Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress
The fraction of absorbed photosynthetically active radiation (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant=&...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/16/2/362 |
| _version_ | 1797342558199742464 |
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| author | Zheng Sun Liang Sun Yu Liu Yangwei Li Luís Guilherme Teixeira Crusiol Ruiqing Chen Deji Wuyun |
| author_facet | Zheng Sun Liang Sun Yu Liu Yangwei Li Luís Guilherme Teixeira Crusiol Ruiqing Chen Deji Wuyun |
| author_sort | Zheng Sun |
| collection | DOAJ |
| description | The fraction of absorbed photosynthetically active radiation (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>) is an important parameter reflecting the level of photosynthesis and growth status of vegetation, and is widely used in energy cycling, carbon cycling, and vegetation productivity estimation. In agricultural production, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> is often combined with the light use efficiency model to estimate crop yield. Therefore, accurate estimation of PAR is of great importance for improving the accuracy of crop yield estimation and ensuring national food security. Existing studies based on vegetation indices have not considered the effects of genetic variety, light, and water stress on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> estimation. This study uses ground-based reflectance data to simulate 21 common Sentinel-2 vegetation indices and compare their estimation ability for winter wheat <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>. The stability of the vegetation index with the highest correlation in inverting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> under different cultivars, light, and water stress was tested, and then the model was validated at the satellite scale. Finally, a sensitivity analysis was performed. The results showed that the index model based on modified NDVI (MNDVI) had the highest correlation not only throughout the critical phenological period of winter wheat (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.6649) but also under different varieties, observation dates, and water stress (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.918, 0.881, and 0.830, respectively). It even performed the highest <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.8312 at the satellite scale. Moreover, through comparison, we found that considering water stress and variety differences can improve the estimation accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>. The study showed that using MNDVI for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> estimation is not only feasible but also has high accuracy and stability, providing a reference for rapid and accurate estimation of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> by Sentinel-2 and further exploring the potential of Sentinel-2 data for high-resolution <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> mapping. |
| first_indexed | 2024-03-08T10:35:03Z |
| format | Article |
| id | doaj.art-07f16f0245614993a6e99f6e5293111d |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-08T10:35:03Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-07f16f0245614993a6e99f6e5293111d2024-01-26T18:19:18ZengMDPI AGRemote Sensing2072-42922024-01-0116236210.3390/rs16020362Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water StressZheng Sun0Liang Sun1Yu Liu2Yangwei Li3Luís Guilherme Teixeira Crusiol4Ruiqing Chen5Deji Wuyun6State Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaState Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaState Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaState Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaEmbrapa Soja (National Soybean Research Center—Brazilian Agricultural Research Corporation), Londrina 86001-970, PR, BrazilState Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaState Key Laboratory of Efficient Utilization of Arid and Semi-Arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, ChinaThe fraction of absorbed photosynthetically active radiation (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>) is an important parameter reflecting the level of photosynthesis and growth status of vegetation, and is widely used in energy cycling, carbon cycling, and vegetation productivity estimation. In agricultural production, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> is often combined with the light use efficiency model to estimate crop yield. Therefore, accurate estimation of PAR is of great importance for improving the accuracy of crop yield estimation and ensuring national food security. Existing studies based on vegetation indices have not considered the effects of genetic variety, light, and water stress on <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> estimation. This study uses ground-based reflectance data to simulate 21 common Sentinel-2 vegetation indices and compare their estimation ability for winter wheat <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>. The stability of the vegetation index with the highest correlation in inverting <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> under different cultivars, light, and water stress was tested, and then the model was validated at the satellite scale. Finally, a sensitivity analysis was performed. The results showed that the index model based on modified NDVI (MNDVI) had the highest correlation not only throughout the critical phenological period of winter wheat (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.6649) but also under different varieties, observation dates, and water stress (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.918, 0.881, and 0.830, respectively). It even performed the highest <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mrow><mi mathvariant="normal">R</mi></mrow><mrow><mn>2</mn></mrow></msup></mrow></semantics></math></inline-formula> of 0.8312 at the satellite scale. Moreover, through comparison, we found that considering water stress and variety differences can improve the estimation accuracy of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula>. The study showed that using MNDVI for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> estimation is not only feasible but also has high accuracy and stability, providing a reference for rapid and accurate estimation of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> by Sentinel-2 and further exploring the potential of Sentinel-2 data for high-resolution <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>f</mi><mi mathvariant="normal">P</mi><mi mathvariant="normal">A</mi><mi mathvariant="normal">R</mi></mrow></semantics></math></inline-formula> mapping.https://www.mdpi.com/2072-4292/16/2/362fraction of absorbed photosynthetically active radiationMNDVIwinter wheatvegetation indexSentinel-2 |
| spellingShingle | Zheng Sun Liang Sun Yu Liu Yangwei Li Luís Guilherme Teixeira Crusiol Ruiqing Chen Deji Wuyun Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress Remote Sensing fraction of absorbed photosynthetically active radiation MNDVI winter wheat vegetation index Sentinel-2 |
| title | Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress |
| title_full | Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress |
| title_fullStr | Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress |
| title_full_unstemmed | Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress |
| title_short | Estimating Fraction of Absorbed Photosynthetically Active Radiation of Winter Wheat Based on Simulated Sentinel-2 Data under Different Varieties and Water Stress |
| title_sort | estimating fraction of absorbed photosynthetically active radiation of winter wheat based on simulated sentinel 2 data under different varieties and water stress |
| topic | fraction of absorbed photosynthetically active radiation MNDVI winter wheat vegetation index Sentinel-2 |
| url | https://www.mdpi.com/2072-4292/16/2/362 |
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