Calibration of Separate Window Model Factors to Calculate Land Surface Temperature using MODIS Images

Land surface temperature (LST) is one of the most important parameters influencing physical processes of energy on the land surface and in high seas, both in local and global scales. Satellite infrared temperature data (TIR) is linked directly to LST using radiation transmission models. However, direct estimation of LST from radiation in TIR spectrum will be of low accuracy. Since the radiation measured by satellites depends not only on land surface parameters (temperature and irradiance power) but also on atmospheric influences. LST calculation suggests different methods for decreasing atmospheric influences, which can be classified in three major classes: single band methods, multiple band methods, and multiple angle methods. The present article investigates multi-temporal data of MODIS images in 12 different dates with quite uniform temporal distribution during 2014 using five useful multiple band methods of calculating LST including, Price Model (1994), Becker and Li Model (1990), Platt and Prata Model (1991), Ulivieri et al. model (1994), Coll et al. model (1994). Then, coefficients of investigated models were calibrated using the least repetitive squares model. During the calibration, main coefficients of the models were used as the initial value and optimal coefficients were calculated using a series of data. Afterward, the accuracy of the modified models was evaluated using LST from MODIS and the Iranian weather stations data. Results illustrate the modified Price Model by an average of RMSE 0.41 Centigrade degree as the most accurate model. Moreover, the variance of RMSE is 0.08 for mentioned dates which confirm generalizability of the outcomes. The maximum and minimum of RMSE equals 0.26 and 0.50 respectively (February 19th and June 27th respectively) for modified Price model. Finally, the linear relation was investigated, between LST calculated using modified Price Model and data measured by Iranian weather stations. The linear regression factor of these two series of data was 0.9978 which indicates a significant linear relation between calculated LST data and reference temperatures of the Iranian weather stations

Assessment of Spatial Data Infrastructure from Risk Perspective

This research presents an operational framework to assess organizational Spatial Data Infrastructures (SDIs) from a risk perspective to develop a stable SDI. The core of the framework is constructed based on a survey, fuzzy inference system and cluster analysis, providing quantitative indicators to measure and prioritize the risks to SDI. This framework could mainly contribute to identifying, mitigating or avoiding the potential risks of different aspects of an SDI, such as spatial data and information, organizational and technological aspects. Additionally, it could be considered as an approach that supports multi-view SDI assessment framework toward a more comprehensive assessment of SDIs. A prototype implementation to assess and prioritize the risks of the spatial data and information demonstrates the framework merit, flexibility and usability for assessing the risks of SDI initiatives at different levels, such as organizational, local and national levels; however, the risks and SDIs change over time; thus, the development of stable SDI initiatives depends on a continuous process for coping with the risks

Modelling since the Earthquake Vulnerability of Urban Areas (Case Study: Tehran District Three)

Earthquake is one of the most disastrous natural calamity in present age which has been demonstrated its importance objectively. Therefore, getting prepared to deal have with always such crisis affected through identifying vulnerable spots and eliminating them are effective strategies in reducing the damage caused by an earthquake. Many Iranian cities are located in the areas with medium or high relative risk of an earthquake. Tehran city, especially area 3, has a high risk of earthquake danger because so many active faults lie around this area. It is necessary to evaluate vulnerable areas for the substantial planning of decreasing vulnerability of the buildings and representing a clear image from earthquake occurrence and its aftermath. In this study, the vulnerability of context in area3, Tehran, in the time of earthquake occurrence has been modulated. The paper methodology is a descriptive- analytic method which through ANP models and analysis of network in Geographic Data system has modulated and evaluated vulnerability in the urban context of area 3. The results showed that from 2296 hectare of the whole of the area, about 36.2 percent lie in very high and high condition, about 30.8 percent lie in intermediate condition and about 33 percent lie in very low and low condition. The space distribution of vulnerability related to northeastern and east of this area that has cumulous residential context. On the basis of the study results, with considering the problems of vulnerable residential context, Emergency Management of the earthquake will be an effective solution for context maintenance and decrease damages of earthquake occurrence in this context

Sensitivity analysis in seismic loss estimation of urban infrastructures

Iran, as a seismic country, is situated over the Himalayan-Alpied seismic belt and has faced many destructive earthquakes throughout history. Therefore, it is very important to evaluate the possible damage to the existing infrastructure based on statistical and spatial analysis. In this study, a new model is developed to analyse seismic damages based on seismic hazard assessment and extraction of the vulnerability function for all features of fuel infrastructure. To consider uncertainty analysis in the model, Monte Carlo simulation is used based on 10,000 iterations. The results of hazard analysis indicated that peak ground acceleration is about 0.18 g and there is slight to moderate damages to the desired fuel infrastructure in the study area. Moreover, sensitivity analysis is also performed to determine how median, standard deviation (or beta), grid size, attenuation relationships, liquefaction and landslide susceptibility impact the seismic loss. Last but not least, the effect of input parameters of earthquake scenarios including magnitude, focal depth and focal distance are also analysed in conjunction with regression analysis. The results of the study show that magnitude and focal distance are the most sensitive parameters in which the expected damage to the fuel infrastructure is reduced by about 25% if the epicentre of the earthquake is moved from 10 to 25 km

Geospatial Analysis of Earthquake Damage Probability of Water Pipelines Due to Multi-Hazard Failure

The main purpose of this study is to develop a Geospatial Information System (GIS) model with the ability to assess the seismic damage to pipelines for two well-known hazards, including ground shaking and ground failure simultaneously. The model that is developed and used in this study includes four main parts of database implementation, seismic hazard analysis, vulnerability assessment and seismic damage assessment to determine the pipeline’s damage probability. This model was implemented for main water distribution pipelines of Iran and tested for two different earthquake scenarios. The final damage probability of pipelines was estimated to be about 74% for water distribution pipelines of Mashhad including 40% and 34% for leak and break, respectively. In the next step, the impact of each earthquake input parameter on this model was extracted, and each of the three parameters had a huge impact on changing the results of pipelines’ damage probability. Finally, the dependency of the model in liquefaction susceptibility, landslide susceptibility, vulnerability functions and segment length was checked out and specified that the model is sensitive just to liquefaction susceptibility and vulnerability functions

Spatial Modelling of Urban Physical Vulnerability to Explosion Hazards Using GIS and Fuzzy MCDA

Most of the world’s population is concentrated in accumulated spaces in the form of cities, making the concept of urban planning a significant issue for consideration by decision makers. Urban vulnerability is a major issue which arises in urban management, and is simply defined as how vulnerable various structures in a city are to different hazards. Reducing urban vulnerability and enhancing resilience are considered to be essential steps towards achieving urban sustainability. To date, a vast body of literature has focused on investigating urban systems’ vulnerabilities with regard to natural hazards. However, less attention has been paid to vulnerabilities resulting from man-made hazards. This study proposes to investigate the physical vulnerability of buildings in District 6 of Tehran, Iran, with respect to intentional explosion hazards. A total of 14 vulnerability criteria are identified according to the opinions of various experts, and standard maps for each of these criteria have been generated in a GIS environment. Ultimately, an ordered weighted averaging (OWA) technique was applied to generate vulnerability maps for different risk conditions. The results of the present study indicate that only about 25 percent of buildings in the study area have a low level of vulnerability under moderate risk conditions. Sensitivity analysis further illustrates the robustness of the results obtained. Finally, the paper concludes by arguing that local authorities must focus more on risk-reduction techniques in order to reduce physical vulnerability and achieve urban sustainability