and sea ice areas. For the in situ data study, the additional input anomalies over sea ice were surface temperature anomalies derived from the Advanced Very High Resolution Radiometer satellite instruments. The use of additional data sources, particularly those located in the Arctic Ocean over sea ice or on islands in sparsely observed regions, can lead to substantial improvements in the accuracy of estimated anomalies. Decreases in Root Mean Square Error can be up to 0.2K for Arctic-average anomalies and more than 1K for spatially resolved anomalies. Further improvements in accuracy may be accomplished through the use of other data sources.

Optimised frequency grids for infrared radiative transfer simulations in cloudy conditions

This paper shows that radiometer channel radiances for cloudy atmospheric conditions can be simulated with an optimised frequency grid derived under clear-sky conditions. A new clear-sky optimised grid is derived for AVHRR channel 5 ð12 m m, 833 cm �1 Þ. For HIRS channel 11 ð7:33 m m, 1364 cm �1 Þ and AVHRR channel 5, radiative transfer simulations using an optimised frequency grid are compared with simulations using a reference grid, where the optimised grid has roughly 100–1000 times less frequencies than the full grid. The root mean square error between the optimised and the reference simulation is found to be less than 0.3 K for both comparisons, with the magnitude of the bias less than 0.03 K. The simulations have been carried out with the radiative transfer model Atmospheric Radiative Transfer Simulator (ARTS), version 2, using a backward Monte Carlo module for the treatment of clouds. With this module, the optimised simulations are more than 10 times faster than the reference simulations. Although the number of photons is the same, the smaller number of frequencies reduces the overhead for preparing the optical properties for each frequency. With deterministic scattering solvers, the relative decrease in runtime would be even more. The results allow for new radiative transfer applications, such as the development of new retrievals, because it becomes much quicker to carry out a large number of simulations. The conclusions are applicable to any downlooking infrared radiometer.

Uncertainties in tidally adjusted estimates of sea level rise flooding (bathtub model) for the Greater London

Sea-level rise (SLR) from global warming may have severe consequences for coastal cities, particularly when combined with predicted increases in the strength of tidal surges. Predicting the regional impact of SLR flooding is strongly dependent on the modelling approach and accuracy of topographic data. Here, the areas under risk of sea water flooding for London boroughs were quantified based on the projected SLR scenarios reported in Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) and UK climatic projections 2009 (UKCP09) using a tidally-adjusted bathtub modelling approach. Medium- to very high-resolution digital elevation models (DEMs) are used to evaluate inundation extents as well as uncertainties. Depending on the SLR scenario and DEMs used, it is estimated that 3%–8% of the area of Greater London could be inundated by 2100. The boroughs with the largest areas at risk of flooding are Newham, Southwark, and Greenwich. The differences in inundation areas estimated from a digital terrain model and a digital surface model are much greater than the root mean square error differences observed between the two data types, which may be attributed to processing levels. Flood models from SRTM data underestimate the inundation extent, so their results may not be reliable for constructing flood risk maps. This analysis provides a broad-scale estimate of the potential consequences of SLR and uncertainties in the DEM-based bathtub type flood inundation modelling for London boroughs.

A new adaptive multiple modelling approach for non-linear and non-stationary systems

This paper proposes a novel adaptive multiple modelling algorithm for non-linear and non-stationary systems. This simple modelling paradigm comprises K candidate sub-models which are all linear. With data available in an online fashion, the performance of all candidate sub-models are monitored based on the most recent data window, and M best sub-models are selected from the K candidates. The weight coefficients of the selected sub-model are adapted via the recursive least square (RLS) algorithm, while the coefficients of the remaining sub-models are unchanged. These M model predictions are then optimally combined to produce the multi-model output. We propose to minimise the mean square error based on a recent data window, and apply the sum to one constraint to the combination parameters, leading to a closed-form solution, so that maximal computational efficiency can be achieved. In addition, at each time step, the model prediction is chosen from either the resultant multiple model or the best sub-model, whichever is the best. Simulation results are given in comparison with some typical alternatives, including the linear RLS algorithm and a number of online non-linear approaches, in terms of modelling performance and time consumption.

A constrained recursive least squares algorithm for adaptive combination of multiple models

In this paper, we develop a novel constrained recursive least squares algorithm for adaptively combining a set of given multiple models. With data available in an online fashion, the linear combination coefficients of submodels are adapted via the proposed algorithm.We propose to minimize the mean square error with a forgetting factor, and apply the sum to one constraint to the combination parameters. Moreover an l1-norm constraint to the combination parameters is also applied with the aim to achieve sparsity of multiple models so that only a subset of models may be selected into the final model. Then a weighted l2-norm is applied as an approximation to the l1-norm term. As such at each time step, a closed solution of the model combination parameters is available. The contribution of this paper is to derive the proposed constrained recursive least squares algorithm that is computational efficient by exploiting matrix theory. The effectiveness of the approach has been demonstrated using both simulated and real time series examples.

Morphometric analysis of the urethra of castrated female rats treated with tamoxifen

Objectives: The aim of this study was to evaluate the effects of tamoxifen on the weight and thickness of the urethral epithelium of castrated female rats. Methods: Forty castrated adult female Wistar-Hannover rats were randomly divided into two groups: Group I (n = 20) in which the animals received only the vehicle (propylene glycol) and Group 11 (n = 20) in which the rats received tamoxifen 250 mu g/day by gavage. After 30 days of treatment, all animals were sacrificed and the urethra was immediately removed for weighing. Next, the urethra was divided into the proximal and distal segments, which were fixed in 10% formaldehyde and submitted to routine histological techniques for morphometric study. The data were analyzed using the weighted minimum mean-square error method and Student`s t-test for two independent samples (p < 0.05). Results: There was a significant increase in the mean weight of the urethra in the rats of Group 11 compared to the control group, 32.0 +/- 2.0 mg and 22.0 +/- 1.6 mg, respectively (p < 0.001). The mean thickness of the distal urethral epithelium of the animals treated with tamoxifen was significantly greater than that of the control group, 42.8 +/- 2.0 mu m and 36.6 +/- 1.5 mu m, respectively (p < 0.001). There was no statistically significant difference between the two groups with respect to the epithelial thickness of the proximal urethra (p = 0.514). Conclusion: Treating castrated adult rats with 250 mu g/day of tamoxifen for 30 days may increase the weight of the urethra and the thickness of the distal urethral epithelium. (c) 2008 Elsevier Ireland Ltd. All rights reserved.

Discrepancies in solar irradiation data for Stockholm and Athens

The aim of this study is to evaluate the variation of solar radiation data between different data sources that will be free and available at the Solar Energy Research Center (SERC). The comparison between data sources will be carried out for two locations: Stockholm, Sweden and Athens, Greece. For the desired locations, data is gathered for different tilt angles: 0°, 30°, 45°, 60° facing south. The full dataset is available in two excel files: “Stockholm annual irradiation” and “Athens annual irradiation”. The World Radiation Data Center (WRDC) is defined as a reference for the comparison with other dtaasets, because it has the highest time span recorded for Stockholm (1964–2010) and Athens (1964–1986), in form of average monthly irradiation, expressed in kWh/m2. The indicator defined for the data comparison is the estimated standard deviation. The mean biased error (MBE) and the root mean square error (RMSE) were also used as statistical indicators for the horizontal solar irradiation data. The variation in solar irradiation data is categorized in two categories: natural or inter-annual variability, due to different data sources and lastly due to different calculation models. The inter-annual variation for Stockholm is 140.4kWh/m2 or 14.4% and 124.3kWh/m2 or 8.0% for Athens. The estimated deviation for horizontal solar irradiation is 3.7% for Stockholm and 4.4% Athens. This estimated deviation is respectively equal to 4.5% and 3.6% for Stockholm and Athens at 30° tilt, 5.2% and 4.5% at 45° tilt, 5.9% and 7.0% at 60°. NASA’s SSE, SAM and RETScreen (respectively Satel-light) exhibited the highest deviation from WRDC’s data for Stockholm (respectively Athens). The essential source for variation is notably the difference in horizontal solar irradiation. The variation increases by 1-2% per degree of tilt, using different calculation models, as used in PVSYST and Meteonorm. The location and altitude of the data source did not directly influence the variation with the WRDC data. Further examination is suggested in order to improve the methodology of selecting the location; Examining the functional dependence of ground reflected radiation with ambient temperature; variation of ambient temperature and its impact on different solar energy systems; Im pact of variation in solar irradiation and ambient temperature on system output.

Independent Domain of Symmetric Encryption using Least SignificantBit : Computer Vision, Steganography and Cryptography Techniques

The rapid development of data transfer through internet made it easier to send the data accurate and faster to the destination. There are many transmission media to transfer the data to destination like e-mails; at the same time it is may be easier to modify and misuse the valuable information through hacking. So, in order to transfer the data securely to the destination without any modifications, there are many approaches like cryptography and steganography. This paper deals with the image steganography as well as with the different security issues, general overview of cryptography, steganography and digital watermarking approaches.  The problem of copyright violation of multimedia data has increased due to the enormous growth of computer networks that provides fast and error free transmission of any unauthorized duplicate and possibly manipulated copy of multimedia information. In order to be effective for copyright protection, digital watermark must be robust which are difficult to remove from the object in which they are embedded despite a variety of possible attacks. The message to be send safe and secure, we use watermarking. We use invisible watermarking to embed the message using LSB (Least Significant Bit) steganographic technique. The standard LSB technique embed the message in every pixel, but my contribution for this proposed watermarking, works with the hint for embedding the message only on the image edges alone. If the hacker knows that the system uses LSB technique also, it cannot decrypt correct message. To make my system robust and secure, we added cryptography algorithm as Vigenere square. Whereas the message is transmitted in cipher text and its added advantage to the proposed system. The standard Vigenere square algorithm works with either lower case or upper case. The proposed cryptography algorithm is Vigenere square with extension of numbers also. We can keep the crypto key with combination of characters and numbers. So by using these modifications and updating in this existing algorithm and combination of cryptography and steganography method we develop a secure and strong watermarking method. Performance of this watermarking scheme has been analyzed by evaluating the robustness of the algorithm with PSNR (Peak Signal to Noise Ratio) and MSE (Mean Square Error) against the quality of the image for large amount of data. While coming to see results of the proposed encryption, higher value of 89dB of PSNR with small value of MSE is 0.0017. Then it seems the proposed watermarking system is secure and robust for hiding secure information in any digital system, because this system collect the properties of both steganography and cryptography sciences.

A finite sample improvement of the fixed effects estimator : applied to technical infficiency

The FE ('fixed effects') estimator of technical inefficiency performs poorly when N ('number of firms') is large and T ('number of time observations') is small. We propose estimators of both the firm effects and the inefficiencies, which have small sample gains compared to the traditional FE estimator. The estimators are based on nonparametric kernel regression of unordered variables, which includes the FE estimator as a special case. In terms of global conditional MSE ('mean square error') criterions, it is proved that there are kernel estimators which are efficient to the FE estimators of firm effects and inefficiencies, in finite samples. Monte Carlo simulations supports our theoretical findings and in an empirical example it is shown how the traditional FE estimator and the proposed kernel FE estimator lead to very different conclusions about inefficiency of Indonesian rice farmers.

Estimação e previsão em processos com longa dependência sazonais

Neste trabalho analisamos alguns processos com longa dependência sazonais, denotados por SARFIMA(0,D, 0)s, onde s é a sazonalidade. Os estudos de estimação e previsão estão baseados em simulações de Monte Carlo para diferentes tamanhos amostrais e diferentes sazonalidades. Para estimar o parâmetro D de diferenciação sazonal utilizamos os estimadores propostos por Geweke e Porter-Hudak (1983), Reisen (1994) e Fox e Taqqu (1986). Para os dois primeiros procedimentos de estimação consideramos seis diferentes maneiras de compor o número de regressores necessários na análise de regressão, com o intuito de melhor comparar seus desempenhos. Apresentamos um estudo sobre previsão h-passos à frente utilizando os processos SARFIMA(0,D, 0)s no qual analisamos o erro de previsão, as variâncias teórica e amostral, o vício, o pervício e o erro quadrático médio.

Núcleos de inflação no Brasil e poder preditivo da inflação total

Este trabalho tem por objetivo avaliar para o caso brasileiro uma das mais importantes propriedades esperadas de um núcleo: ser um bom previsor da inflação plena futura. Para tanto, foram utilizados como referência para comparação dois modelos construídos a partir das informações mensais do IPCA e seis modelos VAR referentes a cada uma das medidas de núcleo calculadas pelo Banco Central do Brasil. O desempenho das previsões foi avaliado pela comparação dos resultados do erro quadrático médio e pela aplicação da metodologia de Diebold-Mariano (1995) de comparação de modelos. Os resultados encontrados indicam que o atual conjunto de medidas de núcleos calculado pelo Banco Central não atende pelos critérios utilizados neste trabalho a essa característica desejada.

Retrievals of a size parameter for phytoplankton and spectral light absorption by colored detrital matter from water-leaving radiances at SeaWiFS channels in a continental shelf region off Brazil

Many efforts are currently oriented toward extracting more information from ocean color than the chlorophyll a concentration. Among biological parameters potentially accessible from space, estimates of phytoplankton cell size and light absorption by colored detrital matter (CDM) would lead to an indirect assessment of major components of the organic carbon pool in the ocean, which would benefit oceanic carbon budget models. We present here 2 procedures to retrieve simultaneously from ocean color measurements in a limited number of bands, magnitudes, and spectral shapes for both light absorption by CDM and phytoplankton, along with a size parameter for phytoplankton. The performance of the 2 procedures was evaluated using different data sets that correspond to increasing uncertainties: ( 1) measured absorption coefficients of phytoplankton, particulate detritus, and colored dissolved organic matter ( CDOM) and measured chlorophyll a concentrations and ( 2) SeaWiFS upwelling radiance measurements and chlorophyll a concentrations estimated from global algorithms. In situ data were acquired during 3 cruises, differing by their relative proportions in CDM and phytoplankton, over a continental shelf off Brazil. No local information was introduced in either procedure, to make them more generally applicable. Over the study area, the absorption coefficient of CDM at 443 nm was retrieved from SeaWiFS radiances with a relative root mean square error (RMSE) of 33%, and phytoplankton light absorption coefficients in SeaWiFS bands ( from 412 to 510 nm) were retrieved with RMSEs between 28% and 33%. These results are comparable to or better than those obtained by 3 published models. In addition, a size parameter of phytoplankton and the spectral slope of CDM absorption were retrieved with RMSEs of 17% and 22%, respectively. If these methods are applied at a regional scale, the performances could be substantially improved by locally tuning some empirical relationships.

Egg production curve fitting using nonlinear models for selected and nonselected lines of White Leghorn hens

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fuzzy modeling to predict chicken egg hatchability in commercial hatchery

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)