Green space estimation using IKONOS imageries

The necessity of successful and practical planning in urban forestry and green space of city, in addition to costs and financial sources, is knowing the present situation and potential of considered area from its kind of requirement and ability in growing plants. In this study, IKONOS images and aer...

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Main Authors: Sara Teimouri, Jahangir Feghhi, Morteza Sharifi
Format: Article
Language:fas
Published: Research Institute of Forests and Rangelands of Iran 2008-06-01
Series:تحقیقات جنگل و صنوبر ایران
Subjects:
Online Access:http://ijfpr.areeo.ac.ir/article_108093_e772b73b0ca717e33e58dfc47d8cbcdf.pdf
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spelling doaj-7d3f821a07e8485e95e7e504181be6272020-11-25T00:26:09ZfasResearch Institute of Forests and Rangelands of Iranتحقیقات جنگل و صنوبر ایران1735-08832383-11462008-06-01162303292108093Green space estimation using IKONOS imageriesSara Teimouri0Jahangir Feghhi1Morteza Sharifi2M.Sc., Faculty of Natural Resources, University of TehranAssistant Professor, Faculty of Natural Resources, University of TehranMember of High Council Forest, Range and Watershed Organization (FRWO).The necessity of successful and practical planning in urban forestry and green space of city, in addition to costs and financial sources, is knowing the present situation and potential of considered area from its kind of requirement and ability in growing plants. In this study, IKONOS images and aerial photos were used to get information about the situation of city green space and calculate average of green space per person in the North West of Tehran, third region and some part of second region of municipality, for 538 hectare. Therefore, satellite images were interpreted by automatic digital analysis with maximum likelihood algorithm after necessary preprocessing. Meanwhile, the aerial photos after digitizing and geometric correction were used as ground-truth in classification.  For this purpose a dot grid with 4371 points, located in 100 square meter cluster, overlaid on the aerial photos. Then it was determined that each dot belonged to which class. The distances of clusters from each other were 100× 100m and the distance of the dots in each cluster was 5×5m. The results were compared with the results of automatic classification of satellite images, and the error matrix was made. Overall accuracy of classification was 97%. The area was divided in 45 zones according to the boundaries the statistic center of Iran and the average of green space was calculated regarding to the number of population and space of green area in each zone. Then the bare lands were detected and measured as a maximum increasable potential to green space. The results represented that the average of green space per person is 14 square meters in the study area that it's about 20% of whole of it, and the range of it, is between 3/9-28/9 square meters per person that varies in different zones. Finally, the bare lands were ranked in allocating to green area via overlaying the maps of empty places and average of green space.http://ijfpr.areeo.ac.ir/article_108093_e772b73b0ca717e33e58dfc47d8cbcdf.pdfdot gridaerial photographsGreen spaceIkonos imageries
collection DOAJ
language fas
format Article
sources DOAJ
author Sara Teimouri
Jahangir Feghhi
Morteza Sharifi
spellingShingle Sara Teimouri
Jahangir Feghhi
Morteza Sharifi
Green space estimation using IKONOS imageries
تحقیقات جنگل و صنوبر ایران
dot grid
aerial photographs
Green space
Ikonos imageries
author_facet Sara Teimouri
Jahangir Feghhi
Morteza Sharifi
author_sort Sara Teimouri
title Green space estimation using IKONOS imageries
title_short Green space estimation using IKONOS imageries
title_full Green space estimation using IKONOS imageries
title_fullStr Green space estimation using IKONOS imageries
title_full_unstemmed Green space estimation using IKONOS imageries
title_sort green space estimation using ikonos imageries
publisher Research Institute of Forests and Rangelands of Iran
series تحقیقات جنگل و صنوبر ایران
issn 1735-0883
2383-1146
publishDate 2008-06-01
description The necessity of successful and practical planning in urban forestry and green space of city, in addition to costs and financial sources, is knowing the present situation and potential of considered area from its kind of requirement and ability in growing plants. In this study, IKONOS images and aerial photos were used to get information about the situation of city green space and calculate average of green space per person in the North West of Tehran, third region and some part of second region of municipality, for 538 hectare. Therefore, satellite images were interpreted by automatic digital analysis with maximum likelihood algorithm after necessary preprocessing. Meanwhile, the aerial photos after digitizing and geometric correction were used as ground-truth in classification.  For this purpose a dot grid with 4371 points, located in 100 square meter cluster, overlaid on the aerial photos. Then it was determined that each dot belonged to which class. The distances of clusters from each other were 100× 100m and the distance of the dots in each cluster was 5×5m. The results were compared with the results of automatic classification of satellite images, and the error matrix was made. Overall accuracy of classification was 97%. The area was divided in 45 zones according to the boundaries the statistic center of Iran and the average of green space was calculated regarding to the number of population and space of green area in each zone. Then the bare lands were detected and measured as a maximum increasable potential to green space. The results represented that the average of green space per person is 14 square meters in the study area that it's about 20% of whole of it, and the range of it, is between 3/9-28/9 square meters per person that varies in different zones. Finally, the bare lands were ranked in allocating to green area via overlaying the maps of empty places and average of green space.
topic dot grid
aerial photographs
Green space
Ikonos imageries
url http://ijfpr.areeo.ac.ir/article_108093_e772b73b0ca717e33e58dfc47d8cbcdf.pdf
work_keys_str_mv AT sarateimouri greenspaceestimationusingikonosimageries
AT jahangirfeghhi greenspaceestimationusingikonosimageries
AT mortezasharifi greenspaceestimationusingikonosimageries
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