Commentary on Section 264 of ITAA 1936: commissioner may require information and evidence
Dabner, Justin
2007-01-01
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6 records were found.
The recent technological developments in remote-sensing sensors and satellites (e.g., the increased spatial and spectral resolutions of sensors, the increased rivisitation time of satellites) offer the possibility of addressing new applications related to environmental monitoring and natural-resource management. In particular, applications connected with the analysis of multitemporal remote-sensing images are becoming more and more important, also in relation to the increased awareness of politicians of the necessity for a regular and efficient control of the environment. This chapter deals with a key issue in multitemporal data analysis, namely, the automatic detection of changes in pairs of images acquired in the same geographical area at different times. In particular, unsupervised change-detection methods (i.e., methods that do not...
A system for a regular updating of land-cover maps is proposed that is based on the use of multitemporal remote-sensing images. Such a system is able to face the updating problem under the realistic but critical constraint that, for the image to be classified (i.e., the most recent of the considered multitemporal data set), no ground truth information is available. The system is composed of an ensemble of partially unsupervised classifiers integrated in a multiple classifier architecture. Each classifier of the ensemble exhibits the following novel peculiarities: i) it is developed in the framework of the cascade-classification approach to exploit the temporal correlation existing between images acquired at different times in the considered area; ii) it is based on a partially unsupervised methodology capable to accomplish the classifi...
In this paper, we propose a classification system based on a multiple-classifier architecture, which is aimed at updating land-cover maps by using multisensor and/or multisource remote-sensing images. The proposed system is composed of an ensemble of classifiers that, once trained in a supervised way on a specific image of a given area, can be retrained in an unsupervised way to classify a new image of the considered site. In this context, two techniques are presented for the unsupervised updating of the parameters of a maximum-likelihood (ML) classifier and a radial basis function (RBF) neural-network classifier, on the basis of the distribution of the new image to be classified. Experimental results carried out on a multitemporal and multisource remote-sensing data set confirm the effectiveness of the proposed system.
In this paper, we propose a system for monitoring abnormal NO2 emissions in troposphere by using remote-sensing sensors. In particular, the system aims at estimating the amount of NO2 resulting from biomass burning by exploiting the synergies between the GOME and the ATSR-2 sensors mounted on board of the ERS-2 satellite. Two different approaches to the estimation of NO2 are proposed: the former, which is the simplest one, assumes a linear relationship between the GOME and ATSR-2 measurements and the NO2 concentration. The latter exploits a nonlinear and nonparametric method based on a radial basis function (RBF) neural network. The architecture of such a network is defined in order to retrieve the values of NO2 concentration on the basis of the GOME and ATSR-2 measurements, as well as of other ancillary input parameters. Experimental ...
In recent work, it was noted that although the subband histograms for standard wavelet coefficients take on a generalized Gaussian form, this is no longer true for wavelet packet bases adapted to a given texture. Instead, three types of subband statistics are observed: Gaussian, generalized Gaussian, and most interestingly, in some subbands, multimodal histograms with no mode at zero. As will be demonstrated in this report, these latter subbands are closely linked to the structure of the texture, and are thus likely to be important for many applications in which texture plays a role. Motivated by these observations, we extend the approach to texture modelling proposed by to include these subbands. We relax the Gaussian assumption to include generalized Gaussians and constrained Gaussian mixtures. We use a Bayesian methodology, finding ...
Due to its intensive data processing and highly distributed organization, the multidisciplinary Earth Science applications community is uniquely positioned for the uptake and exploitation of Grid technologies. Currently Enabling Grids for E-sciencE, and other large Grid infrastructures are already deployed and capable of operational services. So far however, the adoption and exploitation of Grid technology throughout the Earth Science community has been slower than expected. The Dissemination and Exploitation of GRids in Earth sciencE project, proposed by the European Commission to assist and accelerate this process in a number of different ways, had between its main goals the creation of a roadmap towards Earth Science Grid platform. This paper presents the resulting roadmap.
