CN104537718B - Large river basins depression filling preprocess method based on gridded DEM - Google Patents
Large river basins depression filling preprocess method based on gridded DEM Download PDFInfo
- Publication number
- CN104537718B CN104537718B CN201410845310.3A CN201410845310A CN104537718B CN 104537718 B CN104537718 B CN 104537718B CN 201410845310 A CN201410845310 A CN 201410845310A CN 104537718 B CN104537718 B CN 104537718B
- Authority
- CN
- China
- Prior art keywords
- pixel
- priority queues
- dem
- elevation
- current
- 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.)
- Expired - Fee Related
Links
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
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Geometry (AREA)
- Software Systems (AREA)
- Remote Sensing (AREA)
- Computer Graphics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Alarm Systems (AREA)
- Image Processing (AREA)
- Revetment (AREA)
Abstract
Basin depression filling preprocess method of the one kind based on grid digital elevation model (DEM), it is related to the basin numeral ditch extraction method based on gridded DEM in GIS-Geographic Information System and hydrological distribution model, can be especially applied to the method for large river basins.The present invention utilizes a Priority Queues with elevation as keyword, at the minimum pixel in DEM edges internally flood pixel one by one, record each pixel floods order, obtains flooding ordered matrix.All pixels adjacent with sea add Priority Queues, the minimum pixel of elevation is ejected by Priority Queues every time, sea level height rises to the pixel highly, record the pixel floods order, then elevation in the neighborhood pixel of the pixel is risen into sea level height less than all pixels on sea, and is added in Priority Queues.The tasks such as flow direction extraction and river course network extraction are completed instead of original dem data collection by flooding ordered matrix, the complete river system network of large river basins is can extract out.
Description
Technical field
The present invention relates to the basin based on grid digital elevation model in GIS-Geographic Information System and hydrological distribution model
Digital ditch extraction method, can especially be applied to the depression filling preprocess method of large river basins.
Background technology
It is to realize the weight of hydrological distribution model numerical simulation to extract basin water system information based on digital elevation model (DEM)
Want method.The extraction of basin water system information is including calculating flow direction, accumulation flow direction, water type distribution and catchment network etc..Often at present
Above- mentioned information is obtained to method (being abbreviated as D8 methods) with eight, but these information success are extracted and additionally depended on to depression
And the pretreatment of level land pixel.Many is had at present and can be used for the Software tool of these tasks, such as famous GIS business softwares
Spatial analysis instrument in ArcGIS, plug-in unit River Tools, Global Mapper softwares of ENVI etc., these softwares for
Less scale or the little basin of geospatial area can successfully extract complete water system.Because large river basins are related to
Scope is wider, and data volume is larger, can there is a large amount of vertical errors, and identical " level land " pixel of elevation in DEM, even if
Still it is difficult to correctly extract complete water system by the DEM of depression filling treatment.Fact proved, for Upper-middle Reaches of The Yellow River basin,
Still cannot correctly be extracted using above-mentioned Software tool, its output result is a pile " beheaded river ".Using Plachon&Doubarx
(2002)[ Planchon, O. and Darboux, F., 2002. A fast, simple and versatile
algorithm to fill the depressions of digital elevation models. CATENA, 46(2-
3):159-176.] method and its various modifications, what is also obtained is similar " beheaded river ".Liu [Liu Yonghe,
2009.Another Fast and Simple DEM Depression-Filling Algorithm Based on
Priority Queue tructure. Atmospheric and Oceanic Science Letters, 2(4):214-
219.] a kind of depression fill method is proposed, the method has stronger adaptability, but for being flowed greatly as the Huanghe valley
Domain, complete water system information cannot be equally obtained by depression filling.How in the DEM that data volume is larger, spatial extent is big
Correct water system information of extracting is still a problem for needing to solve.
The content of the invention
It is the correct efficient water system information that large river basins are extracted on the basis of gridded DEM, the present invention provides one kind with low-lying area
Ground filling step is the processing method of core.Its basic thought is come from DEM by the depression fill method based on Priority Queues
Start inside " seawater floods " pixel one by one at the minimum pixel in edge, record the order that each pixel is submerged.Due to each picture
Unit can possess a different sequence number, and elevation pixel higher, and the sequence number of acquisition is bigger;Elevation identical is more
Individual pixel, flooding time is more late, and its sequence number is bigger.Replace original DEM elevation matrixes with sequence number matrix is flooded come complete
Matrix, water type distribution matrix, and other catchment network information are flowed into matrix, accumulation is flowed to.
Technical scheme is comprised the following steps:
1. create and initialize a Priority Queues object with floating number as keyword;
2. the order by the pixel on four external boundaries of gridded DEM according to elevation from low to high adds Priority Queues;
3. work as Priority Queues not space-time, continue executing with the 4th step;Performed otherwise since the 12nd step;
4. ejection comes the pixel of foremost, and it is that elevation is minimum in all pixels deposited in Priority Queues, it
Used as current pixel, its elevation is used as current sea level altitude;
5. it is that current pixel sets and floods sequence number by counter, and this numbering is stored in floods in ordered matrix
On relevant position;
If 6. current pixel has been floodage, returns to the 3rd step and perform, performed after being otherwise marked as floodage
7th step;
7. all neighborhood pixels not being submerged on 8 directions around current pixel are found out;
8. the neighborhood pixel that will be less than sea level performs step 9-10;Neighborhood pixel higher than sea level is directly added into preferentially
Queue, is back to the 3rd step afterwards;
9. the neighborhood pixel that will not yet flood adds Priority Queues, and is marked as facing bank state;
10. current neighborhood elevation changes the height for being set to current sea level;Return to the 8th step and other neighborhood pixels are completed same
Operation;
11. are back to the 3rd step;
Ordered matrix is flooded in 12. outputs.
Depression pixel and nothing are filled in completing DEM the beneficial effects of the invention are as follows the processing method based on Priority Queues
While data pixel, and obtain and flood sequence number matrix, original DEM elevations are replaced with it to complete follow-up flow direction and water
It is the extraction of the network information, " level land " pixel in former DEM caused by the identical pixel of elevation can be prevented effectively from and hinders ditch extraction
Problem, the digital drainage network model consistent with true water system can be obtained, can be used for any size basin extract.
The water system that the inventive method has successfully realized Upper-middle Reaches of The Yellow River basin is correctly extracted, and shows that the method can be just
The filling of depression and area without data in DEM is really completed, and the complete river system network of large river basins can be extracted.
Brief description of the drawings
Fig. 1 is the execution flow of the inventive method.
Fig. 2 marks arrays example (1 represents untreated pixel, and 0 represents that, by water submerged pixel, bank pixel is faced in 2 expressions).
Fig. 3 is a small-sized DEM example.
Example DEM after the filling of Fig. 4 depression (zero pixel was depression pixel originally).
Fig. 5 perform export after this method flood ordered matrix (i.e. orders arrays).
Fig. 6 is to flood the Huanghe valley water system extracted on the basis of ordered matrix.
Specific embodiment
Complete implementing procedure is shown in Fig. 1.
(1) preparation of gridded DEM data set
Some non-data regions are there may be in gridded DEM data set, it is necessary to scan these no data pixels.To by remote sensing
The dem data collection that mode is obtained, this kind of pixel is typically found in mountain area or lake position.Their elevation can be set to one
Minimum value, such as -9999, be so the equal of that it is treated as depression present in DEM.Implement the inventive method it
Afterwards, all depression pixels are filled, and realize the interpolation to data, from without influenceing the extraction to trunk river.
(2) establishment of Priority Queues
Need voluntarily to write a Priority Queues structure type, or utilize ready-made Priority Queues structure type.Priority Queues
Keyword be floating type, the height value of correspondence DEM, storage information associated by each keyword is the address of DEM pixels, i.e.,
Ranks position., with ascending sort, the element (i.e. pixel) of foremost is right in Priority Queues for keyword in Priority Queues
Answer minimum key assignments (i.e. elevation).When arbitrarily one element of insertion in Priority Queues, it should value according to keyword come by
Sequence is inserted, to ensure that it is correct that Priority Queues is always maintained at keyword rank.The element always position ejected from Priority Queues every time
In the element that queue forefront, keyword are minimum.
(3) state of pixel and the relation for passing in and out Priority Queues
Pixel point is initial, flood, face three kinds of states of bank, is marked with value 1,0,2 respectively.It is every in Priority Queues
Pixel, corresponding state should all be set to 2, and expression treatment is not fully completed yet;Every pixel for having been ejected from Priority Queues,
Corresponding state should all be set to 0, and this kind of pixel will no longer be required to treatment.When a certain pixel is ejected from Priority Queues, meaning
Taste it and is submerged, and at this moment sea level height should be risen on the elevation of the pixel.And the neighborhood pixel that it those are not submerged
Become to face bank pixel.If face bank pixel less than sea level height, its elevation needs to rise to sea level height, and this is depression filling
Key operation.Every new bank pixel that faces occurs, and not only needs setting to face bank state, also needs to be added into Priority Queues.
(4) array and counter are initialized
In order to mark the treatment state of all pixels, it is necessary to create one and DEM ranks number identical integer arrays, below
The array is referred to title marks;Marks is the array that whether state " is flooded " for depositing pixel, and its element value can only
It is 0,1 and 2.Element value represents that pixel " is flooded " when being 0, and the pixel will be not required to be processed again;Element value is represented when being 1
Pixel both " was not flooded ", also not on bank;Element value represents that pixel is located at bank when being 2, but not yet " is flooded ".marks
Middle all elements value all needs to be initialized as 1.Indicative significance about marks arrays refers to Fig. 2.
Order is flooded in order to record each pixel, in addition it is also necessary to create another integer array, referred to orders below.For
Order is flooded in tracking, in addition it is also necessary to declare an integer counter variables D Count again, its initial value is set to 0.Whenever one new
When pixel is submerged, the value of DCount just increases 1, while this value is write on the position of corresponding current pixel in orders arrays.
Here so-called " flooding ", refers to that, when a record for pixel (or address) is ejected from Priority Queues, its state will be by
It is set to floodage.Therefore, when ejecting a pixel from Priority Queues every time, the value of DCount increases 1, current for recording
Order when pixel is ejected, while the value of the current pixel of correspondence is set to the value of DCount in orders.
(5) to the filling of depression pixel
Filling process to depression pixel can be regarded as what is realized by two steps:The first step is to use current not yet extra large
Water submerged but face (marks be labeled as 2) minimum pixel of elevation of bank and assume sea level altitude;Second step is to update current
Face 8 elevations of neighborhood pixel of bank pixel, i.e., when the elevation of a certain neighborhood pixel is also lower than current sea level, then need it is high
Journey is promoted to sea level height, to add wait in Priority Queues and is submerged, while the marks mark values of the neighborhood pixel should be set to
2, to ensure the marks all 2 of all pixels in Priority Queues (be and face bank pixel).
(6) ordered matrix is flooded in output
Ordered matrix (orders arrays) is flooded by the data of instead original DEM by what the inventive method calculating was obtained
Collection, can be completed using conventional D8 methods on its basis follow-up flow direction, accumulate flow direction, river course catchment network,
The classification of Strahler river courses, basin perimeter etc. extract task.
(8) result verification
Fig. 3 is a small-sized dem data example, by the inventive method process after, obtained depression filling after
DEM(Fig. 4), while having obtained flooding ordered matrix (i.e. orders arrays) (Fig. 5), without the numbering for repeating in the matrix, keep away
Exempt from there is the situation that elevation is sufficiently close in former DEM, and also do not existed depression pixel in matrix, thus can be used for extracting
River channel information.For covering north of China and the DEM on a large scale of the Huanghe valley, it contains many no data pixel blocks, through this
What is obtained after inventive method treatment floods ordered matrix, and it shows that non-data regions have been filled, and flooding ordered matrix also can be anti-
Reflect the topography comparison situation of former DEM.Will drown out ordered matrix and replace original DEM, carry out conventional flow direction and extract and ditch extraction mistake
Journey, obtains Huanghe valley water system situation(Fig. 6), show that extracted water system is complete, and with real Yellow River System ten
Tap is near.
Claims (2)
1. preprocess method is filled in a kind of large river basins depression based on gridded DEM, it is characterised in that comprised the following steps:
(1) create and initialize a Priority Queues object with floating number as keyword;
(2) orders of the by the pixel on four external boundaries of gridded DEM according to elevation from low to high adds Priority Queues;
(3) is when Priority Queues not space-time, continues executing with the(4)Step;Otherwise from(12)Step starts to perform;
(4) ejection comes the pixel of foremost, and it is the minimum pixel of elevation in all pixels deposited in Priority Queues, it
Used as current pixel, its elevation is used as current sea level altitude;
(5) is that sequence number is flooded in the setting of current pixel by counter, and this numbering is stored in the phase flooded in ordered matrix
Answer on position;
(6) if the current pixels of have been floodages, the is returned(3)Step is performed, and is held after being otherwise marked as floodage
The step of row (7th);
(7) all neighborhood pixels not being submerged on 8 directions around current pixel are found out;
(8) the neighborhood pixel that will be less than sea level performs step(9)-(10);It is directly added into higher than the neighborhood pixel on sea level excellent
First queue, is back to afterwards(3)Step;
(9) will not yet flood but face the neighborhood pixel addition Priority Queues of bank, and be marked as facing bank pixel;
(10) current neighborhood elevation changes the height for being set to current sea level;Return to the(8)Other neighborhood pixels are completed same by step
Operation;
(11) it is back to(3)Step;
(12) ordered matrix is flooded in output;
Flood ordered matrix will by original DEM as an alternative come after the completion of afterflow to extract and river course network extraction step data
Collection.
2. method according to claim 1, it is characterised in that:Need to set up one it is identical with original DEM ranks sums, be used for
The array of sequence number is flooded in storage, is referred to as flooding ordered matrix, when having pixel to eject in each Priority Queues, it is necessary to the picture
Unit sets one and floods sequence number, and it is stored on the position for flooding in ordered matrix corresponding current pixel ranks number.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410845310.3A CN104537718B (en) | 2014-12-31 | 2014-12-31 | Large river basins depression filling preprocess method based on gridded DEM |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410845310.3A CN104537718B (en) | 2014-12-31 | 2014-12-31 | Large river basins depression filling preprocess method based on gridded DEM |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104537718A CN104537718A (en) | 2015-04-22 |
CN104537718B true CN104537718B (en) | 2017-06-16 |
Family
ID=52853237
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410845310.3A Expired - Fee Related CN104537718B (en) | 2014-12-31 | 2014-12-31 | Large river basins depression filling preprocess method based on gridded DEM |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104537718B (en) |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101188022A (en) * | 2007-12-20 | 2008-05-28 | 浙江大学 | A flood submerging analysis method oriented to a large city disaster demonstration |
WO2008100645A1 (en) * | 2007-02-15 | 2008-08-21 | Baker Hughes Incorporated | Method of preparing sea bed for jack up rig deployment |
CN102034003A (en) * | 2010-12-16 | 2011-04-27 | 南京大学 | Watershed hydrological model design method based on storage capacity curve and TOPMODEL |
CN102902844A (en) * | 2012-09-03 | 2013-01-30 | 南京师范大学 | Sub-water basin partitioning method based on DEM (Dynamic Effect Model) data with large data quantity |
-
2014
- 2014-12-31 CN CN201410845310.3A patent/CN104537718B/en not_active Expired - Fee Related
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2008100645A1 (en) * | 2007-02-15 | 2008-08-21 | Baker Hughes Incorporated | Method of preparing sea bed for jack up rig deployment |
CN101188022A (en) * | 2007-12-20 | 2008-05-28 | 浙江大学 | A flood submerging analysis method oriented to a large city disaster demonstration |
CN102034003A (en) * | 2010-12-16 | 2011-04-27 | 南京大学 | Watershed hydrological model design method based on storage capacity curve and TOPMODEL |
CN102902844A (en) * | 2012-09-03 | 2013-01-30 | 南京师范大学 | Sub-water basin partitioning method based on DEM (Dynamic Effect Model) data with large data quantity |
Non-Patent Citations (4)
Title |
---|
Another Fast and Simple DEM Depression-Filling Algorithm Based on Priority Queue Structure;Liu Yong-He 等;《ATMOSPHERIC AND OCEANIC SCIENCE LETTERS》;20090716;第2卷(第4期);第215页左栏第2节第2段、右栏第2-4段、第216页左栏第1-2段、Table3 * |
基于DEM模型的新填洼算法;于淼 等;《地球信息科学学报》;20090215;第50-55页 * |
适于CUDA 并行处理的扫描推进式DEM 洼地填充算法;刘永和 等;《适于CUDA 并行处理的扫描推进式DEM洼地填充算法》;20141223;第1-8页 * |
防洪决策中灾情评估***的研究;高燕;《中国优秀博硕士学位论文全文数据库 (硕士) 工程科技Ⅱ辑》;20060715;正文第42页第2段 * |
Also Published As
Publication number | Publication date |
---|---|
CN104537718A (en) | 2015-04-22 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Lindsay | Efficient hybrid breaching‐filling sink removal methods for flow path enforcement in digital elevation models | |
Lahousse et al. | Landslide mapping with multi-scale object-based image analysis–a case study in the Baichi watershed, Taiwan | |
CN106981092B (en) | Priority-Flood-based internal flow domain extraction method | |
CN102426690B (en) | Method for secretly sharing and restoring digital image | |
Hodges | Representing hydrodynamically important blocking features in coastal or riverine lidar topography | |
CN110222760A (en) | A kind of fast image processing method based on winograd algorithm | |
CN103578093A (en) | Image registration method and device and augmented reality system | |
CN103049496A (en) | Method, apparatus and device for dividing multiple users into user groups | |
Rosim et al. | TerraHidro: a distributed hydrology modelling system with high quality drainage extraction | |
Yu et al. | A new algorithm for shoreline extraction from satellite imagery with non-separable wavelet and level set method | |
CN104217436A (en) | SAR image segmentation method based on multiple feature united sparse graph | |
CN105488434A (en) | Mark based vector map completeness authentication method | |
Bahrawi et al. | Simulation of sea level rise and its impacts on the western coastal area of Saudi Arabia | |
CN113643365A (en) | Camera pose estimation method, device, equipment and readable storage medium | |
CN109344850A (en) | A kind of water meter automatic testing method based on YOLO | |
CN112819963B (en) | Batch differential modeling method for tree branch model and related equipment | |
CN104537718B (en) | Large river basins depression filling preprocess method based on gridded DEM | |
CN114913422A (en) | Karst rocky mountain area soil and water loss field monitoring device | |
Zhang et al. | Integrated deep and shallow networks for salient object detection | |
Mishra | Geomorphic regionalization of coastal zone using geospatial technology | |
Ye et al. | A parallel Python-based tool for meshing watershed rivers at continental scale | |
CN111242825B (en) | Water depth feature-based ENC electronic nautical chart zero-watermarking method | |
CN116415318B (en) | Modeling method for hydrologic connectivity of lake in inner flow area based on mathematical morphology | |
CN110334137B (en) | Sea island reef form change quantitative description extraction method based on tidal process | |
CN115035421A (en) | Mangrove forest ecological beach-fixing sand-binding method, device, equipment and storage medium |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20170616 Termination date: 20191231 |
|
CF01 | Termination of patent right due to non-payment of annual fee |