Northren forests boundary mapping of Iran Using Landsat7 ETM+ data

Document Type : Research article

Author

Research Institute of Forests and Rengelands, P.O. Box 13185-116, Tehran, I.R. Iran

Abstract

For sustainable management of the Caspian Forests of Iran, a most appropriate and fastest method of data collection and combination is essential. Combination of Satellite digital data with field data, using Geographic Information Systems, (GIS) could be applied to obtain accurate information for multiple decision making which is influenced by different factors. In this study eight senses of Landsat 7ETM+ data accosted from Caspian Forests of Iran, June and July 2000, were used. Based on OIF index and statistical analysis of the ETM data, color composite 3,4 and 5 were selected for unsupervised classification. The ground observation information were collected from 3860 plots(30*30), using unsupervised map as a primary map. Overall, combining the ETM and the ground data throw the field information, using the supervised classification method, boundary of the Caspian Forests of Iran were achieved in six classes (Dense forest, Sparse forest, Rangeland, Farm land, Water and Bare soil). The classification accuracy assessment showed that the accuracy rates of the dense forest, sparse forast, rangaland, farmland, water and bara soil were 83, 78, 54, 76 and 98 percent, respectively.
 

Keywords

References

1- اداره کل آمار و اطلاعات وزارت کشاورزی، 1373. تهیه نقشه کاربری و پوشش گیاهی اراضی استان گیلان با استفاده از تفسیر ماهواره‌‌ای. نشریه شماره 23/73: 64-48.
2- اداره کل آمار و اطلاعات وزارت کشاورزی، 1376. اطلس کاربری و پوشش گیاهی اراضی استان مازندران با مقیاسهای 000/200/1 و000/100/1. نشریه شماره 9/76:
57- 35.
3- درویش صفت، علی اصغر، 1995. کاربرد اطلاعات ماهواره‌های لندست و اسپات و ترکیب آنها جهت طبقه‌بندی و آمار جنگل. خلاصه رساله دکتری.
4- اداره کل آمار و اطلاعات وزارت کشاورزی، 1373. تهیه نقشه کاربری و پوشش گیاهی اراضی استان گیلان با استفاده از تفسیر ماهواره‌ای. نشریه شماره 23/73، تهران.
5- شتایی جویباری، شعبان، 1375. تهیه نقشه جنگل به کمک تصاویر ماهواره‌ای به روش رقومی. پایان نامه کارشناسی ارشد. دانشکده منابع طبیعی، دانشگاه تهران.
6- Budde P. and Nijmeijer, R. 1997. ILWIS 3.0 Reference Guide. ILWIS department, ITC, Enschede, The Netherlands: 209 - 258.
7- Chris, S. and Nicki, B. 1997. Erdas Field Guide, Chapter 1 & Chapter 6. Erdas, Inc. 4th  Edition, Atlanta, Gorgia, 213 - 257.
8- Congalton, R. 1991. A Review of Assessing the Accuracy of Classifications of Remotely Sensed data. Remote Sensing of Environment, Vol. 37: 35  - 46.
9- Lillesand, Thomas M. and Ralph W. Kiefer, 1987. Remote Sensing and Image Interpretation. New York: John wiley & Sons, Inc, 124  - 158.
10- Li Xueqian, 1999. Researches on Monitoring by Remote sensing the Tropical Forests in Hainan Island China. Meteorological Bureau of Hainan Provincial, China, 4p.
11- Nijmeijer, R., Budde, P. 2001. ILWIS 3.0 Academic, User’s Guide. ILWIS department, ITC, Enschede, The Netherlands: 260 - 276.
‌12- Rikimarus A., S. Miataka, 1997. Development of Forest Canopy Density Mapping and Monitoring Model Using Indices of Vegetation, Bare soil and Shadow. Hosei University, Tokyo, Japan, 7 p.
13- Robert, A. S. 1987. Techniques for Image Processing and Classification. Remote Sensing University of Arizona, Academic Perss, New york:
115 - 165.
14- Star, J. and John, E. 1990. Geographic Information Systems:An Introduction. Englewood Cliffs, New Jersey: Printice – Hall, 85 - 127.
15- Yousef, A. H., 1999. Remote Sensing Applications for Sustainable Management of Forests. ITC, Enschede, The Netherlands, 7 p.
 
Iranian Journal of Forest and Poplar Research
Volume 11, Issue 3
October 2003
Pages 325-358

Files

Share

How to cite

Statistics