CN111951392B - Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data - Google Patents
Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data Download PDFInfo
- Publication number
- CN111951392B CN111951392B CN202010726989.XA CN202010726989A CN111951392B CN 111951392 B CN111951392 B CN 111951392B CN 202010726989 A CN202010726989 A CN 202010726989A CN 111951392 B CN111951392 B CN 111951392B
- Authority
- CN
- China
- Prior art keywords
- beach
- water level
- remote sensing
- river
- water
- 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
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
- G06T17/05—Geographic models
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C15/00—Surveying instruments or accessories not provided for in groups G01C1/00 - G01C13/00
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/29—Geographical information databases
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/40—Protecting water resources
- Y02A20/402—River restoration
Abstract
The invention provides a method for reconstructing topography above the withered water level of a river continent beach based on time series satellite remote sensing data and water level monitoring data, which mainly aims at the river continent beach with larger area change in the annual change along with the water level of the river. According to the invention, a river beach boundary line of a time sequence is extracted from ESA/Sentinel-2 remote sensing images, water level observation data of a nearest hydrologic station at the upstream and downstream of a beach at corresponding time is automatically grabbed, elevation information of each characteristic point of the beach water line Gao Chenghuo is obtained, and the topography above the beach self-damping water line is established through spatial interpolation. The method can fully utilize the existing satellite remote sensing data and water level monitoring data under the condition of not carrying out field measurement, is suitable for the beach with obvious area change affected by water level change, establishes beach topography above a dead water line, and has great significance for scour and siltation analysis, protection, development and utilization of the beach.
Description
Technical Field
The invention relates to the technical field of mapping remote sensing and water conservancy, in particular to a method for reconstructing topography above the beach withered water level of a river based on time series remote sensing images and water level monitoring data.
Background
The technical route for regional topography measurement is a point-to-line-to-face topography measurement method based on the traditional topography measurement method of a level gauge and a total station. The field measurement operation precision is high, but the condition is difficult, the efficiency is low, and the manpower and financial resources consumption is large.
The underwater topography measurement is mainly performed by a ship-borne depth finder. River beach is widely distributed, the area of the beach in dead water period is large, the area of the beach in flood period is small, and beach topography measurement is a long-term puzzled problem, "ship measurement is difficult to go up beach and people are difficult to go down water". The method for measuring underwater topography on the ship is limited by the fact that the ship needs enough water depth to navigate, the method for measuring underwater topography can be used for obtaining the topography of the beach on the beach completely submerged in the flood period, but the method for measuring underwater topography on the beach not completely submerged in the flood period is difficult to approach the ship due to the fact that the water depth of the water area nearby the beach is usually shallower, manpower hiking beach measurement is more difficult to pass, mud depth, beach sinking and grooves of the beach are changeable, measurement efficiency is low, and personal and equipment safety risks exist.
Photogrammetry is an optical image measurement method based on a pair of ground object images. The method is suitable for mountain hilly terrain measurement with a certain topography fluctuation, but most of the topography of the beach is gentle, the high probability of the beach is regularly submerged by flood, the surface coverage is simple, the characteristic points are difficult to determine, an effective stereo photographic image pair is difficult to form, and the method is not suitable for the topography measurement of the beach wetland.
The on-board laser detection and ranging system technology (LiDAR) can rapidly acquire the terrain information of a large-scale tidal flat, and the like, and uses LiDAR data to construct DEM (Yesong, etc., 2010) in the Hubei province, the Yangyang county of Qingjiang river basin; however, the LiDAR technology is limited by the differences of beach vegetation, texture and the like, weather and tidal conditions and other factors during construction, the hardware cost of LiDAR equipment is high, the airborne field measurement is carried out in a wading area, the operation risk is high, and river beach topography monitoring is difficult to effectively carry out by using the LiDAR technology.
Disclosure of Invention
The invention provides a method for reconstructing topography above the withered water level of a river beach based on time series remote sensing images and water level monitoring data, which can solve the defects of high formation cost, high risk and the like in the prior art for collecting the beach.
A terrain reconstruction method above the beach withered water level of a river based on time series remote sensing images and water level monitoring data comprises the following steps:
step 1, determining a river beach with larger area change along with the annual change of the river water level as a terrain reconstruction object;
step 3, using ESA/Sentinel-2 satellite data as a main data source, collecting time sequence remote sensing image data in any year of a typical beach, preprocessing ESA/Sentinel-2 time sequence remote sensing images, and extracting a time sequence beach boundary line based on the remote sensing data by constructing MNDWI or NDWI water body indexes;
step 4, according to the imaging time of the remote sensing image, automatically capturing water level data of the nearest hydrological monitoring station on the upstream and downstream of the beach at the time point nearest to the imaging time of the remote sensing image, and calculating the ratio drop between the nearest water level monitoring sections on the upstream and downstream at the time point;
step 5, calculating elevation information of the water level contour lines or elevation information of each characteristic point of the beach boundary line according to the ratio drop between the upstream nearest hydrologic station and the downstream nearest hydrologic station and the distance between each characteristic point of the beach center point or the beach boundary line and the upstream nearest hydrologic station obtained in the step 4;
step 6, integrating the beach boundary line extracted in the step 3 based on any remote sensing image with the elevation information of the water level contour line or the elevation information of each characteristic point of the beach boundary line obtained from the water level monitoring data in the step 5 to obtain a three-dimensional water boundary line; and the elevation information of each characteristic point of the water level contour line or the beach boundary line extracted from the remote sensing images of the time sequence is integrated by analogy;
step 7, generating TIN (irregular triangular net) by using the 3D analysis function of the existing GIS software according to the three-dimensional water line of the time sequence in any year obtained in the step 6 by adopting a spatial interpolation method, and constructing a digital terrain model above the river beach withered water level;
and 8, performing accuracy inspection on the digital topography above the measured typical beach wither water level and the newly measured topography obtained in the step 7 in the overlapping area by utilizing the newly measured topography data in the monitoring area and adopting a global average elevation comparison method, and finally completing the topography map above the beach wither water level of the monitoring area.
Further, the preprocessing in the step 3 specifically includes: image cropping, radiometric calibration, image registration, cloud detection.
Further, in the step 3, by constructing the MNDWI or NDWI water body index, the extracting of the beach boundary line based on the remote sensing data specifically includes: and (3) analyzing spectral characteristics of various wave bands of ESA/Sentinel-2 satellite images of beach vegetation, beach sand and water at different times by using ENVI remote sensing software, simultaneously analyzing the identification degree of the existing water indexes such as NDWI and MNDWI for distinguishing beach and water in different seasons, selecting a proper water index or characteristic wave band for any ESA/Sentinel-2 satellite image, and extracting beach boundary lines based on remote sensing data by visual interpretation or an image classification algorithm.
Further, in the step 4, the Python program is used to automatically capture the water level data of the last water level monitoring section at the upstream and downstream of the beach at the time point closest to the imaging time of the remote sensing image from the website of the hydrological water resource bureau.
Further, the step 5 specifically includes:
(1) For a beach with smaller area or shorter forward water flow direction, the water level of the front and the tail of the beach is close, and the border line of the beach is assumed to be consistent with the water level contour line, and the elevation of the water level contour line is obtained according to the ratio drop between the upstream nearest hydrologic station and the downstream nearest hydrologic station and the distance between the central point of the beach and the upstream nearest hydrologic station, which are obtained in the step 4;
(2) For a beach with a larger area or a longer along water flow direction, a certain water level difference exists between the beach and the tail of the beach, a characteristic point is arranged on the border line of the beach at certain intervals, and the elevation of each characteristic point of the border line of the beach is obtained according to the ratio drop between the nearest hydrologic stations at the upstream and the downstream and the distance between each characteristic point of the border line of the beach and the nearest hydrologic stations at the upstream and the downstream obtained in the step 4.
Further, a feature point is set on the beach boundary line every 100 meters.
According to the invention, under the condition that field measurement is not carried out, aiming at the river beach with larger area change in the annual change along with the river water level, satellite remote sensing data and water level monitoring data with high time and space resolution are fully utilized, the MNDWI or NDWI water index characteristic parameters are constructed, the beach boundary line is extracted by adopting visual interpretation or object-oriented classification technology, corresponding elevation information is calculated, the river beach topography above the dead water line is established by utilizing the space interpolation function of the 3D analysis of the existing GIS software, and the method has great significance for scour siltation analysis, protection and development and utilization of the beach; compared with the prior art, the method can thoroughly solve the problems of difficult measurement of traditional manual hiking measurement, unmanned aerial vehicle measurement, on-site measurement of ship-borne radar and airborne laser radar measurement, and meanwhile overcomes the problems that unmanned aerial vehicle and LiDAR measurement are limited by weather and air pipes.
Drawings
FIG. 1 is a flow chart of a method for reconstructing topography above the beach withered water level of a river based on time series remote sensing images and water level monitoring data;
FIG. 2 is a flowchart of an embodiment of the present invention, which is exemplified by Nanyang continent of Yangtze river reach;
FIG. 3 is a schematic view of a Yankee river reach of the Yankee river;
fig. 4 is a 2019 year time series remote sensing image of south yang continent;
fig. 5 is a MNDWI water index of the 2019 time series of south yang continent;
FIG. 6 is a three-dimensional water line of the 2019 year time series of Nanyang continent;
FIG. 7 is a numerical elevation model above 2019 in south Africa;
FIG. 8 is a table of water levels of the monitoring section of the water level upstream and downstream of Nanyang continents.
Detailed Description
The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings and specific embodiments.
As shown in fig. 1, the embodiment of the invention provides a method for reconstructing a topography above a river beach withered water level based on a time sequence remote sensing image and water level monitoring data, which comprises the following steps:
step 1, determining a river beach with larger area change along with the annual change of the river water level as a terrain reconstruction object;
step 3, using ESA/Sentinel-2 satellite data as a main data source, collecting time series remote sensing image data of a typical beach within any year, preprocessing ESA/Sentinel-2 time series remote sensing images for image cutting, radiometric calibration, image registration, cloud detection and the like, and extracting beach boundary lines based on the remote sensing data by constructing MNCWI or NDWI water indexes; specifically, ENVI remote sensing software can be utilized to analyze spectral characteristics of various wave bands of ESA/Sentinel-2 satellite images of beach vegetation, beach sand and water at different times, and simultaneously analyze the identification degree of the current water indexes such as NDWI, MNDWI and the like in different seasons to distinguish beach and water, and then select a proper water index or characteristic wave band for any ESA/Sentinel-2 satellite image, and extract beach boundary lines based on remote sensing data through visual interpretation or image classification algorithm.
Step 4, automatically capturing water level data of the last water level monitoring sections at the upstream and downstream of the beach at the time point closest to the imaging time of the remote sensing image from a hydrological water resource bureau website by using a Python program according to the imaging time of the remote sensing image, and calculating the ratio drop between the last water level monitoring sections at the upstream and downstream; specifically, the GIS software can be used for measuring the distance between the beach and the upstream and downstream nearest water level monitoring sections and the water level monitoring value, and calculating the ratio drop between the upstream and downstream nearest water level monitoring sections.
And 5, calculating elevation information of the water level contour lines or elevation information of each characteristic point of the beach boundary line according to the ratio drop between the upstream and downstream nearest water level monitoring sections and the distance between each characteristic point of the beach center point or beach boundary line and the upstream and downstream nearest water level monitoring sections obtained in the step 4. Specifically, the area of the beach or the length of the beach along the water flow direction is taken as the basis for discrimination, and two conditions are adopted:
(1) For a beach with smaller area or shorter forward water flow direction, the water level of the front and the tail of the beach is close, and the border line of the beach is assumed to be consistent with the water level contour line, and the elevation of the water level contour line is obtained according to the ratio drop between the upstream and downstream nearest water level monitoring sections and the distance between the central point of the beach and the upstream and downstream nearest water level monitoring sections, which are obtained in the step 4;
(2) For a beach with a larger area or a longer water flow direction, a certain water level difference exists between the beach and the tail of the beach, a characteristic point is arranged on the border line of the beach at each interval of 100 meters, and the elevation of each characteristic point of the border line of the beach is obtained according to the ratio drop between the upstream and downstream nearest water level monitoring sections and the distance between each characteristic point of the border line of the beach and the upstream and downstream nearest water level monitoring sections, which are obtained in the step 4.
Step 6, integrating the elevation information of the beach boundary line extracted from any remote sensing image in step 3 and the elevation information of the water level contour line or the elevation information of each characteristic point of the beach boundary line obtained from the water level monitoring data in step 5 to serve as a three-dimensional water boundary line, and integrating the elevation information of the beach boundary line extracted from the remote sensing images in a time sequence and the elevation information of the beach boundary line by analogy;
step 7, generating TIN (irregular triangular net) by using the 3D analysis function of the existing GIS software according to the three-dimensional water line of the time sequence in any year obtained in the step 6 by adopting a spatial interpolation method, and constructing a digital terrain model above the river beach withered water level;
and 8, performing accuracy inspection on the digital topography above the measured typical beach wither water level and the newly measured topography obtained in the step 7 in the overlapping area by utilizing the newly measured topography data in the monitoring area and adopting a global average elevation comparison method, and finally completing the topography map above the beach wither water level of the monitoring area.
As shown in fig. 2-8, the technical scheme of the invention is further described in detail by taking the Yankee Nanyang of the Yankee river section as an example:
1. determining that the range of the river beach and the related water area is the water area where the Yankee river reach Nanyang continent is located (shown in figure 2), and the monitoring time is 2019;
2. according to the position of the south yang continent, the upstream and downstream water level monitoring sections closest to the south yang continent are lotus pool sections and spiral mountain sections respectively (the water level of the monitoring sections is shown in figure 8);
3. collecting 73 ESA/Sentinel-2 multi-temporal satellite remote sensing image data (shown in fig. 4) of a monitoring area from 1 month in 2019 to 12 months in 2019, calculating a time sequence MNCWI water index (shown in fig. 5) through preprocessing such as cloud detection, image registration, data acquisition and the like, and extracting 33 effective Nanyang continent beach boundary lines by using Ecognition object-oriented classification software;
4. according to the collection time of the remote sensing images corresponding to 33 south-yang continent beach boundary lines, automatically capturing water level monitoring data of the lotus pool section and the spiral mountain section, which are closest to the collection time of each remote sensing image, at a Hubei province hydrological water resource bureau website by using a Python program; calculating the ratio drop between the lotus pond and the spiral mountain section according to the distance between the lotus pond section and the spiral mountain section and the water head difference;
5. according to actual water level difference and ratio drop of lotus pool and spiral mountain break points in 2019, the annual water level difference of the front and the tail of Nanyang Africa is not more than 30 cm, the conditions of small area or short forward water flow direction of the Africa beach, the front and the tail water level approach are considered to be satisfied, the front and the tail water level approach are assumed to be consistent with the water level contour line, and the elevation of the water level contour line is acquired according to the ratio drop between the upstream and downstream nearest water level monitoring sections and the distance between the front and downstream nearest water level monitoring sections, which are acquired in the step 4;
6. integrating the beach boundary line extracted based on any remote sensing image with the elevation information of the south sun beach contour line obtained from the water level monitoring data to form a three-dimensional water edge line (shown in figure 6), and integrating the beach boundary line extracted from the remote sensing image of the time sequence with the elevation information to form a time sequence three-dimensional water edge line; generating a digital elevation model of Nanyang continent of a Yangtze river segment by generating TIN (irregular triangular net) in a space interpolation method of a 3D analysis module in ArcGIS software by using a feature point of a Nanyang beach boundary line of 33 strips of elevation information acquired in 2019 (shown in figure 7);
7. and (3) performing precision inspection on the generated digital terrain by using the 2016-year 1:1 ten thousand actually measured topographic map of the Yangtze river reach, and finally obtaining the 2019-year Yangtze river reach Nanyang continent topographic map with the terrain spatial resolution equal to the 1:1 ten thousand measured map precision.
The method utilizes the characteristic that the area of the beach changes along with the change of the river water level, extracts the river beach boundary line of the time sequence from ESA/Sentinel-2 remote sensing images with high time resolution (10 days, two satellites can be combined for 5 days, cloudy images and a small amount of data anomalies can be eliminated, the effective data is more than 30), and the space resolution (10 meters); according to the imaging time of the remote sensing image, automatically capturing water level observation data of the last water level monitoring section of the upstream and downstream of the beach at the corresponding time by using a Python program; taking the year as a unit, acquiring all ESA/Sentinel-2 remote sensing data without cloud influence of the beach in the year, extracting beach boundary lines of a time sequence, respectively acquiring elevation information of each characteristic point of the beach water line Gao Chenghuo according to the beach area or the length of the downstream direction as a judging basis, and establishing the topography above the beach self-damping water line through spatial interpolation. The invention can fully utilize the existing satellite remote sensing data and water level monitoring data to establish the river continental beach topography above the dead water level aiming at the river continental beach with the area changing along with the change of the river water level under the condition of not carrying out field measurement.
The foregoing is merely illustrative of the embodiments of the present invention, and the scope of the present invention is not limited thereto, and any person skilled in the art will appreciate that modifications and substitutions are within the scope of the present invention, and the scope of the present invention is defined by the appended claims.
Claims (6)
1. A method for reconstructing topography above the beach withered water level of a river based on time series remote sensing images and water level monitoring data is characterized by comprising the following steps:
step 1, determining a river beach with larger area change along with the annual change of the river water level as a terrain reconstruction object;
step 2, selecting a typical beach, and determining a hydrologic monitoring station with the closest distance between the beach and the upstream and downstream of a river according to the position of the typical beach;
step 3, using ESA/Sentinel-2 satellite data as a main data source, collecting time sequence remote sensing image data in any year of a typical beach, performing radiation calibration and image registration pretreatment processes on the ESA/Sentinel-2 time sequence remote sensing image, and extracting a beach boundary line based on the remote sensing data by constructing MNDWI or NDWI water indexes;
step 4, automatically capturing water level data of the nearest hydrologic monitoring stations on the upstream and downstream of the beach at the nearest time point from the imaging time of the remote sensing image according to the imaging time of the remote sensing image, and calculating the ratio drop between the nearest hydrologic stations on the upstream and downstream;
step 5, calculating elevation information of the water level contour lines or elevation information of each characteristic point of the beach boundary line according to the ratio drop between the upstream nearest hydrologic station and the downstream nearest hydrologic station and the distance between each characteristic point of the beach center point or the beach boundary line and the upstream nearest hydrologic station obtained in the step 4;
step 6, integrating the elevation information of the water level contour line or the elevation information of each characteristic point of the water level boundary line extracted from any remote sensing image in the step 3 and the water level contour line obtained from the water level monitoring data in the step 5, and integrating the elevation information of the water level boundary line and the elevation information of the water level boundary line extracted from the remote sensing images in the time sequence by analogy;
step 7, constructing a digital terrain model above the river beach wither water level according to the time sequence of the beach boundary line with the elevation information in any year obtained in the step 6 by adopting a spatial interpolation method, and generating a digital terrain above the measured typical beach wither water level;
and 8, performing accuracy inspection on the digital topography above the measured typical beach wither water level and the newly measured topography obtained in the step 7 in the overlapping area by utilizing the newly measured topography data in the monitoring area and adopting a global average elevation comparison method, and finally completing the topography map above the beach wither water level of the monitoring area.
2. The method for reconstructing the terrain above the beach withered water level of the river based on the time series remote sensing images and the water level monitoring data, as set forth in claim 1, is characterized in that: the pretreatment in the step 3 specifically includes: image cropping, radiometric calibration, image registration, cloud detection.
3. The method for reconstructing the terrain above the beach withered water level of the river based on the time series remote sensing images and the water level monitoring data, as set forth in claim 1, is characterized in that: in the step 3, by constructing the MNDWI or the MNDWI water index, the extraction of the beach boundary line based on the remote sensing data is specifically as follows: and analyzing spectral characteristics of various wave bands of ESA/Sentinel-2 satellite images of beach vegetation, beach sandy land and water at different times by using ENVI remote sensing software, simultaneously analyzing the current water indexes NDWI and MNDWI to distinguish beach and water identification in different seasons, selecting proper water indexes or characteristic wave bands for any ESA/Sentinel-2 satellite image, and extracting beach boundary lines based on remote sensing data by using a visual interpretation or image segmentation algorithm.
4. The method for reconstructing the terrain above the beach withered water level of the river based on the time series remote sensing images and the water level monitoring data, as set forth in claim 1, is characterized in that: and in the step 4, automatically capturing water level data of the last water level monitoring section at the upstream and downstream of the beach at the time point closest to the imaging time of the remote sensing image from a website of the hydrological water resource bureau by using a Python program.
5. The method for reconstructing the terrain above the beach withered water level of the river based on the time series remote sensing images and the water level monitoring data, as set forth in claim 1, is characterized in that: the step 5 specifically includes:
(1) For a beach with a smaller area or a shorter forward water flow direction, the water level of the front and the tail of the beach is close, and the border line of the beach is assumed to be consistent with the water level contour line, and the elevation of the center point of the beach is determined according to the ratio drop between the upstream nearest hydrologic station and the downstream nearest hydrologic station and the distance between the center point of the beach and the upstream nearest hydrologic station, which are obtained in the step 4, and is used as the elevation of the water level contour line of the beach;
(2) For a beach with a larger area or a longer along water flow direction, a certain water level difference exists between the beach and the tail of the beach, a characteristic point is arranged on the border line of the beach at certain intervals, and the elevation of each characteristic point of the border line of the beach is obtained according to the ratio drop between the nearest hydrologic stations at the upstream and the downstream and the distance between each characteristic point of the border line of the beach and the nearest hydrologic stations at the upstream and the downstream obtained in the step 4.
6. The method for reconstructing the terrain above the beach withered water level of the river based on the time series remote sensing images and the water level monitoring data, as set forth in claim 5, is characterized in that: a feature point is arranged on the beach boundary line every 100 meters.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010726989.XA CN111951392B (en) | 2020-07-26 | 2020-07-26 | Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010726989.XA CN111951392B (en) | 2020-07-26 | 2020-07-26 | Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111951392A CN111951392A (en) | 2020-11-17 |
| CN111951392B true CN111951392B (en) | 2023-04-25 |
Family
ID=73338113
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010726989.XA Active CN111951392B (en) | 2020-07-26 | 2020-07-26 | Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111951392B (en) |
Families Citing this family (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112697232A (en) * | 2020-12-15 | 2021-04-23 | 自然资源部国土卫星遥感应用中心 | Water level measurement and change monitoring method and device based on multi-source satellite height measurement data |
| CN112945352A (en) * | 2021-02-03 | 2021-06-11 | 成都鼎安华智慧物联网股份有限公司 | Extraction method based on remote sensing data water level abnormal information |
| CN112629493B (en) * | 2021-03-09 | 2021-07-02 | 长江水利委员会水文局 | High-precision water channel reconstruction method based on multi-satellite source information coupling |
| CN113011740B (en) * | 2021-03-18 | 2021-09-14 | 长江水资源保护科学研究所 | Method for constructing lake wetland ecology-water level gradient response relation |
| CN113111816B (en) * | 2021-04-20 | 2021-09-28 | 中国水利水电科学研究院 | River landform unit classification and identification method |
| CN113063445A (en) * | 2021-04-26 | 2021-07-02 | 浙江省水利河口研究院(浙江省海洋规划设计研究院) | Method for verifying mudflat resource monitoring error |
| CN113935202B (en) * | 2021-12-17 | 2022-03-01 | 四川省交通勘察设计研究院有限公司 | River channel evolution early warning method based on laser radar |
| CN114155350B (en) * | 2022-02-07 | 2022-04-22 | 北京恒济引航科技股份有限公司 | Underwater terrain erosion and deposition evolution analysis method and device for channel |
| CN116737989B (en) * | 2023-06-13 | 2024-03-01 | 长江水利委员会水文局 | Urban surface hydrologic monitoring network construction method based on video image |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103791890A (en) * | 2014-01-28 | 2014-05-14 | 河海大学 | Telemetering method for quick tidal wetland terrain measurement |
| CN109145709A (en) * | 2018-06-25 | 2019-01-04 | 中国地质大学（武汉） | A kind of the timing remote sensing vegetation index reconstructing method and system of iteration envelope line extraction |
| CN111192282A (en) * | 2019-12-19 | 2020-05-22 | 中国科学院南京地理与湖泊研究所 | Lake and reservoir time sequence water level reconstruction method for lakeside zone virtual station |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7680350B2 (en) * | 2004-05-07 | 2010-03-16 | TerraMetrics, Inc. | Method and system for progressive mesh storage and reconstruction using wavelet-encoded height fields |
-
2020
- 2020-07-26 CN CN202010726989.XA patent/CN111951392B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103791890A (en) * | 2014-01-28 | 2014-05-14 | 河海大学 | Telemetering method for quick tidal wetland terrain measurement |
| CN109145709A (en) * | 2018-06-25 | 2019-01-04 | 中国地质大学（武汉） | A kind of the timing remote sensing vegetation index reconstructing method and system of iteration envelope line extraction |
| CN111192282A (en) * | 2019-12-19 | 2020-05-22 | 中国科学院南京地理与湖泊研究所 | Lake and reservoir time sequence water level reconstruction method for lakeside zone virtual station |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111951392A (en) | 2020-11-17 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111951392B (en) | Method for reconstructing topography above beach withered water level based on time series remote sensing image and water level monitoring data | |
| CN109190538B (en) | Sediment-laden river delta coastal zone evolution analysis method based on remote sensing technology | |
| Velpuri et al. | Influence of resolution in irrigated area mapping and area estimation | |
| CN111046613B (en) | Optimal river channel calculation method based on path tracking and river network extraction method based on multi-temporal remote sensing image | |
| Do et al. | The estimation and evaluation of shoreline locations, shoreline-change rates, and coastal volume changes derived from Landsat images | |
| Kwak et al. | Near real-time flood volume estimation from MODIS time-series imagery in the Indus River Basin | |
| Gao et al. | Analysis of flood inundation in ungauged basins based on multi-source remote sensing data | |
| Li et al. | Dynamic waterline mapping of inland great lakes using time-series SAR data from GF-3 and S-1A satellites: A case study of DJK reservoir, China | |
| Guo et al. | Mozambique flood (2019) caused by tropical cyclone idai monitored from sentinel-1 and sentinel-2 images | |
| CN114112906A (en) | Water body feature extraction system based on unmanned aerial vehicle low-altitude remote sensing and local topography | |
| Athanasiou et al. | Global Coastal Characteristics (GCC): A global dataset of geophysical, hydrodynamic, and socioeconomic coastal indicators | |
| Bi et al. | Delineation water of pearl river basin using Landsat images from Google Earth Engine | |
| CN112926468A (en) | Tidal flat elevation automatic extraction method | |
| Liu et al. | Fractional vegetation cover estimation algorithm based on recurrent neural network for MODIS 250 m reflectance data | |
| Van Liem et al. | Assessment of shoreline changes for setback zone establishment from Son Tra (Da Nang city) to Cua Dai (Hoi An city), Vietnam | |
| Qi et al. | An adaptive threshold selected method from remote sensing image based on water index | |
| Loi et al. | Monitoring of coastline change using Sentinel-2A and Landsat 8 data, a case study of Cam Pha city-Quang Ninh province | |
| Yen et al. | Coastline changes detection from Sentinel–1 satellite imagery using spatial fuzzy clustering and interactive thresholding method in Phan Thiet, Binh Thuan | |
| Tan et al. | Riparian zone DEM generation from time-series Sentinel-1 and corresponding water level: A novel waterline method | |
| Hua et al. | The research of artificial shoreline extraction based on airborne LIDAR data | |
| Liu | Shoreline mapping and coastal change studies using remote sensing imagery and LIDAR data | |
| Li et al. | “3S” TECHNOLOGIES AND APPLICATION FOR DYNAMIC MONITORING SOIL AND WATER LOSS IN THE YANGTZE RIVER BASIN, CHINA | |
| Wei et al. | Long-term observation of global nuclear power plants thermal plumes using Landsat images and deep learning | |
| Yu et al. | Water body extraction and change analysis based on landsat image in Xinjiang coal-mining regions | |
| Wicaksono et al. | Geometric Accuracy Comparison of Shorelines Derived from Multitemporal Sentinel-2a Imagery with Various Image Spectral Transformations (Case Study: Marine Deposition Coasts in Bantul Regency, Yogyakarta, Indonesia) |
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 |