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Land use mapping using visual vs. digital image interpretation of TM and Google earth derived imagery in Shrivan-Darasi watershed (Northwest of Iran)

Ardavan Ghorbani and Mina Pakravan

The availability of landuse/cover information allows decisionmakers to develop short and long term plans for the sustainable use,conservation and development of natural resources. This study was conducted to use Landsat and Google earth derivedimagery for land use /cover mapping in Shirvan-Darasi watershed in north of Ardabil province in Iran. ATM image by considering seasonality and phenological pattern was selected. Pre image processing stages such as atmospheric and geometric correctionwere conducted before image utilization. Moreover, image of the study area extracted from Google earth and imported to ArcGIS environment. Ancillary data such as DEM and slope were derived and added to the datasets of this study for controlling different land uses. Field visit and appropriate ground control points were collected for visual and training area selection, and finally land uses such as rangeland, horticultural land, irrigated and dry farming lands, residential and industrial areas, roads and out crops were considered and land use of the selected images were derived. Finally accuracy of the produced maps were computed and compared.Results show that, the produced map of the image of Google earth using visual interpretation showed high overall accuracy (0.94) and Kappa (0.90). On the other hand, results of the digital interpretation of TM image (unsupervised) showed very low overall accuracy (0.24) and Kappa (0.22) statistics.

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