Presentation of a suitable approach for green programming of urban ways through integrative method CA-Markov: case study—Azadi Street of Tehran, Iran

Abstract

Greenways are networks of some connected linear elements that are designed and programmed for a variety of recreational, cultural, aesthetic, and some other purposes. Therefore, the purpose of this study is to check out the land cover changes around the Azadi Street in past and to predict its future changes. This is done in order for checking the connections of the green spaces around the street, connecting Azadi Street and its surroundings, providing solution for future planning and management, and applying greenway principles. For this purpose, using remote sensing techniques, we extracted land cover maps from satellite pictures of years 1986, 2000, and 2016. We used CA-Markov integrated model to predict future changes-in year 2032. The results demonstrate a decrease of 474 ha of the green spots' area while there is an increase of 658 ha of the built lands during 1986-2016. If the security and management plans on the street area are not going to be changed, this area will transform to a machine-centered space and the limited level of the existing walking-oriented area will disappear soon. The results of this research are effective in reviewing the management approaches of the region so that by providing effective solutions, they can lead the policy makers and planners to follow some of the principles of greenways.

Attitudes and Behaviors toward the Use of Public and Private Green Space during the COVID-19 Pandemic in Iran

“…During the recent decades, urban expansion in Iran has caused a dramatic decrease in UGS [53][54][55], especially in cities located in a dry climate zones, where urban planning has been occurring without an appropriate consideration of public green space [56]. This has yielded high disparities in the distribution of urban parks and contributed to citizens' unequal access to UGS [57].…”

Multi-Decade Land Cover/Land Use Dynamics and Future Predictions for Zambia: 2000 - 2030

“…The Markov-CA approach has been applied in generating dynamics of LULCC modeling at watershed level in Indonesia (Yulianto et al 2016). Further, Markov-CA approach has been used to predict future changes in LULC types (Allahyari and Salehi 2020). The Cellular Automata (CA) model has been used in simulating the spatial LULCC by estimating the state of a pixel according to its initial state, surrounding neighbourhood effects and transition rules (Eastman 2016 Arti cial neural network (ANN) is a popular tool used in the analysis of satellite remotely sensed data (Mas and Flores 2008) mainly due to the fact that it characterizes a comparatively new approach to developing predictive models (Blackard and Dean 1999).…”