Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2
Synthetic-aperture radar’s (SAR’s) capacity to resolve the cloud cover concerns encountered while gathering optical data has tremendous potential for soil moisture data retrieval using SAR data. It is possible to use SAR data to recover soil moisture because the backscatter coefficient is sensitive...
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Multidisciplinary Digital Publishing Institute
2021
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my.upm.eprints.964682023-02-08T03:17:16Z http://psasir.upm.edu.my/id/eprint/96468/ Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md. Rowshon Yang, Ping Lee Takeuchi, Wataru Synthetic-aperture radar’s (SAR’s) capacity to resolve the cloud cover concerns encountered while gathering optical data has tremendous potential for soil moisture data retrieval using SAR data. It is possible to use SAR data to recover soil moisture because the backscatter coefficient is sensitive to both soil and vegetation by penetrating through the vegetation layer. This study investigated the feasibility of employing a SAR-derived radar vegetation index (RVI), the ratios of the backscatter coefficients using polarizations of HH/HV (RHH/HV) and HV/HH (RHH/HV) to an oil palm crops as vegetation indicators in the water cloud model (WCM) using phased-array L-band SAR-2 (PALSAR-2). These data were compared to the manual leaf area index (LAI) and a physical soil sampling method for computing soil moisture. The field data included the LAI input parameters and, more importantly, physical soil samples from which to calculate the soil moisture. The fieldwork was carried out in Chuping District, Perlis State, Malaysia. Corresponding PALSAR-2 data were collected on three observation dates in 2019: 17 January, 16 April, and 9 July. The results showed that the WCM modeled using the LAI under HV polarization demonstrated promising accuracy, with the root mean square error recorded as 0.033 m3/m3. This was comparable to the RVI and RHH/HV under HV polarization, which had accuracies of 0.031 and 0.049 m3/m3, respectively. The findings of this study suggest that SAR-based indicators, RHH/HV and RVI using PALSAR-2, can be used to reduce field-related input in the retrieval of soil moisture data using the WCM for oil palm crop. Multidisciplinary Digital Publishing Institute 2021 Article PeerReviewed Shashikant, Veena and Mohamed Shariff, Abdul Rashid and Wayayok, Aimrun and Kamal, Md. Rowshon and Yang, Ping Lee and Takeuchi, Wataru (2021) Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2. Remote Sensing, 13 (23). pp. 1-17. ISSN 2072-4292 https://www.mdpi.com/2072-4292/13/23/4729 10.3390/rs13234729 |
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Synthetic-aperture radar’s (SAR’s) capacity to resolve the cloud cover concerns encountered while gathering optical data has tremendous potential for soil moisture data retrieval using SAR data. It is possible to use SAR data to recover soil moisture because the backscatter coefficient is sensitive to both soil and vegetation by penetrating through the vegetation layer. This study investigated the feasibility of employing a SAR-derived radar vegetation index (RVI), the ratios of the backscatter coefficients using polarizations of HH/HV (RHH/HV) and HV/HH (RHH/HV) to an oil palm crops as vegetation indicators in the water cloud model (WCM) using phased-array L-band SAR-2 (PALSAR-2). These data were compared to the manual leaf area index (LAI) and a physical soil sampling method for computing soil moisture. The field data included the LAI input parameters and, more importantly, physical soil samples from which to calculate the soil moisture. The fieldwork was carried out in Chuping District, Perlis State, Malaysia. Corresponding PALSAR-2 data were collected on three observation dates in 2019: 17 January, 16 April, and 9 July. The results showed that the WCM modeled using the LAI under HV polarization demonstrated promising accuracy, with the root mean square error recorded as 0.033 m3/m3. This was comparable to the RVI and RHH/HV under HV polarization, which had accuracies of 0.031 and 0.049 m3/m3, respectively. The findings of this study suggest that SAR-based indicators, RHH/HV and RVI using PALSAR-2, can be used to reduce field-related input in the retrieval of soil moisture data using the WCM for oil palm crop. |
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Article |
author |
Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md. Rowshon Yang, Ping Lee Takeuchi, Wataru |
spellingShingle |
Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md. Rowshon Yang, Ping Lee Takeuchi, Wataru Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
author_facet |
Shashikant, Veena Mohamed Shariff, Abdul Rashid Wayayok, Aimrun Kamal, Md. Rowshon Yang, Ping Lee Takeuchi, Wataru |
author_sort |
Shashikant, Veena |
title |
Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
title_short |
Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
title_full |
Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
title_fullStr |
Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
title_full_unstemmed |
Comparison of field and SAR-derived descriptors in the retrieval of soil moisture from oil palm crops using PALSAR-2 |
title_sort |
comparison of field and sar-derived descriptors in the retrieval of soil moisture from oil palm crops using palsar-2 |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2021 |
url |
http://psasir.upm.edu.my/id/eprint/96468/ https://www.mdpi.com/2072-4292/13/23/4729 |
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1758579863365615616 |
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13.214268 |