CN110175537A - A kind of method and system merging multi-source remote sensing index evaluation Land degradation status - Google Patents
A kind of method and system merging multi-source remote sensing index evaluation Land degradation status Download PDFInfo
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Abstract
The invention discloses a kind of method and system for merging multi-source remote sensing index evaluation Land degradation status, which comprises obtains remote sensing image and carries out Yunnan snub-nosed monkey according to research area's actual conditions；Land use and land cover classification are carried out from pretreated remote sensing image, and different land types are recompiled from small to large according to the influence power to land deterioration；Vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion are extracted in remote sensing image after the pre-treatment；After the image data of five indexs is carried out data normalization, and striograph is overlapped, constructs comprehensive land degradation index and go forward side by side line function resolving；According to the calculated result of comprehensive land degradation index output Land degradation degree, and the grade classification of the size progress Land degradation status according to comprehensive land degradation index.The present invention obtains comprehensive land degradation index by integrating multiple indexs, and realization quickly identifies Land degradation status from remote sensing image.
Description
Technical field
The present invention relates to remote sensing and ecological environmental protection technical field more particularly to a kind of fusion multi-source remote sensing index comprehensives
Assess the method and system of Land degradation status.
Background technique
Land resource provides important material conditions for human survival and development.However, in recent years, unreasonable soil
Land use systems and Land Resources Management are not good at, in addition population expansion, causes global land deterioration serious.Land deterioration refers to the mankind
The reduction or loss of the biology of soil caused by activity or Economic productivity, the influence of the natural processes such as climate variation in addition,
Expand the influence of land deterioration.
Rs and gis (geographic information systems, GIS) technology is in land deterioration
Good effect is achieved in research, but currently used land deterioration index is not enough, and the use ratio of land deterioration index
It is more single, it cannot reflect the degree and space-time characteristic of land deterioration comprehensively.Many researchers had made with single index or had answered
The research that index carried out land deterioration is closed, such as vegetation index (normalized difference
Vegetation index, NDVI), soil erosion (water loss and soil erosion, WLSE), land use and
Covering variation and desertification of land etc..Although These parameters can disclose Land degradation degree to a certain extent, however, causing
The reason of land deterioration be it is complicated, land deterioration usually by a variety of phenomenons superposition cause, opened including unreasonable land use
Hair, soil erosion, vegetation coverage decline, arid, wind erosion etc..
That is, land deterioration shape is assessed simply by single index or a few index in the prior art
Condition can not reflect the degree and space-time characteristic of land deterioration comprehensively, lead to the assessment number to the Land degradation status of survey region
According to inaccuracy, timely feedback and measure effectively can not be made according to land deterioration state, it can not be to activety fault and soil
Ground degeneration mitigation provides effective support.
Therefore, the existing technology needs to be improved and developed.
Summary of the invention
The technical problem to be solved in the present invention is that in the prior art simply by single index or a few index
Land degradation status is assessed, can not reflect the degree and space-time characteristic of land deterioration comprehensively, lead to the soil to survey region
The assessment data inaccuracy of degraded condition, effectively can not make timely feedback and measure, the present invention according to land deterioration state
A kind of method and system for merging multi-source remote sensing index evaluation Land degradation status are provided, solving can not integrate in the prior art
And the problem of comprehensively assessing Land degradation status, it is intended to propose that a kind of land deterioration of comprehensive assessment Land degradation status refers to
Number, provides effective support for activety fault and land deterioration mitigation.
The technical proposal for solving the technical problem of the invention is as follows:
A method of fusion multi-source remote sensing index evaluation Land degradation status, wherein the fusion multi-source remote sensing index
Assessment Land degradation status method include:
It obtains remote sensing image and carries out Yunnan snub-nosed monkey according to research area's actual conditions；
Land use and land cover classification are carried out from pretreated remote sensing image, according to the influence to land deterioration
Power from small to large recompiles different land types；
Vegetation coverage, soil erosion degree, soil moisture content and soil wind are extracted in remote sensing image after the pre-treatment
Degree of corrosion；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind
The image data of degree of corrosion carries out data normalization；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind
The striograph of degree of corrosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function resolving；
According to the calculated result of the comprehensive land degradation index output Land degradation degree, and according to the comprehensive soil
The size of deterioration index carries out the grade classification of Land degradation status.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein the vegetation coverage mentions
Take method are as follows:
NDVI=(ρNIR-ρRed)/(ρNIR+ρRed)；
VC=(NDVI-NDVImin)/(NDVImax-NDVImin)；
Wherein, NDVI indicates vegetation index, ρNIRAnd ρRedRespectively represent the close red and feux rouges of remote sensing image
The reflectivity of wave band；
VC indicates vegetation coverage, NDVIminAnd NDVIminRespectively represent the maximum value and minimum value of NDVI.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein the soil erosion degree
Extracting method are as follows:
In conjunction with vegetation coverage, digital elevation model, land use and cover type, soil types and spatially distributed rainfall
Figure extracts soil erosion degree using generic data-access, specific as follows:
WLSE=RKLSCP；
Wherein, WLSE indicates soil erosion degree, and R is the rainfall erosivity factor, and K is soil erodibility factor, and L is length of grade
The factor, S are slope factor, and C is the vegetative coverage factor, and P is the water and soil conservation control measure factor.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein the soil moisture content mentions
Take method are as follows:
Soil moisture content formula is constructed using the humidity component of tasseled cap transformation:
SMCTM=0.0315 ρBlue+0.2021ρGreen+0.3102ρRed+0.1594ρNIR-0.6806ρSWIR1-0.6109
ρSWIR2
SMCOLI=0.1511 ρBlue+0.1972ρGreen+0.3283ρRed+0.3407ρNIR-0.7117ρSWIR1-0.4559
ρSWIR2；
Wherein, SMCTMAnd SMCOLIRespectively represent the soil moisture content of Landsat-TM and Landsat-OLI image, ρBlue、
ρGreen、ρRed、ρNIR、ρSWIR1And ρSWIR2The blue, green, red of remote sensing image, near-infrared, first short red wave wave are respectively represented
The reflectivity of section and second short red wave wave band.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein the soil degree of wind erosion
Extracting method are as follows:
WE=(ρSWIR1-ρBLUE)/(200-ρSWIR1-ρSWIR2)；
Wherein, ρBLUE、ρSWIR1And ρSWIR2Respectively represent blue wave band, the first short red wave wave band and of remote sensing image
The reflectivity of two short red wave wave bands.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein described by the land use
It is counted with the image data of land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion
It is specifically included according to standardization:
The land use and land cover pattern, soil erosion degree and soil degree of wind erosion are positive index, the soil
Ground utilizes and the value of land cover pattern, soil erosion degree and soil degree of wind erosion shows that more greatly Land degradation degree is stronger, just
It is as follows to criterionization:
Xi=(xi-xmin)/(xmax-xmin)；
The vegetation coverage and soil moisture content are negative sense index, and the value of the vegetation coverage and soil moisture content is got over
Show that Land degradation degree is weaker greatly, negative sense criterionization is as follows:
Xi=(xmax-xi)/(xmax-xmin)；
Wherein, XiIt is the value after standardization, xi、xmin、xmaxIt respectively represents the land use and land cover pattern, vegetation is covered
Cover degree, soil erosion degree, original value, minimum value and the maximum value of five indexs of soil moisture content and soil degree of wind erosion；
The land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion
Value after degree progress data normalization is between 0-1.
The method of the fusion multi-source remote sensing index evaluation Land degradation status, wherein described by the land use
It is folded with the striograph of land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion
Add, construct the line function resolving of going forward side by side of comprehensive land degradation index and specifically include:
By the land use and land cover pattern of extraction, vegetation coverage, soil erosion degree, soil moisture content and
The striograph of soil degree of wind erosion is overlapped, and it is as follows to construct comprehensive land degradation index LDI function:
LDI=f (LULC, VC, WLSE, WE, SMC)；
Wherein, LDI is comprehensive land degradation index, and f is the land use and land cover pattern, vegetation coverage, water and soil
The aggregation function of five loss degree, soil moisture content and soil degree of wind erosion indexs；
LDI function is carried out by using principal component analysis method (Principal Component Analysis, PCA)
It solves, principal component analysis compresses original multidimensional remotely-sensed data collection, the first component that wherein principal component analysis obtains, i.e.,
First principal component PC1 contains most information of raw data set, as follows using the linear combination building LDI of PC1:
LDI=(PC1-PC1min)/(PC1max-PC1min)；
Wherein, PC1, PC1minAnd PC1maxRespectively represent the minimum value and maximum value of first principal component, first principal component；
For the value of LDI between 0-1, LDI value is bigger, shows that Land degradation degree is stronger in survey region.
A kind of system merging multi-source remote sensing index evaluation Land degradation status, wherein the fusion multi-source remote sensing index
Assessment Land degradation status system include:
Image capturing processing module, for obtaining remote sensing image and carrying out Yunnan snub-nosed monkey according to research area's actual conditions；
Land classification processing module, for carrying out land use and land cover pattern point from pretreated remote sensing image
Class from small to large recompiles different land types according to the influence power to land deterioration；
Exponent extracting module, for extracting vegetation coverage, soil erosion degree, soil in remote sensing image after the pre-treatment
Earth moisture content and soil degree of wind erosion；
Standardization module, for by the land use and land cover pattern, vegetation coverage, soil erosion degree,
The image data of soil moisture content and soil degree of wind erosion carries out data normalization；
Function constructs module, is used for the land use and land cover pattern, vegetation coverage, soil erosion degree, soil
The striograph of earth moisture content and soil degree of wind erosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function resolving；
Grade classification module, for exporting the calculated result of Land degradation degree according to the comprehensive land degradation index,
And the grade classification of Land degradation status is carried out according to the size of the comprehensive land degradation index.
A kind of device merging multi-source remote sensing index evaluation Land degradation status, wherein the fusion multi-source remote sensing index
The device of assessment Land degradation status includes the system of fusion multi-source remote sensing index evaluation Land degradation status as described above, also
Include: memory, processor and is stored in the fusion multi-source remote sensing that can be run on the memory and on the processor and refers to
The program of mark assessment Land degradation status, the program of the fusion multi-source remote sensing index evaluation Land degradation status is by the processing
The step of method of fusion multi-source remote sensing index evaluation Land degradation status as described above is realized when device executes.
A kind of storage medium, wherein the storage medium is stored with fusion multi-source remote sensing index evaluation Land degradation status
Program, the program of the fusion multi-source remote sensing index evaluation Land degradation status is realized when being executed by processor melts as described above
The step of closing the method for multi-source remote sensing index evaluation Land degradation status.
The invention discloses a kind of method and system for merging multi-source remote sensing index evaluation Land degradation status, the methods
It include: to obtain remote sensing image and carry out Yunnan snub-nosed monkey according to research area's actual conditions；From pretreated remote sensing image into
Row land use and land cover classification from small to large compile different land types according to the influence power to land deterioration again
Code；Vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion journey are extracted in remote sensing image after the pre-treatment
Degree；By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion journey
The image data of degree carries out data normalization；By the land use and land cover pattern, vegetation coverage, soil erosion degree,
The striograph of soil moisture content and soil degree of wind erosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function solution
It calculates；According to the calculated result of the comprehensive land degradation index output Land degradation degree, and according to the comprehensive land deterioration
The size of index carries out the grade classification of Land degradation status.The present invention is based on the indexes of remote sensing appraising Land degradation degree, lead to
It crosses and integrates multiple indexs and obtain comprehensive land degradation index, realization quickly identifies Land degradation status from remote sensing image.
Detailed description of the invention
Fig. 1 is the process of the preferred embodiment of the method for present invention fusion multi-source remote sensing index evaluation Land degradation status
Figure；
Fig. 2 is the execution of the preferred embodiment of the method for present invention fusion multi-source remote sensing index evaluation Land degradation status
Journey schematic diagram；
Fig. 3 is the principle of the preferred embodiment of the system of present invention fusion multi-source remote sensing index evaluation Land degradation status
Figure；
Fig. 4 is the operation ring of the preferred embodiment of the device of present invention fusion multi-source remote sensing index evaluation Land degradation status
Border schematic diagram.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer and more explicit, right as follows in conjunction with drawings and embodiments
The present invention is further described.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and do not have to
It is of the invention in limiting.
The method that multi-source remote sensing index evaluation Land degradation status is merged described in present pre-ferred embodiments, such as Fig. 1 and
Shown in Fig. 2, a method of fusion multi-source remote sensing index evaluation Land degradation status, wherein the fusion multi-source remote sensing index
Assess Land degradation status method the following steps are included:
Step S10, it obtains remote sensing image and carries out Yunnan snub-nosed monkey according to research area's actual conditions.
Specifically, US Geological Survey (United States Geological Survey, USGS) net can be passed through
Stand (GloVis) obtain Landsat (the Landsat plan of U.S. NASA) serial remote sensing image and according to research area's actual conditions
Carry out Yunnan snub-nosed monkey.
Further, the pretreatment includes geometric correction, atmospheric correction, image joint, cutting etc., Yunnan snub-nosed monkey master
If in order to eliminate video imaging in the process due to the attitude of satellite, velocity variations, atmosphere and electromagnetic wave phase interaction, random noise
The problem of etc. image radiation distortion and geometric distortion is caused, and in order to meet the series of processes of Research scale demand progress.
Step S20, land use and land cover classification are carried out from pretreated remote sensing image, are moved back according to soil
The influence power of change from small to large recompiles different land types.
Specifically, carried out from pretreated image land use and land cover pattern (land use/land cover,
LULC) classify, such as image is divided by 10 classifications, including arable land, forest land, garden according to " geographical national conditions generaI investigation content and index "
Ground, meadow, building construction area, road, structures, artificial heap picks up, desert and exposed ground, water body.
Further, different land use type is recompiled from small to large according to the influence power to land deterioration, is compiled
Code value is 0-1.Encoded radio is bigger, illustrates that a possibility that land deterioration occurs for the land use pattern is bigger.It encodes as follows: water body
(0), forest land (0.1), field (0.2), meadow (0.3), building construction area (0.4), arable land (0.5), road (0.6), structures
(0.7), artificial heap pick up (0.8), desert and exposed ground (0.9 or 1).
Step S30, vegetation coverage, soil erosion degree, soil moisture content are extracted in remote sensing image after the pre-treatment
With soil degree of wind erosion.
Specifically, the extracting method of the vegetation coverage (Vegetation Coverage, VC) are as follows:
NDVI=(ρNIR-ρRed)/(ρNIR+ρRed)；
VC=(NDVI-NDVImin)/(NDVImax-NDVImin)；
Wherein, NDVI indicates vegetation index, ρNIRAnd ρRedRespectively represent the close red and feux rouges of remote sensing image
The reflectivity of wave band；
VC indicates vegetation coverage, NDVIminAnd NDVIminRespectively represent the maximum value and minimum value of NDVI.
Wherein, VC value is bigger, shows that the probability that land deterioration occurs is lower.
Specifically, the soil erosion degree (Water Loss and Soil Erosion, WLSE)) extracting method
Are as follows:
In conjunction with vegetation coverage, digital elevation model, land use and cover type, soil types and spatially distributed rainfall
Figure extracts soil erosion degree using generic data-access, specific as follows:
WLSE=RKLSCP；
Wherein, WLSE indicates soil erosion degree, and R is the rainfall erosivity factor, and K is soil erodibility factor, and L is length of grade
The factor, S are slope factor, and C is the vegetative coverage factor, and P is the water and soil conservation control measure factor.
Wherein, WLSE value is bigger, shows that the probability that land deterioration occurs is bigger.
Specifically, the extracting method of the soil moisture content (Soil Moisture Content, SMC) are as follows:
Soil moisture content formula is constructed using the humidity component of tasseled cap transformation (Tasseled Cap, TC):
SMCTM=0.0315 ρBlue+0.2021ρGreen+0.3102ρRed+0.1594ρNIR-0.6806ρSWIR1-0.6109
ρSWIR2
SMCOLI=0.1511 ρBlue+0.1972ρGreen+0.3283ρRed+0.3407ρNIR-0.7117ρSWIR1-0.4559
ρSWIR2；
Wherein, SMCTMAnd SMCOLIRespectively represent the soil moisture content of Landsat-TM and Landsat-OLI image, ρBlue、
ρGreen、ρRed、ρNIR、ρSWIR1And ρSWIR2The blue, green, red of remote sensing image, near-infrared, first short red wave wave are respectively represented
The reflectivity of section and second short red wave wave band.
Landsat-TM indicate US Terrestrial landsat (Landsat) thematic mapper (Thematic Mapper,
TM)；Landsat-OLI indicates land imager (the Operational Land of US Terrestrial landsat (Landsat)
Imager,OLI)。
Wherein, SMC value is bigger, shows that the probability that land deterioration occurs is smaller.
Specifically, the extracting method of the soil degree of wind erosion (Wind Erosion, WE) are as follows:
WE=(ρSWIR1-ρBLUE)/(200-ρSWIR1-ρSWIR2)；
Wherein, ρBLUE、ρSWIR1And ρSWIR2Respectively represent blue wave band, the first short red wave wave band and of remote sensing image
The reflectivity of two short red wave wave bands.
Wherein, WE value is bigger, shows that the probability that land deterioration occurs is bigger.
Step S40, by the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content with
And the image data of soil degree of wind erosion carries out data normalization.
Specifically, by the land use and land cover pattern (LULC), vegetation coverage (VC), soil erosion degree
(WLSE), the image data of soil moisture content (SMC) and soil degree of wind erosion (WE) carries out data normalization, because LULC,
WLSE and WE value shows that more greatly Land degradation degree is stronger, and VC and SMC value shows that more greatly Land degradation degree is weaker.For side
Just calculating makes all finger target values have unified direction, that is, value shows that more greatly Land degradation degree is stronger.
It specifically includes:
The land use and land cover pattern (LULC), soil erosion degree (WLSE) and soil degree of wind erosion (WE) are
Positive index, the land use and land cover pattern (LULC), soil erosion degree (WLSE) and soil degree of wind erosion (WE)
Value show that Land degradation degree is stronger more greatly, positive criterionization is as follows:
Xi=(xi-xmin)/(xmax-xmin)；
The vegetation coverage (VC) and soil moisture content (SMC) are negative sense index, the vegetation coverage (VC) and soil
The value of earth moisture content (SMC) shows that more greatly Land degradation degree is weaker, and negative sense criterionization is as follows:
Xi=(xmax-xi)/(xmax-xmin)；
Wherein, XiIt is the value after standardization, xi、xmin、xmaxRespectively represent the land use and land cover pattern (LULC),
This five vegetation coverage (VC), soil erosion degree (WLSE), soil moisture content (SMC) and soil degree of wind erosion (WE) fingers
Target original value, minimum value and maximum value；
The land use and land cover pattern (LULC), vegetation coverage (VC), soil erosion degree (WLSE), soil contain
Value after water rate (SMC) and soil degree of wind erosion (WE) progress data normalization is between 0-1.
Step S50, by the land use and land cover pattern (LULC), vegetation coverage (VC), soil erosion degree
(WLSE), the striograph of soil moisture content (SMC) and soil degree of wind erosion (WE) is overlapped, and is constructed comprehensive land deterioration and is referred to
Count line function resolving of going forward side by side.
Specifically, by the land use and land cover pattern (LULC) of extraction, vegetation coverage (VC), soil erosion journey
The striograph of degree (WLSE), soil moisture content (SMC) and soil degree of wind erosion (WE) is overlapped, and constructs comprehensive land deterioration
Index LDI function is as follows:
LDI=f (LULC, VC, WLSE, WE, SMC)；
Wherein, LDI is comprehensive land degradation index, and f is the land use and land cover pattern (LULC), vegetation coverage
(VC), the integrated letter of five soil erosion degree (WLSE), soil moisture content (SMC) and soil degree of wind erosion (WE) indexs
Number.
LDI data set is rejected by using principal component analysis method (Principal Component Analysis, PCA)
Redundancy, principal component analysis method can play the role of reduce data dimension, complex data collection is decomposed into a few
The component (i.e. principal component) being independent of each other, wherein each principal component can reflect the partial information of original variable, and contained
Information does not repeat mutually, and complicated factor is attributed to several principal components while introducing many-sided variable by this method, makes problem
Simplify, while obtaining more scientific and effective data information) LDI function is solved, it will be original by principal component analysis
Multidimensional remotely-sensed data collection compressed, the first component that wherein principal component analysis obtains, i.e. first principal component PC1 contains original
Most information of beginning data set are as follows using the linear combination building LDI of PC1:
LDI=(PC1-PC1min)/(PC1max-PC1min)；
Wherein, PC1, PC1minAnd PC1maxRespectively represent the minimum value and maximum value of first principal component, first principal component；
For the value of LDI between 0-1, LDI value is bigger, shows that Land degradation degree is stronger in survey region.
Step S60, according to the calculated result of the comprehensive land degradation index output Land degradation degree, and according to described
The size of comprehensive land degradation index carries out the grade classification of Land degradation status.
Specifically, Land degradation status grade classification can be carried out according to the size of LDI, according to equidistant partitioning LDI
Value be divided into no degeneration (0-0.2), it is slight degenerate (0.2-0.4), gently degraded (0.4-0.6), heavy-degraded (0.6-0.8),
This five grades of extreme degradation (0.8-1), other grade classifications also may be used.
The present invention is based on the Novel land deterioration indexs (LDI) of comprehensive assessment Land degradation status, are activety fault
Effective support and decision are provided with land deterioration mitigation；Based on the thought that index comprehensive integrates, multiple be conducive to can be integrated
Detect the index of Land degradation status；It can be used for multiple dimensioned land deterioration to extract, solve the difficulty that soil moves back manual research
Point；Land degradation degree suitable for mesoscale, large scale and small scale extracts.
Further, the synthesis LDI of building is not limited to be useful on Landsat film sequence, remaining remote sensing image is gathered around
There is approximate Landsat image band class information also applicable, is not limited to the method that the present invention introduces；In addition, LULC, VC, WLSE,
The available index substitution for possessing approximate function of five kinds of indexs of WE, SMC.
Further, as shown in figure 3, the method based on above-mentioned fusion multi-source remote sensing index evaluation Land degradation status, sheet
Invention further correspondingly provides a kind of system for merging multi-source remote sensing index evaluation Land degradation status, and the fusion multi-source remote sensing refers to
Marking the system for assessing Land degradation status includes:
Image capturing processing module 101 is located in advance for obtaining remote sensing image and carrying out image according to research area's actual conditions
Reason；
Land classification processing module 102, for carrying out land use and land cover pattern from pretreated remote sensing image
Classification, from small to large recompiles different land types according to the influence power to land deterioration；
Exponent extracting module 103, for extracting vegetation coverage, soil erosion journey in remote sensing image after the pre-treatment
Degree, soil moisture content and soil degree of wind erosion；
Standardization module 104 is used for the land use and land cover pattern, vegetation coverage, soil erosion journey
The image data of degree, soil moisture content and soil degree of wind erosion carries out data normalization；
Function constructs module 105, for by the land use and land cover pattern, vegetation coverage, soil erosion degree,
The striograph of soil moisture content and soil degree of wind erosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function solution
It calculates；
Grade classification module 106, for the calculating knot according to the comprehensive land degradation index output Land degradation degree
Fruit, and according to the grade classification of the size of comprehensive land degradation index progress Land degradation status.
Further, as shown in figure 4, method based on above-mentioned fusion multi-source remote sensing index evaluation Land degradation status and being
System, the present invention further correspondingly provide a kind of device for merging multi-source remote sensing index evaluation Land degradation status, the fusion multi-source
The device of remote sensing index evaluation Land degradation status includes fusion multi-source remote sensing index evaluation Land degradation status as described above
System, further include processor 10, memory 20 and display 30.Fig. 4 illustrates only fusion multi-source remote sensing index evaluation soil
The members of the device of degraded condition can substitute it should be understood that being not required for implementing all components shown
Implement more or less component.
The memory 20 can be the fusion multi-source remote sensing index evaluation Land degradation status in some embodiments
Device internal storage unit, such as fusion multi-source remote sensing index evaluation Land degradation status device hard disk or memory.
The memory 20 is also possible to the dress of the fusion multi-source remote sensing index evaluation Land degradation status in further embodiments
The plug-in type being equipped on the External memory equipment set, such as the device of the fusion multi-source remote sensing index evaluation Land degradation status
Hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card
(Flash Card) etc..Further, the memory 20 can also both include that merged multi-source remote sensing index evaluation soil moves back
The internal storage unit of the device of change situation also includes External memory equipment.The memory 20 is installed on described melt for storing
The application software and Various types of data of the device of multi-source remote sensing index evaluation Land degradation status are closed, such as multi-source is merged in the installation
The program code etc. of the device of remote sensing index evaluation Land degradation status.The memory 20 can be also used for temporarily storing
Data through exporting or will export.In one embodiment, fusion multi-source remote sensing index evaluation soil is stored on memory 20
The program 40 of the program 40 of ground degraded condition, the fusion multi-source remote sensing index evaluation Land degradation status can be held by processor 10
Row, to realize the method for merging multi-source remote sensing index evaluation Land degradation status in the application.
The processor 10 can be in some embodiments a central processing unit (Central Processing Unit,
CPU), microprocessor or other data processing chips, for running the program code stored in the memory 20 or processing number
According to, such as execute the method etc. of the fusion multi-source remote sensing index evaluation Land degradation status.
The display 30 can be light-emitting diode display, liquid crystal display, touch-control liquid crystal display in some embodiments
And OLED (Organic Light-Emitting Diode, Organic Light Emitting Diode) touches device etc..The display 30 is used
In the information for the device for being shown in the fusion multi-source remote sensing index evaluation Land degradation status and for showing visually
User interface.The component 10-30 of the device of the fusion multi-source remote sensing index evaluation Land degradation status passes through system bus phase
Mutual communication.
In one embodiment, when processor 10 executes fusion multi-source remote sensing index evaluation land deterioration in the memory 20
It is performed the steps of when the program 40 of situation
It obtains remote sensing image and carries out Yunnan snub-nosed monkey according to research area's actual conditions；
Land use and land cover classification are carried out from pretreated remote sensing image, according to the influence to land deterioration
Power from small to large recompiles different land types；
Vegetation coverage, soil erosion degree, soil moisture content and soil wind are extracted in remote sensing image after the pre-treatment
Degree of corrosion；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind
The image data of degree of corrosion carries out data normalization；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind
The striograph of degree of corrosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function resolving；
According to the calculated result of the comprehensive land degradation index output Land degradation degree, and according to the comprehensive soil
The size of deterioration index carries out the grade classification of Land degradation status.
The present invention also provides a kind of storage mediums, wherein the storage medium is stored with fusion multi-source remote sensing index evaluation
The program of the program of Land degradation status, the fusion multi-source remote sensing index evaluation Land degradation status is real when being executed by processor
The step of method of the existing fusion multi-source remote sensing index evaluation Land degradation status；As detailed above.
In conclusion the present invention provides a kind of method and system for merging multi-source remote sensing index evaluation Land degradation status,
The described method includes: obtaining remote sensing image and carrying out Yunnan snub-nosed monkey according to research area's actual conditions；From pretreated remote sensing
Land use and land cover classification are carried out in image, according to the influence power to land deterioration from small to large to different land types
It recompiles；Vegetation coverage, soil erosion degree, soil moisture content and soil wind are extracted in remote sensing image after the pre-treatment
Degree of corrosion；By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind
The image data of degree of corrosion carries out data normalization；By the land use and land cover pattern, vegetation coverage, soil erosion journey
Degree, soil moisture content and soil degree of wind erosion striograph be overlapped, construct comprehensive land degradation index and go forward side by side line function
It resolves；According to the calculated result of the comprehensive land degradation index output Land degradation degree, and moved back according to the comprehensive soil
The size for changing index carries out the grade classification of Land degradation status.The present invention is based on the index of remote sensing appraising Land degradation degree,
Comprehensive land degradation index is obtained by integrating multiple indexs, realization quickly identifies Land degradation status from remote sensing image.
Certainly, those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method,
It is that related hardware (such as processor, controller etc.) can be instructed to complete by computer program, the program can store
In a computer-readable storage medium, described program may include the process such as above-mentioned each method embodiment when being executed.
Wherein the storage medium can be memory, magnetic disk, CD etc..
It should be understood that the application of the present invention is not limited to the above for those of ordinary skills can
With improvement or transformation based on the above description, all these modifications and variations all should belong to the guarantor of appended claims of the present invention
Protect range.
Claims (10)
1. a kind of method for merging multi-source remote sensing index evaluation Land degradation status, which is characterized in that the fusion multi-source remote sensing
The method of index evaluation Land degradation status includes:
It obtains remote sensing image and carries out Yunnan snub-nosed monkey according to research area's actual conditions；
Land use and land cover classification are carried out from pretreated remote sensing image, according to the influence power to land deterioration from
It is small to being recompiled to different land types greatly；
Vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion journey are extracted in remote sensing image after the pre-treatment
Degree；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion journey
The image data of degree carries out data normalization；
By the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil wind erosion journey
The striograph of degree is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function resolving；
According to the calculated result of the comprehensive land degradation index output Land degradation degree, and according to the comprehensive land deterioration
The size of index carries out the grade classification of Land degradation status.
2. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 1, which is characterized in that institute
State the extracting method of vegetation coverage are as follows:
NDVI=(ρNIR-ρRed)/(ρNIR+ρRed)；
VC=(NDVI-NDVImin)/(NDVImax-NDVImin)；
Wherein, NDVI indicates vegetation index, ρNIRAnd ρRedRespectively represent the close red and red spectral band of remote sensing image
Reflectivity；
VC indicates vegetation coverage, NDVIminAnd NDVIminRespectively represent the maximum value and minimum value of NDVI.
3. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 1, which is characterized in that institute
State the extracting method of soil erosion degree are as follows:
In conjunction with vegetation coverage, digital elevation model, land use and cover type, soil types and spatially distributed rainfall figure,
Soil erosion degree is extracted using generic data-access, specific as follows:
WLSE=RKLSCP；
Wherein, WLSE indicates soil erosion degree, and R is the rainfall erosivity factor, and K is soil erodibility factor, L be length of grade because
Son, S are slope factor, and C is the vegetative coverage factor, and P is the water and soil conservation control measure factor.
4. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 1, which is characterized in that institute
State the extracting method of soil moisture content are as follows:
Soil moisture content formula is constructed using the humidity component of tasseled cap transformation:
SMCTM=0.0315 ρBlue+0.2021ρGreen+0.3102ρRed+0.1594ρNIR-0.6806ρSWIR1-0.6109ρSWIR2
SMCOLI=0.1511 ρBlue+0.1972ρGreen+0.3283ρRed+0.3407ρNIR-0.7117ρSWIR1-0.4559ρSWIR2；
Wherein, SMCTMAnd SMCOLIRespectively represent the soil moisture content of Landsat-TM and Landsat-OLI image, ρBlue、
ρGreen、ρRed、ρNIR、ρSWIR1And ρSWIR2The blue, green, red of remote sensing image, near-infrared, first short red wave wave are respectively represented
The reflectivity of section and second short red wave wave band.
5. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 1, which is characterized in that institute
State the extracting method of soil degree of wind erosion are as follows:
WE=(ρSWIR1-ρBLUE)/(200-ρSWIR1-ρSWIR2)；
Wherein, ρBLUE、ρSWIR1And ρSWIR2Respectively represent the blue wave band of remote sensing image, first short red wave wave band and second
The reflectivity of short red wave wave band.
6. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 1, which is characterized in that institute
It states the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion
Image data carry out data normalization specifically include:
The land use and land cover pattern, soil erosion degree and soil degree of wind erosion are positive index, the soil benefit
Show that Land degradation degree is stronger more greatly with the value with land cover pattern, soil erosion degree and soil degree of wind erosion, forward direction refers to
Mark standardization is as follows:
Xi=(xi-xmin)/(xmax-xmin)；
The vegetation coverage and soil moisture content are negative sense index, the bigger table of the value of the vegetation coverage and soil moisture content
Bright Land degradation degree is weaker, and negative sense criterionization is as follows:
Xi=(xmax-xi)/(xmax-xmin)；
Wherein, XiIt is the value after standardization, xi、xmin、xmaxRespectively represent the land use and land cover pattern, vegetation coverage,
Original value, minimum value and the maximum value of five soil erosion degree, soil moisture content and soil degree of wind erosion indexs；
The land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion
Value after carrying out data normalization is between 0-1.
7. the method for fusion multi-source remote sensing index evaluation Land degradation status according to claim 6, which is characterized in that institute
It states the land use and land cover pattern, vegetation coverage, soil erosion degree, soil moisture content and soil degree of wind erosion
Striograph be overlapped, construct the line function resolving of going forward side by side of comprehensive land degradation index and specifically include:
By the land use and land cover pattern of extraction, vegetation coverage, soil erosion degree, soil moisture content and soil
The striograph of degree of wind erosion is overlapped, and it is as follows to construct comprehensive land degradation index LDI function:
LDI=f (LULC, VC, WLSE, WE, SMC)；
Wherein, LDI is comprehensive land degradation index, and f is the land use and land cover pattern, vegetation coverage, soil erosion
The aggregation function of five degree, soil moisture content and soil degree of wind erosion indexs；
LDI function is solved by using principal component analysis method, principal component analysis is by original multidimensional remotely-sensed data collection
It is compressed, the first component that wherein principal component analysis obtains, i.e. first principal component PC1 contain the exhausted big portion of raw data set
Divide information, as follows using the linear combination building LDI of PC1:
LDI=(PC1-PC1min)/(PC1max-PC1min)；
Wherein, PC1, PC1minAnd PC1maxRespectively represent the minimum value and maximum value of first principal component, first principal component；LDI's
For value between 0-1, LDI value is bigger, shows that Land degradation degree is stronger in survey region.
8. a kind of system for merging multi-source remote sensing index evaluation Land degradation status, which is characterized in that the fusion multi-source remote sensing
The system of index evaluation Land degradation status includes:
Image capturing processing module, for obtaining remote sensing image and carrying out Yunnan snub-nosed monkey according to research area's actual conditions；
Land classification processing module is pressed for carrying out land use and land cover classification from pretreated remote sensing image
Different land types are recompiled from small to large according to the influence power to land deterioration；
Exponent extracting module contains for extracting vegetation coverage, soil erosion degree, soil in remote sensing image after the pre-treatment
Water rate and soil degree of wind erosion；
Standardization module is used for the land use and land cover pattern, vegetation coverage, soil erosion degree, soil
The image data of moisture content and soil degree of wind erosion carries out data normalization；
Function constructs module, for containing the land use and land cover pattern, vegetation coverage, soil erosion degree, soil
The striograph of water rate and soil degree of wind erosion is overlapped, and is constructed comprehensive land degradation index and is gone forward side by side line function resolving；
Grade classification module, for exporting the calculated result of Land degradation degree, and root according to the comprehensive land degradation index
The grade classification of Land degradation status is carried out according to the size of the comprehensive land degradation index.
9. a kind of device for merging multi-source remote sensing index evaluation Land degradation status, which is characterized in that the fusion multi-source remote sensing
The device of index evaluation Land degradation status includes fusion multi-source remote sensing index evaluation land deterioration shape as claimed in claim 8
The system of condition, further includes: memory, processor and be stored in the fusion that can be run on the memory and on the processor
The program of multi-source remote sensing index evaluation Land degradation status, the program of the fusion multi-source remote sensing index evaluation Land degradation status
Such as claim 1-7 described in any item fusion multi-source remote sensing index evaluation land deterioration shapes are realized when being executed by the processor
The step of method of condition.
10. a kind of storage medium, which is characterized in that the storage medium is stored with fusion multi-source remote sensing index evaluation land deterioration
The program of the program of situation, the fusion multi-source remote sensing index evaluation Land degradation status realizes such as right when being executed by processor
It is required that the step of method of any one of 1-7 fusion multi-source remote sensing index evaluation Land degradation status.
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