Abstract
Leaf area index (LAI) is an important parameter of vegetation ecosystems for crop monitoring and yield estimations. To resolve the ‘saturation phenomenon’ and develop an ideal LAI retrieval model for Chinese satellite HJ-1 CCD data, a hot dark spot (HDS) index method based on multi-angular remote sensing was investigated in this study. Experiments were conducted to obtain in situ measured spectral reflectance and LAI data. An effective vegetation index, HJVI, was put forward according to the unique characteristics of HJ-1 CCD bands. This index alleviated the vegetation index saturation phenomenon based on the ratio of the red bands to near-infrared bands. The canopy HDSs of winter wheat were simulated for different growth stages using the PROSAIL model and the HDS indices were calculated for different bands. The HDS_HJVI was then developed using an HDS of 865 nm, which was the most sensitive to LAI retrieval (R 2 = 0.9953). HDS_HJVI was shown to be more sensitive to LAI than NDVI, HDS_NDVI, and HJVI. Thus, the LAI was retrieved using the HDS_HJVI index model and validated with the measured data (R 2 = 0.8622 and 0.8512, respectively). Overall, these results indicate that the HDS index method based on multi-angular remote sensing is effective and can serve as a reference for other relative quantitative retrieval research.
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Acknowledgments
We would like to acknowledge support from the following projects:
1. Project Name: Study on Urban Green Space Index Retrieval Model based on Airborne LiDAR, China National Natural Science Foundation with Project No. 41471310.
2. Project Name: The retrieval of characteristic parameters based on GF-4 satellite data, China National Key S & T project of High resolution earth observation system with Project No. 11-Y20A05-9001-15/16.
3. Project Name: A study on the validation of soil moisture from passive microwave based on Bayesian maximum entropy method with auxiliary spatial data, China National Natural Science Foundation with Project No. 41501400.
4. Project Name: Passive microwave soil moisture retrieval validation, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences with Youth fund Project No. Y5SJ0600CX.
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Meng, Q., Wang, C., Gu, X. et al. Hot dark spot index method based on multi-angular remote sensing for leaf area index retrieval. Environ Earth Sci 75, 732 (2016). https://doi.org/10.1007/s12665-016-5549-x
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DOI: https://doi.org/10.1007/s12665-016-5549-x