shaban shataee joibari

Sidewalks are related to social health, urban lifestyle, urban economy and environmental quality. In recent decades, these urban spaces have attracted the attention of urban planning experts for such goals as increasing dynamism, social interactions, environmental issues, and personal and social health. In the last decade in Mashhad, due to issues such as population growth, tourism, the rapid growth of the number of cars, the increase in environmental pollutants caused by transportation, and the increase in the number of sedentary citizens, it is necessary to support clean transportation that is human-centered environment-friendly. The metropolis has grown drastically in recent decades, but little attention has been paid to pedestrians’ needs. This research tried to study the areas that attract travelers from the perspective of citizens and to introduce active pedestrian-oriented paths to improve the quality of sidewalks. For this purpose, a questionnaire was used to get the opinions of people. Moreover, through the analysis and weighting methods of SAW and AHP and the urban network analysis model (UNA), the key issues of active walking and travel attraction were identified. The results show that about 15% of the pedestrian paths of the main streets can attract pedestrian trips and have a favorable function. If a desirable pedestrian path is made, an effective step can be taken for improving the physical, semantic, and human-centered image of this city. The way UNA model was used in this study can be used for future studies for valuating and weighting buildings and urban areas.

In the Mashhad metropolis, due to issues such as tourism, the increase number of cars 4.5 times in the last decade, the increase amount of environmental pollutants caused by transportation, the increase number of sedentary and overweight citizens and in general the unsuitability of livability of this metropolis the need to support clean and human-centered transportation has felt. Creating a desirable and environmentally friendly pedestrian axis can play an important role in improving pedestrian streets. What can play an effective role in planning these spaces and to cover the mentioned goals of urban planners, is to propose a solution that can be adapted to the material and spiritual needs of citizens.For this purpose, using the questionnaire and methods of analysis AHP and SAW, we have examined the sights and expectations of the urban community of an optimal pedestrian axis that effective in a new urban lifestyle.The ratio of increased daily activity of citizens after the addition of greenways to the urban transportation system is more than 3 times. In addition the results show that greenways can be a platform for change in urban lifestyle and the tendency to walk and daily activities and increase the economic value of the land by 23%. In addition, the use of vegetation, the allocation of a special bicycle lane and the consideration of crowded places in the planning of pedestrian spaces can play an important role in increasing the desire of citizens to be present in these spaces on foot.

As one of the most important understory evergreen species in Hyrcanian forests of Iran, information on the distribution of Box (Buxus Hyrcana Pojark.) are essential for both forest research and practice. Here, the capability of very high spatial resolution IKONOS satellite imagery acquired in leaf-off condition was tested for mapping Box distribution in a part of Khiboos-Anjili forest reserve in Mazandaran province. The IKONOS imagery was geometrically corrected with a georefrenced panchromatic Pleaides scene, which was orthorectified using 3D ground control points obtained using differential GPS (RMSE less than one pixel). Reference data samples from three classes of non-forested area, deciduous stands without Box understory and deciduous stands with Box understory were recorded using DGPS-supported field survey. By means of a number of vegetation indices, classes seperabilities were evaluated on main and synthetic image channels by partitioning 75% training area and transformed divergence. IKONOS image was classified using both main and best-selected bands and a number of nonparametric (Maximum Likelihood, Mahalonobis distance, Minimum distance to mean and Paralell piped) and parametric (Suport Vector Machine) classifiers. Then the classified images were assessed using 25 percent of unused sample points. Results of validation using the 25% left-out test data showed the highest performance by SVM algorithm compared to other algorithms, with overall accuracy and Kappa coefficient of 97.87% and 0.96, respectively. The results also showed the potential of IKONOS imagery from leaf-off season has to map Box trees in understory layer.

The purpose of this study was to compare the estimation of the structural attributes of stand volume, basal area, and tree stem density per hectare of the Caspian forests using Radar data and integration of Radar and Lidar data in some parts of the district I and II the ShastKalateh forest in the Golestan province. Forest structural data were measured and computed from 307 circular plots. The required pre-processing and processing was performed using raw data of Radar (2009) and Lidar (2011), and the corresponding values of sample plots were extracted on all Radar and Lidar derived indices. The modeling was performed using extracted Radar features as individual and also using Lidar and Radar extracted features as integrated with the non-parametric random forest algorithm in 75% of samples. The modeling validity was performed using 25% of the remained samples by absolute and relative root mean square error (RMSe) and Bias. The percentage RMSe and the Bias values using Radar data were obtained form stand volume (44.09% and -0.99%), basal area per hectare (35.72% and -3.15%) and tree stem density per hectare (42.73% and 3.52%), respectively, and using the integration of Radar and Lidar data for stand volume (37.23% and 0.76%), basal area per hectare (31.37% and -3.14%), and tree density per hectare (36.44% and 0.95%). The results showed that the integration of Radar and Lidar data could improve the estimates, especially in the stand volume, compared to using Radar data as individually.

Today, it is important to use the ecological indicators, such as canopy cover for recognizing the special status of ecosystems, such as mangrove forests and also monitoring and evaluating changes through a specific period. This study aimed to investigate the sufficiency of parametric and nonparametric algorithms using the spectral data with high spatial resolution in the evaluation of canopy cover in the mangrove forest in the Bushehr province. The vegetative characteristics were studied at 20×20 square meter sample plots. 50 Sample plots were studied for the proposed vegetative characteristic such as diameter, Height and percentage of canopy cover of mangrove forest. The camera UltraCamX digital images which used in this study were harvested to the shooting operation on 2012/01/10. After conducting some proper Preprocessing and processing, the digital values corresponding to the ground samples were extracted from spectral bands and were considered as the independent variables while and the crown canopy percent per plot were considered as the dependent variable. Modeling was carried out based on 75 percent of sample plots using K-Nearest Neighbor methods, support vector machine, random forest and General linear model methods and the results were cross-validated using the remaining 25 percent. The results showed that the best estimates were obtained from the crown canopy percent with method Random Forest, k-NN, SVM and General linear model methods with a root mean square error of 13.57, 13.95, 14.88 and 17.73 percent and relative bias of -3.88, -4.62, -5.05 and -2.88 percent that Random Forest method had the best performance. The results of this study showed UltraCam X Arial spectral data had the high ability for estimating of canopy cover percent.