CN114689545B - Vegetation coverage layered estimation method and medium based on DSM (digital surface model) contour slices - Google Patents

Vegetation coverage layered estimation method and medium based on DSM (digital surface model) contour slices Download PDF

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CN114689545B
CN114689545B CN202210205422.7A CN202210205422A CN114689545B CN 114689545 B CN114689545 B CN 114689545B CN 202210205422 A CN202210205422 A CN 202210205422A CN 114689545 B CN114689545 B CN 114689545B
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顾祝军
童建
郭红丽
李盟
吴芳
扶卿华
林带娣
吴家晟
曾麦脉
王晓刚
吴秉校
赵敏
何秋银
陈黎
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Abstract

The invention discloses a vegetation coverage layered estimation method and medium based on DSM (digital surface model) contour slices, which are characterized in that vegetation indexes of pure vegetation and pure soil are calculated through surface reflectivity data of a digital ortho image (DOM) generated by a multi-angle remote sensing image, a pixel overall vegetation coverage (VFC) is obtained by utilizing a general pixel dichotomy, a pixel relative height value is obtained by combining a Digital Surface Model (DSM) generated by the multi-angle remote sensing image, a pixel VFC cube is obtained, layered cutting is carried out according to equal height intervals, an average overall VFC of each layer is extracted, a vertical overlapping experience model is utilized, layered VFCs of pixel cubes in different height intervals are extracted, vertical distribution curves of layered VFCs with different heights are obtained, and the estimation efficiency and the estimation precision of vertical layering of forest land coverage can be effectively improved; the method opens up a new visual angle for characterizing the specific complex vertical vegetation structure of the forest land by people and promotes the scientific understanding of the forest ecological process by people.

Description

Vegetation coverage layered estimation method and medium based on DSM (digital surface model) contour slices
Technical Field
The invention relates to the technical field of remote sensing, in particular to a vegetation coverage layered estimation method and medium based on DSM (surface-mounted digital image) contour slices.
Background
The vegetation coverage is the percentage of the vertical projection area of vegetation (including leaves, stems and branches) on the ground to the total area of a research area, represents the horizontal distribution density of the vegetation, is an important index for measuring the distribution of the ground vegetation, and has wide application in the fields of land desertification evaluation, resource environment management, water and soil loss monitoring, disaster risk evaluation and the like. The measurement method of vegetation coverage is divided into two types of ground surface actual measurement and remote sensing estimation, and the method of ground surface actual measurement has higher precision but wastes time and labor. The estimation method for extracting the vegetation coverage based on the remote sensing image can realize large-range quick and accurate estimation, and has made certain progress along with the development of the remote sensing technology.
In practical application, the estimation method for extracting vegetation coverage based on the remote sensing image mainly calculates the total VFC or calculates the VFC of a forest canopy layer and an under-forest grass layer, and related reports of calculating the VFC in multiple layers are not found, so that the representation of the special complex vertical vegetation structure of the forest land by people is limited, and the scientific understanding of the forest ecological process by people is restricted.
Disclosure of Invention
The invention provides a vegetation coverage layered estimation method and medium based on DSM (surface digital model) contour slices, which are characterized in that vegetation indexes of pure vegetation and pure soil are calculated through surface reflectivity data of a digital ortho image (DOM) generated by a multi-angle remote sensing image, pixel overall vegetation coverage (VFC) is obtained by using a general pixel dichotomy, a pixel relative height value is obtained by combining a Digital Surface Model (DSM) generated by the multi-angle remote sensing image, a pixel VFC cube is obtained, layered cutting is carried out according to equal height intervals, average overall VFC of each layer is extracted, layered VFC of pixel cubes in different height intervals is extracted by using a vertical overlapping experience model, and vertical distribution of layered VFC with different heights is obtained. The method can effectively solve the problems of the estimation method of the vegetation coverage in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme: a vegetation coverage layered estimation method and medium based on DSM contour slices comprise the following implementation steps:
s1, preprocessing a multi-angle remote sensing image (such as but not limited to a forward-looking camera inclination angle +26 degrees, a backward-looking camera inclination angle-5 degrees and a spatial resolution superior to 1 m) digital ortho image (DOM), and calculating a reflectivity data product;
s2, calculating a normalized vegetation index (NDVI) of the remote sensing image;
s3, calculating the vegetation coverage (VFC) of each pixel by using a general pixel dichotomy;
s4, layering DSMs at equal height intervals based on a Digital Surface Model (DSM) generated by the multi-angle remote sensing image, and reclassifying DSM data according to height intervals to obtain pixel cubes at different height layers;
s5, extracting average overall vegetation coverage of each layer in equal-height interval layering
Figure GDA0003859498870000021
And S6, calculating the layered VFC among different height layers through a vertical overlapping empirical model, and finally obtaining a VFC vertical distribution curve.
According to the technical scheme, the specific steps of preprocessing the remote sensing image in the S1 comprise:
s1-1, radiometric calibration, namely converting the DN value of the remote sensing image into an absolute radiance value;
s1-2, atmospheric correction, wherein absolute radiance values are converted into earth surface reflectivity data;
and S1-3, performing orthorectification to eliminate parallax caused by the ground elevation of the image, thereby obtaining the image with accurate spatial positioning.
According to the above technical solution, in S2, the calculation formula of NDVI is as follows:
NDVI＝(ρ NIR -ρ RED )/(ρ NIR +ρ RED ) (1)
in the formula: rho NIR Representing the reflectivity data of the near infrared band in the remote sensing image;
ρ RED representing the reflectivity data of the red light wave band in the remote sensing image.
According to the above technical solution, in S3, the calculation formula of VFC is as follows:
VFC＝(NDVI-NDVI soil )/(NDVI veg -NDVI soil ) (2)
in the formula: NDVI soil NDVI value of the pure bare soil pixel;
NDVI veg then the NDVI value for the clear vegetation pixel is represented.
According to the technical scheme, when the NDVI value is researched, the NDVI in each pixel is calculated and extracted, and the frequency accumulation value of the NDVI value is calculated for each pixel in a research area;
then, according to the frequency accumulation table, the NDVI value with the frequency of 5 percent is taken as the NDVI soil And NDVI value with a frequency of 95% is NDVI veg 。
According to the technical scheme, in S4, a fishing net with uniform size is established as a sample, the remote sensing image is subjected to equidistant height layering according to a Digital Surface Model (DSM) generated by front-view and back-view multi-angle remote sensing images, and DSM data is reclassified according to layered height intervals to obtain layered raster data.
According to the technical scheme, in S5, the raster data is vectorized according to the layer number field to obtain the vector file of each layer, and statistics is calculated according to the layer number field in the vector file
Figure GDA0003859498870000031
The calculation formula of (a) is as follows:
Figure GDA0003859498870000032
in the formula: n is the total number of the layered pixels.
According to the above technical solution, in S6, the vertical overlap empirical model is:
Figure GDA0003859498870000041
in the formula:
Figure GDA0003859498870000042
is an integral VFC;
VFC n VFC as the lower layer;
VFC n+1 for the upper VFC, the calculation formula is as follows:
Figure GDA0003859498870000043
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure GDA0003859498870000044
And VFC n To obtain VFC n+1 And solving layer by layer to obtain the VFC of the layer cube with different heights, namely obtaining the vertical distribution curve of the VFC.
According to the practical scheme, the medium stores computer executable instructions which are set as the vertical layered estimation method of the vegetation coverage of the forest land based on the multi-angle remote sensing digital surface model and the like.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of obtaining vertical distribution of layered VFCs with different heights through series processing of earth surface reflectivity data of digital ortho images (DOM) generated by multi-angle remote sensing images, avoiding the practical problem of canopy shielding in the remote sensing images, and calculating the mean value of vegetation coverage of different height intervals through the characteristic values (height and vegetation coverage) of a digital surface model based on the neighborhood similarity principle of the first law of geography. The method can effectively improve the estimation efficiency and the estimation precision of the vertical layering of the vegetation coverage of the forest land, opens up a new visual angle for characterizing the specific complex vertical vegetation structure of the forest land, and promotes scientific understanding of the forest ecological process by people.
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The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a diagram of implementation steps of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example 1:
as shown in fig. 1-2, the present invention provides a technical solution, a vegetation coverage layered estimation method and medium based on DSM contour slice, comprising the following implementation steps:
s1, preprocessing a multi-angle remote sensing image (a forward-looking camera inclination angle is +26 degrees, a rear-looking camera inclination angle is-5 degrees, and the spatial resolution is superior to 1 m) digital ortho image (DOM), and calculating a reflectivity data product;
s2, calculating a normalized vegetation index (NDVI) of the remote sensing image;
s3, calculating the vegetation coverage (VFC) of each pixel by using a general pixel dichotomy;
s4, layering DSMs at equal height intervals based on a Digital Surface Model (DSM) generated by the multi-angle remote sensing image, and reclassifying DSM data according to height intervals to obtain pixel cubes at different height layers;
s5, extracting at equal heightAverage overall vegetation coverage per layer in spaced apart tiers
Figure GDA0003859498870000051
And S6, calculating the layered VFC among different height layers through a vertical overlapping empirical model, and finally obtaining a VFC vertical distribution curve.
According to the technical scheme, the specific steps of preprocessing the remote sensing image in the S1 comprise:
s1-1, radiometric calibration, namely converting the DN value of the remote sensing image into an absolute radiance value;
s1-2, correcting atmosphere, and converting absolute radiance values into earth surface reflectivity data;
and S1-3, performing orthorectification, and eliminating parallax caused by the ground elevation of the image so as to obtain the image with accurate spatial positioning.
According to the technical scheme, in S2, the NDVI is calculated according to the following formula:
NDVI＝(ρ NIR -ρ RED )/(ρ NIR +ρ RED ) (1)
in the formula: ρ is a unit of a gradient NIR Representing the reflectivity data of the near infrared band in the remote sensing image;
ρ RED representing the reflectivity data of the red light wave band in the remote sensing image.
According to the above technical solution, in S3, the VFC has the following calculation formula:
VFC＝(NDVI-NDVI soil )/(NDVI veg -NDVI soil ) (2)
in the formula: NDVI soil NDVI value of the pure bare soil pixel;
NDVI veg then the NDVI value for the clear vegetation pixel is represented.
According to the technical scheme, when the NDVI value is researched, the NDVI in each pixel is calculated and extracted, and the frequency accumulation value of the NDVI value is calculated for each pixel in a research area;
then, according to the frequency accumulation table, the NDVI value with the frequency of 5 percent is taken as the NDVI soil And NDVI value with a frequency of 95% is NDVI veg 。
According to the technical scheme, in S4, a fishing net with uniform size is established as a sample, the remote sensing image is subjected to equidistant height layering according to a Digital Surface Model (DSM) generated by front-view and back-view multi-angle remote sensing images, and DSM data is reclassified according to layered height intervals to obtain layered raster data.
According to the technical scheme, in S5, the raster data is vectorized according to the layer number field to obtain the vector file of each layer, and statistics is calculated according to the layer number field in the vector file
Figure GDA0003859498870000071
Figure GDA0003859498870000072
The calculation formula of (c) is as follows:
Figure GDA0003859498870000073
in the formula: n is the total number of the layered pixels.
According to the above technical solution, in S6, the vertical overlap empirical model is:
Figure GDA0003859498870000074
in the formula:
Figure GDA0003859498870000075
is an integral VFC;
VFC n is the lower layer of VFC;
VFC n+1 for the upper VFC, the calculation formula is as follows:
Figure GDA0003859498870000076
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure GDA0003859498870000077
And VFC n To obtain VFC n+1 And solving layer by layer to obtain the VFC of the layer cube with different heights, namely obtaining the vertical distribution curve of the VFC.
According to the practical scheme, the medium stores computer executable instructions which are set as the forest vegetation coverage vertical layered estimation method and medium based on the multi-angle remote sensing digital surface model and the like.
Example 2:
as shown in fig. 1-2, a high-grade 7 # L1A product is used as satellite remote sensing image data, and a certain vegetation coverage area in the south of China is used as an experimental area;
the method comprises the following implementation steps:
s1, acquiring original data of a high-grade No. 7L 1A product, preprocessing the original data, including radiometric calibration, atmospheric correction, orthotropic correction and image fusion, and finally obtaining a ground surface reflectivity data image accurately positioned in an experimental area space.
S2, calculating the normalized vegetation index (NDVI) of the experimental area through the formula (1)
NDVI＝(ρ NIR -ρ RED )/(ρ NIR +ρ RED ) (1)
In the formula: rho NIR Representing the B4 near infrared band reflectivity data in the high-resolution 7 image;
ρ RED representing the reflectance data of the B3 red band in the high-resolution 7 images.
And S3, calculating the vegetation coverage (VFC) of the remote sensing image of the experimental area by using a general pixel dichotomy, namely a formula (2), obtaining a frequency accumulation table by counting pixel values of the experimental area, and taking the NDVI values of 5% and 95% of frequencies as the NDVI value of the pure bare soil and the NDVI value of the pure vegetation respectively.
VFC＝(NDVI-NDVI soil )/(NDVI veg -NDVI soil ) (2)
In the formula: NDVI soil NDVI values for areas that are completely bare or non-vegetation covered;
NDVI veg then the NDVI value for the picture element that is completely covered by vegetation, i.e., the NDVI value for a purely vegetated picture element, is represented.
And S4, establishing fishing nets (namely 144 pixels in one fishing net) with the size of 12 × 12 pixels in the research area, wherein each fishing net is a sample.
According to a Digital Surface Model (DSM) generated by front-view and rear-view multi-angle remote sensing images with the height division of No. 7, the remote sensing images are subjected to equidistant high layering, and a sample is taken as an example and is divided into 16 layers at 20cm as one layer.
And reclassifying the DSM data according to the layered height interval to obtain 16-layer raster data.
And S5, vectorizing the raster data according to the layer number field to obtain a vector file of each layer.
Calculating and counting the VFC mean value of the vegetation coverage of each layer according to the number-of-layers field in the vector file
Figure GDA0003859498870000091
Figure GDA0003859498870000092
In the formula: n is the total number of the layered pixels.
S6, calculating the VFC between different height layers by utilizing a vertical overlapping empirical model in the formula (4), wherein the VFC in two vertically adjacent equal height interval layers is known
Figure GDA0003859498870000093
And VFC n To obtain VFC n+1 And thus, the layer-by-layer solution is carried out to obtain the VFC of the layer cube with different heights, and the vertical distribution curve of the VFC can be obtained.
Figure GDA0003859498870000094
In the formula: VFC n+1 Upper layer VFC value;
Figure GDA0003859498870000095
is the average value of VFC of each layer;
VFC n the lower layer VFC value.
(Note: individual VFC) n+1 >When 1, let it be 1, or<0, making it 0).
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (4)

1. A vegetation coverage layered estimation method based on DSM contour slices is characterized in that: the method comprises the following implementation steps:
s1, preprocessing a multi-angle remote sensing image digital ortho image (DOM) and calculating a reflectivity data product;
s2, calculating a normalized vegetation index (NDVI) of the remote sensing image;
s3, calculating the vegetation coverage (VFC) of each pixel by using a general pixel dichotomy;
s4, performing equal-height-interval layered cutting on a Digital Surface Model (DSM) generated based on the multi-angle remote sensing image, and reclassifying DSM data according to a height interval to obtain pixel cubes of different height layers;
s5, extracting average overall vegetation coverage of each layer in equal-height interval layering
Figure FDA0003859498860000011
S6, calculating layered VFCs among different height layers through a vertical overlapping empirical model, and finally obtaining a VFC vertical distribution curve;
in S1, the specific steps of preprocessing the remote sensing image comprise:
s1-1, radiometric calibration, namely converting the DN value of the remote sensing image into an absolute radiance value;
s1-2, atmospheric correction, wherein absolute radiance values are converted into earth surface reflectivity data;
s1-3, performing orthorectification to eliminate parallax caused by the ground elevation of the image so as to obtain an image with accurate spatial positioning;
in S2, the NDVI is calculated as follows:
NDVI＝(ρ NIR -ρ RED )/(ρ NIR +ρ RED ) (1)
in the formula: rho NIR Representing the reflectivity data of the near infrared band in the remote sensing image;
ρ RED representing the reflectivity data of the red light wave band in the remote sensing image;
in the S3, the VFC has the following calculation formula:
VFC＝(NDVI-NDVI soil )/(NDVI veg -NDVI soil ) (2)
in the formula: NDVI soil Is the NDVI value of the pure bare soil pixel;
NDVI veg then representing the NDVI value of the pure vegetation pixel;
in S5, vectorizing the raster data according to the layer number field to obtain a vector file of each layer, and calculating statistics according to the layer number field in the vector file
Figure FDA0003859498860000021
The calculation formula of (c) is as follows:
Figure FDA0003859498860000022
in the formula: n is the total number of the layered pixels;
in S6, the vertical overlapping empirical model is:
Figure FDA0003859498860000023
in the formula:
Figure FDA0003859498860000024
is an integral VFC;
VFC n is the lower layer of VFC;
VFC n+1 for the upper VFC, the calculation formula is as follows:
Figure FDA0003859498860000025
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure FDA0003859498860000026
And VFC n To obtain VFC n+1 And solving layer by layer to obtain the VFC of the layer cube with different heights, namely obtaining the vertical distribution curve of the VFC.
2. The method of claim 1, wherein when the NDVI value is studied, the NDVI in each pixel is calculated and extracted, and the frequency cumulative value of the NDVI value is calculated for each pixel in a study area;
then, according to the frequency accumulation table, the NDVI value with the frequency of 5 percent is taken as the NDVI soil And NDVI value with a frequency of 95% is NDVI veg 。
3. The method of claim 1, wherein in step S4, a uniform-size fishing net is established as a prototype, the remote-sensing images are highly layered at equal intervals according to a Digital Surface Model (DSM) generated from the multi-angle remote-sensing images, and DSM data is reclassified according to the layered height intervals to obtain layered raster data.
4. A medium for vegetation coverage layered estimation based on DSM contour slices, wherein the medium stores computer-executable instructions configured as the method for forest vegetation coverage vertical layered estimation based on multi-angle remote sensing DSM contour slices according to any one of claims 1-3.
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