CN113324952B - Water body diffuse attenuation coefficient remote sensing inversion method and system - Google Patents
Water body diffuse attenuation coefficient remote sensing inversion method and system Download PDFInfo
- Publication number
- CN113324952B CN113324952B CN202110535158.9A CN202110535158A CN113324952B CN 113324952 B CN113324952 B CN 113324952B CN 202110535158 A CN202110535158 A CN 202110535158A CN 113324952 B CN113324952 B CN 113324952B
- Authority
- CN
- China
- Prior art keywords
- water body
- attenuation coefficient
- turbid
- water
- calculating
- 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.)
- Active
Links
Images
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
- G01N21/55—Specular reflectivity
Abstract
The invention relates to a diffuse attenuation coefficient remote sensing inversion method and system based on water turbidity grading. The method comprises the following steps: calculating remote sensing reflectivity ratio f = R rs (670)/R rs (490) Dividing the water body into a clean water body, a transition water body and a turbid water body; aiming at water bodies with different turbidity degrees, different models are adopted to perform remote sensing inversion of the diffuse attenuation coefficient, and QAA (quality assurance analysis) and SSA (simple sequence analysis) models are respectively adopted to calculate the diffuse attenuation coefficient of the water body for the clean water body and the turbid water body
And
for transitional water bodies
And
the weighted average is used for calculating the diffuse attenuation coefficient of the water body
The method can be simultaneously suitable for remote sensing inversion of the diffuse attenuation coefficients of turbid water bodies (particularly high turbidity) and clean water bodies.
Description
Technical Field
The invention belongs to the field of remote sensing monitoring of ocean and inland water body environments, and particularly relates to a remote sensing inversion method and system for a diffuse attenuation coefficient, which are suitable for a highly turbid water body and a clean water body at the same time.
Background
Diffuse attenuation coefficient (K) d (lambda)) is a basic ocean optical parameter, can reflect the turbidity degree of a water body, and has an important role in understanding water environment change and biogeochemical processes.
The traditional measuring method of the diffuse attenuation coefficient is to use a profile spectrometer to carry out on-site in-situ observation on the sea surface, although the precision is high, the time and the labor are wasted, and the time-space synchronism of observation data is poor. Compared with the prior art, the remote sensing technology has the advantages of large-scale, synchronous and quick observation, and is suitable for large-scale (especially global and regional scale) water body diffuse attenuation coefficient mapping.
Scholars at home and abroad successively put forward different types of remote sensing inversion models of diffuse attenuation coefficients, and in general, the models have better performance in clean water, but have poorer applicability in turbid water, particularly highly turbid water. At present, a transparency remote sensing inversion method suitable for high-turbidity and clean water bodies at the same time is not available.
Disclosure of Invention
The invention aims to provide a diffuse attenuation coefficient remote sensing inversion method which is simultaneously suitable for turbid water bodies (particularly highly turbid) and clean water bodies.
The invention further aims to provide a water body diffuse attenuation coefficient remote sensing inversion method and a water body diffuse attenuation coefficient remote sensing inversion system.
The remote sensing inversion method of the diffuse attenuation coefficient of the water body comprises the following steps:
step 3, aiming at different types of water bodies, calculating diffuse attenuation coefficients K of the water bodies by adopting different models d (λ); wherein the turbid water bodyDiffuse attenuation coefficient of
When calculating, firstly, calculating the diffuse attenuation coefficient K of 490nm wave band d (lambda), calculating the diffuse attenuation coefficients K of 443nm, 532nm, 555nm and 670nm wave bands by utilizing the wave band correlation relation d (λ); diffuse attenuation coefficient of transition water body
Diffuse attenuation coefficient by clean water
And the diffuse attenuation coefficient of turbid water
Is calculated as the weighted average of (a).
The remote sensing inversion system of the water body diffuse attenuation coefficient comprises:
water body remote sensing reflectivity data R rs (lambda) an acquisition module, wherein the wave band lambda takes values of 443nm, 490nm, 532nm, 550nm and 670nm;
a water body turbidity grading module for grading water body according to the water body remote sensing reflectivity data R rs (lambda), calculating the remote sensing reflectivity ratio f = R of 670nm and 490nm wave bands rs (670)/R rs (490) Dividing the water body type according to the magnitude of the parameter f, and dividing the water body into a clean water body, a turbid water body and a transition water body;
the diffuse reflection attenuation coefficient calculation module is used for calculating the diffuse reflection attenuation coefficient K of different types of water bodies by adopting different models d (lambda); wherein the diffuse attenuation coefficient of the turbid water body
When calculating, firstly, calculating the diffuse attenuation coefficient K of 490nm wave band d (lambda), and calculating the diffuse attenuation coefficients K of 443nm, 532nm, 555nm and 670nm wave bands by utilizing the wave band correlation relation d (lambda); diffuse attenuation coefficient of transition water body
Diffuse attenuation coefficient by adopting clean water body
And the diffuse attenuation coefficient of turbid water
Is calculated as the weighted average of (a).
Compared with the prior art, the invention achieves the following technical effects:
the remote sensing inversion method and the remote sensing inversion system have high inversion accuracy on the highly turbid water body, and are very important for monitoring the ecological environment of the offshore area greatly influenced by human activities. In addition, the model adopted by the invention is suitable for the mainstream water color satellite, the model input is the remote sensing reflectivity of 443nm, 490nm, 532nm, 555nm and 670nm wave bands, and the mainstream water color satellite has remote sensing reflectivity data products for the model input at the wave bands or the wavelength positions close to the wave bands. Therefore, the remote sensing inversion method and the remote sensing inversion system can be simultaneously suitable for transparency remote sensing inversion of highly turbid and clean water bodies.
Drawings
FIG. 1 is a flow chart of an inversion method in an embodiment of the invention;
fig. 2 is a spatial distribution diagram of the transparency of the global sea area obtained by the inversion method in the embodiment of the present invention.
Detailed Description
The core of the invention is to provide a remote sensing inversion method and system of the diffuse attenuation coefficient, which are simultaneously suitable for turbid water bodies and clean water bodies.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, fig. 1 is a flow chart of an implementation of a water body diffuse attenuation coefficient inversion method based on a water body remote sensing reflectance spectrum according to an embodiment of the present invention, including the following steps:
With parameter f = R rs (670)/R rs (490) Distinguishing the cleanliness of the water body, and finely dividing the water body into three types according to the turbidity degree: clean water, transition water and turbid water. Specifically, when f < f clear Dividing the water body into clean water bodies; when f > f turbid Dividing the water body into turbid water bodies; when f is clear ≤f≤f turbid Dividing the water body into transition water bodies, wherein the parameter value is f clear ＝0.20，f turbid ＝0.54。
Step 3, aiming at different types of water bodies, calculating diffuse attenuation coefficient K of the water bodies by adopting different models d (λ); for the clean water body and the turbid water body, respectively adopting a QAA model and an SSA model to calculate the diffuse attenuation coefficient of the water body
And
for transitional water bodies, the method adopts
And
the weighted average is used for calculating the diffuse attenuation coefficient of the water body
The weight coefficient is f, f clear 、f turbid And (4) calculating.
(1) When f is less than 0.20 (clean water body),
wherein theta is an observation zenith angle and can be obtained by analyzing and calculating an observation position and time; from remote sensing reflectivity data R rs (lambda), and calculating the total absorption coefficient a (lambda) and backscattering coefficient b of the water body by the following formulas (2) to (10) b (λ)：
r rs (λ)＝R rs (λ)/(0.52+1.7R rs (λ)) (2)
When R is rs (670)＜0.0015sr -1 When the temperature of the water is higher than the set temperature,
wherein λ is 0 ＝555，
When R is rs (670)≥0.0015sr -1 When the utility model is used, the water is discharged,
a(λ 0 )＝a w (λ 0 )+0.39(Rrs(λ 0 )/(Rrs(443)+Rrs(490))) 1.14 (5)
wherein λ is 0 ＝670；
a(λ)＝(1-u(λ))(b bw (λ)+b bp (λ))/u(λ) (9)
b b (λ)＝b bw (λ)+b bp (λ) (10)
Wherein r is rs (λ)、u(λ)、χ、η、b bp (λ 0 )、b bp (lambda) are all from remote sensing reflectance data R rs (λ) calculating the resulting intermediate variable; b bw (λ 0 )、b bw (λ) is each λ 0 And constants of the lambda band.
The total absorption coefficient a (lambda) and the back scattering coefficient b of the water body b The specific calculation procedure of (. Lamda.) is shown in Table 1.
TABLE 1 Total absorption coefficient a (. Lamda.) and backscattering coefficient b b (lambda) specific calculation procedure
Then, using equation (1), the data is represented by a (λ) and b b (lambda) calculation
(2) When f is more than 0.54 (turbid water body),
the calculation is divided into two steps:
first, using equations (11) - (14), K is calculated d (490) (ii) a Then according to the related relation of the wave bands, using the formulas (15) - (18) to calculate the frequency band by K d (490) K was calculated for the remaining 4 bands (443 nm, 532nm, 550nm and 670 nm) d (λ)。
r rs (λ)＝R rs )λ)/(0.52+1.7R rs (λ)) (11)
q＝s(670)/(s490) (13)
K d (490)＝(1+6.201s-4.595s 2 )(0.0001+0.811q-0.036q 2 ) (14)
K d (443)＝1.2028K d (490)+0.0557 (15)
K d (532)＝0.8192K d (490)+0.0207 (16)
K d (555)＝0.7418K d (492)+0.0331 (17)
K d (670)＝0.5652K d (490)+0.5912 (18)
(3) When f is more than 0.20 and less than 0.54 (transition water body),
that is, the weight coefficient w 1 、w 2 From parameters f and f turbid 、f clear Calculating to obtain;
by
And
and obtaining a weighted average.
In the embodiment, MODIS aqua satellite data is adopted for experiments, and the selected experimental area is a global sea area for carrying out seawater diffuse attenuation coefficient inversion; the seawater diffuse attenuation coefficient space distribution obtained by calculating the remote sensing reflectivity evaluation data averaged for years in 2002-2020 is selected and shown in figure 2.
Example 2
Based on the same inventive concept as embodiment 1, the embodiment provides a remote sensing inversion system for water body diffuse attenuation coefficient, which specifically includes:
water body remote sensing reflectivity data R rs (λ) an obtaining module, configured to implement step 1 in embodiment 1, where a value of the wavelength band λ is 443nm, 490nm, 532nm, 550nm, and 670nm;
a water body turbidity grading module for realizing the step 2 in the embodiment 1 and according to the water body remote sensing reflectivity data R rs (lambda), calculating the remote sensing reflectivity ratio f = R of 670nm and 490nm wave bands rs (670)/R rs (490) Dividing the water body types according to the magnitude value of the parameter f, and dividing the water body into a clean water body, a turbid water body and a transitional water body;
a diffuse reflection attenuation coefficient calculation module for realizing the step 3 in the embodiment 1, and calculating the diffuse reflection attenuation coefficient K of different types of water bodies by adopting different models d (lambda); wherein the diffuse attenuation coefficient of the turbid water body
When calculating, firstly, calculating the diffuse attenuation coefficient K of 490nm wave band d (lambda), and calculating the diffuse attenuation coefficients K of 443nm, 532nm, 555nm and 670nm wave bands by utilizing the wave band correlation relation d (lambda); diffuse attenuation coefficient of transition water body
Diffuse attenuation coefficient by clean water
And the diffuse attenuation coefficient of turbid water
Is calculated as a weighted average of (a).
In this embodiment, the classification mode of the water turbidity classification module is as follows: when f is less than f clear Dividing the water body into clean water bodies; when f > f turbid Dividing the water body into turbid water bodies; when f is clear ≤f≤f turbid Dividing the water body into transition water bodies, wherein the parameter value is f clear ＝0.20，f turbid =0.54; in the weighted average calculation of the diffuse reflection attenuation coefficient calculation module, the weight coefficient is formed by f and f clear And f turbid And (4) calculating.
The above examples of the present invention are merely examples for clearly illustrating the present invention and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (2)
1. The remote sensing inversion method of the water body diffuse attenuation coefficient is characterized by comprising the following steps:
step 1, obtaining water body remote sensing reflectivity data R rs (λ) wavelength bands λ are 443nm, 490nm, 532nm, 550nm and 670nm;
step 2, calculating the remote sensing reflectivity ratio f = R of 670nm and 490nm wave bands rs (670)/R rs (490) Dividing the water body type according to the magnitude of the parameter f, and dividing the water bodyDividing into a clean water body, a turbid water body and a transition water body;
step 3, aiming at different types of water bodies, calculating diffuse attenuation coefficients K of the water bodies by adopting different models d (λ); wherein the diffuse attenuation coefficient of the turbid water body
When calculating, the diffuse attenuation coefficient K of 490nm wave band is calculated d (lambda), and calculating the diffuse attenuation coefficients K of 443nm, 532nm, 555nm and 670nm wave bands by utilizing the wave band correlation relation d (λ); diffuse attenuation coefficient of transition water body
Diffuse attenuation coefficient by clean water
And the diffuse attenuation coefficient of turbid water
The weighted average of (2) is calculated;
diffuse attenuation coefficient of clean water body in step 3
Calculating by adopting a QAA model; diffuse attenuation coefficient of turbid water body
When calculating, the diffuse attenuation coefficient K of 490nm wave band d (lambda) is obtained using an SSA model;
the calculation method of the diffuse attenuation coefficient of the turbid water body comprises the following steps:
r rs (λ)＝R rs (λ)/0.52+1.7R rs (λ))
q＝s(670)/s(490)
K d (490)＝(1+6.201s-4.595s 2 )(0.0001+0.811q-0.036q 2 )；
K d (443)＝1.2028K d (490)+0.0557；
K d (532)＝0.8192K d (490)+0.0207；
K d (555)＝0.7418K d (490)+0.0331；
K d (670)＝0.5652K d (490)+0.5912；
in step 2, when f is less than f clear Dividing the water body into clean water bodies; when f > f turbid Dividing the water body into turbid water bodies; when f is clear ≤f≤f turbid Dividing the water body into transition water bodies, wherein the parameter value is f clear ＝0.20，f turbid ＝0.54；
In the weighted average calculation, the weight coefficient is f, f clear And turbid calculating to obtain;
the diffuse attenuation coefficient of the clean water body is as follows:
wherein theta is an observation zenith angle and is obtained by analyzing and calculating an observation position and time; from remote sensing reflectance data R rs (lambda) calculating the total absorption coefficient a (lambda) and backscattering coefficient b of the water body b (λ)：
r rs (λ)＝R rs (λ)/(0.52+1.7R rs (λ))
When R is rs (670)＜0.0015sr -1 When the utility model is used, the water is discharged,
wherein λ is 0 ＝555，
When R is rs (670)≥0.0015sr -1 When the temperature of the water is higher than the set temperature,
a(λ 0 )＝a w (λ 0 )+0.39(R rs (λ 0 )/(R rs (443)+R rs (490))) 1.14
wherein λ is 0 ＝670；
a(λ)＝(1-u(λ))(b bw (λ)+b bp (λ))/u(λ)
b b (λ)＝b bw (λ)+b bp (λ)
Wherein r is rs (λ)、u(λ)、χ、η、b bp (λ 0 )、b bp (lambda) are all from remote sensing reflectance data R rs (λ) calculating the resulting intermediate variable; b bw (λ 0 )、b bw (λ) is each λ 0 A constant of λ band;
diffuse attenuation coefficient of transitional water body
The calculation method is as follows:
wherein the weight coefficient w 1 、w 2 From parameters f and f turbid 、f clear And (4) calculating.
2. Water body diffuse attenuation coefficient remote sensing inversion system, its characterized in that includes:
water body remote sensing reflectivity data R rs (lambda) an acquisition module, wherein the wave band lambda takes values of 443nm, 490nm, 532nm, 550nm and 670nm;
a water body turbidity grading module for grading water body according to the water body remote sensing reflectivity data R rs (lambda), calculating the remote sensing reflectivity ratio f = R of 670nm and 490nm wave bands rs (670)/R rs (490) Dividing the water body type according to the magnitude of the parameter f, and dividing the water body into a clean water body, a turbid water body and a transition water body;
a diffuse reflection attenuation coefficient calculation module for calculating diffuse reflection attenuation coefficient K of different types of water bodies by adopting different models d (lambda); wherein the diffuse attenuation coefficient of the turbid water body
When calculating, the diffuse attenuation coefficient K of 490nm wave band is calculated d (lambda), calculating the diffuse attenuation coefficients K of 443nm, 532nm, 555nm and 670nm wave bands by utilizing the wave band correlation relation d (lambda); diffuse attenuation coefficient of transitional water body
Diffuse attenuation coefficient by adopting clean water body
And the diffuse attenuation coefficient of turbid water
The weighted average of (2) is calculated;
the classification mode of the water turbidity classification module is as follows: when f is less than f clear Dividing the water body into clean water bodies; when f > f turbid When the water is neededDividing the body into turbid water bodies; when f is clear ≤f≤f turbid Dividing the water body into transition water bodies, wherein the parameter value is f clear ＝0.20，f turbid ＝0.54；
In the weighted average calculation of the diffuse reflection attenuation coefficient calculation module, the weight coefficient is formed by f and f clear And f turbid Calculating to obtain;
the diffuse attenuation coefficient of the turbid water body is calculated in the following mode:
r rs (λ)＝R rs (λ)/(0.52+1.7R rs (λ))
q＝s(670)/s(490)
K d (490)＝(1+6.201s-4.595s 2 )(0.0001+0.811q-0.036q 2 )；
K d (443)＝1.2028K d (490)+0.0557；
K d (532)＝0.8192K d (490)+0.0207；
K d (555)＝0.7418K d (490)+0.0331；
K d (670)＝0.5652K d (490)+0.5912；
the diffuse attenuation coefficient of the clean water body is as follows:
wherein theta is an observation zenith angle and is obtained by analyzing and calculating an observation position and time; from remote sensing reflectivity data R rs (lambda) calculating the total absorption coefficient a (lambda) and backscattering coefficient b of the water body b (λ)：
r rs (λ)＝R rs (λ)/(0.52+1.7R rs (λ))
When R is rs (670)＜0.0015sr -1 When the utility model is used, the water is discharged,
wherein λ is 0 ＝555，
When R is rs (670)≥0.0015sr -1 When the utility model is used, the water is discharged,
a(λ 0 )＝a w (λ 0 )+0.39(R rs (λ 0 )/(R rs (443)+R rs (490))) 1.14
wherein λ is 0 ＝670；
a(λ)＝(1-u(λ))(b bw (λ)+b bp (λ))/u(λ)
b b (λ)＝b bw (λ)+b bp (λ)
Wherein r is rs (λ)、u(λ)、χ、η、b bp (λ 0 )、b bp (lambda) are all from remote sensing reflectance data R rs (λ) calculating the resulting intermediate variable; b is a mixture of bw (λ 0 )、b bw (λ) is each λ 0 Constants of λ band;
diffuse attenuation coefficient of transition water body
The calculation method is as follows:
wherein the weight coefficient w 1 、w 2 From parameters f and f turbid 、f clear And (4) calculating.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110535158.9A CN113324952B (en) | 2021-05-17 | 2021-05-17 | Water body diffuse attenuation coefficient remote sensing inversion method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110535158.9A CN113324952B (en) | 2021-05-17 | 2021-05-17 | Water body diffuse attenuation coefficient remote sensing inversion method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113324952A CN113324952A (en) | 2021-08-31 |
| CN113324952B true CN113324952B (en) | 2023-03-03 |
Family
ID=77415693
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110535158.9A Active CN113324952B (en) | 2021-05-17 | 2021-05-17 | Water body diffuse attenuation coefficient remote sensing inversion method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113324952B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114199827B (en) * | 2022-02-21 | 2022-05-10 | 中国石油大学(华东) | Remote sensing data-based method for inverting vertical change of PAR diffuse attenuation coefficient |
| CN115824972B (en) * | 2022-11-29 | 2023-07-25 | 中国科学院空天信息创新研究院 | Inland water body semi-resolution transparency inversion method and system |
| CN116861707B (en) * | 2023-09-04 | 2023-12-01 | 自然资源部第一海洋研究所 | Solar shortwave radiation sea surface albedo parameterization method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105158172A (en) * | 2015-08-22 | 2015-12-16 | 中国城市科学研究会 | Analysis method of remote sensing inversion of water color parameters of inland class II water |
| CN105372641A (en) * | 2015-12-23 | 2016-03-02 | 国家海洋局第一海洋研究所 | Laser radar water body echo signal simulation method |
| CN106248601A (en) * | 2016-09-14 | 2016-12-21 | 南京吉泽信息科技有限公司 | A kind of OLI of utilization data estimation water body overflows the model method of attenuation quotient |
| CN110749568A (en) * | 2019-12-19 | 2020-02-04 | 中国科学院南京地理与湖泊研究所 | MODIS remote sensing inversion method for phytoplankton absorption characteristics of high-turbidity eutrophic lakes |
-
2021
- 2021-05-17 CN CN202110535158.9A patent/CN113324952B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105158172A (en) * | 2015-08-22 | 2015-12-16 | 中国城市科学研究会 | Analysis method of remote sensing inversion of water color parameters of inland class II water |
| CN105372641A (en) * | 2015-12-23 | 2016-03-02 | 国家海洋局第一海洋研究所 | Laser radar water body echo signal simulation method |
| CN106248601A (en) * | 2016-09-14 | 2016-12-21 | 南京吉泽信息科技有限公司 | A kind of OLI of utilization data estimation water body overflows the model method of attenuation quotient |
| CN110749568A (en) * | 2019-12-19 | 2020-02-04 | 中国科学院南京地理与湖泊研究所 | MODIS remote sensing inversion method for phytoplankton absorption characteristics of high-turbidity eutrophic lakes |
Non-Patent Citations (4)
| Title |
|---|
| QAA在遥感影像反演中的性能评估与分析;邢帅 等;《测绘科学技术学报》;20200415;第73卷(第2期);第149-153页 * |
| Remote sensing of diffuse attenuation coefficient using MODIS imagery of turbid coastal waters:A case study in Bohai Sea;Jun Chen et al;《Remote Sensing of Environment》;20130922;第140卷;第78-93页 * |
| Update of the Quasi-Analytical Algorithm"（QAA_v6）;LEE Z P et al;《www．ioccg．org/groups/Sof-tware_OCA/QAA_v6_2014209.pdf》;20181006;第1页 * |
| 渤黄海水体漫衰减系数的遥感反演;毛颖 等;《广西科学》;20161231;第23卷(第6期);第513-519页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113324952A (en) | 2021-08-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113324952B (en) | Water body diffuse attenuation coefficient remote sensing inversion method and system | |
| Gernez et al. | Shellfish aquaculture from space: potential of Sentinel2 to monitor tide-driven changes in turbidity, chlorophyll concentration and oyster physiological response at the scale of an oyster farm | |
| CN107589075B (en) | OLCI remote sensing monitoring method for inherent optical parameters of shallow lake | |
| Doxaran et al. | Optical characterisation of suspended particles in the Mackenzie River plume (Canadian Arctic Ocean) and implications for ocean colour remote sensing | |
| CN110068539B (en) | Remote sensing method for colored dissolved organic matters in eutrophic shallow lake | |
| CN110749568B (en) | MODIS remote sensing inversion method for phytoplankton absorption characteristics of high-turbidity eutrophic lakes | |
| CN111651707B (en) | Tidal level inversion method based on optical shallow water region satellite remote sensing image | |
| CN110909491A (en) | Sea surface salinity inversion algorithm based on wind and cloud meteorological satellite | |
| CN106053370A (en) | Inversion method for offshore secchi disk depth based on HICO simulation | |
| CN112034480B (en) | Wavelength optimization method for dual-wavelength marine laser radar detection | |
| Naik et al. | Light absorption properties of southeastern Bering Sea waters: Analysis, parameterization and implications for remote sensing | |
| CN112630189A (en) | Inland water body water quality inversion method based on improved QAA algorithm | |
| CN110196239B (en) | Spectrum remote sensing inversion method for phytoplankton absorption coefficient of turbid water body | |
| CN114544452A (en) | Multi-angle polarized water color remote sensor satellite atmosphere correction method | |
| Zhang et al. | Phytoplankton size class in the East China Sea derived from MODIS satellite data | |
| CN113763272A (en) | Remote sensing inversion method for photosynthetic effective radiation attenuation coefficient of eutrophic lake | |
| CN105891124A (en) | Water color parameter inversion device and method for near-shore estuary | |
| CN111650128B (en) | High-resolution atmospheric aerosol inversion method based on surface reflectivity library | |
| CN111220552B (en) | Chlorophyll hyperspectral inversion method considering illumination direction leaf radiation transmission model | |
| Hlaing et al. | Validation of ocean color satellite sensors using coastal observational platform in Long Island Sound | |
| CN116223452A (en) | Chlorophyll hyperspectral inversion method based on curled plant leaf radiation transmission model | |
| Wang et al. | Variation in downwelling diffuse attenuation coefficient in the northern South China Sea | |
| CN115389383A (en) | High-precision inversion method for concentration of suspended sediment in offshore area | |
| CN113917462A (en) | Remote sensing estimation method for concentration of dissolved phosphorus in water body | |
| CN114199827B (en) | Remote sensing data-based method for inverting vertical change of PAR diffuse attenuation coefficient |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |