CN103236086B - One takes the contextual multiple dimensioned DEM modeling method of the earth's surface hydrology into account - Google Patents
One takes the contextual multiple dimensioned DEM modeling method of the earth's surface hydrology into account Download PDFInfo
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Abstract
The invention belongs to digital elevation model modeling field, particularly one takes the contextual multiple dimensioned DEM modeling method of the earth's surface hydrology into account.Extract the hydrology response region of topographical surface by carrying out Runoff Analysis to DEM, set up the hierarchical structure tree of watershed; By the hydrological characteristics of extensive earth's surface spot elevation, calculate the hydrology contribution index of spot elevation for landform shape; Terrain feature point set is chosen by the weighting terrain representation error investigating spot elevation; And adopt elasticity to seek position strategy adjustment degree of integration controling parameters automatically, thus realize taking the contextual multiple dimensioned DEM automatic Synthesis of the earth's surface hydrology into account.Therefore, tool of the present invention has the following advantages: landform and the hydrological characteristics that effectively can keep original high accuracy DEM, and can ensure the landform of multiple dimensioned lower DEM and the topological sum logical consistency of hydrological characteristics; Improve robotization and the formation efficiency of multiple dimensioned DEM modeling, and the needs to dimension self-adaption DEM in practical application can be met.
Description
Technical Field
The invention relates to a multi-scale DEM modeling method, in particular to a multi-scale DEM modeling method considering the context of surface hydrology.
Background
The Digital Elevation Model (DEM) is an important component of a spatial data infrastructure as a digital description and simulation mode of the earth surface topography, and has wide application in scientific research fields and production departments relating to earth three-dimensional information, such as water conservancy, surveying and mapping, national defense construction and the like. In order to meet the requirements of different levels, all countries establish a multi-level scale (or multi-resolution) DEM database in a mode of coexistence of multiple scales. For example, the united states department of defense (NASA), national survey and mapping agency (NIMA) and the german and italian space agency, establish a 90 meter resolution SRTM3DEM, a 30 meter resolution SRTM1DEM and a 15 meter resolution asterm, a 25 meter resolution landmapd and a 5 meter resolution BlueskyDTM in the united kingdom, and successively establish a nationwide 1:100, 1:25, 1:5 and a provincial 1:1 million DEM (NFGIS-DEM) in china.
With the updating and improvement of space data acquisition means such as synthetic aperture radars, laser scanning systems and the like, the acquisition of terrain data becomes efficient and rapid, on one hand, the potential requirements of people for earth science research in various fields are greatly met, and on the other hand, the problem of rapid increase of the terrain data in the aspects of data volume, timeliness, complexity and the like is also brought. For example, an earth observation system eos (earth observation system) can realize all-weather and all-time earth observation without interference of cloud fog through seven satellites such as tera, AQUA and quala, remote sensing data acquired by tera every day can reach TB level, and the combination of tera and AQUA satellites can realize data updating for at least 4 times every day in the world. Because the data volume of each scale DEM is rapidly increased in a geometric progression, the storage, updating and consistency maintenance requirements of mass data provide a serious challenge for the sustainability of the method of establishing a base for the scale DEM.
The DEM is converted from a large scale (high precision) to a small scale (low precision) by adopting a DEM comprehensive technology, so that the terrain information service with flexible scale is provided, and the necessary trend of modern DEM production and management is realized. According to different DEM data organization forms, the DEM comprehensive algorithm researched at home and abroad at present can be mainly divided into four types:
(1) DEM integration based on discrete points. The core idea of this type of method is that elevation points on the earth's surface are considered to have a correlation in spatial arrangement with other elevation points within a certain range of the surroundings. The representative researches mainly comprise a point-to-surface distance method, a terrain description error method and a space plane method vector included angle method. These methods use the spatial correlation of the elevation points to realize DEM integration, but the mutual determination of adjacent points causes the processing order of the points to have a large influence on the integration result, and inevitably lacks the overall grasp of the surface morphology.
(2) DEM synthesis based on contour. The contour synthesis method mainly adopts a curve simplification algorithm and an improved algorithm thereof to synthesize the contour, removes detail bending and retains main bending, such as a two-dimensional Douglas-Peucker method, a Li-Openshaw method, a QTM method, a wavelet method, a fractal synthesis method and a genetic algorithm. Because adjacent contour lines generally have different degrees of similarity, and the contour lines express the landform in a grouped manner, a learner also carries out structured synthesis on the contour lines from the interrelation among the contour lines, such as an elevation band synthesis method, a structure line tracking method, a surface water system structure method and a progressive synthesis method. The contour lines perform 'shaping' on the ground surface through continuity on the contour lines and abrupt change between the contour lines, and although the integration process of the contour lines is assisted by using topographic structure lines, the contour lines actually integrate two-dimensional information projected to a plane space and are not truly three-dimensional integration, so that the topological conflict between the contour lines after integration needs to be further processed.
(3) DEM synthesis based on regular grids. The core idea of the synthesis is that regular grids are regarded as digital gray level images, the gray level value of each grid corresponds to the elevation value of the landform point at the place or interpolated at the place, and DEM synthesis is realized by processing the gray level value, such as a filtering method, a wavelet analysis method, an information theory method, a quadtree local entropy method and a map algebra method. Due to the limitations of the data structure of the grid DEM itself, the details of the terrain are always suppressed in the grid, and therefore more feature information must be added in the synthesis. At present, most of comprehensive methods based on grid DEM need to add terrain feature points or feature lines to enhance the coordination relationship between local grids and global earth surface morphology.
(4) DEM integration based on section lines. Mahes (1998) proposed to cut the earth surface at equally spaced vertical sections, and to linearly simplify the resulting section lines, preserving the main concave-convex characteristics of the earth surface. The method provides a new idea for simplifying the topographic information, however, related researches are few at present, and related technologies and application prospects are yet to be further researched and verified.
In the above studies, DEM synthesis is typically represented as data compression at the data processing level. If the requirements of people on processing and analyzing the terrain information are met, DEM data with different scales are required to have dimension-adaptive fidelity to the terrain information, and in an operation decision level, the landform characteristics contained in the DEM are used as a geographical basis and are used as the spatial context of comprehensive behaviors to be associated with a data model for collaborative simplification. As for the landform elements, the geological phenomena and laws of landform units reflected by landform regional relief in the aspects of geological structure, hydrological characteristics and the like belong to the comprehensive space context category of DEM. Particularly for mature landforms, the main valley and ridge structure lines of the landform have obvious water collection and water separation, which is not only the theoretical basis of surface hydrological analysis and hydrological element extraction in the geographic research, but also the context constraint which needs to be considered in the DEM comprehensive process.
Although the study of scholars at home and abroad focuses on the effect of spatial context on the formulation of a comprehensive scheme to different degrees, an effective algorithm is not formed yet to integrate the context information of the geographic level and the data processing of the geometric level. The algorithms are limited to geometrically smoothing the discarded secondary valley and ridge parts through the hierarchical analysis of the terrain structure before synthesis, or supplement unreduced structure line information after synthesis and supplement the structure mode of the synthesis result. How to correlate the spatial context in the DEM synthesis process for the simplification of the consistency is not yet available.
Disclosure of Invention
The technical problem of the invention is mainly solved by the following technical scheme:
a multi-scale DEM modeling method considering surface hydrology context is characterized by comprising the following steps:
step 1, carrying out catchment analysis on an original high-precision DEM, extracting an assembly line and a diversion line of a surface form described by the DEM, and establishing a hydrological network of the original high-precision DEM;
step 2, analyzing the hydrological context of the landform object described by the original high-precision DEM on the basis of the hydrological network established in the step 1: establishing a hierarchical structure of the catchment network by utilizing the influx relation of the surface catchment response area, matching the diversion line with the catchment line based on the coupling relation of the surface valley and the ridge, and determining the hierarchical structure of the diversion network according to the hierarchical structure of the catchment network;
step 3, performing hydrologic semantic enhancement on the surface elevation point of the original high-precision DEM: establishing a hydrologic feature generalization model of the terrain elevation points, and calculating hydrologic contribution indexes of the earth surface elevation points according to the hydrologic context obtained in the step 2;
and 4, decomposing the original high-precision DEM according to the drainage basin according to the hydrological network obtained in the step 1, and extracting a topographic feature point set by taking the drainage basin as a unit: calculating DEM terrain description errors caused by the existence of the surface elevation points by adopting a mode of constructing an irregular triangular network by using a basin boundary convex hull and the surface elevation points, comparing the magnitude of the terrain description errors of the surface elevation points, then intensively extracting landform shaping feature points from the surface elevation points and establishing a terrain feature point queue, and on the basis, acquiring a terrain feature point set of a corresponding scale according to comprehensive degree control parameters determined by a user-specified scale;
step 5, separating high-distance points on the water collecting line and the water distribution line from the topographic feature point set, and simplifying the original high-precision water collecting line network and the water distribution line network in corresponding scales;
step 6, establishing a constrained irregular triangular network TIN according to the terrain feature point set under the corresponding scale obtained in the step 4 and the simplified hydrological system obtained in the step 5, and interpolating a regular grid on the basis to be used as the integrated DEM;
and 7, calculating the precision of the integrated DEM, if the precision does not reach the integrated degree of the scale set by the user, automatically adjusting the integrated degree control parameter by adopting an elastic locating strategy, obtaining a terrain feature point subset of the corresponding scale, and repeating the step 5 to the step 7.
In the above multi-scale DEM modeling method considering the context of the surface hydrology, in step 1, the specific steps of establishing the hydrological network of the original high-precision DEM are as follows:
step 1.1, establishing a flow direction matrix according to the elevation difference of a DEM regular grid, taking an unmarked grid at any position as a seed point, reversely and iteratively searching an influx grid according to eight neighborhoods, taking a point which is only an outflow grid and does not flow into the grid as a runoff source point, tracking according to a runoff direction, and establishing a runoff accumulation matrix by adopting an improved D8 algorithm, wherein the method specifically comprises the following steps: firstly, traversing regular grids, calculating the elevation difference of each grid to eight-field grids, and marking the direction with the maximum elevation difference as the water flow direction to obtain a flow direction matrix; then randomly selecting an unmarked grid as a seed point, reversely searching the afflux grid according to eight neighborhoods, and taking a point which only flows out of the grid and does not flow into the grid as a runoff source point. Tracking according to the runoff direction, wherein the runoff cumulant of a certain grid on the water flow path is the runoff cumulant of an upstream grid plus 1; for grids converged in multiple directions, adding 1 to the accumulated runoff quantity on the basis of the logical sum of the accumulated runoff quantities in the converging directions to obtain a runoff accumulation matrix;
step 1.2, extracting the runoff cumulant of each grid point according to the runoff accumulation matrix obtained in the step 1.1, extracting a sparse grid larger than a set threshold value as an assembly line grid, extracting the source of an assembly line from the assembly line grid by combining the flow direction matrix established in the step 1.1, then reversely extending the assembly line to the runoff source by taking the source of the assembly line as a seed point according to the runoff accumulation matrix established in the step 1.1;
step 1.3, vectorizing the sparse grid of the catchment line established in the step 1.2, and then constructing a catchment line network by using the flow direction matrix established in the step 1.2;
step 1.4, extracting a water collecting core taking a source of a water collecting line and a fork head or a line segment between the fork head and an outlet as a drainage basin, and then marking all areas flowing into the water collecting core as corresponding water collecting response areas according to the flow direction matrix and the runoff accumulation matrix obtained in the step 1.1;
and step 1.5, sharpening and extracting skeleton lines from the catchment area boundary obtained in the step 1.4, and establishing a water distribution network.
In the above multi-scale DEM modeling method considering surface hydrological context, in step 2, the specific steps of analyzing the hydrological context of the geomorphic object described by the original high-precision DEM are as follows:
step 2.1, the water collecting core obtained in the step 1.4 is used as a basic data organization unit of the water collecting system, and the earth surface is utilized
Establishing a hierarchical structure tree of the catchment network by the catchment response area according to the catchment relation, namely:
the catchment response areas of the parent-child water collecting cores comprise catchment response areas of all child water collecting cores;
and the catchment nucleuses in the brother relationship, the catchment nucleuses which are brothers each other have catchment response areas which are converged into the same father-level catchment response area;
step 2.2, taking the starting point and the cross point of the water diversion line or the line segment between the cross point and the outlet as the water diversion core and base of the basin
In the coupling relation between the water distribution line and the drainage basin, the hierarchical structure tree of the water distribution nuclear network is established by utilizing the influx relation of the catchment response area, namely:
the sub-set catchment response area is overlapped with the boundary of the sub-set catchment response area and is intersected with the boundary of the parent-child relationship;
the water diversion cores in the brother relationship are in the brother relationship, and the corresponding catchment response areas of the water diversion cores in the brother relationship are in the brother relationship and are not overlapped with the boundary of the father level catchment response area;
in the multi-scale DEM modeling method considering the surface hydrological context, step 3 is used for performing hydrological semantic enhancement on the surface elevation points of the original high-precision DEM, and the specific implementation mode is that a basin index function is established according to the hierarchical structures of the catchment line network and the diversion line network obtained in step 2, and then the hydrological characteristics of the surface elevation points are generalized by calculating two hydrological contribution indexes, namely a basin index and a micro-landform index.
In the above multi-scale DEM modeling method considering the context of the surface hydrology, in step 4, the specific implementation steps of obtaining the terrain feature point set are as follows:
step 4.1, dividing the original high-precision DEM into a plurality of feature extraction units according to a drainage basin, extracting a drainage basin boundary convex shell to construct an initial irregular triangulation network TIN, and acquiring residual elevation points except the boundary as a candidate feature point set;
step 4.2, randomly extracting one candidate feature point in the candidate feature point set, calculating the weighted point-to-surface distance from the candidate feature point to the irregular TIN surface by combining the hydrologic contribution index of the surface elevation point obtained in the step 3, selecting the elevation point with the largest weighted point-to-surface distance as the current 1 st feature point, and adding the current 1 st feature point into the topographic feature point sequence;
and 4.3, inserting the topographic feature points into the irregular TIN for reconstruction, deleting the feature points from the candidate feature point set, and repeating the steps 4.2-4.3 until the weighted point-to-surface distance is smaller than a given threshold value or all the elevation points enter the feature point sequence.
In the above multiscale DEM modeling method considering the context of the surface hydrology, in step 5, the concrete implementation manner of simplifying the hydrological system is to determine the selected number of the topographic feature points according to the scale designated by the user, obtain the corresponding subsets from the feature point sequence obtained in step 4, then separate the topographic feature points located on the water collecting line and the water dividing line from the topographic feature point subsets, reconstruct new water collecting lines and water dividing lines according to the topographic feature points of the water collecting line and the water dividing line in the subsets along the original water collecting line and water dividing line paths, and keep the topological relation between the water collecting line and the water dividing line and the general topographic feature points unchanged in the reconstruction process.
In the above multi-scale DEM modeling method considering the context of the surface hydrology, in step 7, the automatic adjustment of the comprehensive degree control parameter by using the elastic position-finding strategy is performed by calculating the precision of the comprehensive DEM obtained in step 6, and the specific implementation steps are as follows:
step 7.1, establishing a relation function F _ s of the dimension and DEM elevation description difference according to a multi-dimension DEM resource library, acquiring corresponding F _ s (x) according to the dimension set by a user, comparing DEM elevation description errors before and after synthesis, and calculating the difference F (x) of the elevation description errors;
and 7.2, controlling the comprehensive degree of the DEM by adopting an elastic locating strategy based on the following constraint conditions: the tolerance threshold is set such that if | F _ s (x) -F (x) | > and F _ s (x) > F (x) |, the feature point set extracted from the step 4 feature point sequence is increased, whereas if | F _ s (x) -F (x) | > and F _ s (x) < F (x) < x), the number of feature points extracted from the step 4 feature point sequence is decreased, and steps 4 to 7 are repeated until | F _ s (x) -F (x) | < ends.
Therefore, the invention has the following advantages: (1) the topographic and hydrological characteristics of the original high-precision DEM can be effectively maintained, and the topological and logical consistency of the topographic and hydrological characteristics of the DEM under multiple scales can be ensured; (2) the automation and the generation efficiency of the multi-scale DEM modeling are improved, and the requirement of the scale self-adaptive DEM in practical application can be met.
Drawings
FIG. 1 is a flow diagram for automatic synthesis of DEM in consideration of hydrological context.
FIG. 2 is a flow diagram of the invention for the counter-current extension of the water collection line.
Figure 3a is a schematic view of a water collection system of the present invention.
FIG. 3b is the Shrive code map of the water collection system of the present invention.
Fig. 3c is a diagram of a water collection system hierarchy according to the present invention.
FIG. 4a is a schematic view of the water diversion system and the water diversion line catchment area subdivision of the present invention.
Fig. 4b is a hierarchical structure diagram of the water diversion system of the present invention.
Fig. 5 is a flow chart of feature point selection according to the present invention.
FIG. 6 is a diagram illustrating the determination of an optimal composite threshold based on elastic seek according to the present invention.
Fig. 7 is a flow chart for automatically controlling the DEM integration level according to the present invention.
Fig. 8a is a contour plot of the experimental results DEM of the present invention.
Fig. 8b is a contour plot of the experimental results DEM of the hydrologic enhancement method.
FIG. 8c is a contour plot of experimental results DEM of the VIP method.
FIG. 8d is a contour diagram of DEM as a result of the simulation
Fig. 9 is a topographic moisture index plot showing the different integration levels of the four methods.
Detailed Description
The technical scheme of the invention is further specifically described by the following embodiments and the accompanying drawings.
Example (b):
first, theoretical knowledge related to the present invention is described.
1. The theoretical basis.
The DEM data synthesis is carried out, and the smaller scale (low resolution) DEM is derived from the larger scale (high resolution) DEM, so that the terrain information is summarized and simplified, and the simple detail characteristic discarding is not carried out. Therefore, the DEM synthesis usually represents the compression of data in an operation level, but the topographic features contained in the DEM are used as a geographical basis in an operation decision level, and are used as the spatial context of the synthesis behavior to be associated with the data model for cooperative simplification. As for the landform elements, the topographic relief reflects that the mature valleys and ridges have obvious water collection and water separation, which is not only the theoretical basis of surface hydrological analysis and hydrological element extraction in the geographic research, but also the spatial context for DEM comprehensive operation.
The essence of DEM integration is the conversion of the information flow of the terrain information from a larger scale to a smaller scale. The surface morphology is a concept of a space aggregate, is defined by different geometric surfaces, and has foreign features such as certain volume, size, height, shape and the like. Any complex terrain may be considered to consist of flat terrain (including plateaus, terraces, depressed terraces), hills and depressions (including isolated and combined depressions), and ultimately these basic terrain elements are described "localized" and "qualitative" by the elevation of elevation points in a region relative to surrounding elevation points. Therefore, the landform elevation points have an integration meaning, the point integration integrally forms the basic form of the earth surface, and also forms a support of a landform space geometric body, including a landform area valley network and a water diversion system. Therefore, the key to DEM synthesis is how to choose elevation points that have a large contribution to the description of the surface morphology and the preservation of the terrain context.
The constraint effect of the terrain space context on the DEM comprehensive operation is mainly embodied in the selection process of the terrain characteristic points. In other words, the DEM integration of the surface hydrological features is maintained, and the terrain feature points are selected from the original DEM according to the contribution degree of the associated terrain feature points to the terrain hydrological features. And when the contribution degree of the terrain feature candidate points to the surface shaping is close, the points with larger contribution degree to the terrain hydrological feature expression need to be selected preferentially.
Based on the method, the invention provides and realizes a novel DEM comprehensive method. The method comprises the steps of extracting a hydrological response area of a terrain surface by carrying out runoff analysis on the DEM, establishing a hierarchical organization model of a catchment area, establishing a hydrological feature generalization model of a surface elevation point according to a hierarchical structure of a surface hydrological system on the basis, and selecting a terrain feature point set by quantifying the hydrological contribution degree of the surface elevation point and carrying out hydrological semantic enhancement on the DEM. It can be seen that in this way, the synthesis process of the DEM always considers the constraint effect of the surface hydrologic context, and the DEM is performed from the data conversion from a large scale (high resolution) to a small scale (low resolution) towards the cooperative simplification of the topographic information and the hydrologic information.
2. Generalization of the high-range point hydrological characteristics.
Elevation points on the water collecting network and the water dividing network and general elevation points in other areas have different semantic connotations and play a role in explicitly expressing surface hydrological information in DEM data. Therefore, space constraints above and below the surface hydrology are considered in the DEM synthesis process, and semantic enhancement can be achieved through the elevation points on the hydrology network system. This requires building a basis for information generalization of the surface hydrological context. Hydrologic information is divided into two parts, namely watershed hydrologic information and hydrologic micro-landform information, and hydrologic characteristic values of ground surface elevation points are generalized by defining watershed indexes and micro-landform indexes.
(1) Basin index
According to the basic theory of hydrology, the surface watershed has an obvious hierarchical nested structure, and each level of catchment area is composed of a plurality of next level of catchment subareas. And taking a line segment between the source and the fork of the assembly line or between the fork and the outlet as a water collecting core of the basin, and taking a line segment between the starting point and the fork point of the water dividing line or between the fork point and the outlet as a water dividing core of the basin. And for any water collecting core or water dividing core unit l, setting the area of a corresponding catchment area as area (l) and the catchment area of the whole basin as area (S), wherein the calculation formula of the basin index alpha (pt _ l) of any elevation point pt _ l on the water collecting core or water dividing core unit is as follows:
α(pt_l)=Area(l)/Area(S)（1）
and the watershed index of the merging point of the water collecting core and the water dividing core takes the contribution value of the elevation point of the highest-level water collecting core or the water dividing core connected with the watershed index.
(2) Index of micro landform
For any water collecting core or water dividing core segment l, a micro-terrain contribution index β (pt _ l) of any elevation point pt _ l is defined, and the micro-terrain contribution index is the elevation change rate along the elevation descending direction of the hydrological lineElevation rate of change from the direction perpendicular to the hydrological lineThe vector sum of (a) is:
3. and extracting the topographic feature points.
The earth surface is a three-dimensional continuous body object, and the simplification of the terrain information should be performed in a three-dimensional stereo space. Therefore, whether the elevation point is a topographic feature point or not is judged in the DEM comprehensive process, and the contribution of the elevation point to topographic relief is mainly considered. In the DEM quality analysis field, the terrain description precision of the DEM is evaluated by simulating the difference between the ground and the actual terrain through the DEM. By using the thought, the invention takes DEM terrain expression difference caused by the existence of elevation sampling points as the selection basis of the terrain feature points. And in consideration of the fact that the irregular triangulation network can simulate the surface relief more flexibly, the selection of the topographic features is carried out on the basis of TINDEM.
The basic idea is as follows: firstly, extracting a region boundary, constructing an initial TIN, and taking all elevation points except the boundary as candidate feature points; then the three-dimensional point-to-surface distances of all candidate points to the TIN surface are calculated,
selecting a height point with the largest point-surface distance as a 1 st topographic feature point; inserting the 1 st terrain feature point into the TIN for reconstruction, and then recursively selecting and interpolating the 2 nd and 3 rd feature points 3 … … n until the point-to-surface distance of the selected terrain feature point is smaller than a given threshold value or 0.
In the characteristic point selection process, the point-surface distance of the earth surface elevation point relative to the TIN is used as a quantitative index of DEM terrain expression difference. In order to retain the water collecting and dividing characteristics of the landform form, the invention combines the hydrological characteristic index of the elevation point to calculate the weighted point-surface distance di：
di=delta_d(i,tin)×(1+αi+βi)（3）
Wherein delta _ d(i,tin)For the three-dimensional point-to-face distance of the candidate feature point i with respect to the current TIN, αiAnd βiα of high point on assembly line and distribution lineiAnd βiα of elevation points of other regions calculated by the formulas (1) and (2)iAnd βiThe value is 0.
After the process of selecting the terrain feature points is completed, a feature point sequence for describing the terrain from coarse to fine is obtained. And selecting a terrain feature point set from the sequence from front to back according to the corresponding relation between the scale designated by the user and the DEM elevation difference description error before and after synthesis.
Second, the following will specifically describe the specific implementation steps in combination with the above theoretical knowledge.
As shown in figure 1:
(1) and establishing a flow direction matrix M _ dir and a runoff accumulation matrix M _ acc according to the elevation difference of the original high-precision DEM regular grid. The specific establishment process is as follows:
firstly, traversing regular grids, calculating the elevation difference of each grid to eight-field grids, and marking the direction with the maximum elevation difference as the water flow direction to obtain M _ dir. Then randomly selecting an unmarked grid as a seed point, reversely searching the afflux grid according to eight neighborhoods, and taking a point which only flows out of the grid and does not flow into the grid as a runoff source point. Tracking according to the runoff direction, wherein the runoff cumulant of a certain grid on the water flow path is the runoff cumulant of an upstream grid plus 1; and for grids converged in multiple directions, adding 1 to the accumulated runoff quantity on the basis of the logical sum of the accumulated runoff quantity in each converging direction to obtain M _ acc. The process is an improvement on the D8 algorithm, and the specific implementation program is not described in detail.
(2) And extracting grids with the catchment amount larger than a given threshold value from the runoff accumulation matrix M _ acc, tracing along the water flow direction to obtain an initial catchment line, and then performing counter-current extension of the catchment line. The specific implementation method comprises the following steps:
firstly, extracting a source Pt _ i of a current assembly line as a starting point, and then selecting the source with the largest water collection amount Acc in eight neighborhoods as a first candidate point Pt _ a according to a flow direction matrix M _ dir and a convergence accumulation matrix M _ Acc, namely Acc (Pt _ a) = max (Acc (inflow grid));
secondly, selecting the eight-neighborhood interior elevation Z which is not less than Pt _ i, the catchment amount which is less than Pt _ i and the catchment amount which is maximum as a second candidate point Pt _ b according to the DEM and the convergence accumulation matrix M _ Acc, namely Z (Pt _ b) > Z (Pt _ i), Acc (Pt _ b) < Acc (Pt _ i), and Acc (Pt _ b) = max (Acc (eight neighborhoods));
comparing the catchment amounts of the Pt _ a and the Pt _ b, if the two are equal, selecting the Pt _ a as an upstream extension point Pt _ i-1 of the Pt _ i, otherwise, selecting the one with the larger catchment amount as the upstream extension point Pt _ i-1, namely Acc (Pt _ i-1) is more than or equal to Acc (Pt _ a).
And fourthly, repeating the first step and the fourth step by taking the extension point Pt _ i-1 as a new starting point until the upstream point convergence quantity flowing to the extension point is 0, namely Acc (Pt _0) = 0.
The process of the counter-flow extension of the catchment line is shown in figure 2. The branching problem that the runoff traced to the source can effectively be solved to this process: when a plurality of branches are converged or parallel runoff and the extending direction of the valley land exist, the runoff path with the strongest surface hydrological response is always taken as the extending direction of the valley land.
(3) And the water diversion network and the water collection network are in a dual relationship, all grid areas flowing into the assembly line are marked as corresponding hydrologic response areas according to the flow direction matrix and the runoff accumulation matrix, and the boundaries of the hydrologic response areas are sharpened and skeleton lines are extracted to obtain corresponding water diversion lines. The method for sharpening the boundary of the catchment area and extracting the skeleton line belongs to a grid-based map algebraic processing method designed by people, and the specific implementation process is not described in detail.
(4) The Sheve method is used to organize the hydrological system. And taking a line segment between a source and a fork of the assembly line or between the fork and an outlet as a water collecting core of the drainage basin (shown in figure 3 a), and taking a line segment between a starting point and a fork point of the water distribution line or between the fork point and the outlet as a water distributing core of the drainage basin (shown in figure 4 a), wherein the line segment corresponds to a coding unit (shown in figure 3 b) in the Sheve coding system. The structural relationship between the catchment cores is determined by the influx relationship of the catchment areas, and the data organization model is shown in fig. 3 c.
(5) According to the landform characteristics that watershed can be shared between catchment areas and sub-areas thereof, the structural relationship of the water diversion system is realized by decomposing multiple catchment areas related to the water diversion core. The division core AB is taken as the watershed of the sub-catchment area where the catchment line a (fig. 3 a) is located, and if the division core AB also belongs to the watershed of the father catchment area where the catchment core g (fig. 3 a) is located, the division core AB is taken as the minimum unit of the diversion system. Defining the hierarchical relationship of the water diversion network to be consistent with the hierarchical relationship of the catchment area, and the organization model of the water diversion system is shown as the attached figure 4 b.
(6) On the basis of establishing a hierarchical structure tree of a water collecting network and a water distributing network, hydrologic feature generalization indexes, namely a basin index alpha and a micro-landform index beta, of elevation points of each water collecting core and each water distributing core are calculated.
The formula for calculating the basin index alpha is as follows: α (pt _ l) = area (l)/area(s). Wherein l represents a certain water collecting core or water dividing core, and pt _ l is a height point on the corresponding water collecting core or water dividing core; area (l) is the hydrologic response area of the catchment or diversion core, and area(s) is the area of the whole watershed. When l is a leaf node in the hierarchical tree structure of the hydrological network, taking the hydrological response area of l as a watershed core; and when l has a sub-leaf node in the hierarchical tree structure of the hydrological network, the hydrological response area of l is the sum of the drainage basin of the water collecting core l and the drainage basins of the sub-water collecting cores.
The formula for calculating the microtopography index β is:wherein,indicating the rate of elevation change along the direction of lowering of the hydrological line elevation,the elevation change rate in the direction perpendicular to the hydrological line is shown.
(7) And taking the hydrological feature generalization index of the elevation point as a weight coefficient for feature selection, calculating the shaping contribution of the elevation point to the earth surface form, and establishing a terrain feature point sequence. The specific process is as follows:
① first extracts the three-dimensional boundary of the original high-precision DEM to construct the constrained initial TIN0Dividing to construct a constrained TIN0All the elevation points except the above are taken as candidate feature points cand (n).
② on the basis, calculating the contribution amount of the candidate topographic feature point to the surface morphology by combining the drainage basin index and the micro-topographic index, wherein the calculation formula is di=delta_d(i,tin)×(1+αi+βi). D in the formulaiFor candidate topographic feature point i relative to the current TINiWeighted point-to-surface distance of, delta _ d(i,tin)For candidate topographic feature point i relative to the current TINiThree-dimensional dot-to-surface distance of αiAnd βiα of candidate terrain feature points on assembly line and distribution lineiAnd βiα of candidate terrain feature points of other regions calculated in the process (4)iAnd βiThe value is 0. Selecting a candidate point with the largest weighted point surface distance as a 1 st topographic feature point Pt1And putting the terrain characteristic point sequence Q into the terrain characteristic point sequence Q.
③ the selected topographic feature point Pt is then used1Insertion of TIN0Re-establishing the triangular network to obtain the TIN1And deleting the point from the candidate feature point set.
And fourthly, calculating the contribution amount of the remaining candidate points to the earth surface form, recursively selecting and interpolating the 2 nd and 3 … … n terrain feature points until the point-to-face distance of the selected terrain feature points is 0 or less than a given threshold value, or the candidate points completely enter a terrain feature point sequence Q, and ending the process. The topographic feature point selecting flow chart is shown in figure 5.
(8) Setting the initial quantity of the terrain feature point sets as DEM comprehensive degree control parameters, selecting a feature point subset P from a terrain feature point queue Q, extracting terrain feature points P' from a water collecting network and a water distributing network from P, and simplifying a water collecting line and a water distributing line.
The simplified hydrological network requires that the topological consistency with the selected feature point set is kept. The specific implementation method comprises the following steps: for a certain water-collecting core l, 3 elevation points Pt are sequentially taken from the source to the tail endi-1、PtiAnd Pti+1，Pti-1The elevation points to be reserved on the source point, the bifurcation point or the water collecting core are marked as Pt _ A, Pt _ B, Pt _ C, if Pt _ B ∈ P', or Pt _ A, Pt _ B and Pt _ C are used for establishing a triangle delta ABC, andand Pt _ B and triangle delta ABC have intersection points, Pt is reserved on the runoff path of the water collecting core liLet Pt _ A = Pti，Pt_B=Pti-1(ii) a Otherwise, Pt is deleted on the runoff path of the water collecting core liLet Pt _ B = Pti+1. Taking the next elevation point Pt of the catchment nucleus Ii+2Let Pt _ C = Pti+2The process is repeated until Pt _ B is the end of the water-collecting core l. The simplification process of the water diversion line is the same.
(9) And generating the limited TIN by using the simplified water collecting line and water dividing line and the selected topographic feature point set P, then obtaining a comprehensive DEM by adopting an original high-precision DEM resolution interpolation regular grid, and calculating the root mean square error RMSE of the elevation difference of the comprehensive DEM and the front DEM.
(10) And calculating the elevation difference RMSE of the multi-scale DEM data of the similar landform type area in the national geographic information center, and establishing an accuracy evaluation standard.
If DEM data of a user-specified scale exist in the multi-scale DEM database, directly taking out corresponding elevation difference RMSE from the precision evaluation standard; and if the DEM database of the user-specified scale does not exist, establishing a relation curve function F _ s between the scale and the DEM elevation difference RMSE according to the multi-scale DEM, and then acquiring the corresponding elevation difference RMSE according to the scale specified by the user. The process of establishing the precision evaluation standard can be completed in the process of establishing the multi-scale DEM database, and can also be performed in the early stage of the comprehensive process.
And (3) setting the target scale elevation difference RMSE obtained according to the precision evaluation standard as F _ s (x), calculating the elevation difference RMSE between the integrated front DEM and the integrated rear DEM as F (x), and comparing the magnitudes of F _ s (x) and F (x).
(11) And automatically adjusting the selected number of the elevation points by adopting an elastic bit-seeking strategy according to the comparison result of the F _ s (x) and the F (x). For the number of the initially selected high points, let the compression rate change step delta _ =, the integrated state recorder k1=1, k2= 1. When F _ s (x) < F (x), take k2=1, if k2= = k1, then delta _ = delta _; if k2 ≠ k1, then delta = delta _ × 0.5 and k1= k 2. When F _ s (x) > F (x), take k2= -1, if k2= = k1, delta _ = delta _; if k2 ≠ k1, then delta = delta _ × 0.5 and k1= k 2.
Automatically adjusting the data volume of the topographic feature point set P by using an elastic locating strategy, wherein when F _ s (x) < F (x), = + delta _; when F _ s (x) > F (x), then = -delta _. A schematic diagram of adjusting the data amount of the feature point set by using the elastic locating strategy is shown in fig. 6.
(12) And (4) selecting a new terrain feature point set from the terrain feature point queue according to the data volume of the feature point set, and repeating the steps (8) to (12) until F _ s (x) is approximately equal to F (x) or the condition of jumping out of the cycle is reached, and finishing the process. The flow for automatically controlling the DEM integration degree is shown in figure 7.
(13) DEM data of a certain high mountain sample area in southwest of which the landform is mature is selected for an experiment, the grid resolution is 15m by 15m, and the sample area range is about 3.6km by 4.2 km. The original fine DEM is processed by respectively adopting the DEM comprehensive method taking the surface hydrological characteristics into consideration, the hydrological enhancement comprehensive method, the VIP comprehensive method provided by ArcGIS software and the Decimation comprehensive method.
And selecting 5% of terrain feature points to interpolate to TIN, and drawing contour lines to investigate the terrain description accuracy of the comprehensive result. The superposition of the composite front and rear contour lines is shown in figures 8a-8 d. From the superposition effect of the contour map, under the condition that the feature point is compressed to 5% of the original data, the method provided by the invention can furthest retain the original topographic features, the topographic valley and ridge area contour structural features of the integrated result of the traditional method are hard, and the VIP method and the defect method greatly lose the topographic information of the original data.
And respectively selecting 50%, 25%, 10% and 5% of topographic feature points by adopting four algorithms, then interpolating to generate a grid DEM, calculating topographic humidity indexes of DEMs with different comprehensive degrees, and investigating hydrological feature retention effects of the four methods. The result of the algorithm is shown in figure 9. The comparison of the standard deviation curves of the terrain humidity indexes under the conditions of different feature point selection rates shows that in the comprehensive process, the importance judgment of the method for valleys and ridges and the identification of the terrain feature points take the surface hydrological context information into consideration, and the comprehensive result can better keep the terrain humidity characteristic.
The specific embodiments described herein are merely illustrative of the spirit of the invention. Various modifications or additions may be made to the described embodiments or alternatives may be employed by those skilled in the art without departing from the spirit or ambit of the invention as defined in the appended claims.
Claims (4)
1. A multi-scale DEM modeling method considering surface hydrology context is characterized by comprising the following steps:
step 1, carrying out catchment analysis on an original high-precision DEM, extracting an assembly line and a diversion line of a surface form described by the DEM, and establishing a hydrological network of the original high-precision DEM;
step 2, analyzing the hydrological context of the landform object described by the original high-precision DEM on the basis of the hydrological network established in the step 1: establishing a hierarchical structure of the catchment network by utilizing the influx relation of the surface catchment response area, matching the diversion line with the catchment line based on the coupling relation of the surface valley and the ridge, and determining the hierarchical structure of the diversion network according to the hierarchical structure of the catchment network;
step 3, performing hydrologic semantic enhancement on the surface elevation point of the original high-precision DEM: establishing a hydrologic feature generalization model of the terrain elevation points, and calculating hydrologic contribution indexes of the earth surface elevation points according to the hydrologic context obtained in the step 2;
and 4, decomposing the original high-precision DEM according to the drainage basin according to the hydrological network obtained in the step 1, and extracting a topographic feature point set by taking the drainage basin as a unit: calculating DEM terrain description errors caused by the existence of the surface elevation points by adopting a mode of constructing an irregular triangular network by using a basin boundary convex hull and the surface elevation points, comparing the magnitude of the terrain description errors of the surface elevation points, then intensively extracting landform shaping feature points from the surface elevation points and establishing a terrain feature point queue, and on the basis, acquiring a terrain feature point set of a corresponding scale according to comprehensive degree control parameters determined by a user-specified scale;
step 5, separating high-distance points on the water collecting line and the water distribution line from the topographic feature point set, and simplifying the original high-precision water collecting line network and the water distribution line network in corresponding scales;
step 6, establishing a constrained irregular triangular network TIN according to the terrain feature point set under the corresponding scale obtained in the step 4 and the simplified hydrological system obtained in the step 5, and interpolating a regular grid on the basis to be used as the integrated DEM;
step 7, calculating the precision of the integrated DEM, if the precision does not reach the integrated degree of the scale set by the user, automatically adjusting the integrated degree control parameter by adopting an elastic locating strategy, obtaining a terrain feature point subset of the corresponding scale, and repeating the step 5 to the step 7;
in the step 1, the specific steps of establishing the hydrological network of the original high-precision DEM are as follows:
step 1.1, establishing a flow direction matrix according to the elevation difference of a DEM regular grid, taking an unmarked grid at any position as a seed point, reversely and iteratively searching an influx grid according to eight neighborhoods, taking a point which is only an outflow grid and does not flow into the grid as a runoff source point, tracking according to a runoff direction, and establishing a runoff accumulation matrix by adopting an improved D8 algorithm, wherein the method specifically comprises the following steps: firstly, traversing regular grids, calculating the elevation difference of each grid to eight-field grids, and marking the direction with the maximum elevation difference as the water flow direction to obtain a flow direction matrix; then randomly selecting an unmarked grid as a seed point, reversely searching and merging the grid according to eight neighborhoods, taking a point which only flows out of the grid and does not flow into the grid as a runoff source point, tracking according to the runoff direction, and adding 1 to the runoff cumulant of a certain grid on the water flow path as the runoff cumulant of an upstream grid; for grids converged in multiple directions, adding 1 to the accumulated runoff quantity on the basis of the logical sum of the accumulated runoff quantities in the converging directions to obtain a runoff accumulation matrix;
step 1.2, extracting the runoff cumulant of each grid point according to the runoff accumulation matrix obtained in the step 1.1, extracting a sparse grid larger than a set threshold value as an assembly line grid, extracting the source of an assembly line from the assembly line grid by combining the flow direction matrix established in the step 1.1, then reversely extending the assembly line to the runoff source by taking the source of the assembly line as a seed point according to the runoff accumulation matrix established in the step 1.1;
step 1.3, vectorizing the sparse grid of the catchment line established in the step 1.2, and then constructing a catchment line network by using the flow direction matrix established in the step 1.2;
step 1.4, extracting a water collecting core taking a source of a water collecting line and a fork head or a line segment between the fork head and an outlet as a drainage basin, and then marking all areas flowing into the water collecting core as corresponding water collecting response areas according to the flow direction matrix and the runoff accumulation matrix obtained in the step 1.1;
step 1.5, sharpening and extracting skeleton lines from the catchment area boundary obtained in the step 1.4, and establishing a water distribution network;
in the step 2, the concrete steps of analyzing the hydrological context of the geomorphic object described by the original high-precision DEM are as follows:
step 2.1, the catchment core obtained in step 1.4 is used as a basic data organization unit of the catchment system, and the interflow relation of the surface catchment response area is used for establishing a hierarchical structure tree of the catchment network, namely:
the catchment response areas of the parent-child water collecting cores comprise catchment response areas of all child water collecting cores;
and the catchment nucleuses in the brother relationship, the catchment nucleuses which are brothers each other have catchment response areas which are converged into the same father-level catchment response area;
step 2.2, taking the starting point and the cross point of the water diversion line or the line segment between the cross point and the outlet as the water diversion core of the basin, and establishing a hierarchical structure tree of the water diversion core network by utilizing the influx relation of the catchment response area based on the coupling relation between the water diversion line and the basin, namely:
the sub-set catchment response area is overlapped with the boundary of the sub-set catchment response area and is intersected with the boundary of the parent-child relationship;
the water diversion cores in the brother relationship are in the brother relationship, and the corresponding catchment response areas of the water diversion cores in the brother relationship are in the brother relationship and are not overlapped with the boundary of the father level catchment response area;
in the step 7, the automatic adjustment of the comprehensive degree control parameter by adopting the elastic position-finding strategy is performed by calculating the precision of the comprehensive DEM obtained in the step 6, and the specific implementation steps are as follows:
step 7.1, establishing a relation function F _ s (x) of the dimension and DEM elevation description difference according to a multi-dimension DEM resource library, acquiring corresponding F _ s (x) according to the dimension set by a user, comparing DEM elevation description errors before and after synthesis, and calculating a difference F (x) of the elevation description errors;
and 7.2, controlling the comprehensive degree of the DEM by adopting an elastic locating strategy based on the following constraint conditions: the tolerance threshold is set such that if | F _ s (x) -F (x) | > and F _ s (x) > F (x) |, the feature point set extracted from the step 4 feature point sequence is increased, whereas if | F _ s (x) -F (x) | > and F _ s (x) < F (x) < x), the number of feature points extracted from the step 4 feature point sequence is decreased, and steps 4 to 7 are repeated until | F _ s (x) -F (x) | < ends.
2. The multi-scale DEM modeling method considering surface hydrological context as claimed in claim 1, wherein step 3 is to perform hydrological semantic enhancement on surface elevation points of an original high-precision DEM, and the specific implementation manner is to establish a basin index function according to the hierarchical structure of the catchment line network and the diversion line network obtained in step 2, and then generalize the hydrological features of the surface elevation points by calculating two hydrological contribution indexes, namely a basin index and a micro-landform index.
3. The multi-scale DEM modeling method considering surface hydrology context according to claim 1, wherein in the step 4, the specific implementation steps for obtaining the terrain feature point set are as follows:
step 4.1, dividing the original high-precision DEM into a plurality of feature extraction units according to a drainage basin, extracting a drainage basin boundary convex shell to construct an initial irregular triangulation network TIN, and acquiring residual elevation points except the boundary as a candidate feature point set;
step 4.2, randomly extracting one candidate feature point in the candidate feature point set, calculating the weighted point-to-surface distance from the candidate feature point to the irregular TIN surface by combining the hydrologic contribution index of the surface elevation point obtained in the step 3, selecting the elevation point with the largest weighted point-to-surface distance as the current 1 st feature point, and adding the current 1 st feature point into the topographic feature point sequence;
and 4.3, inserting the topographic feature points into the irregular TIN for reconstruction, deleting the feature points from the candidate feature point set, and repeating the steps 4.2-4.3 until the weighted point-to-surface distance is smaller than a given threshold value or all the elevation points enter the feature point sequence.
4. The multi-scale DEM modeling method considering surface hydrological context as claimed in claim 1, wherein in step 5, the concrete implementation manner of simplifying the hydrological system is that the selected number of the topographic feature points is determined according to the scale specified by the user, the corresponding subsets are obtained from the feature point sequence obtained in step 4, then the topographic feature points on the water collecting line and the water dividing line are separated from the topographic feature point subsets, new water collecting lines and water dividing lines are reconstructed according to the topographic feature points of the water collecting line and the water dividing line in the subsets along the original water collecting line and water dividing line paths, and the topological relations between the water collecting line and the water dividing line and the common topographic feature points are kept unchanged in the reconstruction process.
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