A Remote Sensing Grading Method for Large-scale Crop Growth Condition

A crop and large-scale technology, applied in the field of remote sensing image processing, can solve problems such as irrationality, accuracy problems, and difficulty in ensuring accuracy, and achieve the effects of improving objectivity, reducing monitoring costs, and avoiding phenological changes

Active Publication Date: 2017-09-05
WUHAN HEXUN AGRI INFORMATION TECH
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Problems solved by technology

However, to carry out large-scale monitoring of crop growth, three problems must be solved: (1) Accuracy
Some methods can achieve ideal high precision in small-scale experiments, but it is difficult to guarantee the accuracy in large-scale applications
(2) Speed ​​and efficiency issues
In order to achieve the purpose of real-time monitoring, the growth monitoring method must meet the requirements of fast speed and high efficiency. Therefore, some accurate processing methods suitable for small area applications are not suitable for large-scale operation.
(3) Cost issue
However, this method has the following defects: (1) It does not consider the impact of crop phenology changes
Due to the influence of different meteorological conditions in different years, the growth period of crops may have a large gap, so it is very unreasonable to compare the data of the same period over the years
(2) At present, there is no unified standard for crop growth grading and grading, and the lack of research on grading standards has led to different growth grading results obtained by different institutions

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  • A Remote Sensing Grading Method for Large-scale Crop Growth Condition
  • A Remote Sensing Grading Method for Large-scale Crop Growth Condition

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Embodiment Construction

[0051] Such as figure 1 Shown, the remote sensing rating method of the present invention's large-scale crop growth condition comprises:

[0052] Step 100: Obtain time-series MODIS data, the MODIS data includes quality evaluation parameters, and perform preprocessing to obtain time-series Enhanced Vegetation Index (EVI) data.

[0053]Among them, the present invention mainly adopts the data of a Moderate-resolution Imaging Spectral Imager (MODIS for short) as basic data.

[0054] The present invention uses the enhanced vegetation index (Enhanced Vegetation Index, EVI) as the growth assessment basis. The time-series MODIS data are data obtained from surface albedo (MOD09) or vegetation index (MOD13).

[0055] When the sequential MODIS data is obtained from the surface reflectance, the calculation formula of EVI is divided into two types:

[0056] Normal area, enhanced vegetation index

[0057] Cloud, Snow Covered Areas: Enhanced Vegetation Index

[0058] Among them, G, L...

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Abstract

The invention discloses a remote sensing rating method for the growth of large-scale crops, which includes: A. Obtain MODIS data of time-series resolution imaging spectrometer in the evaluation year, the MODIS data contains quality evaluation information, and perform preprocessing to obtain time-series enhanced vegetation Index EVI data; B, corrected time-series EVI data; C, obtain the time-series EVI data of the comparison year, and analyze the similarity between it and the corrected time-series EVI data, and find the benchmark time-series EVI data for growth evaluation; D, according to the benchmark time-series EVI data, graded evaluation time series EVI data of the specified number of periods in the evaluation year. The invention can adapt to the crop growth monitoring requirements of large-scale and complex planting systems, and can effectively avoid the influence of crop phenological changes and crop planting structure changes compared with the traditional simple historical period comparison method.

Description

technical field [0001] The invention relates to the technical field of remote sensing image processing, in particular to a remote sensing rating method for the growing condition of large-scale crops. Background technique [0002] Crops are related to the national economy and people's livelihood, and it is more important to grasp the crop growth situation as early as possible during the crop growth period than to accurately estimate the crop planting area and total output itself. [0003] Remote sensing technology is often used in large-scale crop growth monitoring because of its fast acquisition of surface information, wide coverage, short cycle, and strong real-time performance. But to carry out large-scale crop growth monitoring must solve three problems: (1) Accuracy problem. Some methods can achieve ideal high precision in small-scale experiments, but it is difficult to guarantee the accuracy in large-scale applications. (2) Speed ​​and efficiency issues. The cultivat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/06G06Q50/02
Inventor 陈康
Owner WUHAN HEXUN AGRI INFORMATION TECH
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