CN108460372A - A kind of potential loss risk recognition methods of ecological land and system - Google Patents
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Abstract
The present invention provides a kind of potential loss risk recognition methods of ecological land, apply in the potential loss risk identifying system of ecological land, including following steps:S1, the data for preparing land use;S2, image data is handled, interprets work;S3, the conversion that data format is carried out to the image data after interpretation;S4, ecological land potential loss risk collection of illustrative plates is established, and collection of illustrative plates is analyzed.The accumulated change trend of quickly and accurately Study of recognition local area ecological land used potential loss risk is capable of in the potential loss risk recognition methods of ecological land of the present invention, and to pointedly alleviate ecological risk, certain guidance is provided for ecological security pattern.
Description
Technical field
The invention belongs to environment monitoring techniques fields, a kind of potential loss risk recognition methods more particularly, to ecological land and
System.
Background technology
The acceleration of urbanization promotes, especially Land-Use unreasonable for a long time so that a large amount of ecological lands
It is converted into non-ecological land, ecological land is lost in seriously, thus brings ecosystem service function to decline, ecological risk aggravation,
Ecological safety is on the hazard.Research about ecological risk identification has very much, and many scholars relate in the ecological risk identification of research
And to based on comprehensive ecological risk index constructed by land use data.About the comprehensive ecological risk based on land use data
Identification, many scholars have only carried out the comprehensive ecological risk of each timing node the making and analysis of collection of illustrative plates, and there is no right
Ecological risk carries out the related of accumulative effect and analyses in depth.And about ecological risk source and its ecological risk assessment of receptor,
On the one hand the correlative study of the accumulative effect of ecology is fewer, and the reproducibility of the evaluation method between the different zones of another aspect is very
Difference, operability be not also strong.
The angle developed from land use ecological protection, while diagnosing state of ecological environment quickly and accurately
The accumulated change trend of Study of recognition local area ecological land used potential loss risk, the person that contributes to ecological risk management make scientific and effective
Land Use Decision, will be as the important foundation of society, economy and ecological safety.
Invention content
In view of this, the present invention is directed to propose a kind of potential loss risk recognition methods of ecological land, existing right to solve
The identification method of ecological risk is more single, the poor situation of the reproducibility between different zones.
In order to achieve the above objectives, the technical proposal of the invention is realized in this way:
A kind of potential loss risk recognition methods of ecological land, is applied in the potential loss risk identifying system of ecological land, packet
Include following steps:
S1, the data for preparing land use;
S2, image data is handled, interprets work;
S3, the conversion that data format is carried out to the image data after interpretation;
S4, ecological land potential loss risk collection of illustrative plates is established, and collection of illustrative plates is analyzed.
Further, in the step S1, the data of the land use of preparation are needed with timing.
Further, the data of the land use of preparation include lteral data and image data, can be led to lteral data
The human-computer interaction interface for crossing system is directly inputted;It needs to handle image data.
Further, in the step S2, the processing procedure to image data includes geometric correction, splicing, Band fusion.
Further, image data after treatment, carries out image interpretation work, and pass through time series using patterning method
Variation track carries out joint correction to interpretation result, it is ensured that the correctly truth of expression present status of land utilization, it can be effective
The precision problem that avoids occurring during current remote Sensing Interpretation, and time series data is changed and is occurred when analysis
Redundancy patch and wrong patch.
Further, according to each land use pattern to the contribution margin of ecological risk come to different land use pattern
Assignment is carried out, and the color that each assignment is shown in the picture also differs, Combining with terrain, then carries out data and divide again
Class.
Further, in the step S3, by the assignment of the image data combination land use pattern after interpretation into line number
According to the conversion of format;
And system is manually or automatically input to for the assignment of lteral data combination land use pattern.
Further, it according to the data or transformed image data directly inputted, establishes with timing and has
There is Ecological Patterns' dynamic change locus spectra of multiple a timing nodes;
By data processing, remove that unreasonable, classification error, area be small and meaningless track, retains to have and represent
The variation track of meaning.
A kind of potential loss risk identifying system of ecological land, including data collection module, data processing module, remote Sensing Interpretation
Module, data conversion module, variation track analysis module;
The data collection module is divided into for collecting data and is manually entered or automatically enters;
The data processing module is used to carry out geometric correction, splicing, Band fusion processing to image information;
Using split plot design, to treated, information is interpreted the remote Sensing Interpretation module;
Result after the data conversion module is used to interpret carries out data conversion;
The variation track analysis module combination land use pattern assignment and transformed re-classification of data, output variation
Trajectory analysis model.
Further, further include joint correction module and risk identification module;
The joint correction module carries out joint correction by time series variation track to the result after interpretation, it is ensured that just
The truth of true expression present status of land utilization, can effectively avoid the precision occurred during current remote Sensing Interpretation from asking
Topic and time series data are changed the redundancy patch occurred when analysis and wrong patch;
After to each land use pattern assignment, ecological risk of the risk identification module to each timing node
Distribution map is exported by variation track analysis model, then calculates the ecological wind with time series by raster symbol-base model again
Dangerous data identify the potential loss risk of ecological land.
Compared with the existing technology, the potential loss risk recognition methods of ecological land of the present invention has the advantage that:
The potential loss risk recognition methods of ecological land of the present invention and system are by landscape pattern analysis from Spatial Dimension
Spatial dimensionality is expanded to, Landscape Spatial Pattern Evolution dynamic and its regularity are evaluated from integrity;Based on certain time sequence
The land use datas of row simultaneously combines variation track analysis method, apply joint bearing calibration correction unreasonable on this basis or
The variation track of mistake builds its research framework, and the quickly and accurately accumulation of Study of recognition local area ecological land used potential loss risk becomes
Change trend provides certain guidance for ecological security pattern to pointedly alleviate ecological risk.
Description of the drawings
The attached drawing for constituting the part of the present invention is used to provide further understanding of the present invention, schematic reality of the invention
Example and its explanation are applied for explaining the present invention, is not constituted improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the potential loss risk recognition methods flow chart of the ecological land described in the embodiment of the present invention;
Fig. 2 is -2015 years 1984 Jing-jin-ji region Land use change analysis charts described in the embodiment of the present invention;
Fig. 3 is the temporal and spatial orientation point of -2015 years 1984 land use ecological risks described in the embodiment of the present invention
Butut;
Fig. 4 is -2015 years 1984 benign and malignant distribution maps of land use ecological risk described in the embodiment of the present invention.
Specific implementation mode
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the present invention can phase
Mutually combination.
In the description of the present invention, it is to be understood that, term "center", " longitudinal direction ", " transverse direction ", "upper", "lower",
The orientation or positional relationship of the instructions such as "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside" is
It is based on the orientation or positional relationship shown in the drawings, is merely for convenience of description of the present invention and simplification of the description, rather than instruction or dark
Show that signified device or element must have a particular orientation, with specific azimuth configuration and operation, therefore should not be understood as pair
The limitation of the present invention.In addition, term " first ", " second " etc. are used for description purposes only, it is not understood to indicate or imply phase
To importance or implicitly indicate the quantity of indicated technical characteristic.The feature for defining " first ", " second " etc. as a result, can
To express or implicitly include one or more this feature.In the description of the present invention, unless otherwise indicated, " multiple "
It is meant that two or more.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected;It can
Can also be electrical connection to be mechanical connection;It can be directly connected, can also indirectly connected through an intermediary, Ke Yishi
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood by concrete condition
Concrete meaning in the present invention.
The present invention will be described in detail below with reference to the accompanying drawings and embodiments.
As shown in Figure 1, a kind of potential loss risk recognition methods of ecological land, applies the potential loss risk identification in ecological land
In system, including following steps:
S1, the data for preparing land use;
S2, image data is handled, interprets work;
S3, the conversion that data format is carried out to the image data after interpretation;
S4, ecological land potential loss risk collection of illustrative plates is established, and collection of illustrative plates is analyzed.
System is provided with ecological land risk identification module, and user is supported to be operated under the interfaces GIS.By data
Input and preprocessing module support the land use data of each timing node to be manually entered or automatically enter under the graphical interface,
The value-at-risk of each land use pattern can sort out the methods of marking using analytic hierarchy process (AHP) or expert and carry out rounding sequence.Pass through
Above-mentioned processing finally obtains contribution degree of each land use pattern to ecological risk.
System core part is variation track analysis model and raster symbol-base model.To each land use pattern assignment
Later, the ecological risk distribution map of each timing node is then exported by variation track analysis model.Pass through grid meter again later
It calculates model and calculates the ecological risk data with time series, thus identify the potential loss risk of ecological land.
System structure carries out the secondary development of ArcGIS using Python.
In the step S1, the data of the land use of preparation are needed with timing.
The data of the land use of preparation include lteral data and image data, can pass through the people of system to lteral data
Machine interactive interface is directly inputted;It needs to handle image data.
In the step S2, the processing procedure to image data includes geometric correction, splicing, Band fusion.
The specific method is as follows for geometric correction:
1) it is opened in ENVI Classic and refers to topographic map and image to be corrected;
2) map- is selected on main menu>Registration->select GCPs:image to image;
3) reference picture is chosen on both sides respectively;
4) control point is selected:Control point is selected using registration with objects as foundation, is easily differentiated on selection image and finer
Characteristic point.Image border has to choose control point, in case image is extrapolated.Expire width as far as possible and uniformly chooses 15 points or more.It (protects
Each point error amount is demonstrate,proved within 0.5) if to abandon the delete last point of point selection lower right corner, or point show
Point pops up image to image gcplist windows, the point for therefrom selecting you to be deleted.
5) after reconnaissance, savepoint:ground control points->file->save gcp as ASCII.
6) followed by correction:It is selected in ground control points. dialog boxes:options->warp
File chooses your image to be corrected, point ok to enter registration in the input warp image of appearance
Parameters dialog boxes:Method for resampling (resampling) is selected, is (bilinear).
The specific method is as follows for splicing:
1) ArcToolbox-Data Management Tools-Raster-Mosaic, Input Rasters are opened
To input figure layer.
2) Target Raster are output figure layer.
3) Mosaic Method (optional) is used for the color of lap in judging result, FIRST-- overlappings
Part and sequence are consistent in upper figure layer;LAST-- laps are consistent with figure layer of the sequence under;Two figures of BLEND--
The average value of two figure layers of secondary colour MEAN-- of layer;Small value is gone in two figure layers of MINIMUM--;MAXIMUM-- two
It takes large values in a figure layer.
4) Mosaic Color map Mode (optional), are set as default value.
5) Ignore Background Value (optional), is set as default value.
6)Nodata Value(optional).NoData is handled as what value, for example, if we write 0,
Nodata will so be handled as black, then makees transparent processing for sky.
Convert 1bit data to 8bit (optional), are set as default value.
Mosaicking Tolerance (optional), are set as default value.
The specific method is as follows for Band fusion:
1) the landsat OLI images of download are decompressed, corresponding shadow under file is found in catalog catalogues
As data, B3, B4, B5, B8 wave band are loaded into ArcMap:
2) ArcToolbox is opened, Data management Tools (data organizing tool)-are found>Raster (grid
Lattice)->Raster Processing (grid processing)->Composite Bands (Band fusion) are double-clicked and are opened, selection
The drop down button of input Rasters boxes, by B5, B4, B3 wave bands, which are sequentially added into, to be merged, output raster's
Give tacit consent to output position:
3) it clicks and confirms, the image after being merged:
4) storing path is finally selected.
Image data carries out image interpretation work after treatment, using patterning method, and passes through time series variation track
Joint correction is carried out to interpretation result, it is ensured that the correctly truth of expression present status of land utilization can effectively avoid mesh
The precision problem occurred during preceding remote Sensing Interpretation, and the redundancy patch occurred when analysis is changed to time series data
With wrong patch.
When obtaining land use pattern, need to carry out remote Sensing Interpretation.The method of remote Sensing Interpretation has very much, what we applied
It is patterning method.If carrying out visual interpretation to all remote sensing image, workload can greatly increase and error also can be with
Increase, therefore visually solved on the basis of previous time point visual interpretation data or acquired land use data
It translates, so that it may quickly and easily to obtain required land use data.
Assignment is carried out to different land use pattern to the contribution margin of ecological risk according to each land use pattern,
And the color that each assignment is shown in the picture also differs, Combining with terrain, then carries out re-classification of data.
In the step S3, the assignment of the image data combination land use pattern after interpretation is subjected to turning for data format
It changes;
And system is manually or automatically input to for the assignment of lteral data combination land use pattern.
According to the data or transformed image data directly inputted, establish with timing and with multiple times
Ecological Patterns' dynamic change locus spectra of node;
By data processing, remove that unreasonable, classification error, area be small and meaningless track, retains to have and represent
The variation track of meaning.
A kind of potential loss risk identifying system of ecological land, including data collection module, data processing module, remote Sensing Interpretation
Module, data conversion module, variation track analysis module;
The data collection module is divided into for collecting data and is manually entered or automatically enters;
The data processing module is used to carry out geometric correction, splicing, Band fusion processing to image information;
Using split plot design, to treated, information is interpreted the remote Sensing Interpretation module;
Result after the data conversion module is used to interpret carries out data conversion;
The variation track analysis module combination land use pattern assignment and transformed re-classification of data, output variation
Trajectory analysis model.
Further include joint correction module and risk identification module;
The joint correction module carries out joint correction by time series variation track to the result after interpretation, it is ensured that just
The truth of true expression present status of land utilization, can effectively avoid the precision occurred during current remote Sensing Interpretation from asking
Topic and time series data are changed the redundancy patch occurred when analysis and wrong patch;
After to each land use pattern assignment, ecological risk of the risk identification module to each timing node
Distribution map is exported by variation track analysis model, then calculates the ecological wind with time series by raster symbol-base model again
Dangerous data identify the potential loss risk of ecological land.
Specific embodiment is as follows:
As shown in Fig. 2, when Beijing-tianjin-hebei Region 1984-2015 ecological land potential loss risks are identified, it is right first
It is changed trajectory analysis by pretreated land use data, according to Chinese Academy of Sciences's land use cover classification system by soil
Use pattern is divided into forest land, meadow, waters, arable land, artificial surface, other lands used and marine site, code is respectively 1,2,3,4,5,
6、7.According to research area's land cover pattern first-level class as a result, by reclassification and raster symbol-base method, 6 timing nodes of acquisition
Ecological Patterns' dynamic change locus spectra.Then by data processing, remove that unreasonable, classification error, area is small and is not intended to
The track of justice retains the variation track for having and representing meaning.Wherein, the color in Fig. 2 represented by each land use pattern
It differs.
Soil potential loss risk is identified then in conjunction with variation track analysis method.As shown in figure 3, by according to land use
Type, to each land use pattern assignment, obtains the land use ecological risk in each period to the contribution degree of ecological risk
Distribution situation.In Beijing-tianjin-hebei Region, there are 7 kinds of land use patterns:Forest land, meadow, waters, arable land, artificial surface, other lands used
And marine site, it is respectively after reclassification:Forest land (1), waters (2), meadow (3), arable land (4), other lands used (5), artificial surface
(6).Soil wastage during time series indicates with variation code, such as 11112,44441 etc., before 11112 show
Four, face time point land use pattern is forest land, the last one time point land use pattern is meadow, so 11112 explanations
Forest land is changed into meadow, and forest land has leakage, ecological potential loss risk to increase;33366 illustrate the soil of three timing nodes in front
Ground use pattern is waters, behind two timing node land use patterns be artificial surface, so 33366 illustrate that waters changes
For artificial surface, waters has leakage, ecological risk to increase.With the transformation of land use pattern in Fig. 3, show on the diagram
The color gone out also will appear variation.
As shown in figure 4, good so as to further analyze ecological risk variation according to land use analysis on Ecological Risk
Property and pernicious region.It is benign to be indicated using green when being drawn in Fig. 4, it is pernicious to be indicated using red.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all essences in the present invention
With within principle, any modification, equivalent replacement, improvement and so on should all be included in the protection scope of the present invention god.
Claims (10)
1. a kind of potential loss risk recognition methods of ecological land is applied in the potential loss risk identifying system of ecological land, special
Sign is, including following steps:
S1, the data for preparing land use;
S2, image data is handled, interprets work;
S3, the conversion that data format is carried out to the image data after interpretation;
S4, ecological land potential loss risk collection of illustrative plates is established, and collection of illustrative plates is analyzed.
2. the potential loss risk recognition methods of ecological land according to claim 1, it is characterised in that:In the step S1,
The data of the land use of preparation are needed with timing.
3. the potential loss risk recognition methods of ecological land according to claim 1 or 2, it is characterised in that:The soil of preparation
The data utilized include lteral data and image data, can be carried out by the human-computer interaction interface of system to lteral data direct
Input;It needs to handle image data.
4. the potential loss risk recognition methods of ecological land according to claim 1, it is characterised in that:In the step S2,
Processing procedure to image data includes geometric correction, splicing, Band fusion.
5. the potential loss risk recognition methods of ecological land according to claim 1 or 4, it is characterised in that:Image data passes through
After crossing processing, image interpretation work is carried out using patterning method, and combine to interpretation result by time series variation track
Correction, it is ensured that the correctly truth of expression present status of land utilization can effectively avoid going out during current remote Sensing Interpretation
Existing precision problem, and the redundancy patch occurred when analysis and wrong patch are changed to time series data.
6. the potential loss risk recognition methods of ecological land according to claim 5, it is characterised in that:According to each soil profit
Assignment carried out to different land use pattern to the contribution margin of ecological risk with type, and each assignment table in the picture
The color revealed also differs, Combining with terrain, then carries out re-classification of data.
7. the potential loss risk recognition methods of ecological land according to claim 6, which is characterized in that in the step S3,
The assignment of image data combination land use pattern after interpretation is carried out to the conversion of data format;
And system is manually or automatically input to for the assignment of lteral data combination land use pattern.
8. the potential loss risk recognition methods of ecological land according to claim 7, it is characterised in that:According to what is directly inputted
Data or transformed image data establish Ecological Patterns' dynamic changes with timing and with multiple timing nodes
Locus spectra;
By data processing, remove that unreasonable, classification error, area be small and meaningless track, retains to have and represents meaning
Variation track.
9. a kind of potential loss risk identifying system of ecological land, it is characterised in that:Including data collection module, data processing mould
Block, remote Sensing Interpretation module, data conversion module, variation track analysis module;
The data collection module is divided into for collecting data and is manually entered or automatically enters;
The data processing module is used to carry out geometric correction, splicing, Band fusion processing to image information;
Using split plot design, to treated, information is interpreted the remote Sensing Interpretation module;
Result after the data conversion module is used to interpret carries out data conversion;
The variation track analysis module combination land use pattern assignment and transformed re-classification of data export variation track
Analysis model.
10. the potential loss risk identifying system of ecological land according to claim 9, it is characterised in that:It further include joint school
Positive module and risk identification module;
The joint correction module carries out joint correction by time series variation track to the result after interpretation, it is ensured that correctly
The truth for expressing present status of land utilization can effectively avoid the precision problem occurred during current remote Sensing Interpretation, with
And time series data is changed the redundancy patch occurred when analysis and wrong patch;
After to each land use pattern assignment, the risk identification module is distributed the ecological risk of each timing node
Figure is exported by variation track analysis model, then calculates the ecological risk number with time series by raster symbol-base model again
According to identifying the potential loss risk of ecological land.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109886593A (en) * | 2019-03-01 | 2019-06-14 | 天津城建大学 | A kind of ecological source based on Thiessen polygon ground optimization method |
CN113610013A (en) * | 2021-08-10 | 2021-11-05 | 四川易方智慧科技有限公司 | Method for extracting building outline based on RGB (Red Green blue) wave bands of high-definition remote sensing image |
Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102855487A (en) * | 2012-08-27 | 2013-01-02 | 南京大学 | Method for automatically extracting newly added construction land change image spot of high-resolution remote sensing image |
CN105005784A (en) * | 2015-05-21 | 2015-10-28 | 中国科学院遥感与数字地球研究所 | Time sequence remote sensing image land cover classification method based on CD-DTW distance |
CN107818519A (en) * | 2017-10-30 | 2018-03-20 | 华南农业大学 | A kind of provincial land use data processing method of timesharing sequence and system |
-
2018
- 2018-04-25 CN CN201810381494.0A patent/CN108460372A/en active Pending
Patent Citations (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102855487A (en) * | 2012-08-27 | 2013-01-02 | 南京大学 | Method for automatically extracting newly added construction land change image spot of high-resolution remote sensing image |
CN105005784A (en) * | 2015-05-21 | 2015-10-28 | 中国科学院遥感与数字地球研究所 | Time sequence remote sensing image land cover classification method based on CD-DTW distance |
CN107818519A (en) * | 2017-10-30 | 2018-03-20 | 华南农业大学 | A kind of provincial land use data processing method of timesharing sequence and system |
Non-Patent Citations (2)
Title |
---|
DONGCHUAN WANG 等: "Comparative analysis of land use/cover change trajectories and their driving forces in two small watersheds in the western Loess Plateau of China", 《INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION》 * |
DONGCHUAN WANG 等: "Spatio-temporal pattern analysis of land use/cover change trajectories in Xihe watershed", 《INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN109886593A (en) * | 2019-03-01 | 2019-06-14 | 天津城建大学 | A kind of ecological source based on Thiessen polygon ground optimization method |
CN113610013A (en) * | 2021-08-10 | 2021-11-05 | 四川易方智慧科技有限公司 | Method for extracting building outline based on RGB (Red Green blue) wave bands of high-definition remote sensing image |
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