چکیده:
Miqan desert wetland is one of the 10 major wetlands in Iran. In 2008, it has changed into a non-hunting area due to its fragile ecology. Evaluating the change trends of the wetland and the use of its surrounding lands is of high significant in order to maintain the wetlands. In this regard, the satellite images of the ETM+ and OLI sensors of years 2002 and 2013 were initially collected. After performing atmospheric and geometrical correction operation through using the instructed samples derived from Maximum Likelihood Classification Method, they were classified into five different classes namely wetlands, barren lands, grasslands, dry-land farming and irrigated farming. The results indicate the overall accuracy of 80.20 and 84.91 for image classification in 2002 and 2013, respectively.The most significant changes observed were an increase of water level water from 7784.57 hectares in 2002 to 7887.35 hectares in 2013 for wetlands; however, the long-term average annual rainfall in recent years shows a 26-percent reduction. Accordingly, the reason of this 0.26-percent increase of the wetland water level can be attributed to the flow of water from the wastewater treatment center. An increase 20% in the dry land farming, and the 12% reduction of grasslands, 0.31% irrigated farming as well as 8.27% barren lands. The main reasons for such changes include setting a sewage refinery in one of the wetland entrances, conversion of grasslands into dry land farming, recent droughts, and growing salinity-tolerant plants such as Nitraria Schoberi.
خلاصه ماشینی:
"After performing atmospheric and geometrical correction operation through using the instructed samples derived from Maximum Likelihood Classification Method, they were classified into five different classes namely wetlands, barren lands, grasslands, dry-land farming and irrigated farming.
The main reasons for such changes include setting a sewage refinery in one of the wetland entrances, conversion of grasslands into dry land farming, recent droughts, and growing salinity-tolerant plants such as Nitraria Schoberi.
In recent years, the use of satellite imagery and remote sensing have been considered in the study of wetlands.
Some research carried out using these tools include the followings: Ulbricht and Heckendorff (1998) carried out a study using satellite imagery to detect changes in land use and ecological conservation landscape in Joapusay, Brazil.
The main objective of the current study is to assess the level and type of changes in the wetland watershed area, land use type, and the coverage of the wetland banks.
(2015) conducted a study entitled"Comparison of different algorithms for land use mapping in dry climate using satellite images, Iran" Results show that for the dry climate areas, Maximum Likelihood and Support Vector Machine algorithms with averages of 0.
The approach combines supervised image classification techniques making use of vegetation indices and decision tree analysis to identify the surface covered by wetlands at a given date.
Comparison of different algorithms for land use mapping in dry climate using satellite images: a case study of the Central regions of Iran."