Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass
The penetration capability of electromagnetic wave signal into forest increases with increasing wavelength. SAR data at each frequency senses different components of forest structure. Therefore the biomass distributed at various tree components could be estimated using different radar frequencies. A...
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Taylor & Francis Group
2025-03-01
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| Series: | Geo-spatial Information Science |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/10095020.2024.2311867 |
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| author | Yongjie Ji Fuxiang Zhang Wangfei Zhang Lei Zhao Kunpeng Xu Jianmin Shi Guoran Huang Qian Jing Lu Wang Feifei Yang |
| author_facet | Yongjie Ji Fuxiang Zhang Wangfei Zhang Lei Zhao Kunpeng Xu Jianmin Shi Guoran Huang Qian Jing Lu Wang Feifei Yang |
| author_sort | Yongjie Ji |
| collection | DOAJ |
| description | The penetration capability of electromagnetic wave signal into forest increases with increasing wavelength. SAR data at each frequency senses different components of forest structure. Therefore the biomass distributed at various tree components could be estimated using different radar frequencies. Additionally, the synthesis of multiple SAR frequencies could improve the accuracy in retrieving forest above-ground biomass (AGB). Taking advantage of available X-, C-, L-, and P-band quad-polarimetric SAR images of airborne or spaceborne for the test site located at Genhe national forest scientific field station, we used a Genetic Algorithm and Support Vector Regression optimization algorithm (GA-SVR) to explore the sensitivity of polarimetric observations at various frequencies to forest AGB and effectiveness of AGB retrievals using single-frequency, dual-frequency, triple-frequency, and quad-frequency SAR observation combinations. We found that: (i) Most of the polarimetric observations are sensitive to forest AGB, (ii) GA-SVR performed well in forest AGB retrieval using the single frequency SAR observations or combinations of multi-frequency observations; the highest Acc. value for single-frequency-retrieved results is 75.13% acquired at P-band, with multi-frequency, the highest Acc. values is 77.34% acquired by combining C- and P-band. (iii) For forest AGB retrievals, the single-frequency P-band accuracy is comparable to the combined C- and P-band retrieval accuracy, indicating that the long-wavelength single-frequency P-band is sufficient for an accurate forest AGB retrieval. The findings reconfirmed potential of P-band for forest AGB retrievals, they also demonstrated that the optimal combination of multi-frequency SAR for AGB retrievals is by using a short-wavelength (X/C-) and a long-wavelength (L/P-). |
| format | Article |
| id | doaj-art-e538e4166b0b4ff6a3826fccc332bdac |
| institution | Kabale University |
| issn | 1009-5020 1993-5153 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Geo-spatial Information Science |
| spelling | doaj-art-e538e4166b0b4ff6a3826fccc332bdac2025-08-20T03:26:52ZengTaylor & Francis GroupGeo-spatial Information Science1009-50201993-51532025-03-0128262964710.1080/10095020.2024.2311867Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomassYongjie Ji0Fuxiang Zhang1Wangfei Zhang2Lei Zhao3Kunpeng Xu4Jianmin Shi5Guoran Huang6Qian Jing7Lu Wang8Feifei Yang9School of Geography and Ecotourism, Southwest Forestry University, Kunming, ChinaSchool of Geography and Ecotourism, Southwest Forestry University, Kunming, ChinaForestry College, Southwest Forestry University, Kunming, ChinaInstitute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing, ChinaInstitute of Forest Resources Information Technique, Chinese Academy of Forestry, Beijing, ChinaForestry College, Southwest Forestry University, Kunming, ChinaForestry College, Southwest Forestry University, Kunming, ChinaSchool of Geography and Ecotourism, Southwest Forestry University, Kunming, ChinaSchool of Geography and Ecotourism, Southwest Forestry University, Kunming, ChinaForestry College, Southwest Forestry University, Kunming, ChinaThe penetration capability of electromagnetic wave signal into forest increases with increasing wavelength. SAR data at each frequency senses different components of forest structure. Therefore the biomass distributed at various tree components could be estimated using different radar frequencies. Additionally, the synthesis of multiple SAR frequencies could improve the accuracy in retrieving forest above-ground biomass (AGB). Taking advantage of available X-, C-, L-, and P-band quad-polarimetric SAR images of airborne or spaceborne for the test site located at Genhe national forest scientific field station, we used a Genetic Algorithm and Support Vector Regression optimization algorithm (GA-SVR) to explore the sensitivity of polarimetric observations at various frequencies to forest AGB and effectiveness of AGB retrievals using single-frequency, dual-frequency, triple-frequency, and quad-frequency SAR observation combinations. We found that: (i) Most of the polarimetric observations are sensitive to forest AGB, (ii) GA-SVR performed well in forest AGB retrieval using the single frequency SAR observations or combinations of multi-frequency observations; the highest Acc. value for single-frequency-retrieved results is 75.13% acquired at P-band, with multi-frequency, the highest Acc. values is 77.34% acquired by combining C- and P-band. (iii) For forest AGB retrievals, the single-frequency P-band accuracy is comparable to the combined C- and P-band retrieval accuracy, indicating that the long-wavelength single-frequency P-band is sufficient for an accurate forest AGB retrieval. The findings reconfirmed potential of P-band for forest AGB retrievals, they also demonstrated that the optimal combination of multi-frequency SAR for AGB retrievals is by using a short-wavelength (X/C-) and a long-wavelength (L/P-).https://www.tandfonline.com/doi/10.1080/10095020.2024.2311867Multi-frequency combinationforest Above-Ground Biomass (AGB)polarimetric synthetic aperture radar |
| spellingShingle | Yongjie Ji Fuxiang Zhang Wangfei Zhang Lei Zhao Kunpeng Xu Jianmin Shi Guoran Huang Qian Jing Lu Wang Feifei Yang Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass Geo-spatial Information Science Multi-frequency combination forest Above-Ground Biomass (AGB) polarimetric synthetic aperture radar |
| title | Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass |
| title_full | Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass |
| title_fullStr | Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass |
| title_full_unstemmed | Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass |
| title_short | Exploring optimal combinations of multi-frequency polarimetric SAR observations to estimate forest above-ground biomass |
| title_sort | exploring optimal combinations of multi frequency polarimetric sar observations to estimate forest above ground biomass |
| topic | Multi-frequency combination forest Above-Ground Biomass (AGB) polarimetric synthetic aperture radar |
| url | https://www.tandfonline.com/doi/10.1080/10095020.2024.2311867 |
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