Azadeh Zaeri Amirani; Alireza Sofyanian
Volume 21, Issue 83 , November 2012, , Pages 65-69
Abstract
Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing ...
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Accessing correct and timely information about urban land use and coverage is especially important for urban planning and management, achieving sustainable development in urban areas and optimal application of land.Impenetrable surfaces are a part of urban coverage with an effective role in changing landform and the quality of urban environment. Regarding the importance of such surfaces, different methods of mapping impenetrable surfaces and investigating its changes with satellite imagery exist. These methods can be classified into five general groups: subpixel classification, neural network, classification with VIS model, regression tree model, and spectral composition analysis. Generally, each of these methods have their own advantages and disadvantages, but they are mostly used to detect and classify impenetrable surfaces. The present article investigate impenetrable surfaces and their importance, along with different methods of mapping these surfaces.
Maliheh Sadat Madanian; Alireza Sofianian
Volume 21, Issue 82 , September 2012, , Pages 44-49
Abstract
Change detection is the process of identifying changes in an object or phenomenon by observing it in different time intervals. Careful and timely detection of changes in land forms and reliefs provides a better basis for understanding relations and the interactions between human and natural phenomena. ...
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Change detection is the process of identifying changes in an object or phenomenon by observing it in different time intervals. Careful and timely detection of changes in land forms and reliefs provides a better basis for understanding relations and the interactions between human and natural phenomena. In this way, it makes managing and exploiting resources possible. Remote sensing data is a wonderful resource for different applications in detecting changes, due to its temporal magnification, spectral and radiometric variety, appropriate digital format and integrated view. Many methods have been developed to detect changes, all of which have advantages and disadvantages. According to the studies, these methods show different results in the same environment. Generally, change detection methods are classified into 3 different classes: pre-classification comparison, post- classification comparison, advanced methods. The present article analyzes some of these methods like image subtraction, image division, main components analysis, detection of controlled changes, and detection of uncontrolled changes, hybrid, artificial neural networks, vegetation-impermeable surfaces-soil model and geographic information systems. Pre-classification methods detect changes caused by multi-temporal data without producing classified vegetation and land-use maps. Yet, post-classification methods provide a precise matrix of changes and they usually need input analysis. There are diverse advanced methods which are usually developed in response to specific studies. Studies indicate that image subtraction, main components analysis and post-classification methods are the most popular methods used for change detection. However in recent years, artificial neural networks and combinations of remote sensing and geographic information systems are regarded as important techniques.
Alirerza Sofianian; Samereh Falahatkar
Volume 17, Issue 68 , February 2008, , Pages 13-18
Abstract
Remote sensing and GIS are widely used in identifying and analyzing land use change. Satellite remote sensing provides multi-time and multi-spectral data that can be used to quantify the type and amount and position of land use change. Furthermore, the GIS also provides a flexible environment for displaying, ...
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Remote sensing and GIS are widely used in identifying and analyzing land use change. Satellite remote sensing provides multi-time and multi-spectral data that can be used to quantify the type and amount and position of land use change. Furthermore, the GIS also provides a flexible environment for displaying, storing and analyzing the digital data needed to detect changes. Since environmental changes are important in order to give a general impression of the region's environment and build credible hypotheses based on sustainable development, detecting these changes is an important process in the monitoring and management of natural resources and urban development. Detection of changes is also considered as a part of modern science due to dependence on remote sensing sciences and GIS. With the rapid growth of cities in recent years, the recognition of their biophysical compounds and their dynamism is of particular importance and is considered as an important research topic. The operations that are carried out in the course of digital analysis and interpretation of satellite data and with the aim of identifying and distinguishing ground phenomena can be summarized in three stages of initial surveys and information preparation, classification of information and finalized reviews and processing. Geometric correction of images and their classification based on existing methods and algorithms, and the accuracy of production maps, and finally comparing the maps at different times are among the stages of detecting changes. In the present study, we try to describe the steps briefly.
