Cotton vegetation index remote sensing detection method based on Sentinel-2 satellite

Abstract

The invention relates to a cotton vegetation index remote sensing detection method based on a Sentinel-2 satellite. The cotton vegetation index remote sensing detection method comprises the followingsteps of acquiring Sentinel-2 satellite remote sensing image data of cotton in different growth stages in a research area; performing radiation correction and atmospheric correction of the remote sensing image data; determining a reflectivity image of the remote sensing image; through distributing Sentinel-2 multispectral satellite data in a plurality of wave bands from visible light to near infrared, obtaining multiple vegetation indices. The method is advantaged in that the Sentinel-2 satellite data has high spatial-temporal resolution and a specific red edge parameter waveband, ideal data sources can be provided for monitoring of different growth stages of cotton, vegetation indexes of different growth stages of cotton can be extracted more accurately and rapidly, the operation processis simple and flexible, detection efficiency is effectively improved, economic cost is low, powerful tool support is provided for timely analysis of physiological parameters of cotton, and the methodhas high application and popularization values.

Description

technical field [0001] The invention relates to the technical field of agricultural remote sensing engineering, in particular to a remote sensing detection method for cotton vegetation index based on Sentinel-2 satellite. Background technique [0002] my country is the largest cotton-producing country in the world. Cotton is the main raw material for making clothes and quilts in my country. Rapid and accurate extraction of cotton planting information is of great significance for mastering the national cotton planting scale, predicting cotton production, and even the economic development of the textile industry. The traditional observation of crop growth period mainly relies on ground survey, which requires a lot of manpower and material resources. Due to its small observation area and long cycle, it cannot reflect the growth and development of crops in real time, which delays the guidance of agricultural production management. Remote sensing technology is a kind of modern in...

AI Technical Summary

Problems solved by technology

However, due to the low time resolution of satellite data, it is easy to cause inaccurate or missed monitoring of the beginning and end of key growth periods of crops, which seriously affects the identification accuracy of growth periods.

To sum up, traditional ground survey methods and wide-spectrum remote sensing technology are used to measure the physical parameters of cotton at different growth stages, not only the accuracy is not high, time-consuming and laborious, but also the applicable area is small, and it cannot monitor the growth status of cotton in a large area in real time.

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