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Sophisticated crop classifying method based on combination of object oriented technology and NDVI (normalized difference vegetation index) time series

A time-series, object-oriented technology, applied in the direction of instruments, character and pattern recognition, computer components, etc., can solve the problems of inability to distinguish the types of ground objects, and achieve the effects of weakening the same object and different spectrum, improving accuracy, and eliminating the salt and pepper effect

Inactive Publication Date: 2015-09-30
INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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Problems solved by technology

At present, this method is mainly applied to the classification of single-temporal high-resolution remote sensing images, so it cannot distinguish the types of ground objects with "different objects with the same spectrum"

Method used

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  • Sophisticated crop classifying method based on combination of object oriented technology and NDVI (normalized difference vegetation index) time series
  • Sophisticated crop classifying method based on combination of object oriented technology and NDVI (normalized difference vegetation index) time series
  • Sophisticated crop classifying method based on combination of object oriented technology and NDVI (normalized difference vegetation index) time series

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Embodiment Construction

[0018] Below in conjunction with example the present invention will be further described.

[0019] Step 1: Construction of high spatial resolution NDVI time series. Although the high-resolution images have high spatial resolution, the revisit cycle is long and subject to the influence of clouds, water vapor and other weather, it is difficult to use homologous high-resolution images to construct NDVI time series data. And the medium-resolution multi-spectral CCD camera carried by HJ-1 satellite, its sensor band setting and spatial resolution are basically consistent with Landsat TM, so the present invention has obtained the test area (located in the middle of Bole City, Bortala Mongolian Autonomous Prefecture, Xinjiang) (April to October 2011) 5 scenes of HJ-1 images and 6 scenes of TM images (see Table 1 for the acquisition time of image sequences), after radiometric calibration, atmospheric correction, geometric correction, etc., extract NDVI and construct a 30m -NDVI time s...

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Abstract

The invention discloses a sophisticated crop classifying method based on combination of object oriented technology and NDVI (normalized difference vegetation index) time series. The characteristic that the NDVI time series can reflect crop phenology information is made into full use for realizing crop distinguishing. In addition, the salt-and-pepper effect can be eliminated on the basis of the object oriented technology, precision in sophisticated crop classification is effectively improved, and a new conception is provided for sophisticated crop classification.

Description

technical field [0001] The present invention is a crop remote sensing fine classification technology, which proposes a crop fine classification method based on the combination of object-oriented technology and NDVI time series, fully utilizes the characteristics that NDVI time series can reflect the phenological information of crops, and realizes the distinction of crops. Eliminate the salt and pepper effect based on object-oriented technology, effectively improve the accuracy of fine classification of crops, and provide a new idea for fine classification of crops. Background technique [0002] Information such as crop planting area and yield is an important basis for the country to formulate food planning and economic policies, and timely and accurate grasp of crop planting distribution is the basis for obtaining crop planting area and forecasting production. With the continuous development of remote sensing platforms and the continuous improvement of image resolution, remo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V20/188G06V20/68G06F18/24
Inventor 占玉林郝鹏宇牛铮王力黄妮高帅
Owner INST OF REMOTE SENSING & DIGITAL EARTH CHINESE ACADEMY OF SCI
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