Wheat scab monitoring method based on satellite remote sensing

Abstract

The invention discloses a wheat scab monitoring method based on satellite remote sensing, and belongs to the technical field of remote sensing monitoring, and the method comprises the steps: firstly obtaining the remote sensing data and meteorological rainfall data of a wheat planting region in a predicted year and N years before the predicted year, wherein the remote sensing data comprise multispectral data and thermal infrared remote sensing data; calculating a relative growth vigor index by utilizing the multispectral data; obtaining a normalized surface temperature index by using the multispectral data and the thermal infrared remote sensing data; obtaining a normalized precipitation index by using the meteorological precipitation data; and finally, calculating the wheat scab incidenceindex of the predicted year by utilizing the relative growth vigor index, the normalized earth surface temperature index and the normalized rainfall index. According to the method, the interference of the difference of wheat growth vigor in different areas in large-scale monitoring on the gibberellic disease monitoring model can be well reduced, and the objectivity and practicability of gibberellic disease remote sensing monitoring are improved.

Description

technical field [0001] The invention relates to the technical field of remote sensing monitoring, in particular to a method for monitoring wheat scab based on satellite remote sensing. Background technique [0002] At present, most of the researches on the monitoring of wheat head blight using remote sensing technology are based on the changes reflected in the spectral characteristics of wheat leaves when the disease occurs. Sensitive indicators of scab occurrence to establish relevant estimation models; because the analysis process of sensitive indicators often requires a large amount of leaf spectral analysis data as the basis, and the growth status of wheat in different regional environments and the agro-ecological conditions and diseases that affect wheat growth There are also differences in non-disease factors. Therefore, some remote sensing monitoring models of wheat scab often have problems such as large-scale sample collection and laboratory workload, low timeliness,...

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Problems solved by technology

However, due to the obvious differences in the index characteristics and non-disease factors affecting wheat scab at different regional scales, in addition, the meteorological factors that have a greater impact on scab also mainly consider the relevant indicators reflecting the near-surface atmosphere rather than the surface temperature, especially It is due to the lack of consideration of the precipitation that has a greater impact on scab, so the previous models still have some shortcomings in the monitoring of large areas and the description of agricultural meteorological conditions.

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