Analytical modelling of positional and thematic uncertainties in the integration of remote sensing and geographical information systems

This paper describes three aspects of uncertainty in geographical information systems (GIS) and remote sensing. First, the positional uncertainty of an area object in a GIS is discussed as a function of positional uncertainties of line segments and boundary line features. Second, the thematic uncertainty of a classified remote sensing image is described using the probability vectors from a maximum likelihood classification. Third, the 'S-band' model is used to quantify uncertainties after combining GIS and remote sensing data.Department of Land Surveying and Geo-Informatic

Theoretical study of the two-proton halo candidate 17^{17}Ne including contributions from resonant continuum and pairing correlations

With the relativistic Coulomb wave function boundary condition, the energies, widths and wave functions of the single proton resonant orbitals for $^{17}$Ne are studied by the analytical continuation of the coupling constant (ACCC) approach within the framework of the relativistic mean field (RMF) theory. Pairing correlations and contributions from the single-particle resonant orbitals in the continuum are taken into consideration by the resonant Bardeen-Cooper-Schrieffer (BCS) approach, in which constant pairing strength is used. It can be seen that the fully self-consistent calculations with NL3 and NLSH effective interactions mostly agree with the latest experimental measurements, such as binding energies, matter radii, charge radii and densities. The energy of $\pi$2s$_{1/2}$ orbital is slightly higher than that of $\pi1d_{5/2}$ orbital, and the occupation probability of the $(\pi$2s$_{1/2})^2$ orbital is about 20%, which are in accordance with the shell model calculation and three-body model estimation

Experimental study on partially internally cooled dehumidification in liquid desiccant air conditioning system

10.1016/j.enbuild.2013.02.034Energy and Buildings61202-209ENEB

Quality assessment for geo-spatial objects derived from remotely sensed data

Airborne laser scanners and multi‐spectral scanners provide information on height and spectra that offer exciting possibilities for extracting features in complicated urban areas. We apply an object‐based approach to building extraction from image data in an approach that differs from conventional per‐pixel approaches. Since image objects are extracted based on the thematic and geometric components of objects, quality assessments will have to be made object‐based with respect to these components. The known per‐pixel‐based methods for assessing quality have been examined in the new situation as well as their limitations. A new framework for carrying out quality assessments by measuring the similarity between the results of feature extraction and reference data is proposed in this paper. The proposed framework consists of both per‐object and per‐pixel measures of quality, thus providing measures pertaining to qualitative and quantitative measurements of object quality from thematic and geometric aspects. The proposed framework and measures of quality have been applied to an assessment of the results of object‐based building extraction using high‐resolution laser data and multi‐spectral data in two test cases. The results show that the per‐object‐based method of assessing quality gives additional information to conventional per‐pixel, attribute‐only assessment methods