CN117253158A - Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data - Google Patents
Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data Download PDFInfo
- Publication number
- CN117253158A CN117253158A CN202311514475.8A CN202311514475A CN117253158A CN 117253158 A CN117253158 A CN 117253158A CN 202311514475 A CN202311514475 A CN 202311514475A CN 117253158 A CN117253158 A CN 117253158A
- Authority
- CN
- China
- Prior art keywords
- water
- lake
- data
- remote sensing
- water level
- 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.)
- Pending
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 225
- 238000003860 storage Methods 0.000 title claims abstract description 62
- 238000000034 method Methods 0.000 title claims abstract description 15
- 238000000605 extraction Methods 0.000 claims abstract description 11
- 238000005516 engineering process Methods 0.000 claims abstract description 6
- 238000007781 pre-processing Methods 0.000 claims abstract description 6
- 238000004364 calculation method Methods 0.000 claims description 9
- 238000002310 reflectometry Methods 0.000 claims description 6
- 238000005259 measurement Methods 0.000 claims description 5
- 239000002352 surface water Substances 0.000 claims description 4
- 230000001788 irregular Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 abstract description 4
- 238000012876 topography Methods 0.000 abstract description 4
- 230000007547 defect Effects 0.000 description 2
- 238000012216 screening Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 1
- 238000005520 cutting process Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000003673 groundwater Substances 0.000 description 1
- 238000009776 industrial production Methods 0.000 description 1
- 238000003973 irrigation Methods 0.000 description 1
- 230000002262 irrigation Effects 0.000 description 1
- 239000003621 irrigation water Substances 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000003809 water extraction Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/13—Satellite images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
-
- 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
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/30—Assessment of water resources
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- Theoretical Computer Science (AREA)
- Public Health (AREA)
- Multimedia (AREA)
- Remote Sensing (AREA)
- Astronomy & Astrophysics (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Measurement Of Levels Of Liquids Or Fluent Solid Materials (AREA)
Abstract
The invention relates to a lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data, and belongs to the technical field of remote sensing image processing and predictive data processing. Obtaining water level data of a lake through a laser altimetry satellite ICESat-2, obtaining time data under the same water level difference, obtaining remote sensing image data of the lake according to different time by utilizing a remote sensing technology, preprocessing the remote sensing image data, automatically extracting a target water body by utilizing an NDWI water body extraction technology, and obtaining lake water surface area data. And finally, constructing a relation curve of the water surface area and the water storage capacity of the lake according to the water surface area data of the lake under the same water level difference and combining the underwater topography data of the lake, and further calculating the water storage capacity of the lake according to the surface area data. The invention can calculate the water storage capacity according to the surface area data with the assistance of the remote sensing image, and greatly improves the efficiency and practicality of calculating the water storage capacity of the lake.
Description
Technical Field
The invention relates to a lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data, and belongs to the technical field of remote sensing image processing and predictive data processing.
Background
The lake is a natural pool with relatively closed earth surface and capable of storing water, and has important effects in the aspects of water resource management, flood control, irrigation water supply, water and soil conservation and the like. The lake can be used as a storage and regulation center of water resources, and can store redundant water in a rainy season or a river water rising period, and the water can supplement water sources for a groundwater system in a dry season, so that a stable water source is provided for surrounding industrial production and agricultural irrigation. In addition, the lake can also maintain the water level and water quality of river and underground water through hydrologic cycle, thereby ensuring the availability of water resources and the stability of ecological environment. Therefore, the water storage capacity of the lake is directly related to the sustainable development of the river basin in which the lake is located, and the grasping of the water storage capacity of the lake becomes particularly important.
The traditional method for calculating the water storage capacity of the lake is generally to calculate according to the measured water level and the underwater topography data, but the water storage capacity of the lake with untimely water level observation or lacking underwater topography data is difficult to calculate. With the rise of remote sensing technology, we can quickly and conveniently acquire the required lake surface remote sensing image, acquire the lake surface area and water level data through technical means, and calculate the lake water storage capacity. For example, in both CN 111504424A and CN 115205698A, the water level value is measured by measuring height data, the water surface area is calculated according to the remote sensing image, the water level variation and the water surface area variation are continuously observed and counted, a water level variation-area variation relation curve is constructed, and then the water level variation-area variation-water storage relation curve is constructed according to the water level variation-area variation relation curve, that is, the water storage amount is required to be obtained, two values of the water level variation and the area variation must be known at the same time, and the method is not convenient.
Disclosure of Invention
The invention aims to overcome the defects, and provides a lake water storage amount estimation method based on remote sensing images and laser altimetry satellite data, which can remarkably improve the efficiency of calculating the lake water storage amount.
The technical scheme adopted by the invention is as follows:
a lake water storage amount estimation method based on remote sensing images and laser altimetry satellite data comprises the following steps:
s1, acquiring corresponding water level data at different moments under the same elevation increment of a lake through a laser height measurement satellite ICESat-2, calculating the water level difference delta H under the same elevation increment, and recording continuous water level data H of the same water level difference (t) Corresponding time data t:
ΔH= H (t+1) - H (t) （1），
H (t+1) : the water level value at time t+1,
H (t) : the water level value at the time t,
t: at different moments in time under the same water level difference,
Δh: the water level difference under the same elevation increment;
s2, acquiring remote sensing image data of the lake at the corresponding moment by utilizing a remote sensing technology according to different moments, preprocessing the remote sensing image data, and acquiring the underwater minimum elevation H of the lake by referring to the data 0 ；
ΔH= H 1 - H 0 （2），
H 0 : the lowest elevation of the lake under water,
H 1 : a water level value at the 1 st moment;
s3, extracting lake surface water body by using the remote sensing image data in the step S2, and calculating the water surface area to obtain the water surface areas S corresponding to different moments under the same water level difference (t) ：
The water body is extracted according to the following extraction principle:
NDWI=(p(Green)-p(NIR))/(p(Green)+p(NIR))，
NDWI: the index of the water body is normalized,
p (Green): the remote sensing reflectivity of the green wave band,
p (NIR): near infrared band remote sensing reflectivity;
according to the result of NDWI extraction, the obtained data is imported into ArcGIS software to be calculated by a calculation geometry toolThe water surface area S corresponding to different time t under the same water level difference (t) ；
S4, calculating the increment delta V of the water storage capacity caused by continuous water level data change of the same water level difference according to the water level difference, the water surface area and the lake underwater minimum elevation data (t) Further obtaining the lake water storage capacity V corresponding to different moments t (t) ：
Assuming that the lake water volume changes to an irregular table body, the calculation formula is as follows:
(3) ，
(4)，
(5)，
S 1 : area of water surface at time 1 (km) 2 ），
S (t) : surface area (km) at time t 2 ），
S (t+1) : surface area (km) at time t+1 2 ），
H 0 : the lowest elevation of the lake under water,
H 1 : the water level value at the 1 st moment,
V 0 : volume from the water surface to the bottom of the lake at the first moment (km) 3 ），
ΔV (t) : lake water storage increment (km) at time t 3 ），
V (t) : lake water storage capacity (km) at time t 3 ），
Obtaining a relational expression of the water surface area and the water storage capacity of the lake at the moment t:
（6）；
and S5, fitting a total relation curve of the lake water surface area and the water storage capacity according to the obtained data of the lake water surface area and the water storage capacity at different moments under the same water level difference, and estimating the lake water storage capacity according to the lake water surface area data.
According to the invention, the water level data of the lake is obtained through the laser height measurement satellite ICESat-2, the time data under the same water level difference are obtained, the remote sensing image data of the lake are obtained and preprocessed by utilizing the remote sensing technology according to different time, the automatic extraction of the target water body is realized by utilizing the NDWI water body extraction technology, and the water surface area data of the lake is obtained. And finally, constructing a relation curve of the water surface area and the water storage capacity of the lake according to the water surface area data of the lake under the same water level difference and combining the underwater topography data of the lake, and further calculating the water storage capacity of the lake according to the surface area data. The invention can calculate the water storage capacity according to the surface area data with the assistance of the remote sensing image, and overcomes the defects of the prior method of firstly constructing the water level-area relation curve, then constructing the water level-water storage capacity relation curve and finally constructing the water level-area-water storage capacity relation curve, thereby greatly improving the efficiency and the practicability of lake water storage capacity calculation.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic view of a cross-section of a lake according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating remote sensing image data according to an embodiment of the present invention;
FIG. 4 is a graph showing the results of water extraction in accordance with an embodiment of the present invention.
Detailed Description
The invention will be further illustrated with reference to specific examples.
Examples: taking remote sensing image data of a certain lake and ICESat-2 data estimation of a laser altimeter satellite as an example.
The lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data comprises the following steps (see figure 1):
s1, acquiring corresponding water level data of lakes at different moments under the same elevation increment through a laser height measurement satellite ICESat-2, calculating the water level difference delta H under the same elevation increment, and recording continuous water level data H of the same water level difference (t) Corresponding time data t:
acquiring water level data H corresponding to different moments t under the same elevation increment of the lake according to the laser height measurement satellite ICESat-2 (t) (t=1, 2,3 … …, n), n representing the maximum moment, two water level values H are found, with a water level difference Δh (t+1) And H is (t) And recording the observation time for obtaining the corresponding water level value. Wherein H is (t+1) And H is (t) The difference deltah of (a) is a fixed value of 0.5 m, as shown in figure 2,
（1），
（2），
H (t+1) : a water level value (m) at time t+1,
H (t) : the water level value (m) at time t,
t: at different moments in time under the same water level difference,
Δh: the water level difference (m) between two adjacent moments;
the specific operation steps are as follows: entering a national ice and snow data center website (https:// nsidc. Org/data/ATL/versions/5), screening out required data according to date, range and product level (ATL 03), submitting orders, and downloading and counting required water level data after application.
S2, acquiring remote sensing image data of the lake at the corresponding moment by utilizing a remote sensing technology according to different moments, preprocessing the remote sensing image data, and acquiring the underwater minimum elevation H of the lake by referring to the data 0 ：
And finding out lake satellite remote sensing images under corresponding time according to water level observation time data obtained by screening the same water level difference, and preprocessing the remote sensing images, wherein the preprocessing comprises atmosphere correction, radiation calibration and image cutting. The remote sensing image data of a lake is shown in fig. 3.
S3, extracting lake surface water body by using the remote sensing image data in the step S2, and calculating the water surface area to obtain corresponding water at different moments under the same water level differenceArea S of surface (t) ：
The surface water body extraction is carried out on the pretreated remote sensing image, and the extraction principle is as follows:
NDWI=(p(Green)-p(NIR))/(p(Green)+p(NIR))，
NDWI: the index of the water body is normalized,
p (Green): the remote sensing reflectivity of the green wave band,
p (NIR): the remote sensing reflectivity of the near infrared band,
the specific operation comprises the following steps: based on ENVI5.3 software, basic Tools->Band Math, then input the expression in enter an expression: (float (b 2) -float (b 4))/(b2+b4), wherein b2 is green band, b4 is near infrared band, and the water index image can be obtained by selecting the derived position; next, the water body and the non-water body are distinguished, and the menu bar is sequentially selected: classification of>Decision Tree->Build New Decision Tree, click Node 1, input the calculation formula b1GT0.2 in the expression, select the water body index image just generated, click execution, can obtain the binarization result, wherein the water body is white. At available vector li st In s window, select file->export layers to shpfile, the water body can be converted into shp data.
According to the water NDWI extraction result (as shown in figure 4), the obtained data are imported into ArcGIS software, an AREA field is newly built in an attribute table, the field type is double-precision, and the water surface AREAs S corresponding to different moments t under the same water level difference are calculated through a calculation geometry tool (t) (t=1,2,3……,n)。
S4, calculating the increment delta V of the water storage capacity caused by continuous water level data change of the same water level difference according to the water level difference, the water surface area and the lake underwater minimum elevation data (t) Further obtaining the lake water storage capacity V corresponding to different moments t (t) ：
According to the water level, the water surface area and the underwater lowest elevation data, calculating the increment delta V of the water storage quantity caused by the continuous water level data change of the same water level difference (t) Volume V from the water surface to the bottom of the lake at the first moment 0 Finally, calculating the total water storage capacity V of the lake in an accumulated manner (t) 。
Assuming that the lake water volume changes to an irregular table body, the calculation formula is as follows:
(3) ，
(4)，
(5)，
S 1 : area of water surface at time 1 (km) 2 ），
S (t) : surface area (km) at time t 2 ），
S (t+1) : surface area (km) at time t+1 2 ），
H 0 : the lowest elevation of the lake under water,
H 1 : the water level value at the 1 st moment,
V 0 : volume from the water surface to the bottom of the lake at the first moment (km) 3 ），
ΔV (t) : lake water storage increment (km) at time t 3 ），
t: at different moments in time.
Obtaining a relational expression of the water surface area and the water storage capacity of the lake at the moment t:
（6），
substituting the formula (1) or the formula (2) into the formula (6) to obtain a relational expression (7) of the water surface area and the water storage capacity of the lake,
（7），
V (t) : lake water storage capacity (km) at time t 3 ），
S 1 : area of water surface at time 1 (km) 2 ），
S (t) : surface area (km) at time t 2 ），
S (t+1) : surface area (km) at time t+1 2 ），
t: different moments under the same water level difference.
S5, fitting a lake water surface area-water storage total relation curve according to the obtained data of the lake water surface areas and the water storage at different moments under the same water level difference:
the calculated water surface area of a certain lake at different moments, the water level data obtained by downloading and the calculated water storage capacity are shown in table 1:
table 1: data of area, water level and water storage capacity of certain lake water surface
。
Fitting a water surface area-water storage capacity relation curve according to the obtained water surface area and water storage capacity data:
V= 0.03S 2 - 7.6099S + 482.33 ，
v: water storage capacity (km) 3 ）
S: surface area (km) 2 ）。
Claims (4)
1. The lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data is characterized by comprising the following steps of:
s1, acquiring corresponding water level data at different moments under the same elevation increment of a lake through a laser height measurement satellite ICESat-2, calculating the water level difference delta H under the same elevation increment, and recording continuous water level data H of the same water level difference (t) Corresponding time data t;
s2, acquiring remote sensing image data of the lake at the corresponding moment by utilizing a remote sensing technology according to different moments, preprocessing the remote sensing image data, and acquiring the underwater minimum elevation H of the lake by referring to the data 0 ；
S3, extracting lake surface water body by utilizing the remote sensing image data in the step S2 and enteringCalculating the water surface area to obtain the corresponding water surface area S at different moments under the same water level difference (t) ；
S4, calculating the increment delta V of the water storage capacity caused by continuous water level data change of the same water level difference according to the water level difference, the water surface area and the lake underwater minimum elevation data (t) Further obtaining the lake water storage volumes V (t) corresponding to different moments t;
and S5, fitting a total relation curve of the lake water surface area and the water storage capacity according to the obtained data of the lake water surface area and the water storage capacity at different moments under the same water level difference, and estimating the lake water storage capacity according to the lake water surface area data.
2. The lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data according to claim 1, wherein the water level difference calculation formula is as follows:
ΔH= H (t+1) - H (t) （1），
ΔH= H 1 - H 0 （2），
H (t+1) : the water level value at time t+1,
H (t) : the water level value at the time t,
t: at different moments in time under the same water level difference,
H 0 : the lowest elevation of the lake under water,
H 1 : a water level value at the 1 st moment;
Δh: water level difference at the same elevation increment.
3. The lake water storage capacity estimation method based on remote sensing images and laser altimetry satellite data according to claim 1, wherein the water body extraction in the step S3 is based on the following extraction principle:
NDWI=(p(Green)-p(NIR))/(p(Green)+p(NIR))，
NDWI: the index of the water body is normalized,
p (Green): the remote sensing reflectivity of the green wave band,
p (NIR): near infrared band remote sensing reflectivity;
according to the extraction result of the NDWI of the water body, the obtained data are imported into ArcGIS software, and the water surface areas S corresponding to different moments t under the same water level difference are calculated through a calculation geometry tool (t) 。
4. The method for estimating water storage capacity of a lake based on remote sensing image and laser altimetry satellite data as set forth in claim 1, wherein the increment Δv of the water storage capacity in step S4 (t) And lake water storage volume V (t) The calculation of (1) assumes that the lake water volume changes to an irregular table body, and the formula is:
(3) ，
(4)，
(5)，
S 1 : the water surface area at time 1,
S (t) : the water surface area at the time t,
S (t+1) : the water surface area at time t+1,
H 0 : the lowest elevation of the lake under water,
H 1 : the water level value at the 1 st moment,
V 0 : the volume from the water surface to the bottom of the lake at the first moment,
ΔV (t) : the lake water storage capacity increment at the t moment,
obtaining a relational expression of the water surface area and the water storage capacity of the lake at the moment t:
。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311514475.8A CN117253158A (en) | 2023-11-15 | 2023-11-15 | Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311514475.8A CN117253158A (en) | 2023-11-15 | 2023-11-15 | Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117253158A true CN117253158A (en) | 2023-12-19 |
Family
ID=89126668
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311514475.8A Pending CN117253158A (en) | 2023-11-15 | 2023-11-15 | Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117253158A (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106354992A (en) * | 2016-08-12 | 2017-01-25 | 中国水利水电科学研究院 | Lake water volume storage variable assessment method based on multi-temporal remote-sensing image and DEM |
| US20200149888A1 (en) * | 2018-11-08 | 2020-05-14 | Tsinghua University | Method and device for monitoring water volume change, computer device and storage medium |
| CN112966570A (en) * | 2021-02-07 | 2021-06-15 | 山东锋士信息技术有限公司 | Reservoir water storage capacity metering method based on satellite remote sensing and DEM data |
| CN114152302A (en) * | 2022-02-07 | 2022-03-08 | 中国科学院地理科学与资源研究所 | Lake water storage variation estimation method, system, electronic device and medium |
| WO2023281289A1 (en) * | 2021-07-07 | 2023-01-12 | Kayrros | Method and system for the automatic monitoring of a liquid resource stored in a lake using satellite imagery |
| CN116642469A (en) * | 2023-04-18 | 2023-08-25 | 中国水利水电科学研究院 | Lake and reservoir water storage space-time change remote sensing monitoring method based on multi-source satellite cooperation |
-
2023
- 2023-11-15 CN CN202311514475.8A patent/CN117253158A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106354992A (en) * | 2016-08-12 | 2017-01-25 | 中国水利水电科学研究院 | Lake water volume storage variable assessment method based on multi-temporal remote-sensing image and DEM |
| US20200149888A1 (en) * | 2018-11-08 | 2020-05-14 | Tsinghua University | Method and device for monitoring water volume change, computer device and storage medium |
| CN112966570A (en) * | 2021-02-07 | 2021-06-15 | 山东锋士信息技术有限公司 | Reservoir water storage capacity metering method based on satellite remote sensing and DEM data |
| WO2023281289A1 (en) * | 2021-07-07 | 2023-01-12 | Kayrros | Method and system for the automatic monitoring of a liquid resource stored in a lake using satellite imagery |
| CN114152302A (en) * | 2022-02-07 | 2022-03-08 | 中国科学院地理科学与资源研究所 | Lake water storage variation estimation method, system, electronic device and medium |
| CN116642469A (en) * | 2023-04-18 | 2023-08-25 | 中国水利水电科学研究院 | Lake and reservoir water storage space-time change remote sensing monitoring method based on multi-source satellite cooperation |
Non-Patent Citations (3)
| Title |
|---|
| WEGAYEHU ASFAW ET.AL: "Combining multisource satellite data to estimate storage variation of a lake in the Rift Valley Basin, Ethiopia", 《INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION》, pages 1 - 13 * |
| 李闯: "多源遥感水库蓄水量估算研究与系统实现", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》, pages 30 - 31 * |
| 杨雄丹;李国元;王佩贤;常晓涛;么嘉棋;: "星载激光测高结合遥感影像的青海湖变化监测", 测绘科学, no. 05, pages 83 - 91 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11231519B2 (en) | Method and device for simulating discharge, and computer device | |
| CN101334896B (en) | Processing method for measuring sub-pixel rim of digital picture | |
| CN106529164A (en) | Method and system for acquiring ground water storage variation value by combining GRACE satellite | |
| CN105118090A (en) | Adaptive point-cloud filtering method for complex terrain structure | |
| CN110929390B (en) | Numerical simulation detection method based on groundwater hydrogeology test | |
| CN110686653B (en) | Reservoir storage variation remote sensing monitoring method without ground hydrological data support | |
| Shakoor et al. | DEVELOPMENT OF GROUNDWATER FLOW MODEL (MODFLOW) TO SIMULATE THE ESCALATING GROUNDWATER PUMPING IN THE PUNJAB, PAKISTAN. | |
| CN108154193A (en) | A kind of long-term sequence precipitation data NO emissions reduction method | |
| CN113095694A (en) | Method for constructing rainfall sand transportation model suitable for multi-landform type area | |
| CN116401327A (en) | Storm flood calculation auxiliary system for small and medium-sized watershed design in non-data area | |
| CN104091040A (en) | Soil infiltrability calculation method | |
| CN113888383A (en) | Coastal ecosystem carbon reservoir estimation method | |
| CN117253158A (en) | Lake water storage amount estimation method based on remote sensing image and laser altimetry satellite data | |
| Nadeem et al. | Quantification of temporal variations in groundwater level using satellite imagery technique: A case study of Rachna Doab, Pakistan | |
| CN112966657B (en) | Remote sensing automatic classification method for large-scale water coverage | |
| CN115965878B (en) | GEE-based inversion monitoring method for suspended sediment in Qinghai-Tibet plateau river | |
| CN106709992A (en) | Information entropy theory-based submarine geomorphy complexity representation method | |
| Schmid et al. | Development of a Regional Groundwater Model for the Indus Basin Irrigation System of Pakistan | |
| CN115221711A (en) | Irrigation water consumption accurate calculation method and device suitable for embedded equipment | |
| Aghbolagh et al. | The study of changes in Ardabil plain groundwater level using GIS | |
| Yong et al. | The enhanced construction method for intertidal terrain of offshore sandbanks by remote sensing | |
| CN112380984A (en) | Remote sensing-based saline marsh vegetation slow flow capacity space evaluation method | |
| CN106595798B (en) | A method of aquifer parameter is sought automatically using high frequency level of ground water data | |
| Mbatya et al. | Assessment of reservoir sedimentation level and storage capacity using remotely sensed data for Namadope Reservoir in Luuka District, Uganda | |
| CN113687042B (en) | Lake sediment buried organic carbon estimation method based on water amount |
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 |