INVESTIGATION ON FOREST EXTEND CHANGES USING AERIAL PHOTOS AND ASTER IMAGERY (CASE STUDY: BORDER FORESTS IN SOUTH AND SOUTHWEST OF GORGAN CITY)

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GHANBARI F.; SHATAEE SH.

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Paper Information

Journal: Journal of Wood and Forest Science and Technology Year:2010 | Volume:17 | Issue:4 Page(s): 1-18

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Title

INVESTIGATION ON FOREST EXTEND CHANGES USING AERIAL PHOTOS AND ASTER IMAGERY (CASE STUDY: BORDER FORESTS IN SOUTH AND SOUTHWEST OF GORGAN CITY)

Author(s)

GHANBARI F. | SHATAEE SH. | Issue Writer Certificate

Keywords

CHANGE DETECTIONQ3

REMOTE SENSINGQ2

GISQ3

AERIAL PHOTOQ3

ASTER IMAGERYQ3

ARTIFICIAL NEURAL NETWORK (ANN)Q1

Abstract

The Hyrcanian forests have been highly exploited in recent decades by human impacts. Easy access, abundance and variety of valuable forest yields have led to population growth density, creation of new residential areas and deforestation activities. CHANGE DETECTION is one of the main methods of management and evaluation of natural resources. We investigated forest changes in southern surrounding of Gorgan city using satellite imagery and AERIAL PHOTOs for three different dates (1966-1994-2006). In order to produce forest extent maps for 1966 and 1994 years, AERIAL PHOTOs of mentioned years were georeferenced by topographic maps and ground control points and digital mosaic of AERIAL PHOTOs were done in GIS environment. Then, the forest extent map was produced by digitizing land use borders on digital photo mosaic for two dates. We used ASTER IMAGERY to produce forest extent map in 2006. We found no radiometric noise in the imagery. Atmospheric correction of imagery was done using Cost method and geometric correction of imagery was accomplished by orthorectification method. Also synthetic bands were generated by suitable image processing methods including ratioing and principal component analyses. After selection of the best bands based on Bhattacharya distance, imagery was classified using supervised classification and neural network algorithms. For exploring of CHANGE DETECTION, post classification comparison technique was employed. Results showed that severe changes were occurred in forest extent during the 41 years. Around 1250.8 ha of the extent of natural forests have been reduced, but 246.29 ha were just increased in this time duration. Hence, net forest extent reduction was 1004.5 hectare. Results also showed that rate of annual changes in the first time interval (1966-1994) was larger than second time interval (1994-2006).

Cites

LAND COVER CHANGE MODELING BASED ON ARTIFICIAL NEURAL NETWORKS AND TRANSMISSION POTENTIAL METHOD IN LCM (CASE: FORESTS GILAN-E GHARB, KERMANSHAH PROVINCE)

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APA: Copy

GHANBARI, F., & SHATAEE, SH.. (2010). INVESTIGATION ON FOREST EXTEND CHANGES USING AERIAL PHOTOS AND ASTER IMAGERY (CASE STUDY: BORDER FORESTS IN SOUTH AND SOUTHWEST OF GORGAN CITY). JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, 17(4), 1-18. SID. https://sid.ir/paper/156885/en

Vancouver: Copy

GHANBARI F., SHATAEE SH.. INVESTIGATION ON FOREST EXTEND CHANGES USING AERIAL PHOTOS AND ASTER IMAGERY (CASE STUDY: BORDER FORESTS IN SOUTH AND SOUTHWEST OF GORGAN CITY). JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY[Internet]. 2010;17(4):1-18. Available from: https://sid.ir/paper/156885/en

IEEE: Copy

F. GHANBARI, and SH. SHATAEE, “INVESTIGATION ON FOREST EXTEND CHANGES USING AERIAL PHOTOS AND ASTER IMAGERY (CASE STUDY: BORDER FORESTS IN SOUTH AND SOUTHWEST OF GORGAN CITY),” JOURNAL OF WOOD AND FOREST SCIENCE AND TECHNOLOGY, vol. 17, no. 4, pp. 1–18, 2010, [Online]. Available: https://sid.ir/paper/156885/en

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