Abstract
Leaf chlorophyll content is an important indicator of crop growth. In coal mine areas with high phreatic level, crop damage caused by coal mining subsidence will inevitably lead to changes in leaf chlorophyll content. Therefore, accurate estimation of the chlorophyll content of winter wheat in subsidence areas of coal mines with high phreatic level can effectively identify the extent of cultivated land damage. In this study, based on the high-resolution unmanned aerial vehicle (UAV) visible-band image and ground sampling data obtained in April 2018, the chlorophyll estimation model of winter wheat in the subsidence area was established. By comparing and analyzing the spectral characteristics of the ground features in 3 visible-bands, the visible-band vegetation index suitable for estimate wheat chlorophyll content is selected for inversion. The results show that the accuracy of the single index, single variable estimation model is relatively low. Owing to the absence of multicollinearity, the proposed multivariate model-combined visible-band vegetation index (CVVI) based on combination index 2 (COM2), visible-band difference vegetation index (VDVI) and red–green–blue vegetation index (RGBVI) has high inversion accuracy. The reliability and effectiveness of the CVVI estimation model are verified by samples. The coefficient of determination (R2), the root mean square error (RMSE) and the normalized root mean square error (NRMSE) are 0.639, 1.750 and 0.196, respectively. This indicates that the estimation model is relatively stable. A chlorophyll map is developed based on estimation using the proposed model. According to the results, the overall chlorophyll content of wheat in the subsidence area is relatively low and chlorophyll is mainly concentrated in 22–44 SPAD (soil and plant analyzer development), which accounts for 80.1% of the cultivated land area. This study indicates that the wheat in the study area is affected by coal mining disturbances to varying extents. The formation of slope land and stagnant water areas reduces the productivity of cultivated land and leads to severe damages on cultivated land. This study provides a methodology for estimations of growth index of crops in the subsidence area of coal mine with high phreatic level.
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We would like to thank TopEdit (www.topeditsci.com) for English language editing of this manuscript.
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This paper was supported by the National Natural Science Foundation of China [No. 41771324; 41807004; 41907399].
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Hu, X., Niu, B., Li, X. et al. Unmanned aerial vehicle (UAV) remote sensing estimation of wheat chlorophyll in subsidence area of coal mine with high phreatic level. Earth Sci Inform 14, 2171–2181 (2021). https://doi.org/10.1007/s12145-021-00676-5
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DOI: https://doi.org/10.1007/s12145-021-00676-5