Investigation and comparison of the accuracy of land use maps obtained from eCognition software and Google Earth Engine (case study of Damghan watershed)

Authors
Peyman Akbarzadeh 1
Shima Nikoo 2
1 Zanjan Agriculture and Natural Resources Research Center, Forest and Pasture Research Department
2 , Faculty of Desert Studies, Semnan University
10.22034/wmji.2024.2039506.1086
Abstract
Land use changes are one of the parameters affecting global environmental changes. These changes affect a wide range of environmental features and natural resources, etc., based on this, it is of particular importance to check the accuracy of land use extraction maps to determine these changes for better management and more appropriate use of watersheds. The purpose of this research was to determine and examine high-precision methods for extracting land use maps for a part of the Damghan watershed. For this purpose, the user maps of the region were prepared using Landsat 8 satellite image processing, eCognition software and Google Earth Engine system for 2020.Then, the accuracy of the resulting maps was checked using Kappa coefficient, overall accuracy coefficient and user accuracy based on field studies in 100 random points, Google Earth images and information on the implementation plan carried out in the region. The results showed that the Kappa coefficient and the overall accuracy for the maps obtained from eCognition software are 0.94 and 0.95, respectively, and for Google Earth Engine 0.66 and 0.73; Based on this, the land use map prepared for the Damghan watershed using eCognition shows higher accuracy. Therefore, in areas with an area around the study area or less, to study and investigate land use changes It is better to use other remote sensing softwares, such as eCognition, which produce maps with higher accuracy and greater adaptation to land uses, instead of Google Earth Engine.
Keywords
Iran Central desert
map efficiency
Object-oriented classification method
Remote sensing
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