Search results for "Change detection"

Radiometric correction effects in Landsat multi‐date/multi‐sensor change detection studies

2006

Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi‐sensor, multi‐date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM+ images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a cross‐calibration between TM and ETM+ images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo‐invariant fe…

Low-Dimensional Representations of Earth System Processes

2020

In times of global change, we must closely monitor the state of our planet in order to understand gradual or abrupt changes early on. In fact, each of the Earth's subsystems-i.e. the biosphere, atmosphere, hydrosphere, cryosphere, and anthroposphere-can be analyzed from a multitude of data streams. However, since it is very hard to jointly interpret multiple monitoring data streams in parallel, one often aims for some summarizing indicator. Climate indices, for example, summarize the state of atmospheric circulation in a region, e.g. the Multivariate ENSO (El Ñino-Southern Oscillation) Index. Indicator approaches have been used extensively to describe socioeconomic data too, and a range of …

A support vector domain method for change detection in multitemporal images

2010

This paper formulates the problem of distinguishing changed from unchanged pixels in multitemporal remote sensing images as a minimum enclosing ball (MEB) problem with changed pixels as target class. The definition of the sphere-shaped decision boundary with minimal volume that embraces changed pixels is approached in the context of the support vector formalism adopting a support vector domain description (SVDD) one-class classifier. SVDD maps the data into a high dimensional feature space where the spherical support of the high dimensional distribution of changed pixels is computed. Unlike the standard SVDD, the proposed formulation of the SVDD uses both target and outlier samples for defi…

Correcting AVHRR Long Term Data Record V3 estimated LST from orbital drift effects

2012

Abstract NOAA (National Oceanic and Atmospheric Administration) satellite series is known to suffer from what is known as the orbital drift effect. The Long Term Data Record (LTDR [Pedelty et al., 2007]), which provides AVHRR (Advanced Very High Resolution Radiometer) data from these satellites for the 80s and the 90s, is also affected by this orbital drift. To correct this effect on Land Surface Temperature (LST) time series, a novel method is presented here, which consists in adjusting retrieved LST time series on the basis of statistical information extracted from the time series themselves. This method is as simple and straightforward as possible, in order to be implemented easily for s…

Lost in space? Using geo-narratives to interpret land use changes in a rural landscape of inner Sicily

2021

Intercropping landscapes characterised by the presence of certain plant features (i.e. old-century olive trees) are usually considered traditional landscapes, extremely important for their biocultural heritage. Olive agroforestry systems were widespread in the past throughout Sicily. Recent evolution processes involving intensification have switched to olive grove monocultures. Here we present ongoing work on the application of geo-narratives to interpret transformation dynamics of land use practices in a rural landscape of inner Sicily. Based on the assumption that spatial patterns are the expression of transformation processes, where the spatial variation of human activities is a signific…

A study about DDoS attacks in SIP environments

2007

Cumulative-Sum-Based Localization of Sound Events in Low-Cost Wireless Acoustic Sensor Networks

2014

Wireless acoustic sensor networks (WASNs) are known for their potential applications in multiple areas, such as audio-based surveillance, binaural hearing aids or advanced acoustic monitoring. The knowledge of the spatial position of a source of interest is usually a requirement for many of these applications. Therefore, source localization is an important problem to be addressed in WASNs. Unfortunately, most localization algorithms need costly signal processing stages that prevent them from being implemented in low-cost sensor networks, requiring additional modules for signal acquisition and processing. This paper presents a low-complexity method for acoustic event detection and localizati…

Mismatch brain response to speech sound changes in rats

2011

Understanding speech is based on neural representations of individual speech sounds. In humans, such representations are capable of supporting an automatic and memory-based mechanism for auditory change detection, as reflected by the mismatch negativity of event-related potentials. There are also findings of neural representations of speech sounds in animals, but it is not known whether these representations can support the change detection mechanism analogous to that underlying the mismatch negativity in humans. To this end, we presented synthesized spoken syllables to urethane-anesthetized rats while local field potentials were epidurally recorded above their primary auditory cortex. In a…

Efficient change point detection in genomic sequences of continuous measurements

2010

Abstract Motivation: Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instance when data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimation of the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed. Results: We present a computationally efficient method to obtain estimates of the number and location of the change points. The method is based on a simple transformation of data and it provides re…

Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Int…

2022

Relative radiometric normalization (RRN) is important for pre-processing and analyzing multitemporal remote sensing (RS) images. Multitemporal RS images usually include different land use/land cover (LULC) types; therefore, considering an identical linear relationship during RRN modeling may result in potential errors in the RRN results. To resolve this issue, we proposed a new automatic RRN technique that efficiently selects the clustered pseudo-invariant features (PIFs) through a coarse-to-fine strategy and uses them in a fusion-based RRN modeling approach. In the coarse stage, an efficient difference index was first generated from the down-sampled reference and target images by combining…