Improvement of FAPAR Estimation Under the Presence of Non-Green Vegetation Considering Fractional Vegetation Coverage
文献类型：期刊论文
| 作者 | Li, Rui5,6; Li, Baolin4,5,6; Yuan, Yecheng6; Liu, Wei5,6; Zhu, Jie5,6; Qi, Jiali3; Liu, Haijiang2; Ma, Guangwen2; Jiang, Yuhao1; Li, Ying5,6 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2025-02-01 |
| 卷号 | 17期号:4页码:603 |
| 关键词 | light use efficiency model Beer-Lambert's law homogeneous turbid medium assumption non-green vegetation canopy gross primary production estimation |
| DOI | 10.3390/rs17040603 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | The homogeneous turbid medium assumption inherent to the Beer-Lambert's law can lead to a reduction in the shading effect between leaves when non-green vegetation canopies are present, resulting in an overestimation of the fraction of absorbed photosynthetically active radiation (FAPAR). This paper proposed a method to improve the FAPAR estimation (FAPARFVC) based on Beer-Lambert's law by incorporating fractional vegetation coverage (FVC). Initially, the canopy-scale leaf area index (LAI) of the green canopy distribution area within the pixel (sample site) was determined based on the FVC. Subsequently, the canopy-scale FAPAR was calculated within the green canopy distribution area, adhering to the assumption of a homogeneous turbid medium in the Beer-Lambert's law. Finally, the average FAPAR across the pixel (sample site) was calculated based on the FVC. This paper conducted a case study using measured data from the BigFoot Project and grass savanna in Senegal, West Africa, as well as Moderate Resolution Imaging Spectroradiometer (MODIS) LAI/FPAR products. The results indicated that the FAPARFVC approach demonstrated superior accuracy compared to the FAPAR determined by MODIS LAI, according to the Beer-Lambert's law (FAPARLAI) and MODIS FPAR products (FAPARMOD). The mean absolute percentage error of FAPARFVC was 48.2%, which is 25.6% and 52.1% lower than that of FAPARLAI and FAPARMOD, respectively. The mean percentage error of FAPARFVC was 16.8%, which was 71.6% and 73.4% lower than that of FAPARLAI and FAPARMOD, respectively. The improvements in accuracy and the decrease in overestimation for FAPARFVC became more pronounced with increasing FVC compared to FAPARLAI. The findings suggested that the FAPARFVC method enhanced the accuracy of FAPAR estimation under the presence of non-green vegetation canopies. The method can be extended to regional scale FAPAR and gross primary production (GPP) estimations, thereby providing more accurate inputs for understanding its tempo-spatial patterns and drivers. |
| URL标识 | 查看原文 |
| WOS关键词 | GROSS PRIMARY PRODUCTION ; LIGHT USE EFFICIENCY ; PHOTOSYNTHETICALLY ACTIVE RADIATION ; CANOPY PAR ABSORPTANCE ; LEAF-AREA INDEX ; MODEL ; MODIS ; VALIDATION ; PRODUCTS ; NDVI |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001431027900001 |
| 出版者 | MDPI |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/213336]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Li, Baolin |
| 作者单位 | 1.Natl Forestry & Grassland Adm, Acad Forest Inventory & Planning, Beijing 100013, Peoples R China 2.China Natl Environm Monitoring Ctr, Beijing 100012, Peoples R China; 3.Qinghai Ecoenvironm Monitoring Ctr, Xining 810007, Peoples R China; 4.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China; 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China; 6.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China; |
| 推荐引用方式 GB/T 7714 | Li, Rui,Li, Baolin,Yuan, Yecheng,et al. Improvement of FAPAR Estimation Under the Presence of Non-Green Vegetation Considering Fractional Vegetation Coverage[J]. REMOTE SENSING,2025,17(4):603. |
| APA | Li, Rui.,Li, Baolin.,Yuan, Yecheng.,Liu, Wei.,Zhu, Jie.,...&Tan, Qiuyuan.(2025).Improvement of FAPAR Estimation Under the Presence of Non-Green Vegetation Considering Fractional Vegetation Coverage.REMOTE SENSING,17(4),603. |
| MLA | Li, Rui,et al."Improvement of FAPAR Estimation Under the Presence of Non-Green Vegetation Considering Fractional Vegetation Coverage".REMOTE SENSING 17.4(2025):603. |
入库方式： OAI收割
来源：地理科学与资源研究所
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