CN114689545A - 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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CN114689545A
CN114689545A CN202210205422.7A CN202210205422A CN114689545A CN 114689545 A CN114689545 A CN 114689545A CN 202210205422 A CN202210205422 A CN 202210205422A CN 114689545 A CN114689545 A CN 114689545A
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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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Pearl River Hydraulic Research Institute of PRWRC
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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 methods 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 invention 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, the inclination angle of a front-view camera is plus 26 degrees, the inclination angle of a rear-view camera is minus 5 degrees, and the spatial resolution is better than 1m) 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 spacing layers
Figure BDA0003527821030000021
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 step of preprocessing the remote sensing image in the step S1 includes:
s1-1, radiometric calibration, namely converting the DN value of the remote sensing image into an absolute radiance value;
s1-2, atmospheric correction, converting the absolute radiance value 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 NDVI is calculated as follows:
NDVI＝(ρNIR-ρRED)/(ρNIR+ρRED) (1)
in the formula: rhoNIRRepresenting the reflectivity data of the near infrared band in the remote sensing image;
ρREDrepresenting 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-NDVIsoil)/(NDVIveg-NDVIsoil) (2)
in the formula: NDVIsoilNDVI value of the pure bare soil pixel;
NDVIvegthen 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 cumulative 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 asNDVIsoilAnd NDVI value with a frequency of 95% is NDVIveg。
According to the technical scheme, in the S4, a uniform-size fishing net is established as a sample, the remote sensing images are 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 are reclassified according to layered height intervals to obtain layered raster data.
According to the above technical solution, in S5, vectorizing 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 BDA0003527821030000031
The calculation formula of (a) is as follows:
Figure BDA0003527821030000041
in the formula: and n is the total number of the layered image elements.
According to the above technical solution, in S6, the vertical overlap empirical model is:
Figure BDA0003527821030000042
in the formula:
Figure BDA0003527821030000043
is an integral VFC;
VFCnVFC as the lower layer;
VFCn+1for the upper VFC, the calculation formula is as follows:
Figure BDA0003527821030000044
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure BDA0003527821030000045
And VFCnTo obtain VFCn+1And 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 intervals with different heights 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 (the inclination angle of a front-view camera is +26 degrees, the inclination angle of a rear-view camera is-5 degrees, and the spatial resolution is superior to 1m) 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 spacing layers
Figure BDA0003527821030000061
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 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, converting the absolute radiance value 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 NDVI is calculated as follows:
NDVI＝(ρNIR-ρRED)/(ρNIR+ρRED) (1)
in the formula: rhoNIRRepresenting the reflectivity data of the near infrared band in the remote sensing image;
ρREDin representative remote sensing imageRed band reflectivity data.
According to the above technical solution, in S3, the VFC has the following calculation formula:
VFC＝(NDVI-NDVIsoil)/(NDVIveg-NDVIsoil) (2)
in the formula: NDVIsoilNDVI value of the pure bare soil pixel;
NDVIvegthen 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 NDVIsoilAnd NDVI value with a frequency of 95% is NDVIveg。
According to the technical scheme, in S4, a fishing net with a 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 are reclassified according to layered height intervals to obtain layered raster data.
According to the technical scheme, in S5, firstly, grid data are vectorized according to the layer number field to obtain a vector file of each layer, and statistics is calculated according to the layer number field in the vector file
Figure BDA0003527821030000071
Figure BDA0003527821030000072
The calculation formula of (a) is as follows:
Figure BDA0003527821030000073
in the formula: and n is the total number of the layered image elements.
According to the above technical solution, in S6, the vertical overlap empirical model is:
Figure BDA0003527821030000074
in the formula:
Figure BDA0003527821030000075
is an integral VFC;
VFCnis the lower layer of VFC;
VFCn+1for the upper VFC, the calculation formula is as follows:
Figure BDA0003527821030000076
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure BDA0003527821030000077
And VFCnThus obtaining VFCn+1And 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:
and S1, acquiring original data of the 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 with accurately positioned experimental area space.
S2, calculating the normalized vegetation index (NDVI) of the experimental area through the formula (1)
NDVI＝(ρNIR-ρRED)/(ρNIR+ρRED) (1)
In the formula: rhoNIRRepresenting the reflectivity data of B4 near infrared wave band in the high-resolution 7 image;
ρREDrepresenting the reflectance data of B3 red band in the high-resolution 7 image.
S3, calculating vegetation coverage (VFC) of the remote sensing image of the experimental area by using a general pixel dichotomy, namely formula (2), obtaining a frequency accumulation table by counting pixel values of the experimental area, and taking NDVI values with frequencies of 5% and 95% as the NDVI value of the pure bare soil and the NDVI value of the pure vegetation respectively.
VFC＝(NDVI-NDVIsoil)/(NDVIveg-NDVIsoil) (2)
In the formula: NDVIsoilNDVI values for completely bare soil or vegetation-free covered areas;
NDVIvegthen 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.
S4, establishing fishing nets (144 pixels in one fishing net) with the size of 12 x 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 raster data divided into 16 layers.
And S5, vectorizing the raster data according to the layer number field to obtain a vector file of each layer.
Calculating and counting the mean value of the vegetation coverage VFC of each layer according to the number of layers field in the vector file
Figure BDA0003527821030000091
Figure BDA0003527821030000092
In the formula: n is the total number of the layered pixels.
S6, calculating VFC between layers with different heights by using a vertical overlapping empirical model in formula (4), wherein the VFC in two vertically adjacent layers with equal height spacing is known
Figure BDA0003527821030000093
And VFCnTo obtain VFCn+1And 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 BDA0003527821030000094
In the formula: VFCn+1Upper layer VFC value;
Figure BDA0003527821030000095
is the average value of VFC of each layer;
VFCnthe lower layer VFC value.
(Note: Individual VFC)n+1If > 1, it is 1, or < 0, it is 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 (9)

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, carrying out 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 height intervals to obtain pixel cubes of different height layers;
s5, extracting average overall vegetation coverage of each layer in equal height spacing layers
Figure FDA0003527821020000011
And S6, calculating the layered VFC among different height layers through a vertical overlapping empirical model, and finally obtaining a VFC vertical distribution curve.
2. The method of claim 1, wherein the step of preprocessing the remote sensing image in S1 comprises:
s1-1, radiometric calibration, namely converting the DN value of the remote sensing image into an absolute radiance value;
s1-2, atmospheric correction, converting the absolute radiance value 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.
3. The method of claim 1, wherein in S2, NDVI is calculated as follows:
NDVI＝(ρNIR-ρRED)/(ρNIR+ρRED) (1)
in the formula: rhoNIRRepresenting the reflectivity data of the near infrared band in the remote sensing image;
ρREDrepresenting the reflectivity data of the red light wave band in the remote sensing image.
4. The method of claim 1, wherein in S3, VFC is calculated as follows:
VFC＝(NDVI-NDVIsoil)/(NDVIveg-NDVIsoil) (2)
in the formula: NDVIsoilIs the NDVI value of the pure bare soil pixel;
NDVIvegthen the NDVI value for the clear vegetation pixel is represented.
5. The method of claim 4, wherein the NDVI value is calculated and extracted in each pixel during research, and the frequency cumulative 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 NDVIsoilAnd NDVI value with a frequency of 95% is NDVIveg。
6. The method of claim 1, wherein in step S4, a uniform-size fishing net is first created 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 height intervals of the layering, so as to obtain layered raster data.
7. The method of claim 1, wherein in step S5, grid data is vectorized according to layer number fields to obtain a vector file for each layer, and statistics are calculated according to the layer number fields in the vector file
Figure FDA0003527821020000021
The calculation formula of (a) is as follows:
Figure FDA0003527821020000031
in the formula: n is the total number of the layered pixels.
8. The method of claim 1, wherein in S6, the vertical overlap empirical model is:
Figure FDA0003527821020000032
in the formula:
Figure FDA0003527821020000033
is an integral VFC;
VFCnis the lower layer of VFC;
VFCn+1for the upper VFC, the calculation formula is as follows:
Figure FDA0003527821020000034
for VFCs in two vertically adjacent equally highly spaced tiers, it is known
Figure FDA0003527821020000035
And VFCnTo obtain VFCn+1And solving layer by layer to obtain the VFC of the layer cube with different heights, namely obtaining the vertical distribution curve of the VFC.
9. A method and medium for hierarchical estimation of vegetation coverage based on DSM contour slices, wherein the medium stores computer-executable instructions configured as the method for vertical hierarchical estimation of forest vegetation coverage based on multi-angle remote sensing DSM contour slices according to any of claims 1-8.
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