Abstract
Chlorophyll is the most important component of crop photosynthesis, and the reviving stage is an important period during the rapid growth of winter wheat. Therefore, rapid and precise monitoring of chlorophyll content in winter wheat during the reviving stage is of great significance. The satellite-UAV-ground integrated inversion method is an innovative solution. In this study, the core region of the Yellow River Delta (YRD) is used as a study area. Ground measurements data, UAV multispectral and Sentinel-2A multispectral imagery are used as data sources. First, representative plots in the Hekou District were selected as the core test area, and 140 ground sampling points were selected. Based on the measured SPAD values and UAV multispectral images, UAV-based SPAD inversion models were constructed, and the most accurate model was selected. Second, by comparing satellite and UAV imagery, a reflectance correction for satellite imagery was performed. Finally, based on the UAV-based inversion model and satellite imagery after reflectance correction, the inversion results for SPAD values in multi-scale were obtained. The results showed that green, red, red-edge and near-infrared bands were significantly correlated with SPAD values. The modeling precisions of the best inversion model are R2 = 0.926, Root Mean Squared Error (RMSE) = 0.63 and Mean Absolute Error (MAE) = 0.92, and the verification precisions are R2 = 0.934, RMSE = 0.78 and MAE = 0.87. The Sentinel-2A imagery after the reflectance correction has a pronounced inversion effect; the SPAD values in the study area were concentrated between 40 and 60, showing an increasing trend from the eastern coast to the southwest and west, with obvious spatial differences. This study synthesizes the advantages of satellite, UAV and ground methods, and the proposed satellite-UAV-ground integrated inversion method has important implications for real-time, rapid and precision SPAD values collected on multiple scales.
Highlights
Chlorophyll is an important pigment in plant photosynthesis, as its content reveals the ability of a plant to conduct material energy exchange with the external environment, as well as growth status, primary productivity, carbon sequestration ability and nitrogen utilization efficiency, and so on.Chlorophyll is the important index for evaluating crop condition, but it is the indicator of growth and development stage [1,2]
This study synthesizes the advantages of satellite, unmanned aerial vehicle (UAV) and ground methods, and the proposed satellite-UAV-ground integrated inversion method has important implications for real-time, rapid and precision Soil and Plant Analysis Development (SPAD) values collected on multiple scales
The reflectance values of the Bg, Bre Breg and Bnir bands of UAV images are positively correlated with the SPAD values, and the Br band was negatively correlated with SPAD
Summary
Chlorophyll is an important pigment in plant photosynthesis, as its content reveals the ability of a plant to conduct material energy exchange with the external environment, as well as growth status, primary productivity, carbon sequestration ability and nitrogen utilization efficiency, and so on. Chlorophyll is the important index for evaluating crop condition, but it is the indicator of growth and development stage [1,2]. Sensors 2019, 19, 1485 at which point the number of tillers increases by 30–40%. During this period, the chlorophyll content has an important influence on the future growth rate of wheat. The spectral characteristics of chlorophyll are the most important basis for its content detection. The green and red bands have been shown as the most valuable for detecting chlorophyll [3,4]; some studies have identified the near-infrared channel as an effective candidate [3,5]
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