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| Content Provider | IET Digital Library |
|---|---|
| Author | Wang, Chao Bian, Changlin Xing, Hongyan Zhang, Xuehong Shen, Yi |
| Abstract | Vegetation chlorophyll content is very important for monitoring the growth and health status of vegetation. Remote sensing of chlorophyll content holds an important potential for evaluating crop growth status and diseases and insects. The both units can represent the chlorophyll content of leaves, but there are some differences between them. The former reflects the proportion of chlorophyll in the leaf components, while the latter displays the weight of chlorophyll in the unit leaf area. Combining ten representative hyperspectral vegetation indices, the effect of measurement units on estimating crop leaf chlorophyll content was studied with winter wheat and summer corn leaf chlorophyll content data and leaf reflectance data. First, the relationships between leaf chlorophyll content and the ten selected hyperspectral vegetation indices were analyzed. Second, the estimating models of leaf chlorophyll were built. Finally, the accuracies of estimating models were also assessed based on the validating data. The results show that: (i) due to chlorophyll absorption effect at visible bands, vegetation indices were highly correlated with chlorophyll content of crop leaves and it is feasible to estimate chlorophyll with vegetation index, for example, the relative errors for the estimating model based on MERIS Terrestrial Chlorophyll Index <14%; (ii) The different measurement units of leaf chlorophyll content can give rise to differences in estimating accuracy. Measurement units of mg g−1 and μg cm−2 can both effectively describe chlorophyll content of vegetation leaves. However, the leaf chlorophyll models based on the former were generally superior to the latter. For instance, the relative errors of summer corn for measurement units of mg g−1 and μg cm−2 are 7.6 and 13.6%, respectively. The reflectance signals of leaves at visible and near infrared regions contain various absorption information on leaf components, especially for pigments. Moreover, the measurement unit of mg g−1 reflects the relative content of chlorophyll in the leaf components. Therefore, the unit of mg g−1 is in agreement with the reflectance signals of leaves. However, the unit of μg cm−2 only represents the absolute weight of chlorophyll in the unit leaf area. Therefore, it is recommended that the measurement unit of mg g−1 should be used as far as possible when estimating chlorophyll of crop leaves or other vegetation leaves with remote sensing. |
| Starting Page | 8627 |
| Ending Page | 8631 |
| Page Count | 5 |
| Volume Number | 2019 |
| e-ISSN | 20513305 |
| Issue Number | Issue 23, Dec (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/2019/23 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.9070 |
| Journal | The Journal of Engineering |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2019-03-25 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution-Non Commercial-No Derivs License (http://creativecommons.org/licenses/by-nc-nd/3.0/) |
| Subject Keyword | Agriculture Crop Leaf Chlorophyll Content Crop Leaves Crops Data And Information; Acquisition, Processing, Storage And Dissemination in Geophysics Different Measurement Units Diseases Earth Sciences Estimating Chlorophyll Estimating Model Geophysical Technique And Equipment Instrumentation And Technique For Geophysical, Hydrospheric And Lower Atmosphere Research Leaf Chlorophyll Model Leaf Component Leaf Reflectance Data Measure Units Measurement Unit MERIS Terrestrial Chlorophyll Index Reflectivity Relative Content Remote Sensing Representative Hyperspectral Vegetation Indices Selected Hyperspectral Vegetation Indices Solid Earth Physics Summer Corn Leaf Chlorophyll Content Data Unit Leaf Area Vegetation Vegetation Chlorophyll Content Vegetation Leaves Vegetation Mapping |
| Content Type | Text |
| Resource Type | Article |
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