A novel spatial index using spatial analyses and hierarchical fuzzy expert system for obtaining green TOD: a case study in Tehran city

Sustainable development is a vital and challenging factor for managing urban growth smartly. This factor contains three main components, namely economic growth, ecological protection and social justice. Green Transit-Oriented Development (GTOD) is a consummate planning approach in line with those components. Implementation of GTOD in an urban area is underpinned by its quantification. Therefore, a quantitative spatial index based on several indicators related to TOD and Green urbanism concepts should be developed. In this study, Geo-spatial Information Science and hierarchical fuzzy inference system (HFIS) were employed to calculate the indicators and aggregate them, respectively. In order to showcase the feasibility of the proposed method, it was implemented in a case study area in the City of Tehran, Iran. The result of this method is an integrated spatial GTOD index, which measures the neighbourhoods’ GTOD levels. These measurements specify weaknesses and strengths of neighbourhoods’ factors. Therefore, this index helps decision-makers to plan neighbourhoods based on land use and public transit views. Additionally, the HFIS method helps decision-makers to consider criteria and indicators with their inherent uncertainties and aggregate them with much fewer rules. For evaluating the results, the developed GTOD index was assessed with municipal action planning and attraction maps. According to the outcomes of the assessment, it is concluded that the proposed method is adequately robust and efficient for smart and sustainable urban planning.     

Statistical analysis of surface urban heat island intensity variations: A case study of Babol city,Iran

The urban heat island is considered as one of the most important climate change phenomena in urban areas, which can result in remarkable negative effects on flora, concentration of pollutants, air quality, energy and water consumption, human health, ecological and economic impacts, and even on global warming. The variation analysis of the surface urban heat island intensity (SUHII) is important for understanding the effect of urbanization and urban planning. The objective of this study was to present a new strategy based on the Shannon’s entropy and Pearson chi-square statistic to investigate the spatial and temporal variations of the SUHII. In this study, Landsat TM, ETM+, OLI and TIRS images, MODIS products, meteorological data, topographic and population maps of the Babol city, Iran, from 1985 to 2017, and air temperature data recorded by ground recorder devices in 2017 were used. First, Single-Channel algorithm was used to estimate land surface temperature (LST), and the maximum likelihood classifier was employed to classify Landsat images. Then, based on LST maps, surface urban heat island ratio index was employed to calculate the SUHII. Further, several statistical methods, such as the degree-of-freedom, degree-of-sprawl and degree-of-goodness, were used to analyse the SUHII variation along different geographic directions and in various time periods. Finally, correlation between various parameters such as air temperature, SUHII, population variation and degree-of-goodness index values were investigated. The results indicated that the SUHII value increased by 24% in Babol over different time periods. The correlation coefficient yielded 0.82 between the values of the difference between the mean air temperature of the urban and suburbs and the SUHII values for the geographic directions. Furthermore, the correlation coefficient between the population variation and the degree-of-goodness index values reached 0.8. The results suggested that the SUHII variation of Babol city had a high degree-of-freedom, high degree-of-sprawl and negative degree-of-goodness.     

Preliminary Study of Catalase Enzyme Activity and Protein Concentrations in the Mediterranean and African Mussels,Mytilus galloprovincialis and Perna perna,Cohabiting on the Same Natural Coastal Site (Figuier,Boumerdes, Algeria)

Ocean Science Journal - Biological monitoring has become one of the most widely used approaches in aquatic monitoring. As a result, the effect of the xenobiotics entrained by the organic and...     

3D Static Modeling and Petrographic Aspects of the Albian/Cenomanian Reservoir,Komombo Basin,Upper Egypt

Natural Resources Research - The Albian/Cenomanian reservoir is one of the two main reservoirs composing the petroleum system in the Komombo Basin. However, these reservoirs have not previously...     

Cluster Analysis of Petrophysical and Geological Parameters for Separating the Electrofacies of a Gas Carbonate Reservoir Sequence

Natural Resources Research - Assessing reservoir properties and knowing the relationship between different reservoir parameters can significantly help to plan for production from a reservoir. In...     

A Study on the Surface Wettability of Clastic Rocks with Potential Application for CO2 Storage Sites

Natural Resources Research - There have been many studies carried out in the past decades attempting to develop strategies for a safe injection of CO2 into storage sites without leakage and...     

Application of Artificial Intelligence to Estimate Oil Flow Rate in Gas-Lift Wells

Natural Resources Research - Optimization and monitoring schemes for oil well and reservoir system require accurate estimation of production rate. Real-time monitoring is conducted typically using...     

3D Structural,Facies and Petrophysical Modeling of C Member of Six Hills Formation,Komombo Basin,Upper Egypt

Natural Resources Research - Two main reservoirs are producing in Komombo Basin: the first one belongs to the C Member of the Six Hills Formation, and the second belongs to the Albian/Cenomanian...     

Physical and geometrical parameters of VCBS XIII: HIP 105947

The best physical and geometrical parameters of the main sequence close visual binary system(CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat's complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution(SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz(ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin's dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the ?θ and ?ρ residuals for the system, is introduced. The combination of Al-Wardat's and Tokovinin's methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.     

Using advanced soft computing techniques for regional shoreline geoid model estimation and evaluation

This study aims at evaluating the global geoid model for a regional shoreline fitting using advanced soft computing techniques and global navigation satellite system/leveling measurements. Artificial neural networks, fuzzy logic, and least square support vector machine models are developed and used to fit the global geoid model for the north coastal Egyptian line. In addition, a novel estimation geoid model is designed and evaluated based on the latest global geoid models. The results of the three estimation models show that they can be used to correct the shoreline geoid model, in terms of root mean square error that ranges from 1.7 to 8.5?cm. Moreover, it is found that the least square vector machine model is a competitive approach with certain advantage in solving complex problems represented by missing data.