Bare soil detecting algorithms in western iran woodlands using remote sensing
This study presents the Modified Bare Soil Index (MBI), an innovative remote sensing instrument that employs Short Wave Infrared (SWIR) and Near Infrared (NIR) wavelengths sourced from Landsat 8 satellite observations. Its purpose is to refine the identification and distinction of bare soil within w...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524000340 |
| _version_ | 1797246790905364480 |
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| author | Hossein Panahi Zahra Azizi Hadi Kiadaliri Seyed Ali Almodaresi Hossein Aghamohamadi |
| author_facet | Hossein Panahi Zahra Azizi Hadi Kiadaliri Seyed Ali Almodaresi Hossein Aghamohamadi |
| author_sort | Hossein Panahi |
| collection | DOAJ |
| description | This study presents the Modified Bare Soil Index (MBI), an innovative remote sensing instrument that employs Short Wave Infrared (SWIR) and Near Infrared (NIR) wavelengths sourced from Landsat 8 satellite observations. Its purpose is to refine the identification and distinction of bare soil within woodland regions. Addressing the limitations of existing methods, MBI represents a significant advancement in land cover change detection. Through a focused study in the Sardasht forests of western Iran, the MBI demonstrates superior accuracy, achieving an overall accuracy of approximately 96 % with a Kappa coefficient exceeding 0.94, surpassing traditional bare soil indices. This innovation improves the classification of land surfaces and also aids in the efficient monitoring and safeguarding of changes in land cover. The MBI's robust performance underscores its potential in smart forestry, enabling more precise identification and surveillance of bare soil areas. This advancement is pivotal for ecological studies and resource management, offering a practical solution to the challenges of soil erosion and land degradation. By integrating advanced spectral analysis with satellite imagery, the MBI sets a new standard in remote sensing techniques, offering vital insights for environmental conservation and agricultural practices. |
| first_indexed | 2024-04-24T19:48:24Z |
| format | Article |
| id | doaj.art-52bdddc7c0f4412c918d1226986bd359 |
| institution | Directory Open Access Journal |
| issn | 2772-3755 |
| language | English |
| last_indexed | 2024-04-24T19:48:24Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj.art-52bdddc7c0f4412c918d1226986bd3592024-03-25T04:18:20ZengElsevierSmart Agricultural Technology2772-37552024-03-017100429Bare soil detecting algorithms in western iran woodlands using remote sensingHossein Panahi0Zahra Azizi1Hadi Kiadaliri2Seyed Ali Almodaresi3Hossein Aghamohamadi4PhD Student in Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran; Corresponding author at: Department of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Environment Science and Forest, Faculty of Natural Resource and Environment, Science and Research Branch, Islamic Azad University, Tehran, IranDepartment of Geography, Faculty of Humanities, Yazd Branch, Islamic Azad University, Yazd, IranDepartment of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, IranThis study presents the Modified Bare Soil Index (MBI), an innovative remote sensing instrument that employs Short Wave Infrared (SWIR) and Near Infrared (NIR) wavelengths sourced from Landsat 8 satellite observations. Its purpose is to refine the identification and distinction of bare soil within woodland regions. Addressing the limitations of existing methods, MBI represents a significant advancement in land cover change detection. Through a focused study in the Sardasht forests of western Iran, the MBI demonstrates superior accuracy, achieving an overall accuracy of approximately 96 % with a Kappa coefficient exceeding 0.94, surpassing traditional bare soil indices. This innovation improves the classification of land surfaces and also aids in the efficient monitoring and safeguarding of changes in land cover. The MBI's robust performance underscores its potential in smart forestry, enabling more precise identification and surveillance of bare soil areas. This advancement is pivotal for ecological studies and resource management, offering a practical solution to the challenges of soil erosion and land degradation. By integrating advanced spectral analysis with satellite imagery, the MBI sets a new standard in remote sensing techniques, offering vital insights for environmental conservation and agricultural practices.http://www.sciencedirect.com/science/article/pii/S2772375524000340SardashtForestMBILandsat 8Spectral Indexes |
| spellingShingle | Hossein Panahi Zahra Azizi Hadi Kiadaliri Seyed Ali Almodaresi Hossein Aghamohamadi Bare soil detecting algorithms in western iran woodlands using remote sensing Smart Agricultural Technology Sardasht Forest MBI Landsat 8 Spectral Indexes |
| title | Bare soil detecting algorithms in western iran woodlands using remote sensing |
| title_full | Bare soil detecting algorithms in western iran woodlands using remote sensing |
| title_fullStr | Bare soil detecting algorithms in western iran woodlands using remote sensing |
| title_full_unstemmed | Bare soil detecting algorithms in western iran woodlands using remote sensing |
| title_short | Bare soil detecting algorithms in western iran woodlands using remote sensing |
| title_sort | bare soil detecting algorithms in western iran woodlands using remote sensing |
| topic | Sardasht Forest MBI Landsat 8 Spectral Indexes |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524000340 |
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