Remote sensing image-based farmland health state prediction method, apparatus and device, and storage medium

Abstract

The embodiment of the invention discloses a remote sensing image-based farmland health state prediction method and device, equipment and a storage medium. The method comprises the following steps: acquiring health state labeling data and satellite remote sensing image data of crops in a preset area in the same preset period; the satellite remote sensing image data comprises a plurality of pixels, and each pixel corresponds to one piece of remote sensing index state data; acquiring historical vegetation index data of a preset area, and determining a vegetation index state vector corresponding to each pixel in combination with the current satellite remote sensing image data; training the health state labeling data and the remote sensing index state data corresponding to each pixel through a hidden Markov model to obtain a parameter set corresponding to each pixel; and according to the parameter set corresponding to each pixel and the vegetation index state vector, determining a health state corresponding to each pixel crop in the current preset area. The intelligent prediction of the health state of agricultural crops in a certain area is realized, and the prediction accuracy and efficiency are improved.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of agricultural prevention and control management, and in particular to a method, device, equipment and storage medium for predicting the health status of agricultural land based on remote sensing images. Background technique [0002] In the process of agricultural production, the health of farmland directly affects the quality of agricultural production. For example, once crops are affected by pests and diseases, their growth status and harvest will be directly affected, which in turn will affect farmers' economic income. Therefore, it is necessary to predict the health status of crops, so as to intervene in time when problems occur, and prevent the health status from further deteriorating, resulting in reduced production and income. [0003] Existing forecasting methods mainly rely on manual investigation, experimentation, and empirical forecasting. The forecasting period is long...

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Problems solved by technology

[0003] Existing forecasting methods mainly rely on manual investigation, experimentation, and empirical forecasting. The forecasting period is long, the labor cost is relatively high, and the accuracy of forecasting cannot be guaranteed; especially when large-scale crop planting areas When there is a long-term and large-scale impact caused by pests and diseases, the disadvantages of on-site investigation such as long time-consuming and labor-intensive are particularly obvious

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