CN108665167A - Estimate method and device of the sponge urban green space to the abatement amount of precipitation waterlogging - Google Patents
Estimate method and device of the sponge urban green space to the abatement amount of precipitation waterlogging Download PDFInfo
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Abstract
The embodiment of the present invention discloses a kind of estimation sponge urban green space to the method and device of the abatement amount of precipitation waterlogging, can estimate abatement amount of the sponge urban green space to precipitation waterlogging.Method includes：S1, the underlying surface remote sensing image for obtaining sponge city to be evaluated generate the grid for presetting specification, and the grid are added to the underlying surface remote sensing image；S2, determined using the underlying surface remote sensing image grid various types vegetation area, and using the underlying surface remote sensing image to the grid carry out city development degree subregion, the soil erosion under the vegetation of the grid is determined according to division result；S3, abatement amount of the greenery patches to precipitation waterlogging that the sponge city is estimated according to the soil erosion under the area of various types vegetation and the vegetation of the grid of the grid.
Description
Technical Field
The embodiment of the invention relates to the field of remote sensing and hydrology, in particular to a method and a device for estimating the amount of reduction of rainfall and waterlogging of a sponge urban green land.
Background
The sponge city is a new generation of urban rainfall flood management concept, and means that the city has good elasticity in the aspects of adapting to environmental changes, coping with natural disasters caused by rainwater and the like. Especially for the rainfall waterlogging of the sponge city, in order to deal with the natural disasters, the elasticity of the sponge city needs to be quantized, namely the reduction of the rainfall waterlogging of the green land of the sponge city needs to be estimated. However, there is no effective estimation method at present.
Disclosure of Invention
Aiming at the defects and shortcomings of the prior art, the embodiment of the invention provides a method and a device for estimating the rainfall and waterlogging reduction of a sponge urban green land.
In one aspect, an embodiment of the present invention provides a method for estimating an amount of reduction of rainfall waterlogging in a sponge urban green land, including:
s1, obtaining an underlying surface remote sensing image of the sponge city to be estimated, generating a grid with a preset specification, and overlapping the grid to the underlying surface remote sensing image;
s2, determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and S3, estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
In another aspect, an embodiment of the present invention provides an apparatus for estimating an amount of reduction of rainfall and waterlogging in a sponge urban green space, including:
the system comprises a superposition unit, a detection unit and a calculation unit, wherein the superposition unit is used for acquiring an underlying surface remote sensing image of a sponge city to be estimated, generating a grid with a preset specification and superposing the grid to the underlying surface remote sensing image;
the determining unit is used for determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and the estimation unit is used for estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
In a third aspect, an embodiment of the present invention provides an electronic device, including: a processor, a memory, a bus, and a computer program stored on the memory and executable on the processor;
the processor and the memory complete mutual communication through the bus;
the processor, when executing the computer program, implements the method described above.
In a fourth aspect, an embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the above method.
The method and the device for estimating the rainfall and waterlogging reduction of the sponge city greenbelt provided by the embodiment of the invention comprise the steps of firstly obtaining an underlying surface remote sensing image of the sponge city to be estimated, generating a grid with a preset specification, and superposing the grid to the underlying surface remote sensing image; then, determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result; and finally, estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of various types of vegetation of the grid and the soil area under the vegetation of the grid.
Drawings
FIG. 1 is a schematic flow chart illustrating an embodiment of the method for estimating rainfall waterlogging reduction in a sponge urban greenbelt according to the present invention;
FIG. 2 is a schematic structural diagram of an embodiment of the device for estimating the rainfall waterlogging reduction of the sponge urban greenbelt according to the present invention;
fig. 3 is a schematic physical structure diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments, but not all embodiments, of the present invention. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments of the present invention without any creative effort belong to the protection scope of the embodiments of the present invention.
Referring to fig. 1, the embodiment discloses a method for estimating the reduction of rainfall waterlogging in a sponge urban green land, which comprises the following steps:
s1, acquiring an underlying surface remote sensing image of the sponge city to be estimated, generating a grid with a preset specification (the grid can be generated by utilizing GIS (geographic information system) professional software), and overlapping the grid to the underlying surface remote sensing image;
s2, determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and S3, estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
In this embodiment, the remote sensing image of the underlying surface of the sponge city is preferably a remote sensing image with medium resolution, and a remote sensing image with low resolution or a remote sensing image with high resolution may be used.
In the prior art, when the method is applied to sponge city hydrology, the method for extracting vegetation area and soil area has certain defects. On one hand, due to the complexity of the underlying surface, information is difficult to obtain; on the other hand, the difference of information extraction of the regions with different development degrees of the city is not considered, so that the accuracy of information extraction is low. In this embodiment, utilize the underlay surface remote sensing image in sponge city to carry out city development degree's subregion to every net, according to the city development degree of difference, determine the soil area under the vegetation of the net of corresponding city development degree to according to the area of the various types vegetation of each net with the soil area under the vegetation of net estimates the reduction of the greenery patches in sponge city to precipitation waterlogging, thereby can effectively estimate the reduction of sponge city greenery patches to precipitation waterlogging.
On the basis of the foregoing method embodiment, the determining areas of various types of vegetation of the grid by using the remote sensing image of the underlying surface may include:
fusing the panchromatic wave band part and the multispectral wave band part of the underlying surface remote sensing image, and segmenting the fused result to obtain a plurality of patches;
for each patch, judging whether the patch is a vegetation area or not, and judging whether the patch is a grassland area or not when the patch is the vegetation area;
and for each grid, determining the areas of various types of vegetation of the grid according to the judgment result of whether each patch forming the grid is a grassland area, wherein the vegetation types of the grid comprise coniferous forests, broad-leaved forests and grasslands.
On the basis of the foregoing method embodiment, the determining whether the patch is a vegetation area may include:
calculating the NDVI (Normalized Difference Vegetation Index) value of the patch, and judging whether the NDVI value of the patch is larger than or equal to a first value;
and if the NDVI value of the patch is greater than or equal to the first value, determining that the patch is a vegetation area, otherwise, determining that the patch is not the vegetation area.
In this embodiment, the NDVI value of the blob is an average of the NDVI values of all the first type pixels in the blob. The first type of pixel refers to a pixel with resolution consistent with the underlying surface remote sensing image. For example, when the resolution of the underlying surface remote sensing image is medium resolution, the first type of image element refers to a medium resolution image element.
On the basis of the foregoing method embodiment, the determining whether the patch is a grassy area may include:
calculating the half variation function value of the plaque, and judging whether the half variation function value of the plaque is smaller than a second value;
and if the half variation function value of the patch is smaller than the second numerical value, determining that the patch is a grassland area, otherwise, determining that the patch is not the grassland area.
On the basis of the foregoing method embodiment, the determining the areas of the various types of vegetation in the grid according to the determination result of whether each patch constituting the grid is a grassy area may include:
calculating the area of the patch of the grassland area in the grid, and calculating the area of the grassland in the grid according to the area of the patch of the grassland area in the grid;
calculating the area of the forest land in the grid according to the area of the grassland in the grid;
and calculating the areas of coniferous forests and broad-leaved forests in the grid according to the areas of the forest lands in the grid.
In this embodiment, for each mesh, the area of the grass in the mesh is the sum of the areas of the patches in the mesh that are areas of grass. The area of the forest land in the grid is the difference between the area of the vegetation in the grid and the area of the grassland in the grid. When calculating the areas of the coniferous forest and the broadleaf forest in the grid, any one of the areas of the coniferous forest and the broadleaf forest in the grid may be calculated first, for example, the area of the coniferous forest may be calculated first, and then the difference between the area of the forest land in the grid and the area of the coniferous forest in the grid is calculated to obtain the area of the broadleaf forest in the grid. Area S of conifer forest in gridzIs calculated by the formulaWherein NDVIiIs the NDVI value of the ith first type pixel in the grid, n is the number of the first type pixels in the grid, NDVIzIs the average value of the NEEDLE NDVI, NDVIwminAverage NDVI value, S, for the underlying surface of very green vegetation in winteraIs the area of the picture element. The formula for calculating the area of the broad leaf forest in the grid is consistent with the formula for calculating the area of the coniferous forest, hereAnd will not be described in detail.
On the basis of the foregoing method embodiment, the partitioning the grid into city development degrees by using the underlying surface remote sensing image may include:
calculating vegetation area proportion S in each grid by using underlying surface remote sensing imagepThe calculation formula isWherein, Sgfor the area of vegetation in the lattice, NDVIiIs the NDVI value, R, of the ith first type pixel in the gridniIs the near infrared band reflectivity, R, of the ith first type pixel in the gridriThe red band reflectivity of the ith pixel of the first type in the grid,is the NDVI mean value of the lower cushion surface of the sponge city,is the NDVI mean value of the whole coverage area of vegetation, SΔIs the area of the grid, n is the number of pixels of the first type in the grid, SaIs the area of the pixel;
for each grid, if the vegetation area proportion in the grid is judged to be smaller than or equal to a third numerical value, determining the grid as a height development area; or
If the area proportion of the vegetation in the grid is judged to be larger than the third numerical value and smaller than or equal to the fourth numerical value, determining that the grid is a medium development area; or
And if the area proportion of the vegetation in the grid is judged to be larger than the fourth numerical value, determining that the grid is a vegetation dense area, wherein the fourth numerical value is larger than the third numerical value.
In this embodiment, the value ranges of the third value and the fourth value are between 0 and 1, and the specific values may be set as needed, which is not described herein again.
On the basis of the embodiment of the method, the city development degree is the soil area S of the grid of the high development areas1May be Ss1＝b1×Sg1Wherein b is1Is a first empirical coefficient, Sg1Is the area of vegetation in the grid,
soil area S of grid with medium development area of city development degrees2May be Ss2＝Sgr+b2×StWherein S istIs the area of the forest land in the grid, SgrIs the area of the grass in the grid, b2Is a second empirical coefficient of the first set of empirical coefficients,
soil area S of grid of vegetation dense area for urban development degrees3Can be calculated asWherein NDVIiIs the NDVI value of the ith first type pixel in the grid, n is the number of the first type pixels in the grid, NDVImaxIs the NDVI value at full vegetation coverage, NDVIminIs the NDVI value of the soil, SaIs the area of the picture element.
On the basis of the foregoing method embodiment, the S3 may include:
for each grid, calculating the leaf area index LAI of the corresponding type of vegetation of the grid according to the area of the various types of vegetation of the grid, and calculating the leaf area index LAI of the grid according to the leaf area index LAI of the various types of vegetation of the grid;
for each grid, calculating vegetation retention evaporation capacity, vegetation transpiration capacity, soil evaporation capacity and deep interflow and underground runoff of the grid according to the soil area and leaf area index LAI under the vegetation of the grid, and calculating the rainfall and waterlogging reduction capacity of the grid according to the vegetation retention evaporation capacity, the vegetation transpiration capacity, the soil evaporation capacity and the deep interflow and underground runoff of the grid;
and calculating the rainfall waterlogging reduction amount of the greenbelt of the sponge city according to the rainfall waterlogging reduction amount of the grids.
In this embodiment, the leaf area index LAI of each type of vegetation may be calculated by using the existing method for estimating the correlation between NDVI and LAI based on the vegetation type. For coniferous and broadleaf forests, the leaf area index LAI of one can be calculated first, and the leaf area index LAI of the other can be calculated according to the leaf area index LAI and the aggregation coefficient calculated first. For example, after calculating the leaf area index LAI of a hardwood forest, the product of the leaf area index LAI of the hardwood forest and the aggregation coefficient may be calculated as the leaf area index LAI of a conifer forest. The leaf area index LAI of a grid is the result of summing the products of the leaf area indexes LAI of the various types of vegetation of the grid and the areas of the corresponding types of vegetation.
Based on the foregoing method embodiments, for each grid, the reduction amount of precipitation and waterlogging by the grid may be the sum of the vegetation retention evaporation amount, the vegetation transpiration amount, the soil evaporation amount, and the deep interflow and subsurface runoff amount of the grid.
In this embodiment, the calculation of the vegetation retention evaporation capacity, the vegetation transpiration capacity, the soil evaporation capacity, and the deep soil underflow and underground runoff is the prior art, and is not described herein again.
Referring to fig. 2, the embodiment discloses an apparatus for estimating the amount of rainfall waterlogging on a sponge urban green land, comprising:
the device comprises a superposition unit 1, a detection unit and a calculation unit, wherein the superposition unit 1 is used for acquiring an underlying surface remote sensing image of a sponge city to be estimated, generating a grid with a preset specification, and superposing the grid to the underlying surface remote sensing image;
the determining unit 2 is used for determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and the estimation unit 3 is used for estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
Specifically, the superposition unit 1 acquires an underlying surface remote sensing image of a sponge city to be estimated, generates a grid with a preset specification, and superposes the grid on the underlying surface remote sensing image; the determining unit 2 determines the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitions the urban development degree of the grid by using the underlying surface remote sensing image, and determines the soil area under the vegetation of the grid according to the partitioning result; the estimation unit 3 estimates the reduction amount of rainfall and waterlogging of the greenbelt of the sponge city according to the areas of various types of vegetation of the grid and the soil area under the vegetation of the grid.
The device for estimating the rainfall and waterlogging reduction of the sponge city greenbelt provided by the embodiment of the invention comprises the following steps of firstly obtaining an underlying surface remote sensing image of the sponge city to be estimated, generating a grid with a preset specification, and superposing the grid to the underlying surface remote sensing image; then, determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result; and finally, estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of various types of vegetation of the grid and the soil area under the vegetation of the grid.
The device for estimating the reduction amount of the rainfall waterlogging in the sponge city greenbelt can be used for executing the technical scheme of the method embodiment, the implementation principle and the technical effect are similar, and the description is omitted here.
Fig. 3 is a schematic entity structure diagram of an electronic device according to an embodiment of the present invention, and as shown in fig. 3, the electronic device may include: a processor 11, a memory 12, a bus 13, and a computer program stored on the memory 12 and executable on the processor 11;
the processor 11 and the memory 12 complete mutual communication through the bus 13;
when the processor 11 executes the computer program, the method provided by the foregoing method embodiments is implemented, for example, including: acquiring a remote sensing image of an underlying surface of a sponge city to be estimated, generating a grid with a preset specification, and overlapping the grid to the remote sensing image of the underlying surface; determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result; and estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of various types of vegetation of the grids and the soil area under the vegetation of the grids.
An embodiment of the present invention provides a non-transitory computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method provided by the foregoing method embodiments, and for example, the method includes: acquiring a remote sensing image of an underlying surface of a sponge city to be estimated, generating a grid with a preset specification, and overlapping the grid to the remote sensing image of the underlying surface; determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result; and estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of various types of vegetation of the grids and the soil area under the vegetation of the grids.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element. The terms "upper", "lower", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the referred devices or elements must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Unless expressly stated or limited otherwise, the terms "mounted," "connected," and "connected" are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the description of the present invention, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description. Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present invention is not limited to any single aspect, nor is it limited to any single embodiment, nor is it limited to any combination and/or permutation of these aspects and/or embodiments. Moreover, each aspect and/or embodiment of the present invention may be utilized alone or in combination with one or more other aspects and/or embodiments thereof.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. A method for estimating the reduction of precipitation waterlogging in a sponge urban green land, comprising:
s1, obtaining an underlying surface remote sensing image of the sponge city to be estimated, generating a grid with a preset specification, and overlapping the grid to the underlying surface remote sensing image;
s2, determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and S3, estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
2. The method of claim 1, wherein determining the area of each type of vegetation for the grid using the remote sensing image of the underlying surface comprises:
fusing the panchromatic wave band part and the multispectral wave band part of the underlying surface remote sensing image, and segmenting the fused result to obtain a plurality of patches;
for each patch, judging whether the patch is a vegetation area or not, and judging whether the patch is a grassland area or not when the patch is the vegetation area;
and for each grid, determining the areas of various types of vegetation of the grid according to the judgment result of whether each patch forming the grid is a grassland area, wherein the vegetation types of the grid comprise coniferous forests, broad-leaved forests and grasslands.
3. The method of claim 2, wherein determining whether the patch is a vegetation area comprises:
calculating the NDVI value of the plaque, and judging whether the NDVI value of the plaque is larger than or equal to a first value;
and if the NDVI value of the patch is greater than or equal to the first value, determining that the patch is a vegetation area, otherwise, determining that the patch is not the vegetation area.
4. The method of claim 2, wherein determining whether the blob is a grassy area comprises:
calculating the half variation function value of the plaque, and judging whether the half variation function value of the plaque is smaller than a second value;
and if the half variation function value of the patch is smaller than the second numerical value, determining that the patch is a grassland area, otherwise, determining that the patch is not the grassland area.
5. The method according to claim 3 or 4, wherein the determining the areas of the various types of vegetation of the mesh according to the determination result of whether the respective patches constituting the mesh are grassy areas comprises:
calculating the area of the patch of the grassland area in the grid, and calculating the area of the grassland in the grid according to the area of the patch of the grassland area in the grid;
calculating the area of the forest land in the grid according to the area of the grassland in the grid;
and calculating the areas of coniferous forests and broad-leaved forests in the grid according to the areas of the forest lands in the grid.
6. The method of claim 1, wherein said partitioning the grid into city development levels using the underlying remote sensing image comprises:
calculating vegetation area proportion S in each grid by using underlying surface remote sensing imagepThe calculation formula isWherein, Rniis the near infrared band reflectivity, R, of the ith first type pixel in the gridriThe red band reflectivity of the ith pixel of the first type in the grid,is the NDVI mean value of the lower cushion surface of the sponge city,is the NDVI mean value of the whole coverage area of vegetation, SΔIs the area of the grid, n is the number of pixels of the first type in the grid, SaIs the area of the pixel;
for each grid, if the vegetation area proportion in the grid is judged to be smaller than or equal to a third numerical value, determining the grid as a height development area; or
If the area proportion of the vegetation in the grid is judged to be larger than the third numerical value and smaller than or equal to the fourth numerical value, determining that the grid is a medium development area; or
And if the area proportion of the vegetation in the grid is judged to be larger than the fourth numerical value, determining that the grid is a vegetation dense area, wherein the fourth numerical value is larger than the third numerical value.
7. Method according to claim 6, characterized in that the city is developed to the extent of the soil area S of the grid of the high development areas1Is calculated by the formula Ss1＝b1×Sg1Wherein b is1Is a first empirical coefficient, Sg1Is the area of vegetation in the grid,
soil area S of grid with medium development area of city development degrees2Is calculated by the formula Ss2＝Sgr+b2×StWherein S istIs the area of the forest land in the grid, SgrIs the area of the grass in the grid, b2Is a second empirical coefficient of the first set of empirical coefficients,
soil area S of grid of vegetation dense area for urban development degrees3Is calculated by the formulaWherein NDVIiIs the NDVI value of the ith first type pixel in the grid, n is the number of the first type pixels in the grid, NDVImaxIs the NDVI value at full vegetation coverage, NDVIminIs the NDVI value of the soil, SaIs the area of the picture element.
8. The method according to claim 1, wherein the S3 includes:
for each grid, calculating the leaf area index LAI of the corresponding type of vegetation of the grid according to the area of the various types of vegetation of the grid, and calculating the leaf area index LAI of the grid according to the leaf area index LAI of the various types of vegetation of the grid;
for each grid, calculating vegetation retention evaporation capacity, vegetation transpiration capacity, soil evaporation capacity and deep interflow and underground runoff of the grid according to the soil area and leaf area index LAI under the vegetation of the grid, and calculating the rainfall and waterlogging reduction capacity of the grid according to the vegetation retention evaporation capacity, the vegetation transpiration capacity, the soil evaporation capacity and the deep interflow and underground runoff of the grid;
and calculating the rainfall waterlogging reduction amount of the greenbelt of the sponge city according to the rainfall waterlogging reduction amount of the grids.
9. The method of claim 8, wherein for each grid, the amount of rainfall waterlogging that the grid consumes is the sum of the vegetation hold-off evapotranspiration, the vegetation transpiration, the soil evapotranspiration, and the deep interflow and subsurface runoff of the grid.
10. An apparatus for estimating the amount of water lost to precipitation in a sponge urban greenbelt, comprising:
the system comprises a superposition unit, a detection unit and a calculation unit, wherein the superposition unit is used for acquiring an underlying surface remote sensing image of a sponge city to be estimated, generating a grid with a preset specification and superposing the grid to the underlying surface remote sensing image;
the determining unit is used for determining the areas of various types of vegetation of the grid by using the underlying surface remote sensing image, partitioning the grid by using the underlying surface remote sensing image according to the urban development degree, and determining the soil area under the vegetation of the grid according to the partitioning result;
and the estimation unit is used for estimating the reduction amount of the rainfall and waterlogging of the green land of the sponge city according to the areas of the various types of vegetation of the grid and the soil area under the vegetation of the grid.
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