Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods
Chlorophyll is a good indicator of health status and nutritional condition as plant grows. Many studies have investigated the feasibility of retrieving leaf chlorophyll content (LCC) using vegetation indices (VIs) of multiple plant species, yet very few studies have examined the multi-temporal Senti...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-10-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0303243421000945 |
| _version_ | 1828196206260518912 |
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| author | Jianing Zhen Xiapeng Jiang Yi Xu Jing Miao Demei Zhao Junjie Wang Jingzhe Wang Guofeng Wu |
| author_facet | Jianing Zhen Xiapeng Jiang Yi Xu Jing Miao Demei Zhao Junjie Wang Jingzhe Wang Guofeng Wu |
| author_sort | Jianing Zhen |
| collection | DOAJ |
| description | Chlorophyll is a good indicator of health status and nutritional condition as plant grows. Many studies have investigated the feasibility of retrieving leaf chlorophyll content (LCC) using vegetation indices (VIs) of multiple plant species, yet very few studies have examined the multi-temporal Sentinel-2 images for mapping LCC of mangrove forests. With field collected leaf SPAD values (relative chlorophyll content), this study explored the relationship of leaf SPAD values against five types of newly-developed VIs derived from leaf hyperspectral data and Sentinel-2 data of four periods (May 2018, January 2019, August 2019, and December 2019). Linear regression with best-performing VIs and Kernel Ridge Regression (KRR) were developed to construct the SPAD retrieval model in each period. The leave-one-out cross-validation technique was employed to compare the estimation results of VIs and KRR method, and the four periods of SPAD maps were produced by the best-performing model. The results showed that the newly-developed index (ratio of single-band reflectance to the sum of two bands reflectance, RSSI) achieved the high correlation coefficient with leaf SPAD value at both leaf and canopy level. At canopy level, the linear model using RSSI (B8/(B2 + B5), B8a/(B2 + B4), B8/(B2 + B5), and B8/(B2 + B3)) outperformed than that using traditional broadband indices and KRR model with R2adjust = 0.496, 0.742, 0.681, and 0.801; RMSE = 5.75, 4.29, 4.00, and 3.46; and RE = 7.67%, 5.68%, 4.97%, and 4.63% in each period. We concluded that there are great potentials of newly-developed index of RSSI using Sentinel-2 data for regional retrieving and mapping LCC of mangrove forests across different time periods, which is essential for mangrove ecological conservation and restoration. |
| first_indexed | 2024-04-12T09:57:37Z |
| format | Article |
| id | doaj.art-79619920a0004ac8879d83e3e1419dbd |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-04-12T09:57:37Z |
| publishDate | 2021-10-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-79619920a0004ac8879d83e3e1419dbd2022-12-22T03:37:39ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322021-10-01102102387Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periodsJianing Zhen0Xiapeng Jiang1Yi Xu2Jing Miao3Demei Zhao4Junjie Wang5Jingzhe Wang6Guofeng Wu7College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China; MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, ChinaMNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China; School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaFaculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7514 AE, NetherlandsMNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China; School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaMNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China; School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaCollege of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China; MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China; Corresponding author.College of Life Sciences and Oceanography, Shenzhen University, Shenzhen 518060, China; MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, ChinaMNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area & Guangdong Key Laboratory of Urban Informatics & Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China; School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, ChinaChlorophyll is a good indicator of health status and nutritional condition as plant grows. Many studies have investigated the feasibility of retrieving leaf chlorophyll content (LCC) using vegetation indices (VIs) of multiple plant species, yet very few studies have examined the multi-temporal Sentinel-2 images for mapping LCC of mangrove forests. With field collected leaf SPAD values (relative chlorophyll content), this study explored the relationship of leaf SPAD values against five types of newly-developed VIs derived from leaf hyperspectral data and Sentinel-2 data of four periods (May 2018, January 2019, August 2019, and December 2019). Linear regression with best-performing VIs and Kernel Ridge Regression (KRR) were developed to construct the SPAD retrieval model in each period. The leave-one-out cross-validation technique was employed to compare the estimation results of VIs and KRR method, and the four periods of SPAD maps were produced by the best-performing model. The results showed that the newly-developed index (ratio of single-band reflectance to the sum of two bands reflectance, RSSI) achieved the high correlation coefficient with leaf SPAD value at both leaf and canopy level. At canopy level, the linear model using RSSI (B8/(B2 + B5), B8a/(B2 + B4), B8/(B2 + B5), and B8/(B2 + B3)) outperformed than that using traditional broadband indices and KRR model with R2adjust = 0.496, 0.742, 0.681, and 0.801; RMSE = 5.75, 4.29, 4.00, and 3.46; and RE = 7.67%, 5.68%, 4.97%, and 4.63% in each period. We concluded that there are great potentials of newly-developed index of RSSI using Sentinel-2 data for regional retrieving and mapping LCC of mangrove forests across different time periods, which is essential for mangrove ecological conservation and restoration.http://www.sciencedirect.com/science/article/pii/S0303243421000945Mangrove forestsLeaf chlorophyll contentSPAD valueSentinel-2Vegetation index |
| spellingShingle | Jianing Zhen Xiapeng Jiang Yi Xu Jing Miao Demei Zhao Junjie Wang Jingzhe Wang Guofeng Wu Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods International Journal of Applied Earth Observations and Geoinformation Mangrove forests Leaf chlorophyll content SPAD value Sentinel-2 Vegetation index |
| title | Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods |
| title_full | Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods |
| title_fullStr | Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods |
| title_full_unstemmed | Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods |
| title_short | Mapping leaf chlorophyll content of mangrove forests with Sentinel-2 images of four periods |
| title_sort | mapping leaf chlorophyll content of mangrove forests with sentinel 2 images of four periods |
| topic | Mangrove forests Leaf chlorophyll content SPAD value Sentinel-2 Vegetation index |
| url | http://www.sciencedirect.com/science/article/pii/S0303243421000945 |
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