Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor

Aim: The purpose of this research is to identify the area of sand dunes and their changes in desert areas using spectral indicators in Landsat 8 and Sentinel 2 satellites. Material & Method: In this research, using four bands of Sentinel 2 data, a new spectral index named NDESI has been presente...

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Main Author: mehdi feyzolahpour
Format: Article
Language:fas
Published: Hakim Sabzevari University 2025-05-01
Series:مطالعات جغرافیایی مناطق خشک
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Online Access:https://jargs.hsu.ac.ir/article_191974_4864c470c987de2c3ec4687dfffbe6b4.pdf
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author mehdi feyzolahpour
author_facet mehdi feyzolahpour
author_sort mehdi feyzolahpour
collection DOAJ
description Aim: The purpose of this research is to identify the area of sand dunes and their changes in desert areas using spectral indicators in Landsat 8 and Sentinel 2 satellites. Material & Method: In this research, using four bands of Sentinel 2 data, a new spectral index named NDESI has been presented for the identification and recognition of sand dunes in the Rig Jen area. This index uses the blue, red, or red edge of vegetation and two short-wave infrared bands, SWIR1 and SWIR2, to produce the image. A threshold calculation method was used to create unique thresholds for each image. Finding:  Based on this, the threshold values for equations 1 and 2 in March and July 2023 of the Sentinel 2 satellite were obtained as 0.261 and 0.217, respectively. This amount for Landsat 8 satellite in 2013, 2018, and 2023 was equal to 0.063, 0.0735, and 0.071, respectively. According to equation 1 of the Sentinel 2 satellite in July 2023, the extent of sand dunes in this area was equal to 2262 square kilometers. For Landsat 8 satellite in the same year, it was 2638 square kilometers. In the discussion of Pearson correlation, it was also observed that the highest correlation of 0.63 between the NDESI index and band 7 of the Landsat 8 satellite and the lowest correlation of -0.14 between this index and band 2 in equation 1 of Sentinel satellite 2 has been. Conclusion: Finally, the accuracy evaluation of the images obtained from equations 1 and 2 showed an overall accuracy of 87.4 and 83.7 percent, respectively. This index is also compatible with Landsat 8 data. Innovation: The results of this research have been used in the investigation of sand dunes and their identification.
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spelling doaj-art-da9ea97b537c4cdd835ae45f26cefefb2025-08-20T03:09:31ZfasHakim Sabzevari Universityمطالعات جغرافیایی مناطق خشک2228-71672981-19102025-05-01165915217010.22034/jargs.2023.409048.1052191974Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensormehdi feyzolahpour0Department of Geography, Faculty of Human Science, University of Zanjan, Zanjan, Iran.Aim: The purpose of this research is to identify the area of sand dunes and their changes in desert areas using spectral indicators in Landsat 8 and Sentinel 2 satellites. Material & Method: In this research, using four bands of Sentinel 2 data, a new spectral index named NDESI has been presented for the identification and recognition of sand dunes in the Rig Jen area. This index uses the blue, red, or red edge of vegetation and two short-wave infrared bands, SWIR1 and SWIR2, to produce the image. A threshold calculation method was used to create unique thresholds for each image. Finding:  Based on this, the threshold values for equations 1 and 2 in March and July 2023 of the Sentinel 2 satellite were obtained as 0.261 and 0.217, respectively. This amount for Landsat 8 satellite in 2013, 2018, and 2023 was equal to 0.063, 0.0735, and 0.071, respectively. According to equation 1 of the Sentinel 2 satellite in July 2023, the extent of sand dunes in this area was equal to 2262 square kilometers. For Landsat 8 satellite in the same year, it was 2638 square kilometers. In the discussion of Pearson correlation, it was also observed that the highest correlation of 0.63 between the NDESI index and band 7 of the Landsat 8 satellite and the lowest correlation of -0.14 between this index and band 2 in equation 1 of Sentinel satellite 2 has been. Conclusion: Finally, the accuracy evaluation of the images obtained from equations 1 and 2 showed an overall accuracy of 87.4 and 83.7 percent, respectively. This index is also compatible with Landsat 8 data. Innovation: The results of this research have been used in the investigation of sand dunes and their identification.https://jargs.hsu.ac.ir/article_191974_4864c470c987de2c3ec4687dfffbe6b4.pdfsand indexndesisentinel 2landsat 8rig jen
spellingShingle mehdi feyzolahpour
Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
مطالعات جغرافیایی مناطق خشک
sand index
ndesi
sentinel 2
landsat 8
rig jen
title Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
title_full Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
title_fullStr Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
title_full_unstemmed Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
title_short Detection of desert sand dunes in the Rig Jen area using the normalized Difference excess sand index (NDESI) in Sentinel 2 images and Landsat 8 OLI sensor
title_sort detection of desert sand dunes in the rig jen area using the normalized difference excess sand index ndesi in sentinel 2 images and landsat 8 oli sensor
topic sand index
ndesi
sentinel 2
landsat 8
rig jen
url https://jargs.hsu.ac.ir/article_191974_4864c470c987de2c3ec4687dfffbe6b4.pdf
work_keys_str_mv AT mehdifeyzolahpour detectionofdesertsanddunesintherigjenareausingthenormalizeddifferenceexcesssandindexndesiinsentinel2imagesandlandsat8olisensor