CN108460372A - A kind of potential loss risk recognition methods of ecological land and system - Google Patents

Abstract

The present invention provides a loss risk identification method of ecological land, which is applied to the loss risk identification system of ecological land, including the following steps: S1, preparing land use data; S2, processing and interpreting image data ; S3, converting the data format of the interpreted image data; S4, establishing an ecological land loss risk map, and analyzing the map. The ecological land loss risk identification method of the present invention can quickly and accurately identify the cumulative change trend of the ecological land loss risk in the research area, thereby mitigating ecological risks in a targeted manner and providing certain guidance for ecological security construction.

Description

Method and system for identifying risk of loss of ecological land

technical field

The invention belongs to the technical field of environmental monitoring, and in particular relates to a method and system for identifying loss risks of ecological land.

Background technique

The acceleration of urbanization, especially the long-term irrational land use, has transformed a large amount of ecological land into non-ecological land, and the loss of ecological land is serious, resulting in the decline of ecosystem service functions, increased ecological risks, and threats to ecological security. . There are many studies on ecological risk identification, and many scholars involved in the construction of comprehensive ecological risk index based on land use data when studying ecological risk identification. Regarding the identification of comprehensive ecological risks based on land use data, many scholars have only made and analyzed maps of comprehensive ecological risks at various time points, and have not conducted in-depth analysis of the cumulative effects of ecological risks. Moreover, regarding the ecological risk assessment of ecological risk sources and their receptors, on the one hand, there are relatively few studies on ecological cumulative effects, and on the other hand, the reproducibility and operability of evaluation methods between different regions are poor.

From the perspective of land use ecological protection development, quickly and accurately identify the cumulative change trend of ecological land loss risk in the study area while diagnosing the ecological environment status, which will help ecological risk managers make scientific and effective land use decisions, and will An important foundation for social, economic and ecological security.

Contents of the invention

In view of this, the present invention aims to propose a method for identifying the loss risk of ecological land, so as to solve the situation that the existing identification method for ecological risk is relatively single and the reproducibility between different regions is poor.

In order to achieve the above object, technical solution of the present invention is achieved in that way:

A method for identifying the risk of loss of ecological land, applied to a system for identifying the risk of loss of ecological land, comprising the following steps:

S1. Prepare land use data;

S2. Processing and interpreting the image data;

S3, performing data format conversion on the interpreted image data;

S4. Establish an ecological land loss risk map and analyze the map.

Further, in the step S1, the prepared land use data needs to be time-series.

Furthermore, the prepared land use data includes text data and image data, and the text data can be directly input through the system's human-computer interaction interface; the image data needs to be processed.

Further, in the step S2, the processing of the image data includes geometric correction, splicing, and band fusion.

Furthermore, after the image data is processed, the cutting method is used for image interpretation, and the interpretation results are jointly corrected through the time series change trajectory to ensure that the real situation of land use status is correctly expressed, which can effectively avoid the current remote sensing solution. Accuracy problems in the translation process, as well as redundant and erroneous patches in the change analysis of time series data.

Further, different land use types are assigned according to the contribution value of each land use type to the ecological risk, and the color of each assignment in the image is different, combined with the terrain, and then the data is reclassified.

Further, in the step S3, the data format conversion is carried out by combining the interpreted image data with the assignment of the land use type;

For text data combined with the assignment of land use types, manually or automatically input to the system.

Further, according to the directly input data or the converted image data, establish a time-series and dynamic change trajectory map of the ecological pattern with multiple time nodes;

Through data processing, unreasonable, misclassified, small and meaningless trajectories are removed, and representative change trajectories are retained.

A loss risk identification system for ecological land, including a data collection module, a data processing module, a remote sensing interpretation module, a data conversion module, and a change track analysis module;

The data collection module is used to collect data, which is divided into manual input or automatic input;

The data processing module is used to perform geometric correction, splicing, and band fusion processing on the image information;

The remote sensing interpretation module uses a segmentation method to interpret the processed information;

The data conversion module is used for performing data conversion on the interpreted result;

The change track analysis module combines land use type assignment and converted data reclassification to output a change track analysis model.

Further, it also includes a joint correction module and a risk identification module;

The joint correction module performs joint correction on the interpreted results through the time series change trajectory to ensure that the real situation of land use status is correctly expressed, and can effectively avoid the accuracy problems that occur in the current remote sensing interpretation process, and the time series data Redundant and erroneous patches when performing change analysis;

After assigning values to each land use type, the risk identification module outputs the ecological risk distribution map of each time node through the change trajectory analysis model, and then calculates the ecological risk data with time series through the grid calculation model to identify the ecological land loss risk.

Compared with the prior art, the loss risk identification method of the ecological land of the present invention has the following advantages:

The ecological land loss risk identification method and system described in the present invention extend the landscape pattern analysis from the spatial dimension to the time-space dimension, and evaluate the evolution dynamics and regularity of the landscape pattern from the process integrity; based on a certain time series of land use data and Combined with the change track analysis method, on this basis, the joint correction method is used to correct the unreasonable or wrong change track, build its research framework, and quickly and accurately identify the cumulative change trend of the ecological land loss risk in the research area, so as to alleviate the ecological land loss in a targeted manner. risk, and provide certain guidance for ecological security construction.

Description of drawings

The drawings constituting a part of the present invention are used to provide a further understanding of the present invention, and the schematic embodiments and descriptions of the present invention are used to explain the present invention, and do not constitute an improper limitation of the present invention. In the attached picture:

Fig. 1 is the flow chart of the loss risk identification method of ecological land described in the embodiment of the present invention;

Fig. 2 is the track analysis diagram of the Beijing-Tianjin-Hebei land use change track in 1984-2015 described in the embodiment of the present invention;

Fig. 3 is the spatial-temporal dynamic change distribution diagram of land use ecological risk in 1984-2015 described in the embodiment of the present invention;

Fig. 4 is a distribution map of benign and malignant land use ecological risks from 1984 to 2015 according to the embodiment of the present invention.

Detailed ways

It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

In describing the present invention, it should be understood that the terms "center", "longitudinal", "transverse", "upper", "lower", "front", "rear", "left", "right", " The orientations or positional relationships indicated by "vertical", "horizontal", "top", "bottom", "inner" and "outer" are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and Simplified descriptions, rather than indicating or implying that the device or element referred to must have a particular orientation, be constructed and operate in a particular orientation, and thus should not be construed as limiting the invention. In addition, the terms "first", "second", etc. are used for descriptive purposes only, and should not be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, a feature defined as "first", "second", etc. may expressly or implicitly include one or more of that feature. In the description of the present invention, unless otherwise specified, "plurality" means two or more.

In the description of the present invention, it should be noted that unless otherwise specified and limited, the terms "installation", "connection" and "connection" should be understood in a broad sense, for example, it can be a fixed connection or a detachable connection. Connected, or integrally connected; it can be mechanically connected or electrically connected; it can be directly connected or indirectly connected through an intermediary, and it can be the internal communication of two components. Those of ordinary skill in the art can understand the specific meanings of the above terms in the present invention based on specific situations.

The present invention will be described in detail below with reference to the accompanying drawings and examples.

As shown in Figure 1, an ecological land loss risk identification method is applied to the ecological land loss risk identification system, including the following steps:

S1. Prepare land use data;

S2. Processing and interpreting the image data;

S3, performing data format conversion on the interpreted image data;

S4. Establish an ecological land loss risk map and analyze the map.

The system has an ecological land use risk identification module, and supports users to operate under the GIS interface. The data input and preprocessing module supports manual or automatic input of land use data at each time node under the graphical interface, and the risk value of each land use type can be rounded and sorted by using methods such as analytic hierarchy process or expert classification and scoring. Through the above processing, the contribution of each land use type to the ecological risk is finally obtained.

The core part of the system is the change trajectory analysis model and the grid calculation model. After assigning values to each land use type, the ecological risk distribution map at each time node is output through the change trajectory analysis model. Afterwards, the grid calculation model is used to calculate the ecological risk data with time series, thereby identifying the loss risk of ecological land.

The system construction adopts Python language for the secondary development of ArcGIS.

In the step S1, the prepared land use data needs to be time-series.

The prepared land use data includes text data and image data. The text data can be directly input through the system's human-computer interaction interface; the image data needs to be processed.

In the step S2, the processing of the image data includes geometric correction, splicing, and band fusion.

The specific method of geometric correction is as follows:

1) Open the reference topographic map and the image to be corrected in ENVI Classic;

2) Select map->Registration->select GCPs: image to image on the main menu;

3) Select reference images on both sides;

4) Selection of control points: The selection of control points is based on the registration object, and the easily distinguishable and finer feature points on the image are selected. Be sure to select control points on the edge of the image to avoid extrapolation of the image. Select more than 15 points uniformly as far as possible. (Guarantee that the error value of each point is within 0.5) If you want to abandon the point, select delete last point at the bottom right, or click showpoint to pop up the image to image gcplist window, and select the point you want to delete.

5) After point selection, save the point: ground control points->file->save gcp as ASCII.

6) Next, perform correction: select in the ground control points. dialog box: options->warpfile, select the image you want to correct in the input warp image that appears, click ok to enter the registrationparameters dialog box: select the resampling method (resampling), For (bilinear).

The specific method of splicing is as follows:

1) Open ArcToolbox-Data Management Tools-Raster-Mosaic, Input Rasters is the input layer.

2) Target Raster is the output layer.

3) Mosaic Method (optional), used to judge the color of the overlapping part in the result, FIRST - the overlapping part is consistent with the upper layer; LAST - the overlapping part is consistent with the lower layer; BLEND - two The mixed color of the layer MEAN - the average value of the two layers; MINIMUM - remove the small value from the two layers; MAXIMUM - take the large value from the two layers.

4) Mosaic Color map Mode (optional), set to the default value.

5) Ignore Background Value (optional), set to the default value.

6) Nodata Value (optional). Treat NoData as what value, for example, if we write 0, then Nodata will be treated as black, and it will be transparent if it is empty.

Convert 1bit data to 8bit(optional), set as default.

Mosaicking Tolerance (optional), set to default.

The specific method of band fusion is as follows:

1) Decompress the downloaded landsat OLI image, find the corresponding image data under the folder in the catalog directory, and load the B3, B4, B5, and B8 bands into ArcMap:

2) Open ArcToolbox, find Data management Tools (data management tools)—>Raster (raster)—>Raster Processing (raster processing)—>Composite Bands (band fusion), double-click to open, and select the drop-down button of the input Rasters box , add the B5, B4, and B3 bands in sequence for fusion, and the default output position of the output raster is:

3) Click OK to get the fused image:

4) Finally select the save path.

After the image data is processed, the cutting method is used for image interpretation, and the interpretation results are jointly corrected through the time series change trajectory to ensure that the real situation of land use status is correctly expressed, which can effectively avoid the current remote sensing interpretation process. Precision issues that arise, as well as redundant and erroneous patches when performing change analysis on time series data.

When obtaining land use types, remote sensing interpretation is required. There are many methods of remote sensing interpretation, we use the cutting method. If all remote sensing images are visually interpreted, the workload will be greatly increased and the error will also increase accordingly. Interpretation, you can simply and quickly obtain the required land use data.

According to the contribution value of each land use type to the ecological risk, different land use types are assigned, and the color of each assignment is different in the image, combined with the terrain, and then the data is reclassified.

In the step S3, the image data after interpretation is combined with the assignment of the land use type to convert the data format;

For text data combined with the assignment of land use types, manually or automatically input to the system.

Based on the directly input data or the converted image data, establish a time-series and dynamic change track map of the ecological pattern with multiple time nodes;

Through data processing, unreasonable, misclassified, small and meaningless trajectories are removed, and representative change trajectories are retained.

A loss risk identification system for ecological land, including a data collection module, a data processing module, a remote sensing interpretation module, a data conversion module, and a change track analysis module;

The data collection module is used to collect data, which is divided into manual input or automatic input;

The data processing module is used to perform geometric correction, splicing, and band fusion processing on the image information;

The remote sensing interpretation module uses a segmentation method to interpret the processed information;

The data conversion module is used for performing data conversion on the interpreted result;

The change track analysis module combines land use type assignment and converted data reclassification to output a change track analysis model.

It also includes a joint correction module and a risk identification module;

The joint correction module performs joint correction on the interpreted results through the time series change trajectory to ensure that the real situation of land use status is correctly expressed, and can effectively avoid the accuracy problems that occur in the current remote sensing interpretation process, and the time series data Redundant and erroneous patches when performing change analysis;

After assigning values to each land use type, the risk identification module outputs the ecological risk distribution map of each time node through the change trajectory analysis model, and then calculates the ecological risk data with time series through the grid calculation model to identify the ecological land loss risk.

Specific examples are as follows:

As shown in Figure 2, when identifying the risk of ecological land loss in the Beijing-Tianjin-Hebei region from 1984 to 2015, the preprocessed land use data was first analyzed for change trajectory, and the land use types were classified according to the land use cover classification system of the Chinese Academy of Sciences. For forest land, grassland, water area, cultivated land, artificial surface, other land use and sea area, the codes are 1, 2, 3, 4, 5, 6, and 7 respectively. According to the results of the primary classification of land cover in the study area, the trajectory map of the dynamic change trajectory of the ecological pattern at six time nodes was obtained through reclassification and grid calculation methods. Then through data processing, unreasonable, misclassified, small and meaningless trajectories are removed, and representative change trajectories are retained. Among them, the colors represented by each land use type in Figure 2 are also different.

Then combined with the change trajectory analysis method to identify the risk of land loss. As shown in Figure 3, by assigning values to each land use type according to the contribution of land use type to ecological risk, the distribution of land use ecological risk in each period is obtained. In the Beijing-Tianjin-Hebei region, there are 7 types of land use: forest land, grassland, water area, cultivated land, artificial surface, other land and sea area. After reclassification, they are: forest land (1), water area (2), grassland (3), Cultivated land (4), other land use (5), artificial surface (6). The land loss in the time series process is represented by change codes, such as 11112, 44441, etc., 11112 indicates that the land use type at the first four time points is forest land, and the land use type at the last time point is grassland, so 11112 indicates that forest land has changed to grassland , the woodland is lost, and the risk of ecological loss increases; 33366 indicates that the land use type of the first three time nodes is water, and the land use type of the next two time nodes is artificial surface, so 33366 indicates that the water area has changed into an artificial surface, and the water area has been lost Phenomenon, ecological risk increases. In Figure 3, as the land use type changes, the colors shown on the map will also change.

As shown in Figure 4, according to the land use ecological risk analysis, the benign and malignant areas of ecological risk changes can be further analyzed. When plotted in Figure 4, benign is represented in green and malignant is represented in red.

The above descriptions are only preferred embodiments of the present invention, and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of the present invention. within the scope of protection.

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.