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A sugarcane distribution recognition method based on optical remote sensing data

A technology of optical remote sensing and recognition methods, applied in image data processing, character and pattern recognition, image analysis, etc., can solve the problems of land fragmentation, cloud cover, low, interference recognition accuracy, etc., to achieve the benefit of agricultural management and planning Effect

Active Publication Date: 2019-03-22
GUANGZHOU INST OF GEOGRAPHY GUANGDONG ACAD OF SCI
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Problems solved by technology

[0005] Based on this, the purpose of the present invention is to provide a sugarcane distribution recognition method based on optical remote sensing data, which solves the problem of low recognition accuracy caused by land fragmentation and cloud interference, and has the ability to accurately reflect the spatial distribution of sugarcane, which is beneficial Benefits of Sugarcane Management and Planning

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  • A sugarcane distribution recognition method based on optical remote sensing data
  • A sugarcane distribution recognition method based on optical remote sensing data
  • A sugarcane distribution recognition method based on optical remote sensing data

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Embodiment 1

[0076] The following takes the sugarcane distribution identification in Zhanjiang City, Guangdong Province, China as an example to describe in detail:

[0077] 1. Since Zhanjiang City is located in the south of China, the temperature and rainfall are sufficient all year round. Then refer to expert knowledge and according to the phenological information of Zhanjiang local sugarcane, select an appropriate time interval and divide it into 5 phenological stages. Please refer to Table 1.

[0078] Table 1 Sugarcane phenological stages in Zhanjiang City

[0079] seedling stage

From January 1st to March 31st

tillering stage

From April 1st to June 25th

Jointing stage

From June 26th to August 10th

elongation period

From August 11th to November 30th

maturity

From December 1st to December 31st

[0080] 2. Please refer to 5. Use the following formula to synthesize the 5 NDVI maximum images corresponding to the 5 phenological sta...

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Abstract

The invention relates to a sugarcane distribution identification method based on optical remote sensing data, which comprises the following steps: acquiring phenological information of sugarcane and history Sentinel-2 and calculate NDVI for each scene image; According to phenological information, phenological stages are divided and several NDVI maximum images corresponding to each phenological stage are synthesized. Cubic dimensionality reduction of a plurality of NDVI maximum images to one-dimensional images; The gradient operator is used for calculating the gradient for the one-dimensional image to obtain an edge amplitude image; A watershed segmentation algorithm is used to extract the distribution of sugarcane from the edge amplitude image. The sugarcane distribution identification method based on the optical remote sensing data solves the problem of low identification accuracy caused by land fragmentation and cloud disturbance, and has the advantages of accurately reflecting the spatial distribution of sugarcane and being beneficial to sugarcane management and planning.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a sugarcane distribution recognition method based on optical remote sensing data. Background technique [0002] The planting area and spatial distribution of sugarcane is an important parameter for monitoring sugarcane planting information. At present, sugarcane planting area and spatial distribution information still rely on traditional statistical reports or on-site measurements. The whole process takes a lot of time, manpower and material resources, and the obtained agricultural information cannot provide timely and accurate spatial distribution of sugarcane planting. [0003] At present, there have been a lot of research on sugarcane classification by using remote sensing technology, but the existing research has the problem of low accuracy in application. It is mainly affected by the following factors: non-large-scale farmland operations, fragmented ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06T7/00G06T7/13
CPCG06T7/0002G06T7/13G06T2207/10032G06T2207/20152G06T2207/30188G06V20/188
Inventor 姜浩周成虎李丹李勇
Owner GUANGZHOU INST OF GEOGRAPHY GUANGDONG ACAD OF SCI
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