CN113392376B - Landscape space adjacency measuring method combining land utilization data - Google Patents

Landscape space adjacency measuring method combining land utilization data Download PDF

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CN113392376B
CN113392376B CN202110656650.1A CN202110656650A CN113392376B CN 113392376 B CN113392376 B CN 113392376B CN 202110656650 A CN202110656650 A CN 202110656650A CN 113392376 B CN113392376 B CN 113392376B
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吝涛
林美霞
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Abstract

The invention relates to a landscape space adjacency measuring method combining land utilization data, which divides different land utilization types into target landscape and non-target landscape by combining specific ecological process and research requirements, reasonably constructs geographical units, judges the landscape space adjacency relation between the target landscape and the non-target landscape in the geographical units by utilizing a space analysis technology, further extracts landscape space adjacency information between different types of non-target landscape and target landscape, and finally calculates landscape adjacency on type level and landscape level, thereby realizing the quantitative research of landscape space adjacency relation and more comprehensively reflecting landscape space pattern characteristics.

Description

Landscape space adjacency measuring method combining land utilization data
Technical Field
The invention relates to the technical field of landscape ecology, urban geography, geographic information technology and remote sensing technology intersection, in particular to a landscape space adjacency measuring method combining land utilization data.
Background
Landscape spatial pattern, landscape function and landscape dynamics are the core contents of landscape ecology research, wherein quantitative analysis of landscape pattern is the basis of researching the mutual relationship between pattern and process, and is also the key to researching landscape dynamics and landscape function. The landscape index is an important mode for developing quantitative research on landscape patterns. Existing landscape indexes can be roughly divided into indexes describing landscape elements and indexes describing overall features of landscape, which reflect partial features of landscape spatial patterns from different angles. The landscape is formed by inlaying different types of landscape plaques, and the spatial mosaic structure determines that the different types of plaques have certain spatial adjacency relation, wherein the most direct expression is the boundary adjacency relation between the plaques, namely whether a common edge exists between the two types of heterogeneous plaques. The method is characterized in that a boundary adjacency index is provided by a scholars based on a spatial adjacency concept, the dominant idea is to calculate the proportion of the total length of a target plaque boundary occupied by the common boundary of a certain target plaque and a plurality of heterogeneous plaques adjacent to the target plaque and the target plaque, the index describes the spatial adjacency relation between the target plaque and other different types of plaques from the plaque level and the type level, and belongs to the index for describing landscape elements. However, the above boundary adjacency index has the following disadvantages: firstly, the index only describes the spatial adjacent characteristics on the landscape element level and cannot reflect the spatial adjacent characteristics of the landscape whole body; secondly, the index only reflects the length of the adjacent edge and does not consider the number characteristic of the adjacent spots; thirdly, the landscape space adjacency characteristics have asymmetry characteristics, namely the space adjacency of the landscape type A to the landscape type B is not equal to the space adjacency of the landscape type B to the landscape type A, and the index only considers the boundary adjacency characteristics of the landscape type A to the landscape type B and does not consider the influence of the space heterogeneity (including the number and the perimeter of adjacent landscape blocks) of the adjacent landscape on the regional landscape space adjacency characteristics.
Disclosure of Invention
The invention aims to provide a landscape space adjacency measuring method combining land use data so as to solve the problems. Therefore, the invention adopts the following specific technical scheme:
a method of landscape space adjacency measure incorporating land use data may include the steps of:
step 1: setting target landscapes and non-target landscapes, preprocessing and reclassifying the land utilization data, determining the types of landscapes in the research area, and setting one of the target landscapes and the rest of the non-target landscapes by combining a specific ecological process;
and 2, step: constructing a geographic unit, selecting a research scale according to research requirements, and dividing a research area into a plurality of regular or irregular geographic units;
and 3, step 3: judging a spatial adjacency relation, carrying out spatial superposition on the geographic units and the land utilization data, and analyzing whether common edges exist among different types of landscape patches in the geographic units one by using a spatial analysis technology so as to judge whether a spatial adjacency relation exists between a target landscape and a non-target landscape;
and 4, step 4: extracting landscape spatial adjacency information, according to the step 3, if the target landscape and the non-target landscape have a common edge in the same geographic unit, further judging the spatial adjacency type of the target landscape patch and the non-target landscape patch, and counting the number of adjacent patches and the circumference of the adjacent edges of the non-target landscape and the target landscape of different types in the geographic unit, and the number of non-target landscape patches and the total circumference of the patches;
and 5: calculating a landscape adjacency index on the type level, which is represented by the formula:
Figure GDA0003292235300000021
to calculate; wherein CV isiThe feature adjacency index is the feature adjacency index on the type level of the ith type of non-target feature, and m is the number of space adjacency patches of the ith type of non-target feature and the target feature; k is the total number of the ith type of non-target landscape plaques; lijThe spatial adjacent length of the jth plaque of the ith type of non-target landscape and the target landscape; l isigThe g-th plaque perimeter of the i-th non-target landscape;
step 6: calculating a landscape adjacency index on the landscape level, which is expressed by the formula:
Figure GDA0003292235300000031
to calculate; where LV is the landscape adjacency index at landscape level, n is the number of non-target landscape types within a geographic cell, CViThe result is calculated for the landscape adjacency index at the type level of step 5.
Further, the geographic unit in step 2 is a square grid, a natural drainage basin unit or an administrative unit.
Further, the spatial adjacent relation in the step 3 comprises three conditions of edge sharing, corner sharing and surface separation of the target landscape and the non-target landscape, and a common edge exists between the target landscape and the non-target landscape when and only when the spatial adjacent relation of the target landscape and the non-target landscape is edge sharing.
Further, in the step 4, if and only if the adjacent relation between the target landscape and the non-target landscape space is edge sharing, the length of the adjacent edge and the number of the adjacent spots are larger than zero; when the adjacent relation of the target landscape and the non-target landscape is corner sharing or surface separation, the length of the adjacent edge and the number of the adjacent patches are equal to zero.
By adopting the technical scheme, the invention has the beneficial effects that: the invention makes up the deficiency of the current landscape index on adjacency research, realizes scientific quantitative measurement of landscape space adjacency relation on type level and landscape level, and intuitively reveals the space adjacency rule of landscape space pattern.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of a landscape space adjacency measurement method incorporating land-use data of the present invention;
FIG. 2 is a graph comparing the landscape adjacency of different types of natural landscapes in various cities;
figure 3 is a landscape adjacency comparison histogram for each city complex.
Detailed Description
To further illustrate the various embodiments, the invention provides the accompanying drawings. The accompanying drawings, which are incorporated in and constitute a part of this disclosure, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the embodiments. Those skilled in the art will appreciate still other possible embodiments and advantages of the present invention with reference to these figures. The components in the drawings are not necessarily to scale, and similar reference numerals are generally used to identify similar components.
The invention will now be further described with reference to the drawings and the detailed description.
As shown in fig. 1, the method for measuring the adjacency of landscape space by combining land use data mainly comprises the following steps:
step 1: and setting target landscape and non-target landscape. The land utilization data is preprocessed and reclassified, the types of landscapes in the research area are determined, one of the landscapes is set as a target landscape in combination with a specific ecological process, and the rest of the landscapes are set as non-target landscapes. Taking a long triangular city group (26 cities) as an example, the land utilization data of the 26 cities are preprocessed and reclassified, and the land utilization types are reclassified into seven types of city landscape, forest land landscape, grassland landscape, water area landscape, arable land landscape, wetland landscape, bare land landscape and the like according to the characteristics of the ecological system of the long triangular city group. In order to research the ecological stress on an ecological system caused by urban space expansion, the urban landscape is set as a target landscape, and the rest landscapes are set as non-target landscapes. The land use data may be interpreted from remote sensing satellite imagery. It should be understood that the landscape types are not limited to the above, and may also include finer classifications of deserts, swamps, paddy fields, dry lands, frozen soil, etc. for different research areas.
And 2, step: a geographic unit is constructed. According to research requirements, a research scale is selected, and a research area is divided into a plurality of regular or irregular geographic units. The geographic units can be regular square grids, irregular natural watershed units or administrative units and the like. The square grid may be divided in a size of 1 km by 1 km. In this embodiment, the research area is divided into 26 city units according to the city administrative boundary.
And step 3: and judging the spatial adjacency relation. And (3) carrying out spatial superposition on the city units obtained in the step (2) and the land utilization data obtained in the step (1), and analyzing whether common edges exist among different types of landscape patches in the city units one by using a spatial analysis technology so as to determine whether a spatial adjacency relation exists between the target landscape and the non-target landscape. Spatial analysis techniques are well known and will not be described in detail herein. The spatial adjacency relationship may include three cases of edge sharing, corner sharing, and face separation of the target landscape and the non-target landscape, and a common edge exists between the target landscape and the non-target landscape if and only if the spatial adjacency relationship is edge sharing.
And 4, step 4: and extracting landscape space adjacency information. According to the step 3, if the target landscape and the non-target landscape have a common edge in the same geographic unit, further judging the spatial adjacent type of the target landscape patch and the non-target landscape patch, and counting the adjacent patch number, the adjacent edge perimeter, the non-target landscape patch number and the total patch perimeter of the non-target landscape and the target landscape of different types in the geographic unit. If and only if the adjacent relation of the target landscape and the non-target landscape is edge sharing, the length of the adjacent edge and the number of the adjacent patches are larger than zero; when the adjacent relation of the target landscape and the non-target landscape is corner sharing or surface separation, the length of the adjacent edge and the number of the adjacent patches are equal to zero. The spatial adjacent type of the target landscape plaque and the non-target landscape plaque may include a city-forest land adjacent type, a city-grass land adjacent type, a city-water area adjacent type, a city-land adjacent type, a city-wet land adjacent type, a city-bare land adjacent type, and the like.
And 5: a landscape adjacency index on the type level is calculated. The index is represented by the formula:
Figure GDA0003292235300000051
to calculate; wherein, CV isiThe scene adjacency index on the type level of the ith type of non-target scene is shown, and m is the number of space adjacency patches of the ith type of non-target scene and the target scene; k is the total number of the ith non-target landscape plaques; l. theijThe spatial adjacent length of the jth plaque of the ith type of non-target landscape and the target landscape; l is a radical of an alcoholigIs the g-th plaque perimeter of the i-th non-target landscape. Therefore, the landscape adjacency on the type level simultaneously considers the adjacent edge length and the adjacent patch number difference of the non-target landscape and the target landscape.
Step 6: and calculating the landscape adjacency index on the landscape level. The index is represented by the formula:
Figure GDA0003292235300000061
to calculate; wherein LV is landscape adjacency index at landscape level, n is the number of non-target landscape types in the city unit, CViThe result is calculated for the landscape adjacency index at the type level of step 5. Thus, landscape adjacency at the landscape level takes into account the difference in the number of types of views within different geographic units.
The calculation results of the landscape adjacency indexes at the type level and the landscape level for the long triangular urban groups studied in this example are shown in table 1 below.
TABLE 1 landscape adjacency index at each City type level and landscape level
Figure GDA0003292235300000062
Figure GDA0003292235300000071
Further, by plotting the results of the adjacency index calculation in table 1 in the form of a line graph and a bar graph, the difference in the landscape adjacency at the 26-city type level and the landscape level of the long triangle city group was compared, and the specific results are shown in fig. 2 and 3. The result shows that the spatial adjacency of the urban landscape and the arable land landscape of the long triangular city group of 26 cities is greater than the spatial adjacency of the urban landscape and the other five types of landscapes, and the landscape spatial adjacency index on the landscape level of the salt city is the highest among the 26 cities.
In summary, the landscape spatial adjacency measuring method provided by the invention divides different land utilization types into the target landscape and the non-target landscape by combining specific ecological processes and research requirements, reasonably constructs the geographic unit, judges the landscape spatial adjacency relation between the target landscape and the non-target landscape in the geographic unit by using the spatial analysis technology, further extracts the landscape spatial adjacency information between the non-target landscape and the target landscape of different types, and finally calculates the landscape adjacency on the type level and the landscape level, thereby realizing the quantitative research of the landscape spatial adjacency relation and more comprehensively reflecting the landscape spatial pattern characteristics. The specific embodiment provided by the invention also shows that when the specific ecological process of urban space expansion is combined, the landscape space adjacency measure based on the land utilization data can reflect the difference of the space adjacency degree of the urban landscape and the natural landscapes of different types in the same urban unit, and can compare the influence of the urban space expansion between different urban units on the space adjacency relation of the natural landscapes.
While the invention has been particularly shown and described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (4)

1. A landscape space adjacency measuring method combining land utilization data is characterized by comprising the following steps:
step 1: setting target landscapes and non-target landscapes, carrying out pretreatment and reclassification on land utilization data, determining the types of landscapes in a research area, and setting one of the landscapes as a target landscape and the other landscapes as non-target landscapes by combining a specific ecological process;
step 2: constructing a geographic unit, selecting a research scale according to research requirements, and dividing a research area into a plurality of regular or irregular geographic units;
and 3, step 3: judging a spatial adjacency relation, carrying out spatial superposition on the geographic unit and the land utilization data, and analyzing whether common edges exist among different types of landscape patches in the geographic unit one by using a spatial analysis technology so as to judge whether a spatial adjacency relation exists between a target landscape and a non-target landscape;
and 4, step 4: extracting landscape spatial adjacency information, according to the step 3, if the target landscape and the non-target landscape have a common edge in the same geographic unit, further judging the spatial adjacency type of the target landscape patch and the non-target landscape patch, and counting the number of adjacent patches and the circumference of the adjacent edges of the non-target landscape and the target landscape of different types in the geographic unit, and the number of non-target landscape patches and the total circumference of the patches;
and 5: calculating a landscape adjacency index at the type level, the index being represented by the formula:
Figure FDA0003292235290000011
to calculate; wherein, CV isiThe scene adjacency index on the type level of the ith type of non-target scene is shown, and m is the number of space adjacency patches of the ith type of non-target scene and the target scene; k is the total number of the ith type of non-target landscape plaques; l. theijThe spatial adjacent length of the jth plaque of the ith type of non-target landscape and the target landscape; l isigIs the g-th plaque perimeter of the i-th class of non-target landscape;
and 6: calculating a landscape adjacency index on the landscape level, which is expressed by the formula:
Figure FDA0003292235290000021
to calculate; where LV is the landscape adjacency index at the landscape level, n is the number of non-target landscape types within a geographic cell, CViThe result is calculated for the landscape adjacency index at the type level of step 5.
2. The method of claim 1, wherein the geographic cells in step 2 are square grids, natural watershed cells, or administrative cells.
3. The method of claim 1, wherein the spatial adjacency in step 3 includes three cases of edge sharing, corner sharing, and face separation of the target landscape and the non-target landscape, and a common edge exists between the target landscape and the non-target landscape if and only if the spatial adjacency is edge sharing.
4. The method of claim 3, wherein in step 4 the adjacent edge length and the number of adjacent patches are greater than zero if and only if the target landscape and non-target landscape spatial adjacent relationship is edge-shared; when the adjacent relation of the target landscape and the non-target landscape is corner sharing or face separation, the length of the adjacent edge and the number of the adjacent spots are equal to zero.
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