CN111521562A - Cotton vegetation index remote sensing detection method based on Sentinel-2 satellite - Google Patents
Cotton vegetation index remote sensing detection method based on Sentinel-2 satellite Download PDFInfo
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- CN111521562A CN111521562A CN202010197257.6A CN202010197257A CN111521562A CN 111521562 A CN111521562 A CN 111521562A CN 202010197257 A CN202010197257 A CN 202010197257A CN 111521562 A CN111521562 A CN 111521562A
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- 229920000742 Cotton Polymers 0.000 title claims abstract description 39
- 238000001514 detection method Methods 0.000 title claims abstract description 14
- 238000012937 correction Methods 0.000 claims abstract description 20
- 238000002310 reflectometry Methods 0.000 claims abstract description 17
- 238000011160 research Methods 0.000 claims abstract description 10
- 238000000034 method Methods 0.000 claims abstract description 9
- 230000005855 radiation Effects 0.000 claims abstract description 9
- 241000219146 Gossypium Species 0.000 claims description 33
- 238000009826 distribution Methods 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 6
- 238000012952 Resampling Methods 0.000 claims description 5
- 239000002689 soil Substances 0.000 claims description 5
- 230000003750 conditioning effect Effects 0.000 claims description 3
- 238000012544 monitoring process Methods 0.000 abstract description 6
- 238000000605 extraction Methods 0.000 abstract description 2
- 238000005516 engineering process Methods 0.000 description 6
- 238000012271 agricultural production Methods 0.000 description 2
- 238000005034 decoration Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 239000002994 raw material Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 239000004753 textile Substances 0.000 description 1
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/01—Satellite radio beacon positioning systems transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/03—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers
- G01S19/07—Cooperating elements; Interaction or communication between different cooperating elements or between cooperating elements and receivers providing data for correcting measured positioning data, e.g. DGPS [differential GPS] or ionosphere corrections
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N2021/1793—Remote sensing
- G01N2021/1797—Remote sensing in landscape, e.g. crops
Abstract
The invention relates to a remote sensing detection method for cotton vegetation index based on a Sentinel-2 satellite, which comprises the following steps: acquiring Sentinel-2 satellite remote sensing image data of cotton in different growth stages in a research area; carrying out radiation correction and atmospheric correction on the remote sensing image data; determining a reflectivity image of the remote sensing image; the Sentinel-2 multi-spectral satellite data has high space-time resolution and a special red edge parameter band, can provide an ideal data source for monitoring different growth stages of cotton, enables the vegetation index extraction of the different growth stages of the cotton to be more accurate and rapid, has simple and flexible operation process, effectively improves the detection efficiency, has low economic cost, provides a powerful tool support for timely analyzing the physiological parameters of the cotton, and has higher application and popularization values.
Description
Technical Field
The invention relates to the technical field of agricultural remote sensing engineering, in particular to a method for detecting cotton vegetation index by remote sensing based on a Sentinel-2 satellite.
Background
China is the largest world cotton-producing country, cotton is the main raw material for making the clothing and quilt in China, and the quick and accurate extraction of cotton planting information has important significance for mastering the national cotton planting scale, predicting the cotton yield, even for the economic development of the textile industry and the like. The traditional crop growth period observation mainly depends on ground investigation, a large amount of manpower and material resources are consumed, and the growth and development conditions of crops cannot be reflected in real time due to small observation area and long period, so that the guidance of agricultural production management is delayed. The remote sensing technology is one of modern information technologies, can be used as a frontier technology of the modern information technologies, can quickly and accurately collect information of agricultural resources and agricultural production, can realize timing, quantification and positioning of information collection and analysis by combining other modern high and new technologies such as a geographic information system, a global positioning system and the like, has strong objectivity, is not interfered by people, and is convenient for decision making. However, because the satellite data time resolution is low, inaccurate or missed monitoring on the beginning and the end of the critical growth period of the crop is easily caused, and the identification precision of the growth period is seriously influenced. In conclusion, the traditional ground investigation method and the wide-spectrum remote sensing technology are adopted to measure the physical parameters of the cotton in different growth stages, so that the precision is not high, the time and the labor are wasted, the applicable area is small, and the effect of monitoring the growth condition of the cotton in a large area in real time cannot be achieved.
Disclosure of Invention
The invention aims to solve the technical problem of overcoming the defects in the prior art and provides a remote sensing detection method for cotton vegetation index based on a Sentinel-2 satellite.
The invention is realized by the following technical scheme:
a remote sensing detection method for cotton vegetation index based on a Sentinel-2 satellite is characterized by comprising the following steps: acquiring Sentinel-2 satellite remote sensing image data of cotton in different growth stages in a research area according to the distribution characteristics of cotton seedling emergence and growth stopping time in the research area; carrying out radiation correction and atmospheric correction on the remote sensing image data; determining a reflectivity image of the remote sensing image; and performing band combination operation on each band through distribution of the Sentinel-2 multispectral satellite data in a plurality of bands from visible light to near infrared to obtain a plurality of vegetation indexes.
According to the technical scheme, preferably, in the step of performing radiation correction and atmospheric correction on the remote sensing image data, SNAP-Sen2Cor software is used for performing radiation calibration and atmospheric correction.
According to the above technical solution, preferably, the step of determining the reflectivity image of the remote sensing image includes: preprocessing the remote sensing image data; and determining a reflectivity image of the remote sensing image according to the preprocessed remote sensing image data.
According to the above technical solution, preferably, the preprocessing includes resampling, and resampling each waveband after atmospheric correction to a spatial resolution of 10m by a nearest neighbor interpolation method, and using the resampled waveband for extracting reflectivity and calculating a vegetation index in a research area.
According to the above technical solution, preferably, the vegetation index includes a normalized vegetation index, a soil conditioning vegetation index, and an enhanced vegetation index.
The invention has the beneficial effects that:
the Sentinel-2 satellite data has high space-time resolution and a specific red edge parameter waveband, can provide an ideal data source for monitoring different growth stages of cotton, enables vegetation indexes of the cotton in different growth stages to be extracted more accurately and rapidly, is simple and flexible in operation process, effectively improves detection efficiency, is low in economic cost, provides a powerful tool support for timely analyzing physiological parameters of the cotton, and has high application and popularization values.
Drawings
FIG. 1 is a schematic workflow diagram of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings and preferred embodiments.
As shown in the figure, the invention comprises the following steps: according to the distribution characteristics of cotton seedling emergence and growth stopping time in a research area, Sentinel-2 satellite remote sensing image data of cotton in different growth stages in the research area are obtained, the cotton growth period is divided into 5 periods, namely a seedling emergence period, a seedling period, a bud period, a boll period and a boll opening period, wherein the bud period, the flower age period and the boll opening period are more critical periods in the cotton growth period; carrying out radiation correction and atmospheric correction on the remote sensing image data; determining a reflectivity image of the remote sensing image; and performing band combination operation on each band through distribution of the Sentinel-2 multispectral satellite data in a plurality of bands from visible light to near infrared to obtain a plurality of vegetation indexes. The Sentinel-2 satellite data has high space-time resolution and a specific red edge parameter waveband, can provide an ideal data source for monitoring different growth stages of cotton, enables vegetation indexes of the cotton in different growth stages to be extracted more accurately and rapidly, is simple and flexible in operation process, effectively improves detection efficiency, is low in economic cost, provides a powerful tool support for timely analyzing physiological parameters of the cotton, and has high application and popularization values.
According to the above embodiment, preferably, in the step of "performing radiation correction and atmospheric correction on the remote sensing image data", the SNAP-Sen2Cor software is used to perform radiation calibration and atmospheric correction. All remote sensing image data are Level-1C atmospheric upper layer apparent reflectivity which is subjected to radiation correction and geometric correction, and the atmospheric correction is required to be carried out to convert the atmospheric upper layer apparent reflectivity into earth surface reflectivity data.
According to the above embodiment, preferably, the step of determining the reflectivity image of the remote sensing image includes: preprocessing the remote sensing image data, wherein the preprocessing comprises resampling, and each wave band after atmospheric correction is resampled to a spatial resolution of 10m by a nearest neighbor interpolation method and then used for extracting reflectivity and calculating a vegetation index in a research area; and determining a reflectivity image of the remote sensing image according to the preprocessed remote sensing image data.
According to the above embodiments, preferably, the vegetation index includes a normalized vegetation index, a soil conditioning vegetation index, and an enhanced vegetation index. In this example, normalized vegetation index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Enhanced Vegetation Index (EVI) are selected, wherein the normalized vegetation index (NDVI) ═ NIR-RED)/(NIR + RED), the Soil Adjusted Vegetation Index (SAVI) ═ NIR-RED)/(NIR + L) × (1+ L), the Enhanced Vegetation Index (EVI) ═ 2.5 × (NIR-RED)/(NIR +6 × RED-7.5 × BLUE +1), where NIR, RED and BLUE represent Near-infrared band (Near-infrared band), RED band and BLUE band reflectivity, respectively, and L is 0.5.
The Sentinel-2 satellite data has high space-time resolution and a specific red edge parameter waveband, can provide an ideal data source for monitoring different growth stages of cotton, enables vegetation indexes of the cotton in different growth stages to be extracted more accurately and rapidly, is simple and flexible in operation process, effectively improves detection efficiency, is low in economic cost, provides a powerful tool support for timely analyzing physiological parameters of the cotton, and has high application and popularization values.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (5)
1. A remote sensing detection method for cotton vegetation index based on a Sentinel-2 satellite is characterized by comprising the following steps: acquiring Sentinel-2 satellite remote sensing image data of cotton in different growth stages in a research area according to the distribution characteristics of cotton seedling emergence and growth stopping time in the research area; carrying out radiation correction and atmospheric correction on the remote sensing image data; determining a reflectivity image of the remote sensing image; and performing band combination operation on each band through distribution of the Sentinel-2 multispectral satellite data in a plurality of bands from visible light to near infrared to obtain a plurality of vegetation indexes.
2. The remote sensing detection method for cotton vegetation index based on the Sentinel-2 satellite according to claim 1, wherein in the step of performing radiometric calibration and atmospheric calibration on the remote sensing image data, SNAP-Sen2Cor software is used for radiometric calibration and atmospheric calibration.
3. The remote sensing detection method for cotton vegetation index based on the Sentinel-2 satellite according to claim 2, wherein the step of determining the reflectivity image of the remote sensing image comprises the steps of: preprocessing the remote sensing image data; and determining a reflectivity image of the remote sensing image according to the preprocessed remote sensing image data.
4. The remote sensing detection method for cotton vegetation indexes based on the Sentinel-2 satellite according to claim 3, characterized in that the preprocessing comprises resampling, and resampling each wave band after atmospheric correction to a spatial resolution of 10m by a nearest neighbor interpolation method for extracting reflectivity and calculating vegetation indexes in a research area.
5. The remote sensing detection method of cotton vegetation index based on the Sentinel-2 satellite of claim 4, wherein the vegetation index comprises a normalized vegetation index, a soil conditioning vegetation index and an enhanced vegetation index.
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| CN112102312A (en) * | 2020-09-29 | 2020-12-18 | 滁州学院 | Moso bamboo forest remote sensing identification method based on satellite image and phenological difference containing red edge wave band |
| CN113128453A (en) * | 2021-04-30 | 2021-07-16 | 内蒙古工业大学 | Mulching film identification method, system and medium adopting remote sensing time sequence data |
| CN114998742A (en) * | 2022-06-16 | 2022-09-02 | 天津市生态环境科学研究院(天津市环境规划院、天津市低碳发展研究中心) | Method for quickly identifying and extracting rice planting area in single-season rice planting area |
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| CN113128453A (en) * | 2021-04-30 | 2021-07-16 | 内蒙古工业大学 | Mulching film identification method, system and medium adopting remote sensing time sequence data |
| CN114998742A (en) * | 2022-06-16 | 2022-09-02 | 天津市生态环境科学研究院(天津市环境规划院、天津市低碳发展研究中心) | Method for quickly identifying and extracting rice planting area in single-season rice planting area |
| CN114998742B (en) * | 2022-06-16 | 2023-08-18 | 天津市生态环境科学研究院(天津市环境规划院、天津市低碳发展研究中心) | Method for rapidly identifying and extracting rice planting area of single-cropping rice region |
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