Evaluation of Changes in Per Capita Green Space through Remote Sensing Data

نویسندگان

  • Amir Eslam Bonyad Associate Professor, Department of Forestry, Faculty of Natural Resources, Guilan University, Iran
  • Javad Sousani Assistant Professor, Department of Forestry, Faculty of Agriculture, Lorestan University, Iran
چکیده مقاله:

Quantitative identification of physical changes, developments and dynamic position of urban green space is considered as the first step in its planning. By means of the aerial photos taken in 1956, 1974, and 1994 as well as the Quick Bird satellite image captured in 2006, this study has dealt with changes in per capita green space in Khorramabad during these years. First, geometric corrections of the photos were made and their orthophotos were provided. Then, through visual interpretation, city area was estimated over different years. Therefore, dot grid was used to calculate the urban green space during these years. Results show that the ratio of the green space area to total urban area is 10.42, 9.67, 15, and 9.1 percent during these years, respectively. Statistical test results indicate that there is a significant difference between green space percentage in 1994 and those of other years. However, there is no significant difference between green space percentages in 1956, 1974, and 2006. Per capita green space was calculated according to the population data provided by the Statistical Center of Iran. Results suggest that per capita green space in Khorramabad is 5.27, 4.2, 7.73, and 6.88 square meters in 1956, 1974, 1994 and 2006, respectively. Thus, its per capita green space is not proportional to universal standards. The relationship between changes in per capita green space and its percentage does not follow a definite procedure. In conclusion, we must actually consider not only the high ratio of green space but also the regional density, so that we may proportionately increase the green space and then take right decisions.

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evaluation of changes in per capita green space through remote sensing data

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عنوان ژورنال

دوره 1  شماره 4

صفحات  321- 330

تاریخ انتشار 2013-04-01

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