CN105930769A - Bio-ecological characteristic-based pest and disease damage occurrence grade precision verification method - Google Patents
Bio-ecological characteristic-based pest and disease damage occurrence grade precision verification method Download PDFInfo
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Abstract
The invention discloses a bio-ecological characteristic-based pest and disease damage occurrence grade precision verification method. According to the method, based on remote sensing image-based forest pest and disease damage classification, the bio-ecological characteristics of forest pest and disease damage are utilized to carry out pest and disease damage occurrence grade monitoring process verification under the premise that no pest and disease damage field investigation data exist; and when the classified grades of the forest pest and disease damage accord with the bio-ecological characteristics of the forest pest and disease damage, and a determination coefficient fitted by using a model is high, it is indicated that classification accuracy is reliable, and the complexity of forest pest and disease damage field investigation can be effectively decreased.
Description
Technical field
The present invention relates to a kind of method that forest disease and pest plague grade based on remotely-sensed data monitors its precision test, special
It not without the pest and disease damage grade monitoring accuracy verification method based on biological and ecological feature during actual measurement checking data.
Background technology
Forest disease and pest long-term hazards the forest ecosystem of China, and the monitoring to forest disease and pest also becomes forest warp
The emphasis place of battalion's research.In traditional forest pest and disease monitoring and grade classification, how with field survey data for mainly depending on
According to, in recent years, complete the area monitoring of pest and disease damage and grade classification by remote sensing and geographic information system technology, but this process
In, the checking of pest and disease damage grade classification precision is always an insoluble problem, and the monitoring of current forest disease and pest grade is main
Problems with to be faced with:
1., in forest disease and pest grade based on remote sensing and GIS-Geographic Information System monitoring and dividing, monitoring and grade are drawn continuously
That divides is a lot of according to having, and its system of selection is also a lot, neither one unification, the most succinct standard；
2. forest disease and pest Occurrence and control data accuracy is the highest and more difficult acquisition, under not having measured data to support, utilizes distant
Sense technology completes forest disease and pest and divides and precision test shortage foundation.
So in the case of deficiency disease insect pest Occurrence and control data, it occurs monitoring and grade classification precision to be difficult to reach
Requirement, its precision test cannot realize simultaneously, therefore, it is achieved monitoring in the forest disease and pest grade without measured data is this field
The problem that research worker is anxious to be resolved.
Summary of the invention
During for current deficiency disease insect pest Occurrence and control data, forest disease and pest grade monitoring accuracy based on remote sensing technology
The problem that cannot verify, the present invention proposes a kind of forest disease and pest grade monitoring accuracy authentication based on biological and ecological feature
Method, overcomes measured data and is difficult to obtain the shortcoming that the pest and disease damage grade classification precision caused is the highest.Its feature mainly by
The Bioecological characteristics of forest disease and pest, tests to the precision of monitoring result indirectly: first determining forest transition
The time of evil plague grade obtains remote sensing image, utilizes remote sensing technology means, analyzes different extent of injury time image Spectral Properties
Levy Changing Pattern, choose the most suitably spectral signature index and complete to monitor the forest disease and pest grade classification in time；Secondly
On the basis of completing forest disease and pest grade classification, utilize the sky that priori relevant in pest and disease damage research is powerful with GIS
Between analytic function combine, the factors such as result and meteorology, the landform of monitoring are overlapped, analyze the difference of same disaster loss grade
Factor ratio distribution trend, utilizes models fitting.When ratio distribution meets monotonic increase (subtracting), use logistics function:(independent variable x is factor values, and dependent variable y is ratio)；When ratio distribution has periodically, use cosine
Function Fitting:(independent variable x is factor values, and dependent variable y is ratio).Determine the decision of matching
Coefficient.By the difference between result and pest and disease damage Bioecological characteristics, to complete grade classification precision test.
This invention major advantage compared with the conventional method is: significantly improve forest disease and pest investigation and grade monitoring is drawn
The efficiency that the division of labor is made, in traditional forest disease and pest grade classification investigation, needs a large amount of on-site inspection, even if utilizing remote sensing number
After completing grade classification, still need on-site inspection to verify grade classification precision.This research is with existing historical data
Carry out the selection of area forest disease and pest grade classification index, in combination with can be with the gas of the pest and disease damage generating region of Free Acquisition
As, the ecological factor such as soil and the terrain factor such as the gradient, slope aspect are analyzed, and complete grade classification precision test, it is achieved that
Grade monitoring accuracy based on forest disease and pest Bioecological characteristics checking during deficiency disease insect pest generation data, effectively reduces
Field process amount, improves work efficiency.
Accompanying drawing explanation
The present invention is further described with embodiment below in conjunction with the accompanying drawings.
Fig. 1 is that forest disease and pest plague grade based on biological and ecological feature divides and monitoring accuracy checking flow chart.
Fig. 2 is the disaster-stricken grade of calendar year 2001 Pinus tabuliformis precision test schematic diagram in slope aspect data.
Fig. 3 is Pinus tabuliformis disaster-stricken grade precision test schematic diagram on rainfall product data in 2000.
Detailed description of the invention
The method of its grade classification precision is different from existing method to utilize forest disease and pest Ecological Characteristics to verify, specifically exists
In:
(1) obtain known pest and disease damage hazard rating time remote sensing image, analyze remote sensing image spectral information after pest and disease damage occurs and become
Law, finds the spectrum indicators meeting pest and disease damage grading standard；
(2) utilize the spectrum indicators obtained that the remote sensing image in required research time is carried out pest and disease damage plague grade to draw
Point, in combination with the Bioecological characteristics of study pest species obtain this area weather, landform and artificially etc. affect because of
Prime number evidence；
(3) select the representative region of different extent of injury, analyze this kind of distinctive Bioecological characteristics of pest and disease damage one by one with sick
The overlaying relation of insect pest extent of injury, is overlapped analyzing to factors such as the result monitored and meteorology, landform, finally obtains substantially
Meet the result of pest and disease damage biological characteristics, then demonstrate monitoring result reliable.
In order to verify the effectiveness of this pest and disease damage plague grade precision test method based on biological and ecological feature, use me
State's western Liaoning Province dendrolimus tabulaeformis disaster monitoring result is tested, and detailed process is as follows.
(1) test block is positioned at Jianping County and the Lingyuan City in Liaoning Province, and the large-area Chinese pine plantation in this place is for a long time by oil
The harm of pine moth, obtains the JIUYUE in 1985 6 days of Landsat series of satellites, JIUYUE in 2000 7 days, the shadow on 9 days Augusts calendar year 2001
Picture, selects ratio vegetation index RVI(near infrared/infrared) it is classified Pinus tabuliformis is disaster-stricken.
(2) easily endanger the Pinus tabulaeformis forest in tailo area according to dendrolimus tabulaeformis, and insect pest is played the priori of inhibitory action by rainfall
Knowledge, selects two ecological factors of slope aspect and rainfall to test.Disaster-stricken Pinus tabuliformis region and healthy Pinus tabuliformis region after classifying
It is superimposed to slope aspect figure and rainfall figure, the statistical analysis of test block respectively.
(3) statistical result to slope aspect uses cosine function fitting result as follows.
On JIUYUE 6th, 1985, the ratio (y) of the Pinus tabuliformis that is injured (x) meets with slope aspect,
The coefficient of determination is 0.9655；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect,
The coefficient of determination is 0.9130.
On JIUYUE 7th, 2000, the ratio (y) of the Pinus tabuliformis that is injured (x) meets with slope aspect,
The coefficient of determination is 0.9597；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect,
The coefficient of determination is 0.9566.
On August 9 calendar year 2001, the ratio (y) of the Pinus tabuliformis that is injured (x) meets with slope aspect,
The coefficient of determination is 0.9524；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect,
The coefficient of determination is 0.9565.As shown in Figure 2.
Statistical result to rainfall uses logistics Function Fitting result as follows.
On JIUYUE 6th, 1985, the ratio (y) of the Pinus tabuliformis that is injured and rainfall mm(x) meet,
The coefficient of determination is 0.9234；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect, determine
Coefficient is 0.8852.
On JIUYUE 7th, 2000, the ratio (y) of the Pinus tabuliformis that is injured and rainfall mm(x) meet,
The coefficient of determination is 0.9268；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect, the coefficient of determination is
0.9104.As shown in Figure 3.
August 9 calendar year 2001, the ratio (y) of the Pinus tabuliformis that is injured and rainfall mm(x) meet,
The coefficient of determination is 0.9026；The ratio (y) of healthy Pinus tabuliformis (x) meets with slope aspect, certainly
Determining coefficient is 0.8761.
The ratiometric result that slope aspect and the rainfall factor draw meets the Bioecological characteristics of dendrolimus tabulaeformis, determining of matched curve
Determine coefficient and be up to 0.87 to 0.96.Visible, the method for patent of the present invention achieves good effect, it is possible to achieve without measured data
Time checking to forest pest and disease monitoring precision.
The above is the preferred embodiment of the present invention, for those skilled in the art,
Without departing from the principles of the invention, it is also possible to make some improvements and modifications, these improvements and modifications are also regarded as this
Bright protection domain.
Claims (1)
1. a pest and disease damage level accuracy verification method based on biological and ecological feature, is characterized in that: utilize forest disease and pest
Bioecological characteristics, indirectly tests to the precision of monitoring result, specifically comprises the following steps that
(1) obtain known pest and disease damage hazard rating time remote sensing image, analyze remote sensing image spectral information after pest and disease damage occurs and become
Law, finds the spectrum indicators meeting pest and disease damage grading standard；Utilize the spectrum indicators pair obtained
The remote sensing image in required research time carries out pest and disease damage plague grade division, in combination with the biological life of studied pest species
State characteristic obtains this area weather, landform and influence factor's data such as artificial；
(2) select the representative region of different extent of injury, analyze this kind of distinctive Bioecological characteristics of pest and disease damage one by one with sick
The overlaying relation of insect pest extent of injury, is overlapped analyzing to factors such as the result monitored and meteorology, landform, finally obtains substantially
Meet the result of pest and disease damage biological characteristics, then demonstrate monitoring result reliable.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN106910214A (en) * | 2017-02-09 | 2017-06-30 | 中国林业科学研究院资源信息研究所 | A kind of santal trunk insect pest degree of injury level images method of discrimination |
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| CN103955606A (en) * | 2014-04-23 | 2014-07-30 | 北京大学 | Remote sensing technology-based grassland locust plague progressive prediction method |
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2016
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| CN102072885A (en) * | 2010-12-06 | 2011-05-25 | 浙江大学 | Machine vision-based paddy neck blast infection degree grading method |
| CN102496077A (en) * | 2011-12-06 | 2012-06-13 | 北京林业大学 | System and method for predicting forest pest disaster |
| CN103955606A (en) * | 2014-04-23 | 2014-07-30 | 北京大学 | Remote sensing technology-based grassland locust plague progressive prediction method |
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| CN106910214A (en) * | 2017-02-09 | 2017-06-30 | 中国林业科学研究院资源信息研究所 | A kind of santal trunk insect pest degree of injury level images method of discrimination |
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Application publication date: 20160907 |