Crop drawing method using Sentinel-2 time sequence image data

Abstract

The invention relates to a crop drawing method using Sentinel-2 time sequence image data. The method comprises the following steps: firstly, carrying out wave band selection and cloud mask pretreatment on an image in a research area, then generating an image data set synthesized according to corn growth stages according to a corn growth phenology law, calculating a normalized vegetation index and a normalized moisture index, adding the normalized vegetation index and the normalized moisture index into wave bands of the image, and then creating sample points of the research area; and forming a sample pair with the image data set at the corresponding position, training the classification model by using a random forest algorithm, finally obtaining a distribution diagram of the corn in the research area by using the trained classification model, and performing pixel-by-pixel summary statistics to obtain the corn planting area in the research area. According to the method, a GoogleEarthEngine cloud platform is utilized to realize storage and calculation of a large amount of data, a method of performing median synthesis according to growth stages is designed to reduce the influence caused by cloud pollution to the greatest extent, and finally, fine mapping and area monitoring of corn are quickly realized.

Description

technical field [0001] The invention belongs to the technical field of agricultural remote sensing, and in particular relates to a crop mapping method using Sentinel-2 time series image data. Background technique [0002] my country is a large agricultural country. As one of the most important food crops, corn is not only crucial to ensuring national food security, but also the corn stalks produced after harvesting are also an important biomass resource. In the context of global warming, the reduction of carbon emissions has been brought to an unprecedented height by our country. The use of corn stalks for biomass power generation is very important for replacing or partially replacing fossil energy, protecting the ecological environment, and realizing the sustainable development of human society. important practical and long-term significance. However, there is still a lack of understanding of the reserves and distribution of corn stalks. The use of remote sensing technolog...

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Problems solved by technology

[0004] In fact, no matter which data source is used, the existence of clouds and fog will seriously affect the imaging quality of remote sensing images, resulting in the failure of crop targets to be recorded by satellites, which seriously limits the practical application of satellite imagery for crop mapping

On the other hand, due to the higher resolution of Sentinel-2 remote sensing data and the shorter revisit period, in order to make full use of the information of each pixel, it is bound to bring a huge amount of data, which has a great impact on data storage, call and calculation. come to great challenge

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