Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A decision tree classification method for middle rice information based on feature extraction from multi-temporal data

A decision tree classification and feature extraction technology, applied in the field of surveying, mapping and remote sensing, can solve the problems of negative impact on image quality, difficult imagery, long revisit cycle of TM image data, etc., to achieve high efficiency and improve accuracy.

Active Publication Date: 2019-01-15
武汉珈和科技有限公司
View PDF4 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the revisit cycle of TM image data is long, and it is difficult to obtain TM time-series images of rice in different periods, especially cloudy and rainy weather can easily have a negative impact on image quality

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A decision tree classification method for middle rice information based on feature extraction from multi-temporal data
  • A decision tree classification method for middle rice information based on feature extraction from multi-temporal data
  • A decision tree classification method for middle rice information based on feature extraction from multi-temporal data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0020] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention and are not intended to limit the invention.

[0021] The embodiment of the present invention provides a kind of mid-season rice information decision tree classification method based on feature extraction in multi-temporal data, such as figure 1 and figure 2 As shown, the described middle rice information decision tree classification method based on feature extraction in multi-temporal data comprises the following steps:

[0022] S1. Obtain the Gaofen-1 image data in different phases in the corresponding area, and perform radiation calibration preprocessing and atmospheric correction preprocessing on the Gaofen-1 image data respe...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

According to the middle rice information decision tree classification method based on feature extraction in multi-temporal data in the present invention, the Gaofen-1 image data selected by it has the advantages of high spatial resolution and high temporal resolution. On this basis, the present invention It not only uses a variety of characteristic parameters used in the extraction of rice distribution from single-temporal images, but also combines the advantages of time-series analysis of multi-temporal images to organically combine multi-parameters and multi-temporal phases, and extract The distribution of middle rice. A variety of characteristic parameters can better eliminate non-target features. Multi-temporal analysis can help to eliminate misclassified features caused by foreign objects with the same spectrum, and can further extract target features. Decision tree classification is flexible, intuitive, and Features such as high efficiency. Therefore, combining these advantages can further improve the accuracy of mid-season rice extraction, which is of positive significance to both the national food security system and the commercial application of remote sensing in agriculture.

Description

technical field [0001] The invention relates to the field of surveying and mapping remote sensing, in particular to a middle rice information decision tree classification method based on feature extraction from multi-temporal data. Background technique [0002] Rice is one of the world's three major food crops, and its sown area accounts for 15% of the world's total arable land. my country is the world's largest rice producer, with a vast area of ​​rice cultivation, ranging from Hainan Province in the south, to Heilongjiang Province in the north, to Taiwan Province in the east, and to the Xinjiang Uygur Autonomous Region in the west. Different regions have different climates, and the varieties of rice planted are also different. According to the planting time, it can be divided into three categories: early rice, middle rice, and late rice. Different regions have different growth periods for early rice, middle rice, and late rice. Taking Hubei Province as an example, double...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06F18/24323
Inventor 彭凯冷伟周学林
Owner 武汉珈和科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products