CN105868761A - Urban forest vegetation coverage sampling method matched with SPOT5 (Systeme Probatoire d'Observation de la Terre 5) image - Google Patents
Urban forest vegetation coverage sampling method matched with SPOT5 (Systeme Probatoire d'Observation de la Terre 5) image Download PDFInfo
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- CN105868761A CN105868761A CN201610411722.5A CN201610411722A CN105868761A CN 105868761 A CN105868761 A CN 105868761A CN 201610411722 A CN201610411722 A CN 201610411722A CN 105868761 A CN105868761 A CN 105868761A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/20—Image preprocessing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2411—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on the proximity to a decision surface, e.g. support vector machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/10—Terrestrial scenes
- G06V20/188—Vegetation
Abstract
The invention provides an urban forest vegetation coverage sampling method matched with an SPOT5 (Systeme Probatoire d'Observation de la Terre 5) image. The urban forest vegetation coverage sampling method matched with the SPOT5 image comprises the following steps of, in a selected area, taking an urban forest coverage area as an object, obtaining the SPOT5 image of the area, segmenting the forest coverage area by adopting an object-oriented segmentation algorithm, forming a sampling area, and generating image areas; in each sampling area, constructing a fuzzy classifier to carry out object-oriented coverage classification; obtaining the position information of each sampling area through the location by a GPS (Global Positioning System), and recording the position information; calculating the position information of all the sampling areas, matching the position information by taking the SPOT5 image as a data source, and carrying out precision evaluation on a classification result; obtaining urban forest vegetation coverage according to the coverage area of a classified object. By using the urban forest vegetation coverage sampling method matched with the SPOT5 image, which is provided by the invention, the accurate sampling for the area of a ground vegetation coverage area of an urban forest can be realized; a sufficient preparation is made for improving the precision of urban forest vegetation coverage monitoring data.
Description
Technical field
The present invention relates to remote sensing technology, be specifically related to a kind of urban forests vegetation with SPOT5 Image Matching and cover
The cover degree method of sampling.
Background technology
Urban forests coverage (The forest coverage) refers to that a urban vegetation area accounts for land area
Percentage ratio, is that one urban forests area of reflection occupies situation or vegetation type is enriched degree and realizes greening journey
The index of degree, determines that again one of important evidence of urban planning and ecosystem environment mensuration.
The measurement measured with common forest cover degree for urban forests vegetation coverage is deposited to a certain extent
In difference, current researcher is the most still used for reference the measurement of common forest cover degree and is measured, common forest
The traditional method that coverage is measured is ground survey, and simplest is eye estimating method, but the method subjectivity is too strong,
Measure not accurate enough.In order to obtain data and rule more accurately, Mind on statistics is introduced, and passes through
A number of ground survey, then carries out time or analysis spatially to measured data, finds forest and covers
The time space distribution of cover degree, forms empirical model, but this method to be normally only applicable to specific region specific
Vegetation classification, limitation is too big, should not promote.The development of remote sensing technology, for the measurement of forest cover degree
Provide a new developing direction, especially the forest cover degree investigation for extensive area and provide possibility,
But the trees for urban forests coverage to be calculated accurately are sampled relatively difficult, and at present for this respect
Research less.
Summary of the invention
In order to solve problems of the prior art, the invention provides a kind of and SPOT5 Image Matching
The urban forests vegetation coverage method of sampling, substantially increases the precision of forest cover degree survey data.
The urban forests vegetation coverage method of sampling of a kind of and SPOT5 Image Matching that the present invention provides, bag
Include following steps:
S1: in selected region, with urban forests overlay area as object, it is thus achieved that high ground resolution, big
The SPOT5 image of ratio, uses object-oriented partitioning algorithm to split urban forests overlay area, shape
Become a series of sample region, generate imagery zone；
S2: in each sample region, builds Fuzzy Classifier and carries out OO arbor, shrub and meadow
Cover classification；
S3: from the beginning of the central point of sample region, obtains the positional information of each sample region by GPS location,
And carry out record；
S4: according to the positional information of a sample region, calculate the positional information of all sample region, and with SPOT5
Image mates as data source, and classification results is carried out precision evaluation；
S5: obtain urban forests vegetative coverage according to the respective area coverage in arbor, shrub and meadow of classification
Degree.
Preferably, the resolution of described SPOT5 image is the ground resolution of 2.5m.
Preferably, in S3, described positional information includes longitude information and latitude information.
Melt it is highly preferred that described SPOT5 image uses panchromatic wave-band spectrum to carry out image with multi light spectrum hands
Close.
Preferably, the spectral region of the panchromatic wave-band of described SPOT5 image is 0.49-0.60 μm, and image divides
Resolution is 2.5m.
Preferably, in S1, according to urban forests crown coverage areas size selected segmentation yardstick, use adjustable
The object-oriented partitioning algorithm of yardstick is split.
It is highly preferred that in S1, each sample region is rhombus, in sample region, choose 45 by matrix form
Sampled point, neighbouring sample point is separated by 2.5-5m.
It is highly preferred that in S3, do not surpass in each pixel in the imagery zone of described SPOT5 video generation
Cross a sampled point.
Preferably, in S2, the Fuzzy Classifier of structure is classified based on vector machine, the sort key feature of employing
Mean difference and average brightness value including samples selection, normalized site attenuation and adjacent object.
The urban forests vegetation coverage method of sampling with SPOT5 Image Matching that the present invention provides, with
SPOT5 image is as data source, from the beginning of the central point of sample region, obtains and record every by GPS location
The positional information of individual sample region mates, fast and accurately lock onto target, thus realizes urban forests
The accurate sampling of trees terrestrial coverage area area, do for improving the precision of forest cover degree survey data
Sufficiently prepare.
Detailed description of the invention
In order to make those skilled in the art be more fully understood that, technical scheme can be practiced, below knot
The invention will be further described to close specific embodiment, but illustrated embodiment is not intended as the scope of the present invention
Limit.
A kind of urban forests vegetation coverage method of sampling with SPOT5 Image Matching, including processing step as follows
Rapid:
S1: in selected region, with urban forests overlay area as object, it is thus achieved that high ground resolution, big
The SPOT5 image of ratio, uses object-oriented partitioning algorithm to split urban forests overlay area, shape
Become a series of sample region, generate imagery zone；
S2: in each sample region, builds Fuzzy Classifier and carries out OO arbor, shrub and meadow
Cover classification；
S3: from the beginning of the central point of sample region, obtains the positional information of each sample region by GPS location,
And carry out record；
S4: according to the positional information of a sample region, calculate the positional information of all sample region, and with SPOT5
Image mates as data source, and classification results is carried out precision evaluation；
S5: obtain urban forests vegetative coverage according to the respective area coverage in arbor, shrub and meadow of classification
Degree.
Preferably, the Fuzzy Classifier of above-mentioned structure is classified based on vector machine, the sort key feature bag of employing
Include mean difference and the average brightness value of samples selection, normalized site attenuation and adjacent object.Tool
The sample that body is chosen is arbor, shrub and grass, and after selection area carries out fuzzy classification, the dirty-green of display is
Arbor, bright green is grass or shrub；The positional information of above-mentioned indication refers to sample region longitude information and latitude
Information.
In the present invention, according to urban forests crown coverage areas size selected segmentation yardstick, adjustable ruler is used
The object-oriented partitioning algorithm of degree is split；SPOT5 image used use panchromatic wave-band spectrum with how light
Spectrum wave band carries out visual fusion, multispectral (blue, green, red, near infrared band) the SPOT5 shadow being utilized
The resolution of picture is less than the ground resolution equal to 10m, this SPOT5 carries out an extraction tree crown and covers
Segmentation for the purpose of district, when using panchromatic wave-band, the spectral region of its panchromatic wave-band is 0.49-0.60 μm,
Image resolution is 2.5m.
Sampling for convenience, generally unit based on a sample region, each sample region is rhombus, is adopting
Choosing 45 sampled points by matrix form in sample district, neighbouring sample point is separated by 2.5-5m, with 2.5m is wherein
Most preferably.In the imagery zone of SPOT5 video generation, black part is divided into sample region, red line composition be
The grid of image, by the positional information of sample region sampled point, and SPOT5 image is carried out as data source
Join, less than a sampled point in each pixel, and the position of each sampled point is fallen as far as possible at image
The center of each grid, so that it is determined that sampling.
The present invention goes out to meet the real crown ground of selection area urban forests by SPOT5 Extraction of Image and covers
Cover region territory, then according to SPOT5 image picture element ground resolution, it is thus achieved that urban forests coverage sample.
Embodiment described above is only the preferred embodiment lifted by absolutely proving the present invention, and it protects model
Enclose and be not limited to this.The equivalent that those skilled in the art are made on the basis of the present invention substitutes or conversion,
All within protection scope of the present invention, protection scope of the present invention is as the criterion with claims.
Claims (9)
1. one kind with the urban forests vegetation coverage method of sampling of SPOT5 Image Matching, it is characterised in that
Comprise the steps:
S1: in selected region, with urban forests overlay area as object, it is thus achieved that high ground resolution, big
The SPOT5 image of ratio, uses object-oriented partitioning algorithm to split urban forests overlay area, shape
Become a series of sample region, generate imagery zone；
S2: in each sample region, builds Fuzzy Classifier and carries out OO arbor, shrub and meadow
Cover classification；
S3: from the beginning of the central point of sample region, obtains the positional information of each sample region by GPS location,
And carry out record；
S4: according to the positional information of a sample region, calculate the positional information of all sample region, and with SPOT5
Image mates as data source, and classification results is carried out precision evaluation；
S5: obtain urban forests vegetative coverage according to the respective area coverage in arbor, shrub and meadow of classification
Degree.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 1
Method, it is characterised in that the resolution of described SPOT5 image is the ground resolution of 2.5m.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 1
Method, it is characterised in that in S3, described positional information includes longitude information and latitude information.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 2
Method, it is characterised in that described SPOT5 image uses panchromatic wave-band spectrum and multi light spectrum hands to carry out image
Merge.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 4
Method, it is characterised in that the spectral region of the panchromatic wave-band of described SPOT5 image is 0.49-0.60 μm,
Image resolution is 2.5m.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 1
Method, it is characterised in that in S1, according to urban forests crown coverage areas size selected segmentation yardstick, adopts
Split with the object-oriented partitioning algorithm of adjustable yardstick.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 6
Method, it is characterised in that in S1, each sample region is rhombus, chooses 45 by matrix form in sample region
Individual sampled point, neighbouring sample point is separated by 2.5-5m.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 7
Method, it is characterised in that in S3, in each pixel in the imagery zone of described SPOT5 video generation
Less than a sampled point.
Urban forests vegetation coverage sampling with SPOT5 Image Matching the most according to claim 1
Method, it is characterised in that in S2, the Fuzzy Classifier of structure closes based on vector machine classification, the classification of employing
Key feature includes samples selection, normalized site attenuation and the mean difference of adjacent object and the brightest
Angle value.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106845366A (en) * | 2016-12-29 | 2017-06-13 | 江苏省无线电科学研究所有限公司 | Sugarcane coverage automatic testing method based on image |
| CN113776487A (en) * | 2021-10-25 | 2021-12-10 | 生态环境部长江流域生态环境监督管理局生态环境监测与科学研究中心 | Aquatic plant coverage evaluation method |
| CN114972750A (en) * | 2022-04-29 | 2022-08-30 | 北京九章云极科技有限公司 | Target coverage rate obtaining method and device and classification model training method and device |
| CN116912706A (en) * | 2023-06-30 | 2023-10-20 | 中国科学院空天信息创新研究院 | Sampling point determination and vegetation remote sensing product authenticity verification method, device and equipment |
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106845366A (en) * | 2016-12-29 | 2017-06-13 | 江苏省无线电科学研究所有限公司 | Sugarcane coverage automatic testing method based on image |
| CN106845366B (en) * | 2016-12-29 | 2020-03-27 | 江苏省无线电科学研究所有限公司 | Sugarcane coverage automatic detection method based on image |
| CN113776487A (en) * | 2021-10-25 | 2021-12-10 | 生态环境部长江流域生态环境监督管理局生态环境监测与科学研究中心 | Aquatic plant coverage evaluation method |
| CN114972750A (en) * | 2022-04-29 | 2022-08-30 | 北京九章云极科技有限公司 | Target coverage rate obtaining method and device and classification model training method and device |
| CN114972750B (en) * | 2022-04-29 | 2023-10-27 | 北京九章云极科技有限公司 | Target coverage rate acquisition method, classification model training method and device |
| CN116912706A (en) * | 2023-06-30 | 2023-10-20 | 中国科学院空天信息创新研究院 | Sampling point determination and vegetation remote sensing product authenticity verification method, device and equipment |
| CN116912706B (en) * | 2023-06-30 | 2024-02-02 | 中国科学院空天信息创新研究院 | Sampling point determination and vegetation remote sensing product authenticity verification method, device and equipment |
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