Leaf chlorophyll content estimation from sentinel-2 MSI data

Ma, Qingmiao; Chen, Jing M.; Li, Yingjie; Croft, Holly; Luo, Xiangzhong; Zheng, Ting; Zamaria, Sophia

doi:10.1109/igarss.2017.8127608

Cited by 2 publications

(1 citation statement)

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“…However, downscaling the canopy reflectance to leaf level reflectance based on their relationship and retrieval using leaf RTMs such as PROSPECT may result in a stronger relationship between the estimated and measured leaf chlorophyll. As such, Ma et al (2017) reported a similar error (RMSE = 8.82) and a higher R 2 (R 2 = 0.59) while predicting leaf chlorophyll from Sentinel-2 data of a mixed temperate forest by downscaling the canopy reflectance to leaf reflectance based on 4-Scale and PROSPECT models. Further, the reasonable retrieval accuracy of foliar chlorophyll is attributed to the large size of LUTs in this study (500,000 records), which allowed for proper sample selection.…”

Section: Discussionmentioning

confidence: 66%

Mapping leaf chlorophyll content from Sentinel-2 and RapidEye data in spruce stands using the invertible forest reflectance model

Darvishzadeh

Skidmore

Abdullah

et al. 2019

International Journal of Applied Earth Observation and Geoinfor

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Leaf chlorophyll plays an essential role in controlling photosynthesis, physiological activities and forest health. In this study, the performance of Sentinel-2 and RapidEye satellite data and the Invertible Forest Reflectance Model (INFORM) radiative transfer model (RTM) for retrieving and mapping of leaf chlorophyll content in the Norway spruce (Picea abies) stands of a temperate forest was evaluated. Biochemical properties of leaf samples as well as stand structural characteristics were collected in two subsequent field campaigns during July 2015 and 2016 in the Bavarian Forest National Park (BFNP), Germany, parallel with the timing of the RapidEye and Sentinel-2 images. Leaf chlorophyll was measured both destructively and nondestructively using wet chemical spectrophotometry analysis and a hand-held chlorophyll content meter. The INFORM was utilised in the forward mode to generate two lookup tables (LUTs) in the spectral band settings of RapidEye and Sentinel-2 data using information obtained from the field campaigns. Before generating the LUTs, the sensitivity of the model input parameters to the spectral data from RapidEye and Sentinel-2 were examined. The canopy reflectance of the studied plots were obtained from the satellite images and used as input for the inversion of LUTs. The coefficient of determination (R 2), root mean square errors (RMSE), and the normalised root mean square errors (NRMSE), between the retrieved and measured leaf chlorophyll, were then used to examine the attained results from RapidEye and Sentinel-2 data, respectively. The use of multiple solutions and spectral subsets for the inversion process were further investigated to enhance the retrieval accuracy of foliar chlorophyll. The result of the sensitivity analysis demonstrated that the simulated canopy reflectance of Sentinel-2 is sensitive to the alternation of all INFORM input parameters, while the simulated canopy reflectance from RapidEye did not show sensitivity to leaf water content variations. In general, there was agreement between the simulated and measured reflectance spectra from RapidEye and Sentinel-2, particularly in the visible and red-edge regions. However, examining the average absolute error from the simulated and measured reflectance revealed a large discrepancy in spectral bands around the near-infrared shoulder. The relationship between retrieved and measured leaf chlorophyll content from the Sentinel-2 data had a higher coefficient of determination with a higher NRMSE (NRMSE = 0.36 μg/cm 2 , R 2 = 0.45) compared to those obtained using the RapidEye data (NRMSE = 0.31 μg/ cm 2 and R 2 = 0.39). Using the mean of the ten best solutions (retrieved chlorophyll) the retrieval error for both Sentinel-2 and RapidEye data decreased (NRMSE = 0.34, NRMSE = 0.26, respectively), as compared to only selecting the single best solution. When the Sentinel-2 red edge bands were used as the spectral subset, the retrieval error of leaf chlorophyll decreased indicating the importance of red edge, as well as properly located spec...

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Section: Discussionmentioning

confidence: 66%