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Vulnerability assessment is one of the prerequisites for risk analysis in disaster management. Vulnerability to earthquakes, especially in urban areas, has increased over the years due to the presence of complex urban structures and rapid development. Urban vulnerability is a result of human behavior which describes the extent of susceptibility or resilience of social, economic, and physical assets to natural disasters. The main aim of this paper is to develop a new hybrid framework using Analytic Network Process (ANP) and Artificial Neural Network (ANN) models for constructing a composite social, economic, environmental, and physical vulnerability index. This index was then applied to Tabriz City, which is a seismic-prone province in the northwestern part of Iran with recurring devastating earthquakes and consequent heavy casualties and damages. A Geographical Information Systems (GIS) analysis was used to identify and evaluate quantitative vulnerability indicators for generating an earthquake vulnerability map. The classified and standardized indicators were subsequently weighed and ranked using an ANP model to construct the training database. Then, standardized maps coupled with the training site maps were presented as input to a Multilayer Perceptron (MLP) neural network for producing an Earthquake Vulnerability Map (EVM). Finally, an EVM was produced for Tabriz City and the level of vulnerability in various zones was obtained. South and southeast regions of Tabriz City indicate low to moderate vulnerability, while some zones of the northeastern tract are under critical vulnerability conditions. Furthermore, the impact of the vulnerability of Tabriz City on population during an earthquake was included in this analysis for risk estimation. A comparison of the result produced by EVM and the Population Vulnerability (PV) of Tabriz City corroborated the validity of the results obtained by ANP-ANN. The findings of this paper are useful for decision-makers and government authorities to obtain a better knowledge of a city's vulnerability dimensions, and to adopt preparedness strategies in the future for Tabriz City. The developed hybrid framework of ANP and ANN Models can easily be replicated and applied to other urban regions around the world for sustainability and environmental management.

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This study presents the applicability of recently launched Landsat-8 data for hydrothermal alteration and lithological mapping aim at porphyry copper exploration in arid and semi-arid regions. Sar Cheshmeh copper mining district in the southeastern part of the Urumieh-Dokhtar volcanic belt, SE Iran has been selected as a case study. Several Red-green-Blue (RGB) color combination images and specialized band ratios were developed using Landsat-8 bands. Band ratios derived from image spectra (4/2, 6/7, 5 and 10 in RGB) allow the identification of altered rocks, lithological units and vegetation at a regional scale. Analytical imaging and geophysics developed hyperspectral analysis processing methods were applied to Landsat-8 bands to identify alteration zone associated with known porphyry copper deposits. Mixture Tuned Matched Filtering (MTMF) method was used to detect alteration zones associated with known porphyry copper deposits in the study area. Fieldwork, pervious remote sensing studies and laboratory analysis were utilized to verify the image processing results derived from Landsat-8 bands. It is concluded that Landsat-8 bands especially bands 2 and 4 in visible and near-infrared, 6 and 7 in shortwave infrared, and 10 in thermal infrared contain useful spectral information for porphyry copper exploration purposes. Moreover, thermal infrared bands of Landsat-8Page 2 of 32 A c c e p t e d M a n u s c r i p t 2 significantly improved the quality and availability of thermal infrared remote sensing data for lithological mapping. The achievements of this investigation should have considerable implications for geologists to utilize Landsat-8 Operational Land Imager (OLI)/ Thermal Infrared Sensor (TIRS) data for porphyry copper exploration and geological purposes in the future.

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