CN111538798B - Urban catchment area refined extraction method considering DSM and DLG - Google Patents
Urban catchment area refined extraction method considering DSM and DLG Download PDFInfo
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Abstract
The invention discloses a refined extraction method of urban catchment areas considering DSM and DLG, which comprises the following steps: step 1, obtaining urban DSM data and corresponding DLG data, and rasterizing the DSM data and the DLG data to obtain a DSM grid and a DLG grid; step 2, removing a non-waterlogged area in the DSM grid; step 3, calculating the flow direction of the DSM grid after the non-waterlogged area is removed, and obtaining flow direction grid data; step 4, combining DLG raster data and flow direction raster data, and calculating flow; step 5, setting a threshold value, extracting a catchment route according to the threshold value, and further extracting a water outlet; and 6, extracting to obtain a catchment area according to the data of the water outlet and the flow direction grating. The DSM is adopted to divide the urban catchment area, so that the transformation influence of urban planning construction on urban topography can be reflected well, and the urban planning construction is more fit to reality; the method solves the problem that the non-waterlogged area cannot be treated in the traditional method for dividing the catchment area.
Description
Technical Field
The invention relates to the technical field of hydrologic analysis, in particular to a refined extraction method of urban catchment areas, which takes DSM (Digital Surface Model ) and DLG (Digital Line Graphic, digital line map) into consideration.
Background
In 2008-2010, 62% of cities have different degrees of waterlogging, wherein more than 3 times of cities have hundreds of waterlogging disasters, and about half of cities have the longest water accumulation time of more than 12 hours. At present, a considerable number of cities in the country do not reach the flood control standard specified by the country. The GIS (Geographic Information System ), DSM and DLG are utilized to build a model for risk assessment, and a rapid and accurate flood control and disaster reduction countermeasure basis is provided.
The current urban storm waterlogging assessment model is mainly characterized in that a D8 algorithm is adopted for DEM (Digital Elevation Model ) data to divide a catchment area, but the urban catchment area divided in this way can not well reflect the transformation influence of urban planning construction on urban topography, especially for buildings, including houses, flower beds, piers and other ground features, rainwater can flow around when falling on the ground features and flow to different catchment areas. If the catchment area is divided using only DEM data, an error will occur.
Some urban storm waterlogging assessment models divide water-collecting areas by adopting a D8 algorithm on DSM data, so that the transformation influence of urban planning construction on urban terrain can be reflected to a certain extent, but if the condition that the roof of a house is concave occurs, the water-collecting areas exist in the house plane. These problems all lead to insufficiently fine, even inaccurate, differentiation of the catchment area, and to large errors in the subsequent evaluation of the waterlogging.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a refined extraction method for urban catchment areas, which considers DSM and DLG, aiming at the defects in the prior art.
The technical scheme adopted for solving the technical problems is as follows:
the invention provides a refined extraction method of urban catchment areas considering DSM and DLG, which comprises the following steps:
step 1, obtaining urban DSM data and corresponding DLG data, and rasterizing the DSM data and the DLG data to obtain a DSM grid and a DLG grid;
step 2, removing a non-waterlogged area in the DSM grid;
step 3, calculating the flow direction of the DSM grid after the non-waterlogged area is removed, and obtaining flow direction grid data;
step 4, combining DLG raster data and flow direction raster data, and calculating flow;
step 5, setting a threshold value, extracting a catchment route according to the threshold value, and further extracting a water outlet;
and 6, extracting to obtain a catchment area according to the data of the water outlet and the flow direction grating.
Further, the method for performing the rasterization processing in the step 1 of the present invention is as follows:
converting DSM data of the city into raster data; extracting a corresponding planar building which does not waterlog in DLG data, and converting the planar building into grid data of an equivalent plane to obtain a DLG grid; the method for extracting the planar building which does not waterlog comprises the following steps:
and (3) carrying out space overlapping extraction by combining with urban vector data to further judge the characteristics of the planar building which is not waterlogged, and judging that the building is the planar building which is not waterlogged if rainwater flows out of the building through a drainage system when the rainwater falls on the building.
Further, the method for removing the non-waterlogged region in the step 2 of the present invention comprises:
removing a non-waterlogged region by a superposition analysis method, wherein the specific process of the superposition analysis is as follows:
for the DSM grid and the DLG grid, the public part of the DSM grid and the DLG grid is removed, the grid data obtained by the DSM is A1, the grid data of the non-waterlogged area obtained by the DLG is A2, and the formula is shown as follows:
A3＝A1-A2
the A3 is a new grid obtained by removing the non-water-stained area in the DSM grid.
Further, the method for calculating the flow direction raster data in the step 3 of the invention comprises the following steps:
generating a new grid B1 which is consistent with the range of the grid A3 and has the same size as the grid units, giving each grid unit in the grid B1 a numerical value according to a D8 algorithm, and expressing the flow direction of each unit by the numerical value, wherein the numerical value change range is 1-255; wherein, 1: east; 2: southeast; 4, south; 8: southwest; 16: western medicine; 32: northwest; 64: north; 128: northeast;
the assignment method of the D8 algorithm comprises the following steps: calculating the distance weight difference between each adjacent grid in the 8 adjacent grids of the central grid by taking the assigned grid unit as the center; the value of the central grid unit is M, and the value of each grid unit in the 8-neighborhood is N i I=1, 2, 3, 4, 5, 6, 7, 8, the distance between the center grid and the center of the neighborhood grid is D i ；
Distance weight drop value calculation
Slope＝(M-N i )/D i
If the maximum distance weight drop value is less than 0, a negative value is given to indicate that the grid direction is not fixed;
if the maximum distance weight difference value is greater than or equal to 0 and the maximum value is only one, taking the direction value corresponding to the maximum value as the direction value at the central grid;
if the maximum distance weight drop is equal to 0 and more than one 0 value exists, adding the direction values corresponding to the 0 values; if the 8 neighborhood elevation values are the same as the central grid elevation value, assigning 255 to the central grid direction value;
if the maximum distance weight drop value is greater than 0 and there is more than one maximum value, then one direction is optionally taken as the water flow direction.
Further, the method for calculating the flow in the step 4 of the invention comprises the following steps:
generating a weight grid C1 with the same size as the grid A3 in the same range; the grid cell weight of the non-intersecting part of the grid C1 and the grid A2 is set to be 1, and the grid cell intersected by the grid C1 and the grid A2 is an edge grid of the planar ground object which cannot be waterlogged, wherein the calculation formula of the weight P is as follows:
P＝S/L
s is the total number of grid units in the planar grid in the grid A2, and L is the total number of grid units at the edge of the planar grid in the grid A2;
and calculating the flow by combining the weight grid and the flow direction grid, wherein the flow is determined by the accumulated weight of all grid units flowing into each downstream grid unit.
Further, the method for extracting the water outlet in the step 5 comprises the following steps:
step 5.1, setting a threshold value of the extracted catchment route to be Q;
step 5.2, traversing each grid in the flow grids in turn, wherein the grids with the grid flow larger than Q are grids on the water collecting route, extracting the grids to form a new grid C, and setting the initial value of the grid C to be 0;
and 5.3, taking one grid unit in the grid C as a seed point, setting a value as a, setting a grid unit adjacent to the grid unit in the grid C as a new seed point, setting b as a value, and carrying out recursive operation until the grid boundary is reached or no new seed point is generated, wherein each seed point is different in value. The grids with different values form a different catchment route;
step 5.4, after the water collecting routes are obtained, for each water collecting route, the maximum flow grid unit is a water outlet;
further, the method for extracting the catchment area in the step 6 of the invention comprises the following steps:
step 6.1, combining the water outlet and water flow direction data, and taking the water outlet as a seed point;
step 6.2, searching the grid units flowing to the seed point in the 8 neighborhood of the seed point, and taking the grid units flowing to the seed point as new seed points;
step 6.3, repeating the operation of the step 6.2 according to the new seed points;
and 6.4, stopping recursion until no new seed points are found or grid boundaries are reached, and forming a catchment area by all seed points.
The invention has the beneficial effects that: according to the urban catchment area refined extraction method considering DSM and DLG, the urban catchment area is divided by adopting DSM, so that the transformation influence of urban planning construction on urban topography can be reflected well, and the urban catchment area is more practical; the method solves the problem that the non-waterlogged area cannot be treated in the traditional method for dividing the catchment area.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a method for refined extraction of urban catchment areas in consideration of DSM and DLG according to an embodiment of the present invention.
Fig. 2 shows a value corresponding to the flow direction calculated by the D8 algorithm according to the embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The example of the present invention finely divides 563 catchments in a small block of DSM data and its corresponding DLG data based on the data.
As shown in fig. 1, the urban catchment area refinement extraction method taking into account the DSM and the DLG according to the embodiment of the present invention includes the following steps:
step 1, DSM and DLG data rasterization.
And 2, removing the non-waterlogged area in the DSM grid.
And 3, calculating the flow direction of the DSM grid after the non-waterlogged area is removed.
And 4, calculating the flow by combining the rasterized DLG data and the flow direction raster data.
And 5, extracting a water collecting route according to the threshold value, and further extracting a water outlet.
And 6, extracting the water collecting area from the water outlet and the flow direction grid.
Examples are detailed below for the 6 steps described above:
step 1: DSM and DLG data rasterization.
The DSM data of the city is converted into raster data. Meanwhile, the corresponding planar building which cannot be waterlogged in the DLG data is converted into raster data of an equivalent plane. The feature of the planar buildings that do not waterlog is that when rain falls on top of these buildings it flows out of the building due to its drainage system. The extraction method of the planar building without waterlogging mainly combines urban vector data to carry out space superposition extraction. Thus, two raster data A1 and A2 are obtained, the raster data obtained by DSM is A1, and the raster data of the non-waterlogged area is A2 by DLG.
Step 2: the non-waterlogged areas are removed in the DSM grid.
Taking A1 and A2 as the difference, A1 will be larger in range than A2 because A2 is the grid into which the extracted part of the feature in DLG is converted. For the common part of A1 and A2, the part is directly deleted in A1, and the other part still takes the value of A1.
A3＝A1-A2
A3 is a new grid obtained by removing the non-water-stained area from the DSM grid.
Step 3: and calculating the flow direction of the DSM grid after the non-waterlogged area is removed.
The algorithm for calculating the flow direction is a D8 algorithm, and the D8 algorithm calculates an integer grid with a value range between 1 and 255. The various direction values from the center are shown in fig. 2.
Generating a new grid B1 which is consistent with the range of the grid A3 and has the same size as the grid units, and giving each grid unit in the grid B1 a numerical value according to a D8 algorithm, wherein the numerical value represents the flow direction of each unit, and the numerical value change range is 1-255. Wherein, 1: east; 2: southeast; 4, south; 8: southwest; 16: western medicine; 32: northwest; 64: north; 128: northeast.
The assignment method of the D8 algorithm comprises the following steps: and calculating the distance weight difference between each adjacent grid in the 8 adjacent grids of the central grid by taking the assigned grid unit as the center. The value of the central grid unit is M, and the value of each grid unit in the 8-neighborhood is N i (i=1, 2, 3, 4, 5, 6, 7, 8), the distance between the centers of the central grid and the neighborhood grid is D i 。
Distance weight drop value calculation
Slope＝(M-N i )/D i 。
If the maximum distance weight drop value is less than 0, a negative value is assigned to indicate that the grid direction is undefined.
If the maximum distance weight difference value is greater than or equal to 0 and the maximum value is only one, the direction value corresponding to the maximum value is taken as the direction value at the central grid.
If the maximum distance weight drop is equal to 0 and more than one 0 value exists, the direction values corresponding to the 0 values are added. In an extreme case, if all 8 neighborhood elevation values are the same as the center grid elevation value, the center grid direction value is assigned 255.
If the maximum distance weight drop value is greater than 0 and there is more than one maximum value, then one direction is optionally taken as the water flow direction.
And traversing each grid unit in A3 to obtain a new flow direction grid, wherein the obtained flow direction is a real flow direction because A3 is grid data after the non-waterlogged area is removed.
Step 4: traffic is calculated by combining the rasterized DLG data with the streaming raster data.
The weight grid C1 with the same grid unit size as the range A3 is newly generated. The grid cell weight of the non-intersecting part of C1 and A2 is set to be 1, and the calculation formula of the weight P is as follows for the grid cell of the intersection of C1 and A2 (the grid cell of the intersection of the grid C1 and the grid A2 is the edge grid of the planar ground object which cannot be waterlogged):
P＝S/L
s is the total number of grid cells inside the planar grid in A2, and L is the total number of grid cells at the edge where A3 meets A2.
The weight of the non-waterlogged area edge is corrected so that the amount of rainwater falling on the non-waterlogged area is distributed into the grid at the non-waterlogged area edge. And then calculating the water quantity value flowing through each point according to the water flow direction data, and obtaining the water flow accumulation quantity, namely the flow of the area.
Step 5: and extracting a water collecting route according to the threshold value, and further extracting a water outlet.
The practical significance of flow calculation is that surface runoff can be generated at a certain flow value, a path formed by grids with the accumulated water flow amount larger than a critical value is a catchment route, and a path formed by all adjacent catchment grid units is a catchment route. The specific extraction method comprises the following steps:
step 5.1, the threshold value of the extracted catchment route is set to be Q.
And 5.2, traversing each grid in the flow grids in turn, wherein the grids with the grid flow larger than Q are grids on the water collecting route, extracting the grids to form a new grid C, and setting the initial value of C to 0.
And 5.3, taking one grid unit in the C as a seed point, setting the value as a, and taking the grid unit adjacent to the grid unit in the C as a new seed point, setting the value as b, wherein the seed point is different every time, and carrying out recursive operation until the grid boundary is reached or no new seed point is generated. The grids with different values form a different water collecting route.
And 5.4, after the water collecting routes are obtained, for each water collecting route, the maximum flow grid unit is the water outlet.
Step 6: and extracting a water collecting area from the water outlet and the flow direction grid.
And 6.1, combining the water outlet and the water flow direction data, and taking the water outlet as a seed point.
Step 6.2, searching the grid units flowing to the seed point in the 8 neighborhood of the seed point, and taking the grid units flowing to the seed point as new seed points.
And 6.3, repeating the operation of 6.2 according to the new seed point.
And 6.4, stopping recursion until no new seed points are found or grid boundaries are reached, and forming a catchment area by all seed points.
Through the steps, the urban catchment area can be finely divided.
The urban catchment area is divided by DSM and DLG, so that the transformation influence of actual buildings in urban cities on urban terrains can be reflected well, and the urban terrains are more fit to reality; the method solves the problem that rainwater can be discharged to the periphery without ponding when the non-waterlogged area cannot be treated in the traditional method for dividing the catchment area.
It will be understood that modifications and variations will be apparent to those skilled in the art from the foregoing description, and it is intended that all such modifications and variations be included within the scope of the following claims.
Claims (5)
1. A method for finely extracting urban catchment area in consideration of DSM and DLG, comprising the steps of:
step 1, obtaining urban DSM data and corresponding DLG data, and rasterizing the DSM data and the DLG data to obtain a DSM grid and a DLG grid;
step 2, removing a non-waterlogged area in the DSM grid;
step 3, calculating the flow direction of the DSM grid after the non-waterlogged area is removed, and obtaining flow direction grid data;
step 4, combining DLG raster data and flow direction raster data, and calculating flow;
step 5, setting a threshold value, extracting a catchment route according to the threshold value, and further extracting a water outlet;
step 6, extracting to obtain a catchment area according to the data of the water outlet and the flow direction grating;
the method for carrying out the rasterization processing in the step 1 comprises the following steps:
converting DSM data of the city into raster data; extracting a corresponding planar building which does not waterlog in DLG data, and converting the planar building into grid data of an equivalent plane to obtain a DLG grid; the method for extracting the planar building which does not waterlog comprises the following steps:
the urban vector data is combined to carry out space overlapping extraction, so that the characteristics of the planar building which is not waterlogged are judged, and if rainwater falls on the building and flows out of the building through a drainage system of the building, the building is judged to be the planar building which is not waterlogged;
the method for removing the non-waterlogged area in the step 2 comprises the following steps:
removing a non-waterlogged region by a superposition analysis method, wherein the specific process of the superposition analysis is as follows:
for the DSM grid and the DLG grid, the public part of the DSM grid and the DLG grid is removed, the grid data obtained by the DSM is A1, the grid data of the non-waterlogged area obtained by the DLG is A2, and the formula is shown as follows:
A3＝A1-A2
the A3 is a new grid obtained by removing the non-water-stained area in the DSM grid.
2. The urban catchment area refinement extraction method considering DSM and DLG according to claim 1, wherein the method of calculating the flow direction raster data in step 3 is:
generating a new grid B1 which is consistent with the range of the grid A3 and has the same size as the grid units, giving each grid unit in the grid B1 a numerical value according to a D8 algorithm, and expressing the flow direction of each unit by the numerical value, wherein the numerical value change range is 1-255; wherein, 1: east; 2: southeast; 4, south; 8: southwest; 16: western medicine; 32: northwest; 64: north; 128: northeast;
the assignment method of the D8 algorithm comprises the following steps: calculating the distance weight difference between each adjacent grid in the 8 adjacent grids of the central grid by taking the assigned grid unit as the center; the value of the central grid unit is M, and the value of each grid unit in the 8-neighborhood is N i I=1, 2, 3, 4, 5, 6, 7, 8, the distance between the center grid and the center of the neighborhood grid is D i ；
Calculating a distance weight drop value:
Slope＝(M-N i )/D i
if the maximum distance weight drop value is less than 0, a negative value is given to indicate that the grid direction is not fixed;
if the maximum distance weight difference value is greater than or equal to 0 and the maximum value is only one, taking the direction value corresponding to the maximum value as the direction value at the central grid;
if the maximum distance weight drop is equal to 0 and more than one 0 value exists, adding the direction values corresponding to the 0 values; if the 8 neighborhood elevation values are the same as the central grid elevation value, assigning 255 to the central grid direction value;
if the maximum distance weight drop value is greater than 0 and there is more than one maximum value, then one direction is optionally taken as the water flow direction.
3. The urban catchment area refinement extraction method considering DSM and DLG according to claim 1, wherein the method of calculating the flow rate in step 4 is:
generating a weight grid C1 with the same size as the grid A3 in the same range; the grid cell weight of the non-intersecting part of the grid C1 and the grid A2 is set to be 1, and the grid cell intersected by the grid C1 and the grid A2 is an edge grid of the planar ground object which cannot be waterlogged, wherein the calculation formula of the weight P is as follows:
P＝S/L
s is the total number of grid units in the planar grid in the grid A2, and L is the total number of grid units at the edge of the planar grid in the grid A2;
and calculating the flow by combining the weight grid and the flow direction grid, wherein the flow is determined by the accumulated weight of all grid units flowing into each downstream grid unit.
4. The method for refined extraction of urban catchment area considering DSM and DLG according to claim 1, wherein the method for extracting water outlet in step 5 is as follows:
step 5.1, setting a threshold value of the extracted catchment route to be Q;
step 5.2, traversing each grid in the flow grids in turn, wherein the grids with the grid flow larger than Q are grids on the water collecting route, extracting the grids to form a new grid C, and setting the initial value of the grid C to be 0;
step 5.3, taking one grid unit in the grid C as a seed point, setting a value as a, setting a grid unit adjacent to the grid unit in the grid C as a new seed point, setting a value as b, and carrying out recursive operation until the grid boundary is reached or no new seed point is generated, wherein each seed point has different values; the grids with different values form a different catchment route;
and 5.4, after the water collecting routes are obtained, for each water collecting route, the maximum flow grid unit is the water outlet.
5. The method for finely extracting a catchment area in a city, taking account of DSM and DLG according to claim 1, wherein the method for extracting the catchment area in step 6 is as follows:
extracting a water collecting area from the water outlet and the flow direction grids, and analyzing and searching all grids flowing to the water outlet at the upstream of the water outlet by combining with water flow direction data to obtain the water collecting area;
the specific method comprises the following steps:
step 6.1, combining the water outlet and water flow direction data, and taking the water outlet as a seed point;
step 6.2, searching the grid units flowing to the seed point in the 8 neighborhood of the seed point, and taking the grid units flowing to the seed point as new seed points;
step 6.3, repeating the operation of the step 6.2 according to the new seed points;
and 6.4, stopping recursion until no new seed points are found or grid boundaries are reached, and forming a catchment area by all seed points.
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| CN111898229A (en) * | 2020-09-29 | 2020-11-06 | 中国水利水电科学研究院 | Urban rainwater catchment area based calculation method and system |
| CN112242003B (en) * | 2020-10-19 | 2021-04-13 | 中国测绘科学研究院 | City sub-catchment area division method considering land type and flow direction |
| CN112530137A (en) * | 2020-11-27 | 2021-03-19 | 淮阴师范学院 | Distributed medium and small watershed geological disaster and flood early warning method based on critical rainfall |
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| CN114612631B (en) * | 2022-03-02 | 2023-06-09 | 自然资源部重庆测绘院 | InSAR technology-based high-precision vulnerability-free DSM extraction method |
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