CN116303861B - Drawing method and device for submarine habitat - Google Patents
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Abstract
The invention provides a method and a device for drawing a submarine habitat, comprising the following steps: dividing the submarine habitat to obtain a classification mode of a plurality of layers; acquiring single-element data associated with the distribution of the benthonic habitat; converting the single-element data into face vector data; carrying out semantic conversion and ecological classification on the single-element data to obtain classified data; carrying out standardized coding on the single-element data, and carrying out space superposition according to a classification mode of a plurality of layers to obtain a distribution map layer and a standard name of the submarine habitat; the classification mode of single elements and the submarine habitat is constructed, the types of the submarine habitat are determined, the drawing technology of the submarine habitat is perfected, and the biodiversity protection is guided.
Description
Technical Field
The invention relates to the technical field of marine ecological environment, in particular to a method and a device for drawing a submarine habitat.
Background
The seafloor habitat mapping refers to a process of integrating information such as marine organisms and environments, assisting in remote sensing technology and space analysis means, and interpreting and converting collected data into an ecologically meaningful map. At present, habitat mapping has become an internationally universal ecosystem management tool, is widely applied in the United states, europe and the like, and becomes an essential basic work for ocean management and research.
Currently, the more widely used European benthonic habitat mainly comprises 5 levels, the first level being divided according to the substrate and the biological zone, wherein the biological zone refers to the area where light can reach the seafloor; the second level adds ecoregion information, such as atlantic; adding biological community information such as mussel and barnacle community to the third level; a fourth level adds a sub-population habitat, such as the genus xiaotenus; the fifth level adds other variables such as the symbiotic species Lichina pygmaea.
In the aspect of the graphics making method, europe mainly adopts the following technical scheme: firstly, processing an environment layer related to each habitat into a grid layer; secondly, converting the map into a vector map layer, and then superposing the vector map layers to form a total perch map layer; finally, comparing with the habitat classification comparison table, adding the habitat number to form a classification map.
The scheme integrates biological environment information such as biological belts, substrate types, biological communities and the like, builds a five-level submarine habitat classification system, and builds a drawing technology frame. However, due to the difference between Europe and the natural geographical environment of the sea area of China, certain limitation exists in the practical application of China.
Firstly, the arrangement of the biological belt is difficult to be suitable for the practice of shallow water depth in the coastal sea area of China. The water depth of European sea is relatively deep, the first level is formed by stacking substrates with biological bands, and the biological bands refer to the maximum depth of light reaching the seabed and can reach 20-30 m generally. In China, the coastal areas of China are basically located on the continental shelf, have wide beach resources, particularly coastal zone areas, are concentrated distribution areas of mangrove forests, salt marsh, natural coasts and other various ecosystems, are divided at 20-30 m, have low ecological characteristic differentiation degree, and are difficult to highlight rich coastal zone typical ecosystems of China.
Secondly, the arrangement of the ecological area is to be optimized. Although the arrangement of the ecological area can rapidly judge the biological geographical scene where the habitat is located, the number of the habitat types is doubled, and certain types are not obviously different in practice, so that the scientificity is poor, such as the muddy coast of the Bohai yellow sea ecological area and the muddy coast of the east sea ecological area, and the difference between the two types is difficult to be described.
Disclosure of Invention
In view of the above, the present invention aims to provide a method and a device for drawing a submarine habitat, construct a submarine habitat classification mode, determine the types of the submarine habitat, and perfect the drawing technology of the submarine habitat.
In a first aspect, embodiments of the present invention provide a method of mapping a benthonic habitat, the method comprising:
dividing the submarine habitat to obtain a classification mode of a plurality of layers;
acquiring single-element data associated with the seafloor habitat distribution;
converting the single-element data into face vector data;
carrying out semantic conversion and ecological classification on the single-element data to obtain classified data;
and carrying out standardized coding on the single-element data, and carrying out space superposition according to the classification modes of the multiple layers to obtain a distribution map layer and a standard name of the submarine habitat.
Further, the classification method for dividing the submarine habitat to obtain a plurality of layers comprises the following steps:
the first level includes substrate type, coast/seafloor tidal data;
a second hierarchy, based on the first hierarchy, overlays biological classes/subclasses;
a third level refines the biological class/subclass to a specific biological group/community based on the second level;
and the fourth level is based on the third level and supplements the landform type, the water temperature at the bottom layer, the salinity, the dissolved oxygen, the ocean current and the transparency.
Further, converting the single-element data into face vector data includes:
when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
converting the raster data into the face vector data.
Further, the single-element data includes tidal data, substrate type, substrate water temperature, substrate salinity, substrate dissolved oxygen, substrate ocean current flow rate and transparency, benthonic animals, mangrove, seaweed beds, coral reefs, seaweed farms, mollusk reefs and salt marsh.
Further, performing semantic conversion and ecological classification on the single-element data to obtain classified data, including:
carrying out ecological classification on the water body element data according to the relation between the water body environment and the biological growth, and obtaining classified water body element data by adopting a reclassification method;
carrying out semantic conversion and ecological classification on the substrate type data according to the sizes of the constituent substances and particles to obtain classified substrate type data;
carrying out semantic conversion and ecological classification on the landform type data according to the cause type, the morphological structure and the power process to obtain classified landform type data;
and carrying out semantic conversion and ecological classification on the biological type data according to the classification order elements and the life habits to obtain classified biological type data.
Further, the single-element data is subjected to standardized coding, and spatial superposition is performed according to a classification mode of the multiple layers, so that a distribution map layer and a standard name of the submarine habitat are obtained, and the method comprises the following steps:
determining classification attribute codes of each layer corresponding to the data subjected to the hierarchical classification;
combining the layers by using a combination tool to obtain a superimposed layer, wherein the superimposed layer is used for representing the distribution of the submarine habitat;
integrating the classification attribute codes of each layer by using python sentences to obtain standard codes of the submarine habitat;
and sorting the standard codes of each submarine habitat to obtain the standard name of each submarine habitat.
In a second aspect, embodiments of the present invention provide a mapping apparatus for a benthonic habitat, the apparatus comprising:
the habitat classification module is used for dividing the submarine habitat to obtain classification modes of a plurality of levels;
the single-element data acquisition module is used for acquiring single-element data associated with the submarine habitat distribution;
the conversion module is used for converting the single-element data into face vector data;
the classification module is used for carrying out semantic conversion and ecological classification on the single-element data to obtain classified data;
and the habitat drawing module is used for carrying out standardized coding on the single-element data, and carrying out space superposition according to the classification modes of the multiple layers to obtain a distribution map layer and a standard name of the submarine habitat.
Further, the conversion module is specifically configured to:
when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
converting the raster data into the face vector data.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory, and a processor, where the memory stores a computer program executable on the processor, and where the processor implements a method as described above when executing the computer program.
In a fourth aspect, embodiments of the present invention provide a computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method as described above.
The embodiment of the invention provides a method and a device for drawing a benthonic habitat, comprising the following steps: dividing the submarine habitat to obtain a classification mode of a plurality of layers; acquiring single-element data associated with the distribution of the benthonic habitat; converting the single-element data into face vector data; carrying out semantic conversion and ecological classification on the single-element data to obtain classified data; carrying out standardized coding on the single-element data, and carrying out space superposition according to a classification mode of a plurality of layers to obtain a distribution map layer and a standard name of the submarine habitat; a classification scheme of the submarine habitat is constructed, the types of the submarine habitat are determined, and the drawing technology of the submarine habitat is perfected.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
In order to make the above objects, features and advantages of the present invention more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for mapping a benthonic habitat according to an embodiment of the present invention;
FIG. 2 is a schematic drawing of a benthonic habitat provided in accordance with an embodiment of the present invention;
fig. 3 is a schematic diagram of a mapping apparatus for a submarine habitat according to a second embodiment of the present invention.
Icon:
1-a habitat classification module; 2-a single-element data acquisition module; a 3-conversion module; 4-a classification module; 5-habitat mapping module.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to facilitate understanding of the present embodiment, the following describes embodiments of the present invention in detail.
Embodiment one:
fig. 1 is a flowchart of a method for mapping a benthonic habitat according to an embodiment of the present invention.
Referring to fig. 1, the method includes the steps of:
step S101, dividing the submarine habitat to obtain a classification mode of a plurality of layers;
step S102, acquiring single-element data related to the distribution of the benthonic habitat;
step S103, converting the single-element data into face vector data;
step S104, carrying out semantic conversion and ecological classification on the single-element data to obtain classified data; wherein, the classified data has ecological significance;
and step S105, carrying out standardized coding on the single-element data, and carrying out space superposition according to a classification mode of a plurality of layers to obtain a distribution map layer and a standard name of the submarine habitat.
Specifically, the application reflects the characteristics of species and spatial distribution of the submarine habitat formed by interaction of various ecological components such as topography, substrate, organisms and water, promotes scientific understanding of a marine ecological system, and also provides ecological base map and scientific reference for developing marine organism diversity protection, implementing marine ecological protection restoration and the like.
Dividing the submarine habitat to obtain a classification mode of a plurality of layers; wherein the plurality of levels may be four levels, referring to the benthic list structure and examples as shown in table 1; the first level includes substrate type, coast/seafloor tidal data; the second level is based on the first level, and the biological class/subclass is overlapped, wherein the biological class/subclass comprises benthonic animals, mangroves, seaweed beds, coral reefs, seaweed fields, mollusk reefs and salt biogas; the third level refines the biological class to specific biological groups/communities based on the second level; and the fourth level is based on the third level and supplements environmental information such as landform type, bottom water temperature, salinity, dissolved oxygen, ocean current, transparency and the like.
TABLE 1
The main technical route of the submarine habitat map is shown with reference to fig. 2. Firstly, processing single-element data, wherein the single-element data comprises tidal data, landform type, substrate type, temperature, salinity, dissolved oxygen, ocean current flow rate, transparency and other data, and carrying out semantic conversion and ecological classification; and then carrying out standardized coding on the single-element data, and carrying out space superposition according to a submarine habitat classification scheme to obtain a submarine habitat distribution map layer and a standard name.
Further, step S103 includes the steps of:
step S201, when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
step S202, converting raster data into face vector data.
Further, the single-element data includes environmental data such as tidal data, substrate type, substrate water temperature, substrate salinity, substrate dissolved oxygen, substrate ocean current flow rate and transparency, and biological data such as benthonic animals, mangroves, seaweed beds, coral reefs, seaweed fields, mollusk reefs and salt marsh.
When the type of the single-element data is point vector data, the point vector data is used for obtaining raster data by a spatial interpolation algorithm. The spatial interpolation algorithm is an important means for displaying the continuous distribution condition of biological indexes in a region, and common spatial interpolation algorithms mainly comprise a kriging method, an inverse distance weight method, a spline function containing obstacles, a trend surface method and the like.
The inverse distance weighting method is a deterministic interpolation method, and the attribute values of unknown points are estimated by taking the distance between the unknown points and the known points as the weight to carry out weighted average through linear combination of the attribute values of the known data sets.
The trend surface method is based on a known data set in the whole area, and a polynomial equation is used to estimate the attribute value of the unknown point.
The kriging method is a geostatistical method, takes the stability of spatial data as a premise, fully considers the spatial distribution of a known data set and the spatial azimuth relation of unknown points on the basis of distance, and estimates the attribute value of the unknown points.
It is generally necessary to select a suitable method according to the characteristics and spatial characteristics of the data itself, and a cross-validation method may be used to compare the differences between the estimated values and the actual values of different interpolation methods. The kriging method is usually preferred to fully consider the spatial structural characteristics of regional variables, but in special cases, when the randomness of each station is strong, the difference is large and the spatial autocorrelation is lacking, the inverse distance weighting method is suggested to be adopted so as to highlight the local characteristics of the small-scale region.
Further, step S104 includes:
step S301, ecologically classifying the water body element data according to the relationship between the water body environment and the biological growth, and obtaining classified water body element data by adopting a reclassification method;
step S302, performing semantic conversion and ecological classification on the substrate type data according to the sizes of the constituent substances and particles to obtain classified substrate type data;
step S303, carrying out semantic conversion and ecological classification on the landform type data according to the cause type, the morphological structure and the power process to obtain classified landform type data.
Step S304, carrying out semantic conversion and ecological classification on the biological type data according to the classification order elements and the life habits, and obtaining classified biological type data.
The classification criteria of the water body element data are shown in table 2, and the data can be increased or decreased as appropriate.
TABLE 2
The substrate type data is based on the marine field investigation record to judge the main components of the substrate, and determine which of land source materials, biological source materials and artificial source materials in the substrate components has the largest proportion.
(1) The components are mainly land-source substances, the percentage contents of gravel, sand, silt and clay particle fractions are calculated based on granularity analysis data, screening is carried out according to whether the gravel content in sediment substrates is more than or equal to 0.01%, when the gravel content is more than or equal to 0.01%, the classification and subdivision are carried out according to a gravel-containing sediment triangular diagram in a Folk (1970) scheme, and when the gravel content is less than 0.01%, the classification and subdivision are carried out according to a gravel-free sediment triangular diagram in the Folk (1970) scheme, and finally the corresponding substrate type is obtained.
(2) The components are mainly biological sources, and the main components are identified to be substrate types including coral substrate, shell substrate, soft mud, organic matter, algae substrate and worm substrate, and then further divided according to different classification subdivision methods.
(3) The components are mainly of artificial origin, the main components of the components are identified to be substrate categories, including artificial rock, artificial wood, building materials, metals, garbage and the like, and then further division is carried out according to the particle size of the main components.
The landform type data is based on the overall pattern reflecting the control structure and the geographical environment, and the main elements for representing various landform cause types, landform morphological structures, restricting landform causes and power processes thereof are emphasized as basic contents. The contour shaping, positioning and drawing of the landform are carried out by using the contour lines and the slope directions as the basis of the landform; judging the type of the landform formed by erosion or deposition by combining with geophysical data; the substrate data is used as a reference for the boundary line between the submarine topography cause and the topography type.
The biological type data mainly comprises two layers of biological class/subclass and biological group/community. The biota/subclass mainly comprises benthonic animals, coral reefs, mollusk reefs, seaweed fields, seaweed beds, salt marsh, mangrove and other types. The biological group/community is a description of a combination of characteristic organisms that can be reproduced, principally dominant species or indicator species in the biological class, with specific examples being shown in table 3.
TABLE 3 Table 3
Biological class/subclass | Biological group/community paradigm |
Benthonic animal | Clam seabed and sea urchin seabed |
Coral reef | Branched deer-horn coral reef and lump-shaped platycephalomannia reef |
Mollusc reef | Mussel reef and oyster reef |
Seaweed field | Sargassum community and ulva community |
Seaweed bed | Salicornia tabaci community and acorus gramineus community |
Salt marsh | Spartina alterniflora and reed community |
Mangrove forest | Tinospora root forest and avicennia marina forest |
Further, step S105 includes the steps of:
step S401, determining classification attribute codes of each layer corresponding to the data classified by each layer;
specifically, the first level consists of a substrate type and tidal data, the tidal data is divided into a coast (tidal zone) and a seabed (non-tidal zone), the tidal data are respectively encoded into 1 and 2, and the substrate type is sequentially encoded from 01 to 99; the second hierarchy adds biological classes/subclasses, encoded sequentially from 1 to 9; a third hierarchical increase in biota/community, sequentially encoded from 01 to 99; the fourth level comprises environmental information such as landform type, bottom water temperature, salinity, dissolved oxygen, ocean current, transparency and the like, the water temperature is sequentially encoded from T1 to T9, the salinity is sequentially encoded from S1 to S6, the dissolved oxygen is sequentially encoded from O1 to O6, the ocean current is sequentially encoded from C1 to C4, the transparency is sequentially encoded from L1 to L5, and the landform type is sequentially encoded from G01 to G99.
Step S402, combining all the layers by using a combination tool to obtain a superimposed layer, wherein the superimposed layer is used for representing the distribution of the submarine habitat;
step S403, integrating the classification attribute codes of all the layers by using python sentences to obtain the standard codes of the submarine habitat;
and step S404, sorting the standard codes of each submarine habitat to obtain the standard name of each submarine habitat.
The method constructs a classification mode of single elements and the submarine habitat, provides naming methods of different ecological elements and different levels of the submarine habitat, and can more systematically know the types of the marine ecological elements and the types of the submarine habitat; the technical route for drawing the benthonic habitat is constructed, and the distribution and ecological characteristics of the benthonic habitat can be more finely and thoroughly depicted. The first level of the submarine habitat is tidal data and substrate types, so that the problems that the offshore division of the European submarine habitat is rough and the typical ecosystem of a coastal zone is difficult to embody are solved; the ecological area level is cancelled, and the problem that the same ecological characteristics of different ecological areas are difficult to describe and the scientificity is poor is avoided.
Embodiment two:
fig. 3 is a schematic diagram of a mapping apparatus for a submarine habitat according to a second embodiment of the present invention.
Referring to fig. 3, the apparatus includes:
the habitat classification module 1 is used for dividing the submarine habitat to obtain classification modes of a plurality of levels;
a single-element data acquisition module 2 for acquiring single-element data associated with a submarine habitat distribution;
a conversion module 3 for converting the single-element data into face vector data;
the classification module 4 is used for carrying out semantic conversion and ecological classification on the single-element data to obtain classified data;
and the habitat drawing module 5 is used for carrying out standardized coding on the single-element data, and carrying out space superposition according to a classification mode of a plurality of layers to obtain a distribution map layer and a standard name of the submarine habitat.
Further, the conversion module 3 is specifically configured to:
when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
the raster data is converted into face vector data.
The method builds a division system of the submarine habitat, grasps five typical characteristics of tidal property, substrate type, biological community, landform type and water environment, describes the submarine habitat of the coastal sea area, and can answer the scientific question of how many types of habitat are on the seabed; an ecological drawing method based on a geographic information platform is constructed, each operation step is thinned, a drawing chain of 'environment elements-biological elements-habitat types' is realized, and the scientific problem of 'habitat distribution where' can be answered; the classification mode of the submarine habitat is constructed, the types of the submarine habitat are determined, and the drawing technology of the submarine habitat is perfected.
The embodiment of the invention provides a method and a device for drawing a benthonic habitat, comprising the following steps: dividing the submarine habitat to obtain a classification mode of a plurality of layers; acquiring single-element data associated with the distribution of the benthonic habitat; converting the single-element data into face vector data; carrying out semantic conversion and ecological classification on the single-element data to obtain classified data; carrying out standardized coding on the single-element data, and carrying out space superposition according to a classification mode of a plurality of layers to obtain a distribution map layer and a standard name of the submarine habitat; a classification scheme of the submarine habitat is constructed, the types of the submarine habitat are determined, and the drawing technology of the submarine habitat is perfected.
The embodiment of the invention also provides electronic equipment, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the method for drawing the submarine habitat provided by the embodiment.
The present invention also provides a computer readable medium having non-volatile program code executable by a processor, the computer readable medium having stored thereon a computer program which, when executed by the processor, performs the steps of the method for mapping a benthonic habitat of the above embodiments.
The computer program product provided by the embodiment of the present invention includes a computer readable storage medium storing a program code, where instructions included in the program code may be used to perform the method described in the foregoing method embodiment, and specific implementation may refer to the method embodiment and will not be described herein.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the foregoing method embodiments, which are not described herein again.
In addition, in the description of embodiments of the present invention, unless explicitly stated and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention will be understood in specific cases by those of ordinary skill in the art.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. are based on the directions or positional relationships shown in the drawings, are merely for convenience of describing the present invention and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
Finally, it should be noted that: the above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A method of mapping a benthonic habitat, the method comprising:
dividing the submarine habitat to obtain a classification mode of a plurality of layers;
acquiring single-element data associated with the seafloor habitat distribution;
converting the single-element data into face vector data;
carrying out semantic conversion and ecological classification on the single-element data to obtain classified data;
carrying out standardized coding on the single-element data, and carrying out space superposition according to the classification modes of the multiple layers to obtain a distribution map layer and standard names of the submarine habitat;
carrying out semantic conversion and ecological classification on the single-element data to obtain classified data, wherein the method comprises the following steps:
carrying out ecological classification on the water body element data according to the relation between the water body environment and the biological growth, and obtaining classified water body element data by adopting a reclassification method;
carrying out semantic conversion and ecological classification on the substrate type data according to the sizes of the constituent substances and particles to obtain classified substrate type data;
carrying out semantic conversion and ecological classification on the landform type data according to the cause type, the morphological structure and the power process to obtain classified landform type data;
and carrying out semantic conversion and ecological classification on the biological type data according to the classification order elements and the life habits to obtain classified biological type data.
2. A method of mapping a benthonic habitat as claimed in claim 1, wherein the benthonic habitat is partitioned to provide a plurality of levels of classification comprising:
the first level includes substrate type, coast/seafloor tidal data;
a second hierarchy, based on the first hierarchy, overlays biological classes/subclasses;
a third level refines the biological class/subclass to a specific biological group/community based on the second level;
and the fourth level is based on the third level and supplements the landform type, the water temperature at the bottom layer, the salinity, the dissolved oxygen, the ocean current and the transparency.
3. A method of mapping a benthonic habitat of claim 1, characterized in that converting said single element data into face vector data comprises:
when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
converting the raster data into the face vector data.
4. A method of mapping a benthonic habitat according to claim 1, characterized in that said single element data includes tidal data, substrate type, substrate water temperature, substrate salinity, substrate dissolved oxygen, substrate ocean current flow rate and transparency, as well as benthonic animals, mangroves, seaweed beds, coral reefs, seaweed farms, mollusk reefs and salt-biogas.
5. The method for drawing a benthonic habitat of claim 1, characterized in that the standardized encoding of the single-element data, the spatial superimposition according to the classification of the plurality of levels, the obtaining of a profile layer and a standard name of the benthonic habitat, comprises:
determining classification attribute codes of each layer corresponding to the data subjected to the hierarchical classification;
combining the layers by using a combination tool to obtain a superimposed layer, wherein the superimposed layer is used for representing the distribution of the submarine habitat;
integrating the classification attribute codes of each layer by using python sentences to obtain standard codes of the submarine habitat;
and sorting the standard codes of each submarine habitat to obtain the standard name of each submarine habitat.
6. A mapping apparatus for a benthonic habitat, the apparatus comprising:
the habitat classification module is used for dividing the submarine habitat to obtain classification modes of a plurality of levels;
the single-element data acquisition module is used for acquiring single-element data associated with the submarine habitat distribution;
the conversion module is used for converting the single-element data into face vector data;
the classification module is used for carrying out semantic conversion and ecological classification on the single-element data to obtain classified data;
the habitat drawing module is used for carrying out standardized coding on the single-element data, and carrying out space superposition according to the classification modes of the multiple layers to obtain a distribution map layer and a standard name of the submarine habitat;
the classification module is specifically configured to:
carrying out ecological classification on the water body element data according to the relation between the water body environment and the biological growth, and obtaining classified water body element data by adopting a reclassification method;
carrying out semantic conversion and ecological classification on the substrate type data according to the sizes of the constituent substances and particles to obtain classified substrate type data;
carrying out semantic conversion and ecological classification on the landform type data according to the cause type, the morphological structure and the power process to obtain classified landform type data;
and carrying out semantic conversion and ecological classification on the biological type data according to the classification order elements and the life habits to obtain classified biological type data.
7. A mapping apparatus of a benthonic habitat as claimed in claim 6, characterized in that said conversion module is specifically adapted to:
when the type of the single-element data is point vector data, the point vector data is utilized to obtain raster data by utilizing a spatial interpolation algorithm;
converting the raster data into the face vector data.
8. An electronic device comprising a memory, a processor, the memory having stored thereon a computer program executable on the processor, characterized in that the processor implements the method of any of the preceding claims 1 to 5 when the computer program is executed.
9. A computer readable medium having non-volatile program code executable by a processor, the program code causing the processor to perform the method of any one of claims 1 to 5.
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Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102306169A (en) * | 2011-08-23 | 2012-01-04 | 国家***卫星测绘应用中心 | Digital vector sea and land map fusion method and system |
CN104252665A (en) * | 2014-09-16 | 2014-12-31 | 国家海洋信息中心 | Method and system for managing marine environment monitoring data |
WO2015003496A1 (en) * | 2013-07-08 | 2015-01-15 | 国家***第二海洋研究所 | Method for constructing submarine topography and geomorphology based on fusion of bathymetric data from multiple sources |
CN106204684A (en) * | 2016-07-13 | 2016-12-07 | 国家海洋信息中心 | A kind of marine thematic map automatization preparation method of task based access control stream |
CN106710437A (en) * | 2016-12-26 | 2017-05-24 | 中国矿业大学(北京) | Compilation method and system for electronic map |
CN112948576A (en) * | 2020-12-28 | 2021-06-11 | 国家海洋信息中心 | Marine ecology classification method |
-
2023
- 2023-03-21 CN CN202310281967.0A patent/CN116303861B/en active Active
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN102306169A (en) * | 2011-08-23 | 2012-01-04 | 国家***卫星测绘应用中心 | Digital vector sea and land map fusion method and system |
WO2015003496A1 (en) * | 2013-07-08 | 2015-01-15 | 国家***第二海洋研究所 | Method for constructing submarine topography and geomorphology based on fusion of bathymetric data from multiple sources |
CN104252665A (en) * | 2014-09-16 | 2014-12-31 | 国家海洋信息中心 | Method and system for managing marine environment monitoring data |
CN106204684A (en) * | 2016-07-13 | 2016-12-07 | 国家海洋信息中心 | A kind of marine thematic map automatization preparation method of task based access control stream |
CN106710437A (en) * | 2016-12-26 | 2017-05-24 | 中国矿业大学(北京) | Compilation method and system for electronic map |
CN112948576A (en) * | 2020-12-28 | 2021-06-11 | 国家海洋信息中心 | Marine ecology classification method |
Non-Patent Citations (3)
Title |
---|
Integrating Spatial Multi-criteria Evaluation and Expert Knowledge for GIS-based Habitat Suitability Modeling;Ron Store et al;《Landscape and Urban Planning》;第55卷(第2期);第79-93页 * |
基于GIS的海洋专题要素自动化制图模式研究与实现;樊妙 等;《地理与地理信息科学》;第26卷(第4期);第109-110页 * |
海底地形成图子***MBMap的设计及特点;吴自银 等;《海洋通报》;第21卷(第1期);第69-79页 * |
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