Grassland Chlorophyll Content Estimation from Drone Hyperspectral Images Combined with Fractional-Order Derivative
文献类型：期刊论文
| 作者 | Zhang, Aiwu1,2; Yin, Shengnan1,2; Wang, Juan1,2; He, Nianpeng3; Chai, Shatuo4; Pang, Haiyang5 |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 15期号:23页码:18 |
| 关键词 | grassland hyperspectrum fractional-order derivative chlorophyll content |
| DOI | 10.3390/rs15235623 |
| 通讯作者 | Zhang, Aiwu(zhangaiwu@cnu.edu.cn) |
| 英文摘要 | Chlorophyll plays a critical role in assessing the photosynthetic capacity and health of grasslands. However, existing studies on the hyperspectral inversion of chlorophyll have mainly focused on field crops, leading to limited accuracy when applied to natural grasslands due to their complex canopy structures and species diversity. This study aims to address this challenge by extrapolating the measured leaf chlorophyll to the canopy level using the green vegetation coverage approach. Additionally, fractional-order derivative (FOD) methods are employed to enhance the sensitivity of hyperspectral data to chlorophyll. Several FOD spectral indices are developed to minimize interference from factors such as bare soil and hay, resulting in improved chlorophyll estimation accuracy. The study utilizes partial least squares regression (PLSR) and support vector machine regression (SVR) to construct inversion models based on full-band FOD, two-band FOD spectral indices, and their combination. Through comparative analysis, the optimal model for estimating grassland chlorophyll content is determined, yielding an R2 value of 0.808, RMSE value of 1.720, and RPD value of 2.347. |
| WOS关键词 | REMOTE ESTIMATION ; INDEXES ; BANDS ; CROP |
| 资助项目 | Science and Technology Program of Qinghai Province of China |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:001116236000001 |
| 出版者 | MDPI |
| 资助机构 | Science and Technology Program of Qinghai Province of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/201858]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhang, Aiwu |
| 作者单位 | 1.Capital Normal Univ, Key Lab Informat Acquisit & Applicat 3D, Minist Educ, Beijing 100048, Peoples R China 2.Capital Normal Univ, Engn Res Ctr Spatial Informat Technol, Minist Educ, Beijing 100048, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Beijing 100101, Peoples R China 4.Qinghai Univ, Acad Anim Sci & Vet Med, Xining 810016, Peoples R China 5.Dezhou Univ, Sch Ecol Resources & Environm, Dezhou 253023, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zhang, Aiwu,Yin, Shengnan,Wang, Juan,et al. Grassland Chlorophyll Content Estimation from Drone Hyperspectral Images Combined with Fractional-Order Derivative[J]. REMOTE SENSING,2023,15(23):18. |
| APA | Zhang, Aiwu,Yin, Shengnan,Wang, Juan,He, Nianpeng,Chai, Shatuo,&Pang, Haiyang.(2023).Grassland Chlorophyll Content Estimation from Drone Hyperspectral Images Combined with Fractional-Order Derivative.REMOTE SENSING,15(23),18. |
| MLA | Zhang, Aiwu,et al."Grassland Chlorophyll Content Estimation from Drone Hyperspectral Images Combined with Fractional-Order Derivative".REMOTE SENSING 15.23(2023):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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