Method and equipment for constructing geographical teaching library based on remote sensing products

Abstract

The present invention relates to the technical field of geography teaching library construction, and specifically to a method and device for constructing a geography teaching library based on remote sensing products, aiming to improve the intuitiveness of teaching content. The geography teaching library of the present invention comprises: a first database and a second database. The geography teaching library construction method comprises: storing teaching courseware in an unstructured first database; storing remote sensing products in a second database according to a preset data structure; performing word segmentation on the content of each teaching courseware in the first database; establishing an association relationship between the teaching courseware and the remote sensing product in the second database based on the word segmentation results of each teaching courseware, and storing the association relationship in the first database. Utilizing the method of the present invention not only enriches teaching resources, but also improves the intuitiveness of teaching content.

Description

Technical Field

[0001] The present invention relates to the technical field of geography teaching library construction, and in particular to a method and device for constructing a geography teaching library based on remote sensing products. Background Art

[0002] The Geography Teaching Library is a comprehensive platform that integrates the collection, organization, storage, sharing and application of geography teaching resources. It is an important part of the informatization of geography education. It aims to improve the quality and efficiency of geography teaching by integrating, managing and sharing geography teaching resources.

[0003] The development of information technology has promoted the informatization of education. However, the current geography teaching library has limited teaching resources, lacks intuitiveness in teaching content, and is difficult to effectively convey complex geographical concepts. Summary of the Invention

[0004] In order to solve the above problems in the prior art, the present invention proposes a method and device for constructing a geographical teaching library based on remote sensing products, which improves the intuitiveness of teaching content.

[0005] In a first aspect of the present invention, a method for constructing a geographical teaching library based on remote sensing products is proposed. The geographical teaching library includes: a first database and a second database; the method includes:

[0006] Storing the teaching courseware in the first unstructured database;

[0007] Storing the remote sensing products in the second database according to a preset data structure;

[0008] Performing word segmentation on the content of each teaching courseware in the first database;

[0009] An association relationship is established between the teaching courseware and the remote sensing products in the second database according to the word segmentation result of each teaching courseware, and the association relationship is stored in the first database.

[0010] Preferably, the step of "establishing an association relationship between the teaching courseware and the remote sensing products in the second database based on the word segmentation results of each teaching courseware, and storing the association relationship in the first database" includes:

[0011] Obtain one or more courseware keywords according to the word segmentation result;

[0012] Matching the teaching courseware with the remote sensing product in the second database according to the courseware keyword, storing the ID and path of the matched remote sensing product in the first database, and establishing an association relationship with the teaching courseware;

[0013] The courseware keywords include: one or more place name keywords, and one or more knowledge type keywords.

[0014] Preferably, the data types of the remote sensing products include:

[0015] Landmark data, used to identify and display important geographical landmarks;

[0016] Zoning data, used to display administrative or geographic division information;

[0017] Three-dimensional data, used to provide a three-dimensional geospatial view;

[0018] Imagery data, used to show surface features and changes;

[0019] Vector data, used to represent the shape and location of geographic features;

[0020] Meteorological data, which reflects climate conditions and weather patterns;

[0021] Road data, used to display transportation network and route information;

[0022] Basemap, which provides a basic view of the geographical environment;

[0023] The annotated base map is formed by adding annotation information to the basic base map and is used to locate and identify geographic elements.

[0024] Preferably, the step of "matching the teaching courseware with the remote sensing product in the second database according to the courseware keyword, storing the ID and path of the matched remote sensing product in the first database, and establishing an association relationship with the teaching courseware" includes:

[0025] Perform fuzzy matching on each of the place name keywords with the landmark name and landmark keyword in the landmark data to obtain a landmark dataset; the landmark data includes: the landmark name, the center longitude and latitude coordinates and the landmark keyword;

[0026] Traversing the landmark dataset to obtain a set of center longitude and latitude coordinates;

[0027] Matching each of the obtained center longitude and latitude coordinates with the spatial range in the division data to obtain an administrative division dataset; the division data includes: an administrative division name and the spatial range;

[0028] Respectively acquiring data from the three-dimensional data, the image data, the vector data, the meteorological data, and the road data whose geographical location belongs to the spatial range in the administrative division dataset and whose data type fuzzy matches the knowledge type keyword, to form a three-dimensional dataset, an image dataset, a vector dataset, a meteorological dataset, and a road dataset;

[0029] Perform fuzzy matching on the knowledge type keywords and the keywords in the basic base map and the annotated base map respectively to obtain a basic base map set and an annotated base map set;

[0030] Obtain the ID and path of each data in the landmark dataset, the administrative division dataset, the three-dimensional dataset, the image dataset, the vector dataset, the meteorological dataset, the road dataset, the basic base map set and the annotated base map set, save them in the first database, and establish an association relationship with the teaching courseware.

[0031] Preferably, the geography teaching database further includes: an unstructured third database;

[0032] The third database stores videos and pictures for geography teaching;

[0033] The method further comprises:

[0034] Matching the courseware keywords with the keywords in the video and picture data to obtain a static data set;

[0035] The ID and path of each data in the static data set are obtained, saved in the first database, and associated with the teaching courseware.

[0036] Preferably, the geography teaching database further comprises: an unstructured fourth database;

[0037] The fourth database stores a plurality of remote sensing information tools;

[0038] The method further comprises:

[0039] matching the remote sensing product with the remote sensing information tool according to the data type of each remote sensing product in the second database, storing the ID and path of the matched remote sensing information tool in the second database, and establishing an association relationship with the remote sensing product;

[0040] Among them, the types of remote sensing information tools include: perspective control tools, positioning and roaming tools, measurement and drawing tools, navigation and compass tools, data analysis and visualization tools, and comparison and fusion tools.

[0041] Preferably, the step of “matching the remote sensing product with the remote sensing information tool according to the data type of each remote sensing product in the second database, storing the ID and path of the matched remote sensing information tool in the second database, and establishing an association relationship with the remote sensing product” includes:

[0042] For each remote sensing product in the second database, determining the data type of the remote sensing product;

[0043] If the data type of the remote sensing product is the three-dimensional data, storing the IDs and paths of the navigation and compass tool and the data analysis and visualization tool in the second database, and establishing an association relationship with the remote sensing product;

[0044] If the data type of the remote sensing product is the image data, storing the IDs and paths of the positioning and roaming tool and the measuring and mapping tool in the second database, and establishing an association relationship with the remote sensing product;

[0045] If the data type of the remote sensing product is the vector data, the meteorological data, or the road data, the IDs and paths of the measurement and mapping tool and the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product;

[0046] If the data type of the remote sensing product is the basic base map, the IDs and paths of the measurement and drawing tool and the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product;

[0047] If the data type of the remote sensing product is the annotated base map, the ID and path of the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product;

[0048] If the data type of the remote sensing product is the zoning data, the ID and path of the viewing angle control tool are stored in the second database, and an association relationship is established with the remote sensing product;

[0049] If the data type of the remote sensing product is the landmark data, the IDs and paths of the viewing angle control tool and the positioning and roaming tool are stored in the second database and associated with the remote sensing product.

[0050] Preferably, the geography teaching library further comprises: a pre-trained classification model;

[0051] The classification model is used to retrieve target courseware in the first database according to the search keyword.

[0052] According to a second aspect of the present invention, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method described above.

[0053] According to a third aspect of the present invention, a computer-readable storage device is provided, storing a computer program that can be loaded by a processor and execute the method described above.

[0054] The present invention has the following beneficial effects:

[0055] The method for constructing a geography teaching library based on remote sensing products proposed in the present invention establishes an association between teaching courseware and remote sensing products, so that remote sensing products can be used to help students understand geographical knowledge more intuitively in geography teaching. It can also provide teachers with convenient and efficient teaching resources, reducing the time and energy teachers spend on preparing teaching materials, allowing them to focus more on teaching itself.

[0056] When matching teaching courseware with remote sensing products, first match them to specific administrative divisions based on landmark keywords, and then further match them based on knowledge type keywords to make the matching results more accurate.

[0057] Videos and images are stored and associated with teaching materials to further enrich teaching resources. This fusion of multi-source data helps students acquire more comprehensive and in-depth geographical knowledge in their studies.

[0058] Store remote sensing information tools and establish an association with teaching courseware, so that remote sensing products can be fully utilized to generate rich and diverse teaching scenarios during the teaching process.

[0059] The classification model facilitates the retrieval of corresponding teaching courseware according to teaching needs, because the teaching courseware is associated with remote sensing products, videos and pictures, and remote sensing information tools. Therefore, after the teaching courseware is retrieved using the classification model, the resources in the geography teaching library constructed by the present invention can be fully utilized to implement teaching. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 1 is a schematic diagram of the main steps of the first embodiment of the method for constructing a geographical teaching library based on remote sensing products of the present invention;

[0061] Figure 2 This is a schematic diagram of the main steps of Example 2 of the method for constructing a geographical teaching library based on remote sensing products of the present invention;

[0062] Figure 3 This is a schematic diagram of the main steps of Example 3 of the method for constructing a geographical teaching library based on remote sensing products of the present invention. DETAILED DESCRIPTION

[0063] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0065] It should be noted that, in the description of the present invention, the terms "first" and "second" are merely for the convenience of description, and do not indicate or imply the relative importance of the devices, elements or parameters, and therefore should not be understood as limiting the present invention. In addition, the term "and / or" in the present invention is merely a description of the corresponding relationship between associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article, unless otherwise specified, generally indicates that the related objects are in an "or" relationship.

[0066] Remote sensing technology boasts a broad field of view, capable of covering the entire globe or large regions. Satellite remote sensing technology can easily acquire geographic data from areas with harsh natural conditions, such as mountains, glaciers, and deserts, where ground-based research is difficult. Therefore, a geography teaching scenario library built using this technology can contain rich geospatial information, encompassing a wide range of terrain, landforms, and climate types, transcending geographical limitations and providing students with a more diverse range of geography learning scenarios.

[0067] Figure 1 This is a schematic diagram of the main steps of the first embodiment of the method for constructing a geographical teaching library based on remote sensing products of the present invention. The geographical teaching library of this embodiment includes: a first database and a second database.

[0068] like Figure 1 As shown, the geography teaching library construction method of this embodiment includes steps A10-A40:

[0069] Step A10: Store the teaching courseware into the unstructured first database.

[0070] In this embodiment, a collection script is created using Python to automatically collect geography teaching resources, such as curriculum standards, courseware, and exercises, from authoritative open educational resources (OER), internal school resources, and established third-party education platforms. Alternatively, a data entry function can be established based on web technology to batch upload digital electronic courseware. A parsing program is then constructed to automatically parse the collected or uploaded teaching resources, establish storage rules, and store them in an unstructured first database.

[0071] In this embodiment, the first database uses the Redis database, and the courseware can be stored in the following format:

[0072] "high_school:geography:xxx" / / Courseware ID

[0073] "chapter_class":"xxx" / / Courseware chapter

[0074] "chapter_title":"xxx" / / Courseware title

[0075] "chapter_conternt":"xxx" / / Course content

[0076] "chapter_img":"xxx" / / Courseware picture

[0077] "chapter_video":"xxx" / / Courseware video

[0078] "chapter_remark":"xxx" / / Courseware description

[0079] "chapter_keyword":"xxx" / / Courseware label

[0080] A specific teaching courseware storage example is as follows:

[0081] HMSET

[0082] "high_school:geography:one"

[0083] "chapter_class" "Earth in the Universe"

[0084] "chapter_title" "History of Earth"

[0085] "chapter_conternt" "Earth's Place in the Universe: On a clear night, looking up at the sky, you can see twinkling stars, nebulae with fuzzy outlines, and planets that appear to be noticeably offset from the starry background. Sometimes, you can also see fleeting meteoroids and comets with long tails. These are all forms of matter in the universe, and they, along with other space exploration methods, can only be detected through astronomical telescopes or other space exploration methods..."

[0086] "chapter_img""http: / / xxx / a.jpg; http: / / xxx / b.jpg"

[0087] "chapter_video""http: / / xxx / a.mp4; http: / / xxx / ab.mp4"

[0088] Step A20: Store the remote sensing product into the second database according to the preset data structure.

[0089] In this embodiment, the second database uses a structured spatial database PostgreSql combined with PostGis, and the preset data structure can be as shown in Table 1 below:

[0090] Table 1 Preset data structure

[0091] name type illustrate name string Data Name id string Data Identification remark string Data Description sort int Service Order browserimg string Thumbnail geometry string Spatial range url string Data Path service string Service Address type string Service Type map_num string Drawing review number centerlong number Central longitude centerlat number Central latitude max_level int Maximum level of service min_level int Minimum level of service keyword string Keywords of data, used for matching classification retrieval, etc.

[0092] In this embodiment, the data types of remote sensing products include: landmark data, zoning data, three-dimensional data, image data, vector data, meteorological data, road data, basic base map and annotated base map.

[0093] Among them, landmark data includes landmark names, location information (latitude and longitude), description information, etc., providing convenient data support for various application scenarios, and is used to identify and display important geographical landmarks; zoning data includes relevant spatial data generated by regional divisions implemented for hierarchical management of countries around the world, such as countries, provinces, cities, counties / districts, etc., represented in the form of polygons, and including attributes such as codes and names of administrative divisions for displaying administrative or geographical division information; three-dimensional data includes three-dimensional terrain models, building models, etc., for providing three-dimensional geographic spatial views; image data includes high-resolution satellite images, aerial images, etc., for displaying surface features and changes, such as research on surface cover, land use, environmental monitoring, etc. Data; vector data is used to represent the shape and position of geographic features; meteorological data provides observation data of meteorological elements such as temperature, precipitation, and wind direction, which is used to reflect climate conditions and weather patterns; road data records road networks, transportation facilities and other information in detail, provides support for transportation planning and navigation services, and is used to display transportation networks and route information; basic base maps include standard map data, administrative division layer data and classified area layer data, etc. The data is stored in the form of raster or vector, and undergoes strict geographic coordinate correction and projection transformation to ensure the accuracy and consistency of the data, and is used to provide a basic view of the geographical environment; annotated base maps are formed by adding annotation information (such as place names, road names, water system names, etc.) to the basic base map, which is used to locate and identify geographic features.

[0094] These data types provide rich material for geography teaching, supporting comprehensive presentation and in-depth analysis from the macro to the micro level. By combining the spatial database PostGresql with PostGis, they provide structured storage, normalized processing, and consistent representation. These data contain at least attributes such as data identifier, name, description, keywords, spatial extent, and service address. This ensures data accessibility, maintainability, and scalability, providing a solid data foundation for geography teaching and research.

[0095] Step A30: Segment the content of each teaching courseware in the first database.

[0096] Specifically, the courseware content stored in the first database is obtained, and the IK word segmentation plug-in (analysis-ik) is used. The extended word segmentation dictionary (ext.dic) and the stop word segmentation dictionary (stopword.dic) are configured to accurately segment the courseware content and output the word segmentation results. In some embodiments, the extended word segmentation dictionary and the stop word segmentation dictionary can also be adjusted based on the word segmentation results to further improve the word segmentation accuracy.

[0097] Expand the word segmentation dictionary: By adding professional vocabulary, ensure that the vocabulary related to geography teaching is correctly identified and segmented during the word segmentation process, thereby improving the accuracy of word segmentation. By collecting a large number of professional vocabulary from professional books, papers, reports, websites and other channels in the fields of geography teaching and remote sensing, sorting them, removing duplicates, and classifying them as needed, according to the requirements of the word segmentation tools or libraries used. Such as basic concepts such as the earth, map, longitude and latitude, hemisphere, time zone, covering natural geographical elements such as topography, landform, climate, vegetation, hydrology, including population, settlement, culture, economy and other human geographical elements, involving remote sensing, geographic information system (GIS), global positioning system (GPS) and other modern geographical technologies, etc., it helps teaching resources extract more professional vocabulary in the field of geography and improve the accuracy of word segmentation matching.

[0098] Pause word segmentation dictionary: By identifying and processing pause words, it clarifies the boundaries between words and avoids mis-segmentation or splicing during word segmentation. In addition to normal words, texts also contain punctuation marks, spaces, special characters, etc. that are used to separate sentences, phrases, or words.

[0099] Step A40: Establish an association relationship between each teaching courseware and the remote sensing products in the second database based on the word segmentation results of the teaching courseware, and store the association relationship in the first database.

[0100] In this embodiment, step A40 may include steps A41-A42:

[0101] Step A41: Obtain one or more courseware keywords based on the word segmentation results.

[0102] The courseware keywords include: one or more place name keywords, and one or more knowledge type keywords.

[0103] Step A42: Match the teaching courseware with the remote sensing products in the second database according to the courseware keywords, store the ID and path of the matched remote sensing product in the first database, and establish an association relationship with the teaching courseware.

[0104] Specifically, step A42 may include steps A421-A426:

[0105] Step A421: Perform fuzzy matching on each place name keyword with the landmark name and landmark keyword in the landmark data to obtain a landmark dataset.

[0106] The landmark data includes: landmark name, center longitude and latitude coordinates and landmark keywords.

[0107] Step A422: traverse the landmark dataset to obtain a set of center longitude and latitude coordinates.

[0108] Step A423: Match each obtained center longitude and latitude coordinate with the spatial range in the division data to obtain an administrative division dataset.

[0109] Among them, the zoning data includes: administrative division name, spatial range and remote sensing product path.

[0110] Specifically, you can use one of the following two methods to match administrative divisions:

[0111] (1) The obtained central longitude and latitude coordinates are directly intersected with the spatial range in the zoning data. The central longitude and latitude coordinate point is matched to the corresponding administrative district in which it falls.

[0112] (2) Generate a circular or custom-shaped area with the central longitude and latitude coordinates as the center and the specified buffer distance as the radius as the buffer area, intersect the buffer area with the spatial range in the zoning data, and find the administrative districts that intersect with the buffer area.

[0113] Step A424: respectively obtain data from the three-dimensional data, image data, vector data, meteorological data, and road data whose geographical locations belong to the spatial range in the administrative division dataset and whose data types fuzzily match the knowledge type keywords, to form a three-dimensional dataset, an image dataset, a vector dataset, a meteorological dataset, and a road dataset.

[0114] Step A425: Fuzzy matching is performed on the knowledge type keywords with the keywords in the basic base map and the annotated base map to obtain the basic base map set and the annotated base map set.

[0115] Generally speaking, the base map and the annotated base map can represent geographic information ranging from local areas to the global scope. If the second database stores the base map and the annotated base map within the scope of a specific administrative division, the place name keyword and the knowledge type keyword need to be used simultaneously when matching.

[0116] Step A426, obtain the ID and path of each data in the landmark dataset, administrative division dataset, three-dimensional dataset, image dataset, vector dataset, meteorological dataset, road dataset, basic base map set and annotation base map set, save it to the first database, and establish an association relationship with the teaching courseware.

[0117] For example, a passage in a courseware on common landform types describes, "Karst landform: Some of the rocks that make up the Earth's crust are soluble rocks, such as limestone. Under appropriate conditions, the materials in these rocks dissolve in water and are carried away, or re-precipitate, forming a variety of landforms on the surface and underground, collectively known as karst landforms. The karst landforms in Guizhou and Yunnan provinces of my country are the most classic and widely distributed. It is these areas that Xu Xiake described."

[0118] By performing word segmentation on the above text, we can extract keywords such as crust, karst, rock, surface, underground, landform, Xu Xiake, Guizhou, and Yunnan. The place name keywords can be matched to landmarks such as Guizhou and Yunnan. The landmark buffer range can be matched to Sichuan, Guizhou, Yunnan and city and county-level administrative divisions. The spatial range of the administrative division can be matched to remote sensing products. At the same time, the knowledge type keywords such as crust, karst, and landform can be combined with the keywords in remote sensing products for further precise matching, so that the three-dimensional data, image data, meteorological data, road data, vector data, etc. in the remote sensing products can be matched more accurately with the courseware.

[0119] It should be noted that some of the data sets constructed in the above steps A421-A425 may be empty sets, that is, no remote sensing products of the relevant type are matched.

[0120] Figure 2 This is a schematic diagram of the main steps of the second embodiment of the method for constructing a geography teaching library based on remote sensing products of the present invention. The geography teaching library of this embodiment includes: a first database, a second database and a third database. The unstructured third database stores videos and pictures for geography teaching. These animated description videos and pictures that explain the formation process of geographical landforms and other things help to better understand geographical knowledge. Figure 2 As shown, the geography teaching library construction method of this embodiment includes steps B10-B60:

[0121] Among them, steps B10-B40 correspond to steps A10-A40 in the above embodiment 1 and are respectively the same and will not be repeated here.

[0122] Step B50: Match the courseware keywords with the keywords in the video and picture data to obtain a static data set.

[0123] Step B60: Obtain the ID and path of each data in the static data set, save it to the first database, and establish an association relationship with the teaching courseware.

[0124] Figure 3 This is a schematic diagram of the main steps of the third embodiment of the method for constructing a geographical teaching library based on remote sensing products of the present invention. The geographical teaching library of this embodiment includes: a first database, a second database, a third database and a fourth database. The unstructured fourth database stores multiple remote sensing information tools. Figure 3 As shown, the geography teaching library construction method of this embodiment includes steps C10-C70:

[0125] Among them, steps C10-C70 correspond to steps B10-B60 in the above embodiment 2, respectively, and are not repeated here.

[0126] Step C70: Match the remote sensing product with the remote sensing information tool according to the data type of each remote sensing product in the second database, store the ID and path of the matched remote sensing information tool in the second database, and establish an association relationship with the remote sensing product.

[0127] The types of remote sensing information tools include: view control tools, positioning and roaming tools, measurement and drawing tools, navigation and compass tools, data analysis and visualization tools, and comparison and fusion tools, as shown in Table 2 below:

[0128] Table 2 Remote sensing information tools

[0129]

[0130]

[0131] In this embodiment, the specific storage structure of the remote sensing information tool is as follows:

[0132] "high_school:tool:xxx" / / tool identifier

[0133] "tool_class":"xxx" / / Tool category

[0134] "tool_title":"xxx" / / Tool title

[0135] "tool_remark":"xxx" / / Tool description

[0136] "tool_code":"xxx" / / Tool code block

[0137] "tool_word":"xxx" / / Tool keyword

[0138] "tool_resource":"xxx" / / Image ID

[0139] Specifically, in this embodiment, step C70 may include steps C71-C78:

[0140] Step C71: for each remote sensing product in the second database, determine the data type of the remote sensing product;

[0141] Step C72: If the data type of the remote sensing product is three-dimensional data, the IDs and paths of the navigation and compass tool and the data analysis and visualization tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0142] Step C73: If the data type of the remote sensing product is image data, the IDs and paths of the positioning and roaming tool and the measuring and drawing tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0143] Step C74: If the data type of the remote sensing product is vector data, meteorological data or road data, the IDs and paths of the measurement and drawing tool and the comparison and fusion tool are stored in the second database and associated with the remote sensing product.

[0144] Step C75: If the data type of the remote sensing product is a base map, the IDs and paths of the measurement and drawing tool and the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0145] Step C76: If the data type of the remote sensing product is a labeled base map, the ID and path of the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0146] Step C77: If the data type of the remote sensing product is zoning data, the ID and path of the viewing angle control tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0147] Step C78: If the data type of the remote sensing product is landmark data, the IDs and paths of the viewing angle control tool and the positioning and roaming tool are stored in the second database, and an association relationship is established with the remote sensing product.

[0148] Remote sensing information tools provide a richer and more intuitive geographic information experience for the application of remote sensing technology. Using remote sensing information tools to learn and understand geographical knowledge can greatly improve the expressive ability of geography teaching.

[0149] In an optional embodiment, the geography teaching library may further include a pre-trained classification model. This classification model is used to retrieve target courseware from the first database based on search keywords. For example, based on the user-entered teaching requirement "display karst landforms," ​​the search keyword "karst landforms" can be extracted. The text classification model can then use this keyword to retrieve target courseware related to karst landforms from the first database.

[0150] Dataset construction: The courseware word segmentation is converted into a 70% training set, a 20% validation set, and a 10% test set, with the courseware name as the classification label.

[0151] Selection of a classification model: The classification model can use the deep learning model BERT model transformers library. Select the BERT-base-chinese version to convert the text into a format that BERT can process, including token IDs and attention masks.

[0152] Training a classification model: Define the training loop parameters, including learning rate, batch size, training rounds, optimizer, etc., iteratively train the model on the training set, calculate the loss through forward propagation, and then use backpropagation and the optimizer to update the model parameters. After each training round (epoch) or every few batch sizes (batch), evaluate the model performance on the validation set and save the best performing model.

[0153] Evaluation of the classification model: Use the test set to evaluate the performance of the final model to obtain an unbiased performance estimate and analyze the classification results of the model to see if there are any classification errors or errors in specific patterns.

[0154] Iteration of classification model: Iterative training process. When the model matching rate does not meet the preset threshold, additional teaching resources are collected and a new training set is constructed to continue training the model.

[0155] After the entire geography teaching library of this embodiment is built, users who wish to use it can first enter their teaching requirements through the human-computer interaction interface. The search program then extracts search keywords based on these requirements and uses the classification model to find the target courseware. Next, using remote sensing information tools, and based on the relationships between the target courseware and remote sensing products, the relationships between the courseware and videos and images, and the relationships between remote sensing products and remote sensing information tools, a richer and more intuitive geography learning experience can be provided to users.

[0156] Although the various steps in the above embodiment are described in the above-mentioned order, those skilled in the art will understand that in order to achieve the effect of this embodiment, different steps do not have to be executed in such an order. They can be executed simultaneously (in parallel) or in a reverse order. These simple changes are within the scope of protection of the present invention.

[0157] Furthermore, based on the above method embodiment, the present invention also provides an embodiment of an electronic device. The electronic device of this embodiment includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the above method.

[0158] Furthermore, based on the above method embodiment, the present invention also provides an embodiment of a computer-readable storage device. The storage device of this embodiment stores a computer program that can be loaded by a processor and execute the above method.

[0159] The computer-readable storage device may include: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc., which can store program codes.

[0160] Those skilled in the art should be able to appreciate that the method steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of electronic hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in electronic hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0161] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is clearly not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent modifications or substitutions to the relevant technical features, and the technical solutions after such modifications or substitutions will fall within the scope of protection of the present invention.

Claims

1. A method for constructing a geographical teaching library based on remote sensing products, characterized in that: The geography teaching library includes: a first database and a second database; the method includes: Storing the teaching courseware in the first unstructured database; Storing the remote sensing products in the second database according to a preset data structure; Performing word segmentation on the content of each teaching courseware in the first database; Establishing an association relationship between each teaching courseware and the remote sensing product in the second database according to the word segmentation result of the teaching courseware, and storing the association relationship in the first database; The step of "establishing an association relationship between each teaching courseware and the remote sensing product in the second database based on the word segmentation result of each teaching courseware, and storing the association relationship in the first database" includes: Obtain one or more courseware keywords according to the word segmentation result; Matching the teaching courseware with the remote sensing product in the second database according to the courseware keyword, storing the ID and path of the matched remote sensing product in the first database, and establishing an association relationship with the teaching courseware; The courseware keywords include: one or more place name keywords, and one or more knowledge type keywords; The data types of remote sensing products include: Landmark data, used to identify and display important geographical landmarks; Zoning data, used to display administrative or geographic division information; Three-dimensional data, used to provide a three-dimensional geospatial view; Imagery data, used to show surface features and changes; Vector data, used to represent the shape and location of geographic features; Meteorological data, which reflects climate conditions and weather patterns; Road data, used to display transportation network and route information; Basemap, which provides a basic view of the geographical environment; Annotation base map, formed by adding annotation information to the basic base map, for locating and identifying geographic elements; The step of "matching the teaching courseware with the remote sensing product in the second database according to the courseware keyword, storing the ID and path of the matched remote sensing product in the first database, and establishing an association relationship with the teaching courseware" includes: Perform fuzzy matching on each of the place name keywords with the landmark name and landmark keyword in the landmark data to obtain a landmark dataset; the landmark data includes: the landmark name, the center longitude and latitude coordinates and the landmark keyword; Traversing the landmark dataset to obtain a set of center longitude and latitude coordinates; Matching each of the obtained center longitude and latitude coordinates with the spatial range in the division data to obtain an administrative division dataset; the division data includes: an administrative division name and the spatial range; Respectively acquiring data from the three-dimensional data, the image data, the vector data, the meteorological data, and the road data whose geographical location belongs to the spatial range in the administrative division dataset and whose data type fuzzy matches the knowledge type keyword, to form a three-dimensional dataset, an image dataset, a vector dataset, a meteorological dataset, and a road dataset; Perform fuzzy matching on the knowledge type keywords and the keywords in the basic base map and the annotated base map respectively to obtain a basic base map set and an annotated base map set; Obtain the ID and path of each data in the landmark dataset, the administrative division dataset, the three-dimensional dataset, the image dataset, the vector dataset, the meteorological dataset, the road dataset, the basic base map set and the annotated base map set, save them in the first database, and establish an association relationship with the teaching courseware.

2. The method for constructing a geographical teaching library based on remote sensing products according to claim 1, characterized in that: The geography teaching library further includes: an unstructured third database; The third database stores videos and pictures for geography teaching; The method further comprises: Matching the courseware keywords with the keywords in the video and picture data to obtain a static data set; The ID and path of each data in the static data set are obtained, saved in the first database, and associated with the teaching courseware.

3. The method for constructing a geographical teaching library based on remote sensing products according to claim 1, characterized in that: The geography teaching database further includes: an unstructured fourth database; The fourth database stores a plurality of remote sensing information tools; The method further comprises: matching the remote sensing product with the remote sensing information tool according to the data type of each remote sensing product in the second database, storing the ID and path of the matched remote sensing information tool in the second database, and establishing an association relationship with the remote sensing product; Among them, the types of remote sensing information tools include: perspective control tools, positioning and roaming tools, measurement and drawing tools, navigation and compass tools, data analysis and visualization tools, and comparison and fusion tools.

4. The method for constructing a geographical teaching library based on remote sensing products according to claim 3, characterized in that: The step of "matching the remote sensing product with the remote sensing information tool according to the data type of each remote sensing product in the second database, storing the ID and path of the matched remote sensing information tool in the second database, and establishing an association relationship with the remote sensing product" includes: For each remote sensing product in the second database, determining the data type of the remote sensing product; If the data type of the remote sensing product is the three-dimensional data, storing the IDs and paths of the navigation and compass tool and the data analysis and visualization tool in the second database, and establishing an association relationship with the remote sensing product; If the data type of the remote sensing product is the image data, storing the IDs and paths of the positioning and roaming tool and the measuring and mapping tool in the second database, and establishing an association relationship with the remote sensing product; If the data type of the remote sensing product is the vector data, the meteorological data, or the road data, the IDs and paths of the measurement and mapping tool and the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product; If the data type of the remote sensing product is the basic base map, the IDs and paths of the measurement and drawing tool and the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product; If the data type of the remote sensing product is the annotated base map, the ID and path of the comparison and fusion tool are stored in the second database, and an association relationship is established with the remote sensing product; If the data type of the remote sensing product is the zoning data, the ID and path of the viewing angle control tool are stored in the second database, and an association relationship is established with the remote sensing product; If the data type of the remote sensing product is the landmark data, the IDs and paths of the viewing angle control tool and the positioning and roaming tool are stored in the second database and associated with the remote sensing product.

5. The method for constructing a geographical teaching library based on remote sensing products according to any one of claims 1 to 4, characterized in that: The geography teaching library also includes: a pre-trained classification model; The classification model is used to retrieve target courseware in the first database according to the search keyword.

6. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and execute the method according to any one of claims 1 to 5.

7. A computer-readable storage device, characterized in that: The computer program is stored and can be loaded by a processor to execute the method according to any one of claims 1 to 5.

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