[go: up one dir, main page]

WO2020165671A1 - Procédé de surveillance de couvertures de sol de végétation - Google Patents

Procédé de surveillance de couvertures de sol de végétation Download PDF

Info

Publication number
WO2020165671A1
WO2020165671A1 PCT/IB2020/050671 IB2020050671W WO2020165671A1 WO 2020165671 A1 WO2020165671 A1 WO 2020165671A1 IB 2020050671 W IB2020050671 W IB 2020050671W WO 2020165671 A1 WO2020165671 A1 WO 2020165671A1
Authority
WO
WIPO (PCT)
Prior art keywords
series
pixel
led
spectral
values
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/IB2020/050671
Other languages
English (en)
Inventor
Antonio MOTISI
Santo ORLANDO
Mario MINACAPILLI
Mauro SARNO
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Universita degli Studi di Palermo
Original Assignee
Universita degli Studi di Palermo
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Universita degli Studi di Palermo filed Critical Universita degli Studi di Palermo
Publication of WO2020165671A1 publication Critical patent/WO2020165671A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • 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
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/251—Colorimeters; Construction thereof
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J1/00—Photometry, e.g. photographic exposure meter
    • G01J1/02—Details
    • G01J1/04—Optical or mechanical part supplementary adjustable parts
    • G01J1/0407—Optical elements not provided otherwise, e.g. manifolds, windows, holograms, gratings
    • G01J1/0414—Optical elements not provided otherwise, e.g. manifolds, windows, holograms, gratings using plane or convex mirrors, parallel phase plates, or plane beam-splitters
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/0205—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows
    • G01J3/021—Optical elements not provided otherwise, e.g. optical manifolds, diffusers, windows using plane or convex mirrors, parallel phase plates, or particular reflectors
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/2803—Investigating the spectrum using photoelectric array detector
    • 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
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/10—Arrangements of light sources specially adapted for spectrometry or colorimetry
    • G01J2003/102—Plural sources
    • G01J2003/104—Monochromatic plural sources
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/02—Details
    • G01J3/10—Arrangements of light sources specially adapted for spectrometry or colorimetry
    • G01J2003/102—Plural sources
    • G01J2003/106—Plural sources the two sources being alternating or selectable, e.g. in two ranges or line:continuum
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colours
    • G01J3/28—Investigating the spectrum
    • G01J3/2803—Investigating the spectrum using photoelectric array detector
    • G01J2003/2816—Semiconductor laminate layer
    • 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
    • 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
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
    • 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
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3181—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths using LEDs
    • 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
    • G01N21/84—Systems specially adapted for particular applications
    • G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/06—Illumination; Optics
    • G01N2201/062—LED's
    • G01N2201/0627—Use of several LED's for spectral resolution
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods

Definitions

  • the present invention refers to the field of environmental diagnostics since discloses a method for monitoring of the physiological state of turfgrass which can be used for the accurate characterization and management of plant coverings such as sports fields, natural green areas or artificial greens.
  • spectral signature i.e. the quantification of the radiometric behavior of a surface, generally expressed in terms of percentage of radiant energy (sunlight or artificial light) that is reflected from a surface at different wavelengths of the electromagnetic spectrum ranging (bands) from visible (VIS) to shortwave infrared (SWIR) regions.
  • This percentage called reflectance, can be considered as a unique signature of the observed surface, under the same own and intrinsic conditions, such as humidity, organic content, mineralogical composition of the soil and water state, chlorophyll content and leaf structure of the vegetation, .
  • the spectral signature of vegetation depends on the presence of chlorophyll pigments, which absorb light radiation near the wavelengths of 450 nm (blue) and 650 (red) nm and partially reflect the green radiation (wavelength 550 nm) .
  • leaf structure influences the spectral behavior in the near infrared (NIR) bands, between 700 and 1350 nm, and cause a very high reflection, around 50-70%, of incident energy, whereas the leaf water content is responsible for absorption in the short-wave infrared domain (SWIR) , between 1350 and 2200 nm, which is evidenced in the spectrum by the so-called "absorption holes", around 1400 and 1900 nm (Gomarasca M. , 1997. Introduée a telerilevamento e GIS per la
  • Vegetation Indices (Vis), using specific and characteristic values of the spectral signature, allow to express by numbers certain physiologic states of vegetation.
  • NDVI Normalized Difference Vegetation Index
  • the NDVI index assumes a value between 0 and 1 1973. Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation. Prog. Rep. RSC 1978-1, Remote Sensing Center, Texas A&M Univ., College Station, 93p. NTIS No. E73-106393) and is able to indirectly estimate physiologic parameters such as the leaf area index (LAI), the ground covering factor (Fc, Fraction Cover) and crop coefficients (Kc, Crop Index) .
  • LAI leaf area index
  • Fc ground covering factor
  • Kc Crop Index
  • radiometric indices are for example the EVI index (Enhanced Vegetation Index) , the SAVI index (Soil Adjusted Vegetation Index) , the green GI index (Green Index) .
  • these other indices are based on simple algebraic combinations of spectral reflectance in the VIS-NIR domain .
  • passive systems systems based on the measurement of the reflection of solar radiation from the observed surface are classified as passive systems.
  • the measurement obtainable from passive systems should take into account the time and atmospheric changes of incident solar radiation which must correct.
  • Passive systems include handheld instruments without image acquisition for the estimation of chlorophyll or of a unique vegetation index (FieldScout CM1000, Spectrum Technologies, inc.), systems based on image acquisition using only the green spectral band (FieldScout Greenlndex +, Spectrum Technologies, inc.), systems based on multispectral digital cameras that acquire images in natural lighting conditions (Tetracam ADC, Tetracam inc.), generally installed on remote platforms such as drones, balloons and kites.
  • active systems use an own light source with a defined and constant radiant flux.
  • the measurement obtained by the active systems does not require corrections due to the variability of the light source and allows to obtain calibration of reflectance values being independent from the condition at the time of the measurement.
  • the accuracy of the measurements depends on specific internal calibrations of sensors to transform the measured signal into a spectral reflectance value and / or vegetation index.
  • passive sensors both spot- based or image-based are generally internally calibrated to give yield NDVI values, without giving imagines that evidence of NDVI of the observed surface.
  • the above disclosed system does not give any information in the infrared, and allows to distinguish, within the images, of the percentage of soil which is covered by vegetation (fraction cover) .
  • the method proposed in the present invention allows to calculate the most suitable vegetation indices for monitoring vegetation cover, allows to obtain radiometrically correct output data, allows monitoring the physiological status of natural vegetation cover and turf surfaces to identify abnormal conditions or phytopathies in any environmental and lighting conditions, therefore, in laboratory and in the open field conditions and without the need of complex calibration procedures, therefore exceeding the limits of the systems known in the art .
  • a) positioning of a device for measuring the spectral reflectance of vegetable surfaces consisting of a multispectral camera operating in the visible and infrared spectral regions comprising a chamber, externally covered with shielding and optically reflective material and internally of white color, having an opened outlet wall and an opposite inlet wall accommodating a night vision camera and sets of white LEDs and monoband LEDs in the spectral regions of red, green, blue and near infrared, disposed on inclined planes., resting of the surface of a vegetation ground cover to be monitored
  • step d) Calculation of vegetation indices; wherein in step d) specific corrective masks are used; predetermined during the preparation and calibration of the device, by capturing images for any spectral band red R, green G, blue B and infrared IR on a flat and homogeneous reference surface, evaluation of the variability of the digital number values for each reference image acquired along the main and diagonal axes of the same image and verification of the radial vignetting effect, calculating for each wavelength of the devignetting mask, obtained by calculating for each pixel the DDN ratio between the digital number value in the central area of the image and the DN value of the considered pixel, and are used further cropping image masks which remove the border pixels affected by optical aberrations from each wavelength that cannot be corrected during the devignetting phase.
  • Figure 1 shows a longitudinal section of the device proposed in the method of the present invention.
  • Figure 2 shows the details of the internal surface of the device where the camera and LEDs are placed.
  • FIG. 3 shows a flowchart which summarizes the method of the present invention.
  • Figure 4 shows the graphs whit the frequency histograms and the statistical values obtained from images of NDVI measured in three different parcels P1, P2 and P3.
  • Figure 5 shows the reflectance spectral signatures measured in the plots P1, P2 and P3 with a spectroradiometer working in the VIS-NIR domain (300 and 900nm) in the plots P1, P2 and P3 (box A) ; in box B the comparison between the values of NDVI measured with the device over different turfs and those obtained from the corresponding spectral signatures measured with a spectroradiometer are plotted.
  • Figure 6 shows the trend of NDVI values measured with the device over different turfs respect to the seeding density and subjected or not to fertilization.
  • spectral reflectance means the percentage of radiant energy reflected relative to the incident radiation (solar or artificial light) at different wavelengths .
  • vegetation ground cover means the community of grass plants that covers a soil surface such as sports fields, golf courses (turfgrass) , recreational and aesthetic purposes areas (lawn), natural and cultivated pastures.
  • shielding and optically reflective material means a material of limited thickness but sufficient to ensure the opacity of the chamber surfaces to the solar radiation, for example a metal foil, preferably aluminium.
  • NDVI Normalized Difference Vegetation Index
  • Enhanced Vegetation Index means the index that expresses the physiological state of vegetation ground cover
  • Green Index, (GI) means the index expressing the rate of chlorophyll pigments on the vegetation ground cover
  • Green Leaf Index means the index related to the rate of chlorophyll pigments on the leaf surface
  • Visible Atmosperically Resistant Index means the index indicating the physiological state of vegetation
  • pixel means the elementary unit that constitutes a digital image (array of pixels) .
  • digital number values means the numeric value related to each pixel.
  • geometric resolution means the number of pixels that constitutes a digital image and it is expressed as the number of rows by number of columns.
  • system setup means executing a set of image-processing procedures to be performed in laboratory conditions in order to define a set of numerical values of the parameters to be used in acquisition phase.
  • multispectral camera means a device able to provide digital images constituted by pixels associated with values of spectral Reflectance for different wavelength .
  • mask means a digital image generated during the system setup having the same geometric resolution of the images captured by the device, wherein the numerical values associated to each pixel have been determined to correct the geometric and radiometric aberrations by means of mathematical functions between the correspondent pixel of the mask and those of captured images to be corrected.
  • vignetting effect means radially gradual reduction of the brightness of the image in peripheral pixel versus those in the central area.
  • devignetting means the procedure to correct DN values of the obtained image to nullify the vignetting effect by applying a predetermined corrective mask suitably computed during the system setup.
  • cropping means the procedure that removes peripheral parts of the acquired images; wherein the peripheral parts consist of a number of pixels determined during the system setup procedure and generally affected by optical aberrations.
  • radiometric correction or reflectance spectral calibration means a procedure that, for each spectral band, R Red, G Green, B Blue and IR Infrared, transforms the DN values of each pixel of the acquired images in spectral reflectance values by means of a corrective mask appropriately obtained during system setup.
  • the present invention refers to a method for monitoring vegetation ground covers comprising the following steps: a) positioning of a device 1 for measuring the spectral reflectance of vegetated surfaces comprising a chamber 2 endowed with a inlet wall 3 an opened outlet wall 4 and side walls 6 with external surfaces coated with a shielding and optically reflective material and internal surfaces of withe color wherein in the central area of the inlet wall is fixed a night vision camera 8 operating in the spectral range between 400 and 800 nm and with a geometric resolution of not less than 1296x972 pixels, to which are laterally placed two symmetric plates 10, 11 inclined with respect to the perpendicular of the input direction of an angle a comprised between 25 and 35 degrees having on the surfaces 12,13 facing the inlet wall a led lighting system consisting of: at least one white light led or a series thereof, arranged in series or in parallel, emitting in the range of wavelength comprised between 400 and 800 nm; at least one led or a series thereof, arranged in series
  • R GREEN + R RED R BLUE where R NIR is the image which stores, for each pixel, the reflectance values in the IR band obtained at point e) .
  • R RED is the image which stores, for each pixel, the reflectance values in the R band obtained at the point e) .
  • R GREEN is the image which stores, for each pixel, the reflectance values in the G band obtained at point e for each pixel.
  • R BLUE is the image which stores, for each pixel, the reflectance values in the B band obtained at the point a) .
  • step d) specific corrective image masks are used, which are predetermined during the set up of the device, by capturing images for each spectral band , red R, green G, blue B and infrared IR on a flat and homogeneous control surface, variability analysis of digital number values along the main and diagonal axes thereof for each control images obtained along the main and diagonal axes thereof and confirmation of the radial symmetry of the vignetting effect, evaluation for each wavelength of the vignetting mask by calculating for each pixel the ratio DDN between the digital number valuein the central area of the image and the value of DN of the pixel thereof, and are used additional cropping corrective masks which remove for each wavelength the peripheral area of pixel with optica abberration not corrected during devignetting .
  • step a) the at least one or a series of LEDs, arranged in series or parallel, emitting in the wavelength range between 400 and 800 nm, are white light LEDs;
  • step a) the at least one or a series of LEDs, arranged in series or parallel, with peak emission at 460 nm and Full Width at Half Maximum FWHM of 20 are monochrome blue-light LEDs;
  • step a) the at least one or a series of LEDs, arranged in series or parallel, with peak emission at 520 nm and Width at Half Maximum FWHM of 20 are monochrome green-light LEDs;
  • step a) the at least one or a series of LEDs, arranged in series or parallel, with peak emission at 630 nm and Width at Half Maximum FWHM of 20 are monochrome red-light LEDs;
  • step a) the at least one or a series of LEDs, arranged in series or parallel, with peak emission at 830 nm and Width at Half Maximum FWHM of 30 are monochrome infrared LEDs; in step a) , nearby to the night vision video camera 8, is also present a through hole 9 which allows to optionally house an optical fiber of a spectroradiometer . Said optical fiber is used for optional periodic calibration checks on the radiative flux emitted by the LEDs system.
  • the device can further comprise suitable power supply means for the individual LEDs from i) to v) and for the night vision camera .
  • the device can further comprise suitable connecting means to a data acquisition and storage system.
  • step a) the angle a is preferably equal to 30 degrees.
  • the flat and homogeneous control surface can be commercially available (Reflectance Reference Targets, Labsphere, US) .
  • step e) the radiometric corrective masks are predetermined during the system setup phase using conventional techniques as described in Kelcey J. and Lucieer A. (2012) . Sensor Correction of a 6-Band Multispectral Imaging Sensor for UAV Remote Sensing, Remote Sens. 2012, 4(5), 1)462-1493.). Red R, green G, blue B, and infrared IR Images of a reference flat surface are acquired by placing side by side 10 reference plates having known and homogeneous reflectance vary from 2% to 99%.
  • R i a i + b i DN i
  • ai and bi are the values of the "intercept" and "slope" obtained applying the least squares method for each LED i sources.
  • the reference plate with known and homogeneous reflectance varying from 2% to 99% can be commercially available (SRS-02, SRS-05, SRS- 10, SRS-20, SRS-40, SRS-50, SRS-60, SRS-75, SRS-80, SRS-99, Reflectance Reference Targets, Labsphere, USA) .
  • the method of the present invention can be used to monitor the effectiveness of crop interventions carried out in the management of turf shards of sports fields, golf courses, recreational areas and green spaces, natural and artificial pastures.
  • Figure 3 shows the frequency F histograms and the statistical values obtained from NDVI images for each parcels P1, P2 and P3.

Landscapes

  • Physics & Mathematics (AREA)
  • Spectroscopy & Molecular Physics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Chemical & Material Sciences (AREA)
  • Analytical Chemistry (AREA)
  • Biochemistry (AREA)
  • General Health & Medical Sciences (AREA)
  • Immunology (AREA)
  • Pathology (AREA)
  • Investigating Or Analysing Materials By Optical Means (AREA)
  • Control Of Steam Boilers And Waste-Gas Boilers (AREA)

Abstract

L'invention concerne un procédé destiné à être utilisé pour la surveillance de surfaces de végétation, qui comprend l'utilisation d'un dispositif pour mesurer la réflectance spectrale de la végétation à l'aide d'images acquises avec un système d'éclaircissement sur la base de LED monobandes visibles et infrarouges et comprenant un dé-vignetage, un rognage d'image, des procédures d'étalonnage radiométrique et un calcul de valeurs de réflectance et d'indices de végétation.
PCT/IB2020/050671 2019-02-11 2020-01-29 Procédé de surveillance de couvertures de sol de végétation Ceased WO2020165671A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
IT102019000001891A IT201900001891A1 (it) 2019-02-11 2019-02-11 Metodo per il monitoraggio di superfici vegetali
IT102019000001891 2019-02-11

Publications (1)

Publication Number Publication Date
WO2020165671A1 true WO2020165671A1 (fr) 2020-08-20

Family

ID=66641224

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2020/050671 Ceased WO2020165671A1 (fr) 2019-02-11 2020-01-29 Procédé de surveillance de couvertures de sol de végétation

Country Status (2)

Country Link
IT (1) IT201900001891A1 (fr)
WO (1) WO2020165671A1 (fr)

Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112147078A (zh) * 2020-09-22 2020-12-29 华中农业大学 一种农作物表型信息多源遥感监测方法
CN112710613A (zh) * 2020-12-18 2021-04-27 太原理工大学 一种三组分状态下的光合植被参数遥感估算指数确定方法
CN113255592A (zh) * 2021-06-25 2021-08-13 成都信息工程大学 枯草光谱识别方法及系统
CN113283281A (zh) * 2021-02-26 2021-08-20 中科禾信遥感科技（苏州）有限公司 基于多时相遥感影像的茭白种植面积提取方法
CN113553549A (zh) * 2021-07-26 2021-10-26 中国科学院西北生态环境资源研究院 一种植被覆盖度反演方法、装置、电子设备及存储介质
CN114543638A (zh) * 2022-01-12 2022-05-27 四川恒得复生态科技有限公司 一种可以快速测定草本覆盖度的工具
CN115292616A (zh) * 2022-06-30 2022-11-04 北京大学 基于光谱不变理论的植被蓝天空反照率估算方法及装置
CN117437554A (zh) * 2023-11-01 2024-01-23 苏州大学 基于机器学习的平原水网地区非正式绿地识别方法和系统
CN118397559A (zh) * 2024-05-23 2024-07-26 黑龙江省农业科学院农业遥感与信息研究所 一种农作物数据采集及种植面积的遥感监测方法
CN119125081A (zh) * 2024-11-08 2024-12-13 天津市地质工程勘测设计院有限公司 一种矿山修复的植被状态监测方法及系统

Families Citing this family (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112697752B (zh) * 2020-12-09 2022-11-18 中国科学院东北地理与农业生态研究所 估算全球内陆水体透明度的方法
CN118364295B (zh) * 2024-06-18 2024-08-20 北京师范大学 一种用于植被异常遥感探测的光谱指数自动生成方法

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101419166A (zh) * 2008-11-18 2009-04-29 江苏大学 基于近红外光谱和机器视觉技术的茶叶品质无损检测方法及装置
CN1995987B (zh) * 2007-02-08 2010-05-12 江苏大学 基于高光谱图像技术的农畜产品无损检测方法
US20110002536A1 (en) * 2009-07-01 2011-01-06 The Texas A&M University System Multispectral natural fiber quality sensor for real-time in-situ measurement
US20120018356A1 (en) * 2009-03-06 2012-01-26 Hendrik Jalink Title of invention method and device for determining plant material quality using images containing information about the quantum efficiency and the time response of the photosynthtic system
CN101915738B (zh) * 2010-06-23 2013-06-12 江苏大学 基于高光谱成像技术的茶树营养信息快速探测方法及装置
CN102829739B (zh) * 2012-08-21 2015-03-25 北京农业信息技术研究中心 一种面向对象的作物叶面积指数遥感反演方法
WO2016176612A1 (fr) * 2015-04-29 2016-11-03 Board Of Trustees Of Michigan State University Procédés d'estimation des caractéristiques photosynthétiques de couvertures végétales, et systèmes et appareil associés
US20170205335A1 (en) * 2016-01-14 2017-07-20 Ramot At Tel-Aviv University Ltd. Portable soil spectral probe

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1995987B (zh) * 2007-02-08 2010-05-12 江苏大学 基于高光谱图像技术的农畜产品无损检测方法
CN101419166A (zh) * 2008-11-18 2009-04-29 江苏大学 基于近红外光谱和机器视觉技术的茶叶品质无损检测方法及装置
US20120018356A1 (en) * 2009-03-06 2012-01-26 Hendrik Jalink Title of invention method and device for determining plant material quality using images containing information about the quantum efficiency and the time response of the photosynthtic system
US20110002536A1 (en) * 2009-07-01 2011-01-06 The Texas A&M University System Multispectral natural fiber quality sensor for real-time in-situ measurement
CN101915738B (zh) * 2010-06-23 2013-06-12 江苏大学 基于高光谱成像技术的茶树营养信息快速探测方法及装置
CN102829739B (zh) * 2012-08-21 2015-03-25 北京农业信息技术研究中心 一种面向对象的作物叶面积指数遥感反演方法
WO2016176612A1 (fr) * 2015-04-29 2016-11-03 Board Of Trustees Of Michigan State University Procédés d'estimation des caractéristiques photosynthétiques de couvertures végétales, et systèmes et appareil associés
US20170205335A1 (en) * 2016-01-14 2017-07-20 Ramot At Tel-Aviv University Ltd. Portable soil spectral probe

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
IHAB E. GHALI ET AL: "Using Variability within Digital Images to Improve Tall Fescue Color Characterization", CROP SCIENCE, vol. 52, no. 5, 1 January 2012 (2012-01-01), pages 2365, XP055476017, DOI: 10.2135/cropsci2011.10.0553 *
S. LENK ET AL: "Multispectral fluorescence and reflectance imaging at the leaf level and its possible applications", JOURNAL OF EXPERIMENTAL BOTANY, vol. 58, no. 4, 30 November 2006 (2006-11-30), GB, pages 807 - 814, XP055275913, ISSN: 0022-0957, DOI: 10.1093/jxb/erl207 *
SCOTFORD I M ET AL: "Applications of Spectral Reflectance Techniques in Northern European Cereal Production: A Review", BIOSYSTEMS ENGINEERING, ACADEMIC PRESS, UK, vol. 90, no. 3, 1 March 2005 (2005-03-01), pages 235 - 250, XP004769511, ISSN: 1537-5110 *
WIDJAJA PUTRA BAYU TARUNA ET AL: "Enhanced broadband greenness in assessing Chlorophyll a and b, Carotenoid, and Nitrogen in Robusta coffee plantations using a digital camera", PRECISION AGRICULTURE, SPRINGER US, BOSTON, vol. 19, no. 2, 11 March 2017 (2017-03-11), pages 238 - 256, XP036443453, ISSN: 1385-2256, [retrieved on 20170311], DOI: 10.1007/S11119-017-9513-X *

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112147078A (zh) * 2020-09-22 2020-12-29 华中农业大学 一种农作物表型信息多源遥感监测方法
CN112710613A (zh) * 2020-12-18 2021-04-27 太原理工大学 一种三组分状态下的光合植被参数遥感估算指数确定方法
CN113283281A (zh) * 2021-02-26 2021-08-20 中科禾信遥感科技（苏州）有限公司 基于多时相遥感影像的茭白种植面积提取方法
CN113255592A (zh) * 2021-06-25 2021-08-13 成都信息工程大学 枯草光谱识别方法及系统
CN113255592B (zh) * 2021-06-25 2021-11-19 成都信息工程大学 枯草光谱识别方法及系统
CN113553549B (zh) * 2021-07-26 2023-04-14 中国科学院西北生态环境资源研究院 一种植被覆盖度反演方法、装置、电子设备及存储介质
CN113553549A (zh) * 2021-07-26 2021-10-26 中国科学院西北生态环境资源研究院 一种植被覆盖度反演方法、装置、电子设备及存储介质
CN114543638A (zh) * 2022-01-12 2022-05-27 四川恒得复生态科技有限公司 一种可以快速测定草本覆盖度的工具
CN115292616A (zh) * 2022-06-30 2022-11-04 北京大学 基于光谱不变理论的植被蓝天空反照率估算方法及装置
CN115292616B (zh) * 2022-06-30 2023-07-18 北京大学 基于光谱不变理论的植被蓝天空反照率估算方法及装置
CN117437554A (zh) * 2023-11-01 2024-01-23 苏州大学 基于机器学习的平原水网地区非正式绿地识别方法和系统
CN118397559A (zh) * 2024-05-23 2024-07-26 黑龙江省农业科学院农业遥感与信息研究所 一种农作物数据采集及种植面积的遥感监测方法
CN119125081A (zh) * 2024-11-08 2024-12-13 天津市地质工程勘测设计院有限公司 一种矿山修复的植被状态监测方法及系统

Also Published As

Publication number Publication date
IT201900001891A1 (it) 2020-08-11

Similar Documents

Publication Publication Date Title
WO2020165671A1 (fr) Procédé de surveillance de couvertures de sol de végétation
Stamford et al. Development of an accurate low cost NDVI imaging system for assessing plant health
US11181516B2 (en) Methods and systems for analyzing a field
Wang et al. Estimating rice chlorophyll content and leaf nitrogen concentration with a digital still color camera under natural light
AU752868B2 (en) Method for monitoring nitrogen status using a multi-sprectral imaging system
Hoffmann et al. Crop water stress maps for an entire growing season from visible and thermal UAV imagery
Chen et al. Applying high-resolution visible-channel aerial imaging of crop canopy to precision irrigation management
Plant et al. Relationships between remotely sensed reflectance data and cotton growth and yield
US8488874B2 (en) Variable rate sprayer system and method of variably applying agrochemicals
Wilke et al. Assessment of plant density for barley and wheat using UAV multispectral imagery for high-throughput field phenotyping
US20120155714A1 (en) Vegetation indices for measuring multilayer microcrop density and growth
Bravo et al. Foliar disease detection in the field using optical sensor fusion
US20200182697A1 (en) Active illumination 2d and/or 3d imaging device for agriculture
WO2001033505A2 (fr) Modele multivariable destine a identifier des zones de reaction de culture dans un champ
Zhang et al. Fusion of remotely sensed data from airborne and ground-based sensors to enhance detection of cotton plants
US12270966B2 (en) Apparatus for determining agricultural relevant information
CN106841116B (zh) 人工绿色目标的检测方法和装置
Osroosh et al. Detecting fruit surface wetness using a custom-built low-resolution thermal-RGB imager
Zhang et al. Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data
JP3551264B2 (ja) 植物活力変動の評価画像作成方法
Doi Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images
JP2004213627A (ja) 植物活力変動の評価画像作成方法
Volterrani et al. Effects of nitrogen nutrition on bermudagrass spectral reflectance
Yang et al. Evaluation of cotton defoliation strategies using airborne multispectral imagery
Katsoulas et al. Calibration methodology of a hyperspectral imaging system for greenhouse plant water status assessment

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20707314

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20707314

Country of ref document: EP

Kind code of ref document: A1