CN104574512A - Multi-scale DEM (digital elevation model) construction method considering topographical semantic information - Google Patents

Multi-scale DEM (digital elevation model) construction method considering topographical semantic information Download PDF

Info

Publication number
CN104574512A
CN104574512A CN201410836988.5A CN201410836988A CN104574512A CN 104574512 A CN104574512 A CN 104574512A CN 201410836988 A CN201410836988 A CN 201410836988A CN 104574512 A CN104574512 A CN 104574512A
Authority
CN
China
Prior art keywords
dem
point
tsi
importance degree
scale
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
Application number
CN201410836988.5A
Other languages
Chinese (zh)
Inventor
董有福
汤国安
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to CN201410836988.5A priority Critical patent/CN104574512A/en
Publication of CN104574512A publication Critical patent/CN104574512A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G06T17/05Geographic 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)
  • Image Analysis (AREA)

Abstract

The invention discloses a multi-scale DEM (digital elevation model) construction method considering topographical semantic information. The method comprises the following steps: calculating a DEM point location local geometric importance degree TSIlocal(terrain significance index) for a DEM point location local importance degree; determining a semantic importance degree weighing allocation scheme of topographic feature points according to the type of the topographic feature points and topographic hierarchical structures, and calculating a DEM point location global semantic importance degree TSIglobal; measuring and extracting a DEM point location comprehensive importance degree index TSI; determining a TSI threshold value according to a corresponding relation between the scale size of a reconstructing target DEM which is obtained by comparison and the threshold value of the comprehensive importance degree index TSI; choosing a candidate topographic feature points; performing spatial interpolation, and completing target scales to construct DEM. According to the method, high-grade main geomorphic elements are preferentially reserved, and secondary-grade geomorphic elements are gradually abandoned, so that topographical framework features under different scale conditions can be kept, maintaining the consistency between a multi-scale DEM construction result and the application thereof is facilitated, and the practical effect of multi-scale DEM construction technology is effectively improved so as to meet multi-scale DEM application demand of different social levels.

Description

A kind of multiple dimensioned DEM construction method taking landform semantic information into account
Technical field
The present invention relates to a kind of multiple dimensioned DEM construction method, particularly a kind of multiple dimensioned DEM construction method taking landform semantic information into account.
Background technology
Digital elevation model (Digital Elevation Model, DEM), as the important numbers carrier of terrain information, is the core data source of carrying out spatial analysis and geoscience modeling.Flourishing in the world countrynot only establish the multiple scale DEM covering this country, simultaneously also start to advance high precision, high resolution DEM, and Global Scale SRTM DEM, ASTER GDEM construction; In China, complete the foundation covering nationwide 1:100 ten thousand, 1:25 ten thousand, 1:5 ten thousand dem data storehouse successively, among 1:1 ten thousand DEM is also actively building, nationalplay an increasingly important role in economy, national defense construction and scientific research.
But, the DEM of limited several engineer's scale often can not meet the practical application request of engineering project and scientific research, the dem data of existing fixed resolution does not usually mate with geoanalysis model data yardstick, thus have influence on reliability and the validity of geoanalysis result, need the dem data building multiple dimensioned sequence badly.In addition, wide-range terrain scene real-time visual, also needs dynamically to generate multiple dimensioned DEM.Therefore, be very necessary based on existing large scale DEM automatic acquisition small scale DEM.Meanwhile, along with countrythe foundation in succession of large scale DEM, and various novelhigh resolution sensor, as the appearance of LiDAR, InSAR, SAR etc., makes DEM more rapid, flexible on data acquiring mode, thus provides good Data support for carrying out the expression of multiple dimensioned landform based on high accuracy DEM.
With regard to building the method in multiple dimensioned dem data storehouse at present, can be summed up as two kinds of major programmes, one is based on dissimilar and different scale data source, according to respective standard and different operation independentproduce multiple dimensioned dem data storehouse (to be called independentstructure method), two is based on single large scale dem data source, obtains multiple dimensioned DEM (being called Terrain Simplification method) by Terrain Simplification mode.
For independentstructure method, current each countryusually based on independentstructure method produces multiple dimensioned dem data storehouse, and the dem data storehouse that this multiple engineer's scale coexists, while bringing great convenience to application, but exists the problem that some are difficult to avoid.(1) independentthe several scale DEM that structure method is produced often can not meet practical application request.(2) independentbuild multiple dimensioned DEM method and there is more serious data redundancy and a Data Update difficult problem, this is because terrain data amount is huge, the mode data redundancy that multi-scale DEM coexists is comparatively outstanding; Simultaneously for the same area based on dissimilar and different scale data source independentbuild storehouse, when regional feature feature changes, need to carry out Resurvey and amendment to different types of data source, and repeat whole DEM and build comprehensive renewal that storehouse process just can complete different scale dem data.(3) independentbuild multiple dimensioned DEM method meetingthe inconsistency producing terrain feature modeling result inconsistency and bring to application result.This is because, based on dissimilar or different scale data source, according to respective standard and different operation independentwhen building multiple dimensioned dem data storehouse, the incident inconsistency that will be the same area terrain modeling result; On the other hand, the inconsistency of different scale DEM terrain modeling result, brings the inconsistency of terrain analysis application result simultaneously.Such as, in the landform of producing different scale figureduring data, often need according to system figurethe principle of compositionality carries out smoothing processing to some extent to level line, so, by different scale landform figureas the DEM that data source is produced, although good 3-D display effect can be obtained, but then there is larger uncertainty in the quantification terrain parameter therefrom obtained or terrain feature key element, as relatively obvious in same charge for remittance line or watershed line skewed logic on different scale DEM ( accompanying drawing 1with fig. 2), thus reliability and the suitability of subsequently Epidemiological Analysis and application can be had influence on.
For Terrain Simplification method, be the common method building multiple dimensioned dem data storehouse, due to using existing large scale DEM as building the data source of multiple dimensioned DEM, with independentstructure method is compared, have data redundancy lower, upgrade very fast, the relative advantages of higher of the degree of consistency.At present, relevant DEM Methods of Terrain Simplification is very many, according to the ground areas size considered when accepting or rejecting ground point in Terrain Simplification process, DEM Methods of Terrain Simplification can be summed up as two large main Types: one is the DEM Terrain Simplification based on local neighborhood, and two is the DEM Terrain Simplifications based on global structure.The former has by representative algorithm: stratification, vital point method, tolerance method, selective filter method etc., and this class methods Main Basis local neighborhood relief form intensity of variation is accepted or rejected ground point, and Problems existing is, more responsive to topography variation among a small circle; Many terrain feature points be positioned on landform skeleton line, because Local terrain changes amplitude not quite and is easily left in the basket, therefore, Terrain Simplification result lacks the precision controlling of the overall situation.In addition, also has the local landform shortcut calculation that a few class is special, as resampling method, global filtering method, mathematics morphology, wavelet analysis method etc., these algorithms have done identical smoothing processing to each point of DEM, do not meet the Terrain Simplification principle of " getting main house ", result is that mountain peak is scabbled, cheuch lifting, causes the distortion to a certain degree of overall landform skeleton.DEM Terrain Simplification basic thought based on overall topographic structure is, analyzes spatial relationship between landform characteristic sum topographic entity, thus determine topocentric choice and degree of integration by extracting and evaluate topographic structure line.For this reason, there is the algorithm of a large amount of extraction structure lines, summed up and get up to have analytical method, simulation and mixing method that the two combines.Topographic structure line short cut technique is topographic structure line due to reasonable employment, thus avoid the distortion of landform shape, but landform structure lines importance degree in Terrain Simplification process is lacked quantize further to distinguish at present, not easily determine that different topographic structure lines is applicable to the DEM with which kind of yardstick of reconstruct.In addition, three-dimensional douglas' method is a kind of representational DEM Terrain Simplification algorithm taking landform global structure into account, the method is by judging that the distance of dimensionally form point and specific basal plane decides it and accepts or rejects, thus complete three-dimensional topocentric simplify processes, achieve " getting main house " principle that Terrain Simplification is followed, landform overall profile can be kept preferably; But terrain feature point is accepted or rejected and is remained based on landform geometric properties, often be difficult to consider landform self system hierarchy and structure and spatial coherence, and unique point is chosen in process and is subject to the impact of the factor such as direction of scanning, initial basal plane, require relatively high to computational resource, when regional extent is comparatively large or simplify yardstick increase, its relevance measure is corresponding reduction then.
accompanying drawing 3with fig. 4it is candidate's terrain feature point signal of application vital point method and three-dimensional douglas' method reservation when carrying out Terrain Simplification figure, in order to ensure two kinds of method comparabilities, in figurethe candidate feature retained is counted out identical.Visible due to different terrain short-cut method reconnaissance principle difference, the candidate feature space of points distributional difference for building multiple dimensioned DEM in Terrain Simplification process is obvious, and so, result DEM then can exist bigger difference on modeling accuracy and effect.
At present, the level of detail technology LOD (Level-of-Detail) applying Terrain Simplification method obtains extensive application in large scene terrain environment is visual.Namely the acquisition of the same area numerical cutting tool is gone from the simple to the complex, by slightly representing to some yardsticks of essence, selecting the model of different resolution according to specific needs, and achieve good display effect during drafting.LOD technology experienced by discrete LOD model, LOD Model and multiresolution LOD model three developing stage.When adopting the discrete LOD model established in advance, although calculate simple and draw speed, level is limited easily there is vision " jump ", actual needs can not be met under many circumstances, and provide abundant level both unrealistic, not only there is data redundancy, require to have network response fast and transmittability simultaneously.When adopting LOD Model, frequently change with viewpoint along with scene constantly switches, topographic details consecutive variations can be realized, but require higher to computer hardware and processing capability in real time; If adopt the dynamic multiple resolution ratio LOD approximate model relevant to viewpoint, easily there is connecting cracks between same level different resolution terrain block, had a strong impact on the visual level of terrain modeling and efficiency.Although LOD algorithm is more, be often difficult to the framework characteristic keeping landform in actual applications, make then to become relatively outstanding along with resolution reduces the landform collimation error.
In DEM Terrain Simplification scheme, choosing terrain feature point by the importance of metewand DEM grid points in the modeling of earth's surface, to reconstruct multiple dimensioned DEM be its key problem in technology.But, the method of current differentiation DEM grid point importance degree in landform is expressed, mainly be described from local landform geometric properties, the system quantifies research of relative shortage landform unique point semantic information aspect, cause in multiple dimensioned DEM landform expression process, the tap drain valley point of relatively " putting down " and main ridge point are more easily left in the basket, thus occur that mountain peak is scabbled, the phenomenon of cheuch lifting, cause the distortion to a certain degree of overall landforms skeleton; Further, express and apply easily to multiple dimensioned DEM landform and bring inconsistency.As: there is certain skewed logic in the watershed line extracted from different scale result DEM and charge for remittance line, can not ensure matching relationship during mutual fit.In traditional anthropogenic landforms's combined process, can the thinking of brain abstract be passed through, fully take into account the semantic features such as relief elements type, hierarchical organization and spatial relationship, realize that major landform key element retains, secondary atural object key element gives up gradually.And in current multiple dimensioned DEM restructuring procedure, be difficult to take terrain feature system hierarchy and structure, mutually space constraint relation into account, the multiple dimensioned landforms " getting main house " are expressed principle and are not easily realized, thus constrain effective raising of DEM multiple dimensioned terrain modeling degree of being practical.
As can be seen here, the importance degree of system evaluation DEM grid cell in landform is expressed, be the Main Basis accepting or rejecting terrain feature point in reconstruct DEM committed step, being determine that multiple dimensioned DEM builds the central factor of effect, is the basis of carrying out multiple dimensioned landform expression based on high accuracy DEM.Scientific knowledge, the system quantifies DEM grid cell importance degree in digital terrain is expressed, expresses the multiple dimensioned landform based on high accuracy DEM and has very important significance.And the importance degree of DEM grid cell in landform is expressed, not only relevant with the Local terrain changes form at its place, be associated with its place landform positions simultaneously, be the domatic point and mild ridge point that local relief degree is less equally, when multiple dimensioned landform is expressed, the former is suitable for ignoring and the latter is suitable for retaining; Furthermore, the terrain feature point that place landform positions type is identical, often corresponds to different landform level, such as the ditch valley point on tap drain and Zhigou, and the importance in multiple dimensioned landform is expressed is also obviously different.
Summary of the invention
1. the technical matters that will solve
Be difficult to take terrain feature system hierarchy and structure into account for existing in prior art in multiple dimensioned DEM reconfiguration technique, mutual space constraint relation, the multiple dimensioned landforms " getting main house " are expressed principle and are not easily realized, thus cause mountain peak to be scabbled, the phenomenon of cheuch lifting, cause the distortion of overall landforms skeleton, especially browse geographic scenes on a large scale to have no alternative but adopt mosaic technology, seriously constrain the problems such as effective raising of the multiple dimensioned constructing technology degree of being practical of DEM, core technology thought of the present invention is towards overall shaped area, fully take into account relief elements type, the semantic feature such as hierarchical organization and spatial relationship, combine from local geometric version and overall landform layer of structure two aspect, comprehensive measurement is carried out to the importance of DEM point position in the modeling of earth's surface, obtain DEM point position comprehensive importance degree index TSI (Terrain Significance Index), on this basis, set up the rule-of-thumb relation between reconstruct DEM target scale (engineer's scale or resolution) size and comprehensive importance degree index TSI threshold value, the target DEM of the terrain feature point reconstruct corresponding scale of different significance level is selected by setting threshold value.The invention provides a kind of multiple dimensioned DEM construction method taking landform semantic information into account, the method is chosen terrain feature point according to it and is reconstructed multiple dimensioned DEM maintenance landform framework characteristic, can realize the multiple dimensioned DEM structure needs of different levels, serves the multiple dimensioned DEM application demand of different levels.
2. technical scheme
Object of the present invention is achieved through the following technical solutions: the multiple dimensioned DEM construction method taking landform semantic information into account, and step comprises:
1) according to Local terrain changes form, applied differential geometry principle is estimated DEM point position geometry importance degree, passes through formula carry out calculating DEM point position local geometric importance degree TSI local; In formula: θ itarget grid cell and adjacent cells elements method vector angle, namely by target grid cell and adjacent 8 grid cell normal vector angle averages, local importance degree is estimated, and be normalized all DEM point positions local geometric importance value in whole sample district is unified;
2) according to landform unique point type and landform level shape unique point semantic importance weight allocation scheme definitely, DEM point position overall situation semantic importance TSI is calculated global;
Ditch valley point and ridge point: divide minimum unbranched river or ridge into the 1st grade, that only receives the 1st grade of tributary or ridge divides the 2nd grade into, and that receives 1,2 two-stage tributaries or ridge belongs to 3rd level, and the rest may be inferred carries out classification to ditch valley line and topographical crest; Be positioned at grade be 1 cheuch or ridge on some position overall situation importance value be set to 1, then grade often increases by 1, and its overall importance value increases by 1;
Ditch is put and toe point along the line: be 1 by all DEM grid point position equal assignment of overall importance degree be positioned on the along the line and leg wire of slope of ditch;
Mountain top point and saddle point: when determining mountain top point and saddle point overall situation semantic importance value, considering that they and crestal line point have repeatability on locus, is 1 by their the other assignment of overall importance value;
Cheuch node and crestal line node: consider that itself and ditch valley point or ridge point have position registration, using it connect 1/10th of secondary ditch valley point or ridge point rating value as its additional overall semantic importance values;
3) comprehensive importance degree index TSI in DEM point position estimates and extraction: extracting local geometric importance degree TSI for all DEM point positions localwith overall semantic importance TSI globalbasis on, applying equation TSI=TSI local+ TSI globaldEM point position comprehensive importance degree index TSI is estimated and extraction;
4) the choosing of candidate's terrain feature point: the corresponding relation between the reconstruct target DEM scale size obtained according to Comparison Method and comprehensive importance degree index TSI threshold value determines TSI threshold value; When landform is Gullied Rolling Loess Region, extracting comprehensive importance degree index TSI data source is country's basethis engineer's scale 1:1 ten thousand resolution is the dem data of 5 meters, and the threshold value extracting charge for remittance line and watershed line employing is 200, then build and 1:2.5 ten thousand landform figureduring corresponding DEM, TSI threshold value is 0.5; Build country's baseduring this engineer's scale 1:5 ten thousand DEM, TSI threshold value is 1.0; Build and 1:10 ten thousand landform figureduring corresponding DEM, TSI threshold value is 2.0; Build country's baseduring this half size scale 50,000 DEM, TSI threshold value is 5.0; And then the comprehensive importance degree index TSI threshold value by selecting, extract candidate's terrain feature point of respective numbers, be used for reconstructing target scale DEM;
5) the DEM constructing technology flow process that application is conventional, the DEM using the candidate's terrain feature point extracted to complete target scale builds, and namely carries out thinization process according to Terrain Simplification efficiency to candidate's terrain feature; Then use the terrain feature of reservation point to add Feature line and build constraint TIN, carry out space interpolation on this basis and complete target scale structure DEM.
Step 1) described in DEM be countrythe primary scale 5m that Mapping departments produce or 25m resolution DEM or the gridded DEM generated by ground or airborne laser radar point cloud.
Step 4) in adopt mean square error of height numerical analysis method and level line structure cover legally to determine comprehensive importance degree index TSI threshold value.
Step 5) described in space interpolation adopt interpolation or Natural neighbors method of interpolation.
3. beneficial effect
Compared to prior art, the invention has the advantages that:
as Fig. 7shown in, when TSI threshold value is less, the point that locally landform metamorphosis is obvious is retained, and can portray the detail characteristic of landform to a certain extent; When TSI threshold value increases, low-grade cheuch and ridge are gradually by comprehensively, and the integral structure characteristic of different brackets is retained, thus reaches different levels Terrain Simplification demand.As can be seen here, take the multiple dimensioned DEM constructing plan of landform semantic information into account, preferentially retained by major landform key element, secondary atural object key element gives up gradually, the landform framework characteristic under different scale condition can be kept, be conducive to safeguarding that multiple dimensioned DEM builds the consistance of result and application thereof, significantly improve the practical function of multiple dimensioned DEM constructing technology, thus meet the multiple dimensioned DEM application demand of social different levels.
Accompanying drawing explanation
fig. 1for light ditch extraction is in 1:1 ten thousand DEM, dark ditch extraction extracts water system fit in 1:5 ten thousand DEM figure.
fig. 2for light ditch extraction is in 1:1 ten thousand DEM, dark ditch extraction extracts water system fit in 1:25 ten thousand DEM figure.
fig. 3for terrain feature point (black) space distribution that vital point (VIP) method is reconstruct DEM figure.
fig. 4for terrain feature point (black) space distribution that three-dimensional Douglas (3DD-P) method is reconstruct DEM figure.
fig. 5for flow process of the present invention figure.
fig. 6for the comprehensive importance degree index (TSI) in DEM point position extracts result signal figure.
fig. 7for the multiple dimensioned DEM effect of application TSI index construction figure.
fig. 8for reconstructing DEM and 1:50 under different TSI threshold value, 000 vector level line fit figure.
Embodiment
Below in conjunction with instructions accompanying drawingand specific embodiment, the present invention is described in detail.
Embodiment 1
as Fig. 5shown in, take the multiple dimensioned DEM construction method of landform semantic information into account, step comprises:
1) DEM is countrythe primary scale 5m that Mapping departments produce or 25m resolution DEM or the gridded DEM generated by ground or airborne laser radar point cloud.According to Local terrain changes form, applied differential geometry principle is estimated DEM point position geometry importance degree, passes through formula to calculating DEM point position local geometric importance degree TSI local; In formula: θ itarget grid cell and adjacent cells elements method vector angle, namely by target grid cell and adjacent 8 grid cell normal vector angle averages, local importance degree is estimated, and be normalized all DEM point positions local geometric importance value in whole sample district is unified, make its value be between 0 ~ 1;
2) according to landform unique point type and landform level shape unique point semantic importance weight allocation scheme definitely, DEM point position overall situation semantic importance TSI is calculated global;
Ditch valley point and ridge point: application GIS software extracts high-precision ditch valley line and topographical crest as adopted hydrological analysis method in ARCGIS, on this basis, divide minimum unbranched river or ridge into the 1st grade, that only receives the 1st grade of tributary or ridge divides the 2nd grade into, receive 1,2 two-stage tributaries or ridge belong to 3rd level, the rest may be inferred carries out classification to ditch valley line and topographical crest; Then directly according to classification results, semantic importance assignment is carried out to the ditch valley point of different stage and crestal line point in software, should figurein layer, other some position semantic importance assignment is 0.Be positioned at grade be 1 cheuch or ridge on some position overall situation importance value be set to 1, then grade often increases by 1, and its overall importance value increases by 1;
Ditch is put and toe point along the line: according to ditch, the along the line and leg wire of slope both sides gradient has significant difference, application ARCGIS software adopts nature knick point stage method to extract, or put along the line or toe point according to edge detection algorithm or snake algorithm application third party software MATLAB or extraction ditch of programming, on this basis, considering and there is no the along the line and leg wire of slope quantitative classification research of ditch at present, is 1 by all DEM grid point position equal assignment of overall importance degree be positioned on the along the line and leg wire of slope of ditch; Should figurein layer, other some position semantic importance assignment is 0.
Mountain top point and saddle point: due to mountain top point and saddle point in position with topographical crest there is coincidence relation, extract in ARCGIS on the basis of topographical crest, window analysis method is adopted to extract mountain top point and saddle point by setting appropriate threshold, namely mountain top point is local elevation maximum of points on topographical crest, saddle point is local elevation minimum point on topographical crest, then be 1 by all mountain tops point of extracting and saddle point overall situation semantic importance assignment, should figurein layer, other some position semantic importance assignment is 0.When determining mountain top point and saddle point overall situation semantic importance value, added value 1 on the crestal line point overall situation importance value basis belonging to it;
Cheuch node and crestal line node: because cheuch node and crestal line node have repeatability and correlativity with ditch valley line and topographical crest position respectively, extract on the basis of ditch valley line and topographical crest in ARCGIS, other three positions, ditch valley point or this feature of crestal line point position is at least connected according to cheuch node or crestal line node, cheuch node and crestal line node are extracted, using it connect 1/10th of secondary ditch valley point or ridge point rating value as its additional overall semantic importance values; Should figurein layer, other some position semantic importance assignment is 0.
3) comprehensive importance degree index TSI in DEM point position estimates and extraction: extracting local geometric importance degree TSI for all DEM point positions localwith overall semantic importance TSI globalbasis on, applying equation TSI=TSI local+ TSI globaldEM point position comprehensive importance degree index TSI is estimated and extraction, as Fig. 6shown in;
4) the choosing of candidate's terrain feature point: as Fig. 8shown in, corresponding relation between the reconstruct target DEM scale size obtained according to Comparison Method and comprehensive importance degree index TSI threshold value determines TSI threshold value, (its numerical value corresponding relation is relevant to factors such as benchmark DEM resolution, terrain feature elements recognition threshold value, target DEM yardsticks), when landform is Gullied Rolling Loess Region, extracting comprehensive importance degree index TSI data source is country's basethis engineer's scale 1:1 ten thousand resolution is the dem data of 5 meters, and the threshold value extracting charge for remittance line and watershed line employing is 200, then build and 1:2.5 ten thousand landform figureduring corresponding DEM, TSI threshold value is 0.5; Build country's baseduring this engineer's scale 1:5 ten thousand DEM, TSI threshold value is 1.0; Build and 1:10 ten thousand landform figureduring corresponding DEM, TSI threshold value is 2.0; Build country's baseduring this half size scale 50,000 DEM, TSI threshold value is 5.0, and then the comprehensive importance degree index TSI threshold value by selecting in ARCGIS software, and the candidate's terrain feature point extracting respective numbers is used for reconstructing target scale DEM;
5) utilize GIS software as in ARCGIS, by the above-mentioned candidate's terrain feature point chosen, adopt conventional DEM constructing technology flow process reconstruct target scale DEM.Specifically, applied mathematics Morphology Algorithm can be needed to carry out thinization process to candidate's terrain feature according to Terrain Simplification efficiency; Then use the terrain feature of reservation point to add Feature line and build constraint TIN (TIN, Triangulated Irregular Network), carry out the structure that interpolation or Natural neighbors method of interpolation complete target scale gridded DEM on this basis.

Claims (4)

1. take the multiple dimensioned DEM construction method of landform semantic information into account, it is characterized in that step comprises:
1) according to Local terrain changes form, applied differential geometry principle is estimated DEM point position geometry importance degree, passes through formula to calculating DEM point position local geometric importance degree TSI local; In formula: θ itarget grid cell and adjacent cells elements method vector angle, namely by target grid cell and adjacent 8 grid cell normal vector angle averages, local importance degree is estimated, and be normalized all DEM point positions local geometric importance value in whole sample district is unified;
2) according to landform unique point type and landform level shape unique point semantic importance weight allocation scheme definitely, DEM point position overall situation semantic importance TSI is calculated global;
Ditch valley point and ridge point: divide minimum unbranched river or ridge into the 1st grade, that only receives the 1st grade of tributary or ridge divides the 2nd grade into, and that receives 1,2 two-stage tributaries or ridge belongs to 3rd level, and the rest may be inferred carries out classification to ditch valley line and topographical crest; Be positioned at grade be 1 cheuch or ridge on some position overall situation importance value be set to 1, then grade often increases by 1, and its overall importance value increases by 1;
Ditch is put and toe point along the line: be 1 by all DEM grid point position equal assignment of overall importance degree be positioned on the along the line and leg wire of slope of ditch;
Mountain top point and saddle point: when determining mountain top point and saddle point overall situation semantic importance value, considering that they and crestal line point have repeatability on locus, is 1 by their the other assignment of overall importance value;
Cheuch node and crestal line node: consider that itself and ditch valley point or ridge point have position registration, using it connect 1/10th of secondary ditch valley point or ridge point rating value as its additional overall semantic importance values;
3) comprehensive importance degree index TSI in DEM point position estimates and extraction: extracting local geometric importance degree TSI for all DEM point positions localwith overall semantic importance TSI globalbasis on, applying equation TSI=TSI local+ TSI globaldEM point position comprehensive importance degree index TSI is estimated and extraction;
4) the choosing of candidate's terrain feature point: the corresponding relation between the reconstruct target DEM scale size obtained according to Comparison Method and comprehensive importance degree index TSI threshold value determine TSI threshold value when landform be Gullied Rolling Loess Region, to extract comprehensive importance degree index TSI data source be national primary scale 1:1 ten thousand resolution is the dem data of 5 meters, the threshold value extracting charge for remittance line and watershed line employing is 200, then during the DEM that structure is corresponding with 1:2.5 ten thousand topomap, TSI threshold value is 0.5; When building national primary scale 1:5 ten thousand DEM, TSI threshold value is 1.0; When building the DEM corresponding with 1:10 ten thousand topomap, TSI threshold value is 2.0; When building national primary scale 1:25 ten thousand DEM, TSI threshold value is 5.0; And then the comprehensive importance degree index TSI threshold value by selecting, extract candidate's terrain feature point of respective numbers, be used for reconstructing target scale DEM;
5) the DEM constructing technology flow process that application is conventional, the DEM using the candidate's terrain feature point extracted to complete target scale builds, and namely carries out thinization process according to Terrain Simplification efficiency to candidate's terrain feature; Then use the terrain feature of reservation point to add Feature line and build constraint TIN, carry out space interpolation on this basis and complete target scale structure DEM.
2. the multiple dimensioned DEM construction method taking landform semantic information into account according to claim 1, is characterized in that step 1) described in the DEM gridded DEM that is the primary scale 5m that produces of national Mapping departments or 25m resolution DEM or generated by ground or airborne laser radar point cloud.
3. the multiple dimensioned DEM construction method taking landform semantic information into account according to claim 1, is characterized in that step 4) adopt when determining comprehensive importance degree index TSI and DEM target scale rule-of-thumb relation mean square error of height numerical analysis method and level line structure to overlap legally to determine comprehensive importance degree index TSI threshold value.
4. the multiple dimensioned DEM construction method taking landform semantic information into account according to claim 1, is characterized in that step 5) described in space interpolation adopt interpolation or Natural neighbors method of interpolation.
CN201410836988.5A 2014-12-29 2014-12-29 Multi-scale DEM (digital elevation model) construction method considering topographical semantic information Pending CN104574512A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201410836988.5A CN104574512A (en) 2014-12-29 2014-12-29 Multi-scale DEM (digital elevation model) construction method considering topographical semantic information

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201410836988.5A CN104574512A (en) 2014-12-29 2014-12-29 Multi-scale DEM (digital elevation model) construction method considering topographical semantic information

Publications (1)

Publication Number Publication Date
CN104574512A true CN104574512A (en) 2015-04-29

Family

ID=53090475

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201410836988.5A Pending CN104574512A (en) 2014-12-29 2014-12-29 Multi-scale DEM (digital elevation model) construction method considering topographical semantic information

Country Status (1)

Country Link
CN (1) CN104574512A (en)

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105469061A (en) * 2015-08-04 2016-04-06 电子科技大学中山学院 Topographic feature line extraction method and device
CN105894471A (en) * 2016-03-30 2016-08-24 广东中冶地理信息股份有限公司 Medium-small scale orthoimage rapid correction method based on large-scale topographic map
CN106033611A (en) * 2016-05-23 2016-10-19 西安建筑科技大学 Method for extracting surface peaks in DEM data
CN107315813A (en) * 2017-06-29 2017-11-03 中国测绘科学研究院 A kind of tree-like river networks hierarchical relationship of stroke feature constraints is built and method for simplifying
CN107341493A (en) * 2017-07-14 2017-11-10 电子科技大学中山学院 Terrain feature line extraction method and device based on branch similarity and electronic equipment
CN108761458A (en) * 2018-08-15 2018-11-06 中国科学院电子学研究所 Interference SAR water body digital elevation model modification method based on morphologic thinning
CN109887086A (en) * 2019-02-25 2019-06-14 南京工业大学 It is a kind of based on a Methods of Terrain Simplification for gradient entropy
CN110019613A (en) * 2017-11-24 2019-07-16 中国人民解放军装备学院 The Feature line extracting method that a kind of water simulation and double TPI parametric methods combine
CN110031004A (en) * 2019-03-06 2019-07-19 沈阳理工大学 Unmanned plane static state and dynamic path planning method based on numerical map
CN112099009A (en) * 2020-09-17 2020-12-18 中国有色金属长沙勘察设计研究院有限公司 ArcSAR data back projection visualization method based on DEM and lookup table
CN114037723A (en) * 2022-01-07 2022-02-11 成都国星宇航科技有限公司 Method and device for extracting mountain vertex based on DEM data and storage medium
US11810251B2 (en) 2019-10-03 2023-11-07 General Electric Company Remote sensing method to model terrain shape by detecting reliable ground points

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030210180A1 (en) * 2002-05-13 2003-11-13 Hager James R. Methods and apparatus for terrain correlation
CN101344390A (en) * 2008-08-19 2009-01-14 南京师范大学 High-fidelity digital modeling method for landform altitude
CN102122395A (en) * 2011-01-31 2011-07-13 武汉大学 Adaptive scale DEM (digital elevation model) modeling method capable of keeping terrain features
US20110224840A1 (en) * 2010-03-12 2011-09-15 U.S.A As Represented By The Administrator Of The National Aeronautics And Space Administration Methods of Real Time Image Enhancement of Flash LIDAR Data and Navigating a Vehicle Using Flash LIDAR Data
CN103236086A (en) * 2013-04-24 2013-08-07 武汉大学 Multiscale DEM (Digital Elevation Model) modeling method giving consideration to contents of surface hydrology
JP2013196151A (en) * 2012-03-16 2013-09-30 Chikyu Joho Gijutsu Kenkyusho:Kk Geography image processing device, geography image processing method, geography image processing program, computer-readable recording medium with the same recorded thereon, geography image data, and topographic map data

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030210180A1 (en) * 2002-05-13 2003-11-13 Hager James R. Methods and apparatus for terrain correlation
CN101344390A (en) * 2008-08-19 2009-01-14 南京师范大学 High-fidelity digital modeling method for landform altitude
US20110224840A1 (en) * 2010-03-12 2011-09-15 U.S.A As Represented By The Administrator Of The National Aeronautics And Space Administration Methods of Real Time Image Enhancement of Flash LIDAR Data and Navigating a Vehicle Using Flash LIDAR Data
CN102122395A (en) * 2011-01-31 2011-07-13 武汉大学 Adaptive scale DEM (digital elevation model) modeling method capable of keeping terrain features
JP2013196151A (en) * 2012-03-16 2013-09-30 Chikyu Joho Gijutsu Kenkyusho:Kk Geography image processing device, geography image processing method, geography image processing program, computer-readable recording medium with the same recorded thereon, geography image data, and topographic map data
CN103236086A (en) * 2013-04-24 2013-08-07 武汉大学 Multiscale DEM (Digital Elevation Model) modeling method giving consideration to contents of surface hydrology

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
FEI LIFAN 等: "A Three Douglas-Peucher Akgorithm and Its Application to Automated Generalization of DEMs", 《INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE》 *
杨族桥 等: "DEM多尺度表达与地形结构线提取研究", 《测绘学报》 *
董有福 等: "利用地形信息强度进行DEM地形简化研究", 《武汉大学学报.信息科学版》 *
蔡先华 等: "数字高程模型数据压缩及算法研究", 《测绘通报》 *

Cited By (20)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105469061A (en) * 2015-08-04 2016-04-06 电子科技大学中山学院 Topographic feature line extraction method and device
CN105469061B (en) * 2015-08-04 2018-07-17 电子科技大学中山学院 Feature line extracting method and device
CN105894471A (en) * 2016-03-30 2016-08-24 广东中冶地理信息股份有限公司 Medium-small scale orthoimage rapid correction method based on large-scale topographic map
CN106033611A (en) * 2016-05-23 2016-10-19 西安建筑科技大学 Method for extracting surface peaks in DEM data
CN106033611B (en) * 2016-05-23 2018-11-30 西安建筑科技大学 A kind of mountain top point extracting method in dem data
CN107315813A (en) * 2017-06-29 2017-11-03 中国测绘科学研究院 A kind of tree-like river networks hierarchical relationship of stroke feature constraints is built and method for simplifying
CN107315813B (en) * 2017-06-29 2020-07-17 中国测绘科学研究院 Method for constructing and simplifying hierarchical relation of tree-shaped river system constrained by stroke features
CN107341493A (en) * 2017-07-14 2017-11-10 电子科技大学中山学院 Terrain feature line extraction method and device based on branch similarity and electronic equipment
CN107341493B (en) * 2017-07-14 2020-03-06 电子科技大学中山学院 Terrain feature line extraction method and device based on branch similarity and electronic equipment
CN110019613A (en) * 2017-11-24 2019-07-16 中国人民解放军装备学院 The Feature line extracting method that a kind of water simulation and double TPI parametric methods combine
CN108761458B (en) * 2018-08-15 2021-06-29 中国科学院电子学研究所 Morphological refinement-based interference SAR water body digital elevation model correction method
CN108761458A (en) * 2018-08-15 2018-11-06 中国科学院电子学研究所 Interference SAR water body digital elevation model modification method based on morphologic thinning
CN109887086A (en) * 2019-02-25 2019-06-14 南京工业大学 It is a kind of based on a Methods of Terrain Simplification for gradient entropy
CN110031004A (en) * 2019-03-06 2019-07-19 沈阳理工大学 Unmanned plane static state and dynamic path planning method based on numerical map
CN110031004B (en) * 2019-03-06 2023-03-31 沈阳理工大学 Static and dynamic path planning method for unmanned aerial vehicle based on digital map
US11810251B2 (en) 2019-10-03 2023-11-07 General Electric Company Remote sensing method to model terrain shape by detecting reliable ground points
CN112099009A (en) * 2020-09-17 2020-12-18 中国有色金属长沙勘察设计研究院有限公司 ArcSAR data back projection visualization method based on DEM and lookup table
CN112099009B (en) * 2020-09-17 2022-06-24 中国有色金属长沙勘察设计研究院有限公司 ArcSAR data back projection visualization method based on DEM and lookup table
CN114037723A (en) * 2022-01-07 2022-02-11 成都国星宇航科技有限公司 Method and device for extracting mountain vertex based on DEM data and storage medium
CN114037723B (en) * 2022-01-07 2022-03-29 成都国星宇航科技有限公司 Method and device for extracting mountain vertex based on DEM data and storage medium

Similar Documents

Publication Publication Date Title
CN104574512A (en) Multi-scale DEM (digital elevation model) construction method considering topographical semantic information
CN102122395B (en) Adaptive scale DEM (digital elevation model) modeling method capable of keeping terrain features
CN103236086B (en) One takes the contextual multiple dimensioned DEM modeling method of the earth's surface hydrology into account
Erener et al. Landslide susceptibility assessment: what are the effects of mapping unit and mapping method?
Lv et al. Chinese progress in geomorphometry
CN104376595B (en) A kind of three-dimensional road generation method cooperateed with based on airborne LiDAR and GIS
CN103886152B (en) Drainage basin water catchment range manufacturing method based on urban concave downward flyover area DEM
CN102902844A (en) Sub-water basin partitioning method based on DEM (Dynamic Effect Model) data with large data quantity
CN110276732B (en) Mountain area point cloud cavity repairing method considering topographic characteristic line elements
CN103679655A (en) LiDAR point cloud filter method based on gradient and area growth
CN106446910B (en) Complex geological curved surface feature extraction and reconstruction method
CN107657618B (en) Automatic extraction method of regional scale erosion gully based on remote sensing image and topographic data
CN102708587A (en) Method and system for acquiring three-dimensional building information rapidly
CN104463164A (en) Tree canopy structure information extraction method based on rib method and crown height ratio
CN102693328A (en) Application of ARCVIEW GIS (geographic information system) 3.2 technology in mountainous land building design
CN104200044A (en) GIS (geographic information system)-based three-dimensional power transmission line path selection method
CN115659816A (en) Urban waterlogging point prediction method and system based on twin model
CN114580910B (en) Watershed sediment connectivity evaluation method considering road influence
CN111985389A (en) Basin similarity discrimination method based on basin attribute distance
CN110175370A (en) A kind of REGION OF WATER INJECTION OILFIELD recognition methods of city charge for remittance
CN114926602B (en) Building singleization method and system based on three-dimensional point cloud
Khayyal et al. Creation and spatial analysis of 3D city modeling based on GIS data
Domingo et al. Long-term changes in 3D urban form in four Spanish cities
Zhang et al. A study on coastline extraction and its trend based on remote sensing image data mining
CN109190593A (en) Slope stability principium identification method along mountain road based on concave-convex category division

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
WD01 Invention patent application deemed withdrawn after publication

Application publication date: 20150429

WD01 Invention patent application deemed withdrawn after publication