Mrs Mehrnaz Rezvani, Mr Yosefali Ziari, Mr Naser Eghbali, Mr Hosein Mojtabazade Khanghahi,
Volume 20, Issue 57 (6-2020)
Abstract
Urban land utilize planning, for optimal use of existing facilities and urban spaces is one of the main cores of urban planning, which is usually defined as a multi-objective issue. In line with the absence of specific categorization, system for land use in Iran the use of metaheuristic algorithm and artificial intelligence is required. One of the algorithms that introduced and used in recent years are the optimization algorithm (BBO) based on biogeography. Current research is from practical research group and type of descriptive-analytic research, the data analysis method would be write and execute in MATLAB software by using biogeography algorithm. The purpose, after identifying most effective variable, will be to improve the present status of the system's distribution use indicators and their adjacency in the county surface. For comparing the results of current research, in terms of desired area needed uses with development plan of Semnan County, each dimension of (GIS) layer should be provide.overlapping of the layers would be compare with development design.
Negar Ghasemi, Marzieh Alikhah Asl, Mohammad Rezvani,
Volume 22, Issue 66 (9-2022)
Abstract
Study of resources changes in previous years could be useful in the planning and optimal using of resources to control inappropriate changes. Because land use changes occur on large-scale, remote sensing technique is a useful and valuable tool for monitoring the changes. The aim of this research is land cover changes detection in a period of 32 years in Pishva town with using remote sensing technique .First TM, ETM and OLI images for the years 1986, 2002 and 2018 were collected respectively and after geometric and radiometric corrections, images were classified by using maximum likelihood classification methods. Kappa and overall indexes were used to calculate classification accuracy. Results showed in past 32 years, bare land and irrigated land have decreased while residential and greenhouse areas have increased. Classification accuracy showed that OLI, ETM and TM sensors have high accuracy respectively with kappa 0.96, 0.80 and 0.76 and also overall indexes of 97.56, 86.54 and 86 percent. Based on results, in the first period (1986-2002) 27.6%, in the second period (2002-2018) 29.60% and in the third period (1986-2018) 31.8% of area land cover have been changed. Results showed land cover changes in the area is related to climate changes like low precipitation, drought and social condition like population and food need increasing and economic condition like high production and efficiency.
