aylar hoseinzadeh

In Iran, the extent of worn-out and marginal structures and the inefficiency of the mechanisms to deal with these structures is considered as a fundamental issue in urban planning and management. Despite the age of schools of morphology, limited research has been done in the field of typology of urban fabric. Today, remote sensing and GIS techniques are considered suitable methods for data collection and quick and accurate decision-making in environmental studies. The main goal of this research is comparative comparison of parts grading. In order to carry out the research, IRS, Sanjande (Liss) satellite images in 2017 and Sentinel 2 images, bands 2, 3, 4, 8 (visible) with a spatial resolution of 10 meters were used and it was tried to find the best methods and Criteria should be adopted to evaluate the granularity of parts using remote sensing techniques, especially the object-oriented method of images. After making the necessary corrections, it was processed in the eCognition software environment and object-based algorithms were used for evaluation. The results of this research showed that this method (objective thresholding classification) has a good accuracy for evaluation with an overall accuracy of 93% and a Kappa coefficient of 91%, and in both studied tissues (worn and marginal), The indicators of fineness and impermeability were concretely present, so that in both tissues, the area of ​​more than 50% of the plaques is below 200 square meters. The results of the research show that there is no significant difference between the worn and marginal tissue and both the studied areas have fine-grained and impermeable tissue. Also, the map and data related to the urban context, due to their collection in the field and the outdated classification method, cannot meet the current study and executive needs. In this regard, with new developments and technologies such as remote sensing, which have caused a significant reduction in field studies, time and cost, it has been possible to study the granularity of tissues.

Urban green space is one of the important indicators in the fields of urban planning, environmental protection and sustainable urban development policies. Knowledge of the location, amount and distribution of urban green space is a necessity. The available green space is decreasing for the purpose of developing residential lands. Today, with the progress made in the production of satellite images with high spatial and spectral resolution and remote sensing techniques, ARCGIS and image processing have made it possible to collect data and make quick and accurate decisions in environmental studies. The main goal of this research is to reveal the coverage of urban green space using object oriented processing. In order to carry out this research, IRS, Sanjande (Liss) satellite images in 2017, as well as Sentinel 2 images, bands 2, 3, 4, 8 (visible) with a spatial resolution of 10 meters were used. After making the necessary corrections, the images in the ENVI5 software environment.1 and eCognition processed that these processes include algorithms (SI, NDSI, NDVI, Brightness, etc.) to identify the area and object-based algorithms are used for evaluation. The results of this research showed that this method had a good accuracy for evaluation with an overall accuracy of 93% and a Kappa coefficient of 92%, and it was possible to detect urban green spaces using the object-oriented processing method, and it was determined that using Satellite images and object-oriented algorithms are possible to identify and investigate urban green space, and its results can be an efficient way to identify object-based algorithms and use them in future research studies