Classification of Land Cover and Land Use in Mobarakeh County Using Landsat 9 Imagery Data
Remote sensing is defined as the science and art of acquiring information about objects, land, or various phenomena through the collection of data without direct contact with the phenomena under investigation. In terrestrial resources, the use of aerial photographs, space images, and satellite-deriv...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
Scientific Association of Waste Management
2024-08-01
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| Series: | اکولوژی انسانی |
| Subjects: | |
| Online Access: | https://www.landscapeecologyjournals.ir/article_212648_9dbd60e373ae6b50b78f7119f7e6cbd1.pdf |
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| Summary: | Remote sensing is defined as the science and art of acquiring information about objects, land, or various phenomena through the collection of data without direct contact with the phenomena under investigation. In terrestrial resources, the use of aerial photographs, space images, and satellite-derived imagery for interpreting, identifying, and obtaining information about phenomena is referred to as remote sensing. Today, understanding the environment for planning based on the ecological potential of each region, in line with assessing capabilities in specific geographical areas, is considered a crucial phase in the implementation of projects, especially at macro and national levels. Therefore, the objective of this research is to classify land cover and land use in Mobarakeh County. To create the land use map, ENVI 3.5 software, which is designed for processing and analyzing remote sensing data, particularly satellite data, was utilized. Additionally, to identify land cover, products available in the Google Earth Engine platform were employed, which support various types of widely-used satellite data offered for free. Ultimately, to evaluate the accuracy of the classified results, the produced map was compared with ground truth data using Google Earth. Furthermore, to determine the overall accuracy of the classification, the overall accuracy and Kappa coefficient were calculated. The results of this research indicate that the assessment of the produced map's accuracy, which was examined against ground reality using 388 reference points in Google Earth, yielded an overall accuracy of 95.36% and a Kappa coefficient of 0.92, indicating a reliable measure. Finally, it is suggested that future studies consider using segmentations of satellite imagery with the assistance of remote sensing software to define units and assign them to compatible zones instead of employing pixel-based methods for managing such areas. |
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| ISSN: | 3041-9255 |