The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We show an application of Moran's Index to process and analyze the waterbody-spread extracted from remotely sensed data. A method that is employed to quantify division-wise waterbody-spread, district-wise waterbody-spread and taluk-wise waterbody-spread spatial complexity is based on Moran's Index computation. The waterbody-spread data for each of the hierarchically partitioned geographical unit-wise...
More information can be obtained with the improved spatial resolution of ultra-high resolution (UHR) SAR, whereas the increasing complexity and rich details lead to extreme difficulties in the automatic interpretation. In this paper, we propose a new texture feature set which involves four types of characteristic signatures and nine features to benefit applications of UHR SAR. Experiment based on...
Small UAVs (Unmanned Aerial Vehicles) have high potential to be used to detect and manage the diseases of various crops because they are low cost and user-friendly. Objective of this study is to develop a UAV platform to detect sheath blight in rice in the field. A quadrotor UAV equipped with high-resolution RGB-/multispectral camera was developed and images from these sensors were collected over...
The hyperspectral image features wide coverage, high dimensional bands and a huge amount of data, which leads to time-consuming computation when processing hyperspectral data. Spark is a distributed big data processing framework, integrated in-memory computation. So Spark is suitable for complex iterative calculation. In order to classify massive hyperspectral data efficiently, the Spark version of...
Since Moran's seminal paper on an index to measure spatial autocorrelation among a set of geographic objects, spatial autocorrelation coefficients have been widely used in many research and application fields. In this paper, we provide detailed reasoning for indices for measuring spatiotemporal autocorrelation. We first briefly highlight the classic Moran's Index for measuring spatial autocorrelation...
Spaceborne SAR interferometry (InSAR) has the potential of detecting forest change on a global scale with fine (meter-level) spatial resolution as well as on a monthly/weekly basis regardless of day or night. This is significant to characterize the land-use change and its impact on climate change. In this paper, both single-pass and repeat-pass SAR interferometry from spaceborne sensors are combined...
Previous studies have shown that changes in human emotions or public opinions can have an impact on volatility of stock market. In this paper, we make use of the unstructured comments data from the stock forum on the Shanghai Composite Index to generate the structural emotion time series of the stock market based on a series of methods including word segmentation, feature extraction, machine learning...
Is there a general representation of the information content of human brain, which can be extracted from the functional magnetic resonance imaging (fMRI) data? Is it possible to learn this representation automatically from big data sets by unsupervised learning methods? Is it possible to transfer this representation to learn and decode a set of cognitive states in other fMRI data sets? This study...
In this paper, we propose a persistent scatterer clustering method for high-resolution structure displacement analysis. Persistent scatterer interferometry can monitor millimetric displacement of structures like bridges, buildings, and roads by analysis at persistent scatterers (PSs), pixels with high coherence in synthetic aperture radar (SAR) images. However, it requires great time and effort to...
Only using the post-earthquake PolSAR imagery to interpret collapsed buildings information is a rapid and effective disaster investigation means, which is also easy and fast for implementation of the earthquake damage assessment. This work is focused on rapid building earthquake damage information detection in urban areas using a single post-earthquake PolSAR image. In this paper, the Precision Weighted...
This paper presents the registration and orthorectification, without any GCP, of multi-date satellite data acquired in the Himalayas. To solve that problem, a complete and automatic pipeline that performes tie points detection through a Fourier transform based correlation, bundle block adjustment and orthorectification has been developed. The paper focuses on the effect of the DTM in the bundle block...
The Detrending Moving Average (DMA) algorithm can be implemented to estimate the Shannon entropy of a long-range correlated sequence which will be shown to be of particular relevance for its significance in finance. The entropy is written as the sum of two terms corresponding respectively to power-law (ordered) and exponentially (disordered) distributed blocks (clusters). Interestingly, the behaviour...
We addressed two areas of concern regarding the analysis of a financial time series with a correlation structure, coarse graining (or renormalization) and the extraction of leading and lagging structures. We introduce the complex Hilbert principal component analysis to solve these two problems, and apply them to the time series of 33 Tokyo Stock Exchange industry indices and Tokyo Stock Price Index...
Predicting upcoming bands of hyperspectral images is an important task in modern image compression algorithms. This paper proposes a new algorithm to predict the band-wise correlation of hyperspectral images based on a generalized regression neural network (GRNN). The proposed algorithm uses the intensity values of the previous bands to train the GRNN and approximates the correlation between them...
Sparse dictionary selection (SDS) has demonstrated to be an effective solution for keyframe based video summarization (VS), which generally assumes a linear relation among similar video frames. However, such a linear assumption is not always true for videos. In this paper, the nonlinearity among frames is taken into consideration and a nonlinear SDS model is formulated for VS, in which the nonlinearity...
Spreadsheets often contain faults that are difficult to localize. Spectrum-based Fault Localization (SFL) assists users in the fault localization process by ranking cells by their suspiciousness to contain a fault. Since the ranking of the basic SFL approach is often imprecise, we propose three techniques to improve it, i.e., dynamic cones, grouping, and tie-breaking. We evaluate these techniques...
Dempster-Shafer (D-S) evidence theory is widely used for information fusion field. However, one of the main issues of D-S evidence theory is that, when large amount of focal elements in Basic Probability Assignment (BPA) are available, the fusion of BPA requires high computational cost and long computing time. This problem greatly limits its application. In this paper, a novel method for approximating...
In this paper, the effect of air pollutants (PM2.5, PM10, SO2, NO2, CO and O3) on the Air quality index (AQI) from Jan. to Feb., 2016 in Jinan was studied by using correlation analysis and path analysis. The results of the correlation analysis show that AQI has a negative correlation with O3, and has a positive correlation with PM2.5, PM10, SO2, NO2 and CO. Meanwhile, PM2.5, PM10, SO2, NO2 and CO...
online social networks are progressively being adopted among young people in developing countries. The public is questioning why so many people adopt this technology in many aspects of their lives? The purpose of this study is to understand the acceptance of social networks by Thai students. We used traditional TAM's behavioral constructs: subjective norms (SN), perceived usefulness, perceived ease...
Wind power short-term power prediction is an important index to evaluate the level of wind power operation, and it is also an important parameter to guide the safe operation of power system. Considering the singleness one-sidedness of the existing evaluation index, this paper aims to construct a comprehensive evaluation index system for regional wind power forecasting. The traditional single evaluation...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.