Urban land planning analysis method based on remote sensing image

Abstract

The invention provides an urban land planning analysis method based on a remote sensing image. The method comprises the following steps: determining a temporary building land block of a target city and a temporary building land type of the temporary building land block; determining the geospatial variation degree of the temporary building land block according to the first historical geospatial data and the second historical geospatial data of the temporary building land block; determining whether the temporary building land block is an abnormal land block according to the historical remote sensing image of the target city at the second historical time node and the current remote sensing image; and performing association analysis on the temporary building land blocks and the land blocks corresponding to the land types identical to the temporary building land types. By analyzing the current remote sensing image of the target city, the temporary building land block and the corresponding temporary building land type of the target city can be determined, and the attribute information of the temporary building land block marked as the abnormal land block can be used as the analysis reference of the same land type.

Description

[0001] This application is a divisional application of patent number "2024112183416", application date "2024-09-02", and name "A GIS-based urban land planning analysis method and system". Technical Field

[0002] The present invention relates to the technical field of urban land planning, and in particular to an urban land planning analysis method based on remote sensing images. Background Art

[0003] GIS (Geographic Information System) data is the basis for the operation of GIS technology. It contains geographic spatial data and attribute data, which are used to store, analyze and display geographic information. GIS technology can realize the collection and integration of geographic information such as landforms and land types, provide basic data for land use planning, analyze the spatial relationship between plots of land with different uses, and simulate and analyze land planning plans by establishing models. GIS technology can quickly and accurately analyze and comprehensively evaluate the spatial distribution and characteristics of land, providing a scientific basis and decision-making support for land planning.

[0004] Land use patterns are considered to be an important factor affecting the balance between residents' jobs and residences, which in turn affects urban residents' transportation, and even urban residents' carbon emissions and the urban environment. In related technologies, urban land use vector data of different periods are analyzed using software such as ArcGIS, so as to determine the overall characteristics of the land, regional differentiation laws, and changes in major land use types. Traditional urban planning often differs from the actual urban spatial status. Traditional land survey data are usually permanent construction land, but lack investigation and analysis of temporary construction land, making it difficult to better reflect the most realistic urban spatial status and affect urban land planning and analysis. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide an urban land planning analysis method based on remote sensing images, which solves the problem that the prior art lacks investigation and analysis of temporary building land, making it difficult to better reflect the most realistic urban space status and affect urban land planning and analysis.

[0006] In the first aspect, the present application provides an urban land planning analysis method based on remote sensing images, comprising:

[0007] Determine, based on the current remote sensing image of the target city, a temporary construction land block of the target city and a temporary construction land type of the temporary construction land block;

[0008] Calling the historical planning data of the temporary building land block, and determining at least one target planning time interval of the temporary building land block based on the historical planning data; the target planning time interval includes a time segment between a first historical time node and a second historical time node located after the first historical time node;

[0009] Determining the geospatial change degree of the temporary construction land block according to the first historical geospatial data of the temporary construction land block at the first historical time node and the second historical geospatial data at the second historical time node;

[0010] When the geographic space change degree is lower than a preset geographic space change threshold, determining whether the temporary construction land block is an abnormal land block according to the historical remote sensing image of the target city at the second historical time node and the current remote sensing image;

[0011] When it is determined that the temporary construction land block is an abnormal land block, the temporary construction land block is subjected to association analysis with a land block corresponding to the same land type as the temporary construction land block.

[0012] In one embodiment, determining the temporary construction land block of the target city and the land type of the temporary construction land block based on the current remote sensing image of the target city specifically includes:

[0013] Allocating pixels of the current remote sensing image of the target city to preset land categories, and dividing the target city into a plurality of land units; the land categories include land cover categories and land use categories;

[0014] Performing spatial analysis on each of the land units to determine attribute information corresponding to each of the land units and a first matching degree between the attribute information and a preset temporary building land attribute;

[0015] Marking a land unit whose first matching degree exceeds a preset first matching degree threshold as a reference land unit, merging at least another adjacent land unit with the reference land unit as the center to generate a land block to be determined, and determining a second matching degree between the land block to be determined and the land attribute of the temporary building;

[0016] The to-be-determined land block whose second matching degree exceeds a preset second matching degree threshold is marked as a temporary construction land block, and the temporary construction land type of the temporary construction land block is determined according to the land category of the land units contained in the temporary construction land block.

[0017] In one embodiment, the step of allocating pixels of the current remote sensing image of the target city to preset land categories and dividing the target city into a plurality of land units specifically includes:

[0018] Based on the spectral band corresponding to the preset land category, spectral analysis is performed on the current remote sensing image, and pixels matched by the spectral analysis of the current remote sensing image are assigned to the land category;

[0019] The pixels belonging to the same land category and connected are merged into the same land unit.

[0020] In one embodiment, performing spatial analysis on each of the land units to determine the attribute information corresponding to each of the land units specifically includes:

[0021] extracting geometric features of each of said land units;

[0022] Based on the geometric features, the land unit is superimposed with a preset human factor layer, and the land unit whose intersection area after superposition is greater than a preset intersection area threshold is marked with a corresponding artificial structure label;

[0023] The attribute information corresponding to each of the land units is determined based on the query index corresponding to the man-made structure tag.

[0024] In one embodiment, determining at least one target planning time interval of the temporary construction land block based on the historical planning data specifically includes:

[0025] The planning project of the temporary building land block in the historical planning data is determined, and the start and end time of the planning project is used as the target planning time interval.

[0026] In one embodiment, determining the geospatial change degree of the temporary construction land block according to the first historical geospatial data of the temporary construction land block at the first historical time node and the second historical geospatial data at the second historical time node specifically includes:

[0027] The geospatial change degree between the first historical geospatial data and the second historical geospatial data is determined according to a preset loss function.

[0028] In one embodiment, the historical remote sensing image and the current remote sensing image include the temporary building land block and a land block adjacent to the temporary building land block; determining whether the temporary building land block is an abnormal land block based on the historical remote sensing image of the target city at the second historical time node and the current remote sensing image specifically includes:

[0029] In the historical remote sensing image, taking the boundary line of the temporary construction land block as a reference, performing negative buffer processing of a preset distance on the temporary construction land block and obtaining a negative buffer area, and performing mask processing on the negative buffer area to obtain a masked historical remote sensing image of the temporary construction land block;

[0030] Inputting the masked historical remote sensing image into a preset image restoration model for restoration, thereby obtaining a restored remote sensing image;

[0031] When the similarity between the restored remote sensing image and the current remote sensing image is less than a preset similarity threshold, the temporary building land block is determined to be an abnormal land block.

[0032] In one embodiment, before inputting the masked historical remote sensing image into a preset image restoration model for restoration to obtain a restored remote sensing image, the method further includes:

[0033] Constructing an image restoration sample data set; the image restoration sample data set includes remote sensing images of multiple temporary buildings that have not been demolished at different time nodes and non-demolished planning information of the temporary buildings that have not been demolished;

[0034] Based on the image restoration sample data set, the image restoration model is trained by a neural network model.

[0035] In a second aspect, the present application provides a GIS-based urban land planning analysis system, comprising a processor and a memory; wherein the memory stores a computer program, and the computer program is used to be loaded by the processor and execute an urban land planning analysis method based on remote sensing images as described in any one of the first aspects.

[0036] In a third aspect, the present application provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores instructions, and the instructions are used by a processor to load and execute an urban land planning analysis method based on remote sensing images as described in any one of the first aspects.

[0037] In an urban land planning analysis method and system based on remote sensing images of the present embodiment, by analyzing the current remote sensing images of the target city, the temporary building land blocks and the corresponding temporary building land types of the target city can be determined, and combined with the historical planning data and historical geographic spatial data of the temporary building land blocks, it can be determined whether the temporary building land blocks are land blocks where temporary buildings have not been demolished under abnormal circumstances, so that the attribute information of the temporary building land blocks marked as abnormal land blocks can be used as an analysis reference for the same land type. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 Schematic diagram of the process of urban land planning analysis method based on remote sensing images in an embodiment of the present application. DETAILED DESCRIPTION

[0040] The specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all of the embodiments. Based on the description of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] In the description of the present invention, unless otherwise clearly specified and limited, the terms "set", "install", "connection" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0042] The directions or positional relationships indicated by terms such as “upper”, “lower”, “left”, “right”, “front”, “back”, “top”, “bottom”, “inside” and “outside” are based on the directions or positional relationships shown in the accompanying drawings, or are the directions or positional relationships in which the inventive product is usually placed when used. They are only for the convenience of description and simplified description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present invention.

[0043] The terms "first", "second", "third" and the like are merely used to distinguish elements of similar nature, and do not indicate or imply relative importance or a particular order.

[0044] The terms "comprises," "comprising," or any other variations thereof, are intended to cover a non-exclusive inclusion of the elements listed and may also include additional elements not expressly listed.

[0045] like Figure 1 As shown, this embodiment provides an urban land planning analysis method based on remote sensing images, including:

[0046] Step S100: determining a temporary construction land block of the target city and a temporary construction land type of the temporary construction land block based on a current remote sensing image of the target city;

[0047] Step S200: calling the historical planning data of the temporary building land block, and determining at least one target planning time interval of the temporary building land block based on the historical planning data; the target planning time interval includes a time segment between a first historical time node and a second historical time node located after the first historical time node;

[0048] Step S300: determining the geographic space change degree of the temporary construction land block according to the first historical geographic space data of the temporary construction land block at the first historical time node and the second historical geographic space data at the second historical time node;

[0049] Step S400: when the geographic space change degree is lower than a preset geographic space change threshold, determining whether the temporary building land block is an abnormal land block according to the historical remote sensing image of the target city at the second historical time node and the current remote sensing image;

[0050] Step S500: When it is determined that the temporary construction land block is an abnormal land block, the temporary construction land block is subjected to association analysis with land blocks corresponding to the same land type as the temporary construction land block.

[0051] In an urban land planning analysis method based on remote sensing images in the present embodiment, by analyzing the current remote sensing images of the target city, the temporary building land blocks and the corresponding temporary building land types of the target city can be determined, and combined with the historical planning data and historical geographic spatial data of the temporary building land blocks, it can be determined whether the temporary building land blocks are land blocks where temporary buildings have not been demolished under abnormal circumstances, so that the attribute information of the temporary building land blocks marked as abnormal land blocks can be used as an analysis reference for the same land type.

[0052] Step S100: Based on the current remote sensing image of the target city, determine the temporary construction land block of the target city and the temporary construction land type of the temporary construction land block.

[0053] In step S100, the target city refers to a designated or selected city. Remote sensing images refer to surface images acquired by remote sensing satellites (such as Landsat remote sensing satellites, Sentinel remote sensing satellites), aircraft or UAV platforms. The current remote sensing images of the target city can be acquired through satellite map tools such as USGS and Google Earth Engine. The current remote sensing image records the spectral information, spatial information, texture information, shape information, and location information of the target city in the current state. Among them, the spectral information includes multiple spectral bands, and different land objects (such as vegetation, water bodies, soil, man-made structures, etc.) have different reflection characteristics in different spectral bands; spatial information records surface features in the form of spatial resolution; shape information records the shape and layout of surface features; and location information records the association between points on the remote sensing image and actual geographic location coordinates.

[0054] Temporary construction land blocks refer to land blocks containing temporary construction land. Temporary buildings include tents, mobile cabins, container houses, temporary fences, temporary bridges, temporary roads and other spatial structures. Since temporary buildings are designed for short-term use or for a specific period of time, they can be quickly erected, are low-cost, and are easy to disassemble and move. When conducting land planning analysis, planning analysis is usually conducted on land for permanent buildings that have existed for a long time, while analysis of temporary construction land is less common or lacking.

[0055] Determining the temporary construction land block of the target city and the land type of the temporary construction land block based on the current remote sensing image of the target city specifically includes:

[0056] Step S101: assigning pixels of the current remote sensing image of the target city to preset land categories, and dividing the target city into a plurality of land units; the land categories include land cover categories and land use categories;

[0057] Step S102: performing spatial analysis on each of the land units to determine the attribute information corresponding to each of the land units and a first matching degree between the attribute information and the preset temporary building land attribute;

[0058] Step S103: marking the land unit whose first matching degree exceeds the preset first matching degree threshold as a reference land unit, merging at least another adjacent land unit with the reference land unit as the center to generate a land block to be determined, and determining a second matching degree between the land block to be determined and the land attribute of the temporary building;

[0059] Step S104: Mark the undetermined land block whose second matching degree exceeds the preset second matching degree threshold as a temporary construction land block, and determine the temporary construction land type of the temporary construction land block according to the land category of the land unit contained in the temporary construction land block.

[0060] By dividing the current land use types of the target city, the target city can be divided into multiple land units, and the attribute information of each land unit can be determined through spatial analysis. The attribute information of each land unit is matched with the preset temporary building land attributes, and the land unit with a large difference from the preset land type can be identified as the benchmark land unit, and it can be further determined whether the land unit near the benchmark land unit has similar characteristics to the benchmark land unit, so as to determine a collection of land units with a large deviation from the preset attribute information as the temporary building land block.

[0061] Step S101: Allocate pixels of the current remote sensing image of the target city to preset land categories, and divide the target city into a plurality of land units; the land categories include land cover categories and land use categories.

[0062] In step S101, since different land objects (such as forests, water bodies, soil, man-made structures, etc.) have different reflective characteristics in different spectral bands, the current remote sensing image can be spectrally analyzed through the spectral bands corresponding to different land objects to determine which pixels in the current remote sensing image have a higher matching degree, and multiple land units can be divided according to the set of pixels.

[0063] Remote sensing images include raster data. Raster data is a data form that divides space into regular grids, each grid is called a unit, and each unit is assigned a corresponding attribute value to represent an entity. In a raster dataset, each grid is called a pixel, and each pixel has a value to express the phenomenon being depicted, such as category, height, magnitude, or spectrum, etc. The category can be land use classes such as grassland, forest, or road; the height (distance) can represent the surface elevation above the mean sea level, which can be used to derive slope, aspect, and watershed attributes; the magnitude can represent gravity, noise pollution, or rainfall percentage; the spectrum can represent light reflectance and color in satellite images and aerial photography.

[0064] The method of allocating pixels of the current remote sensing image of the target city to a preset land category and dividing the target city into multiple land units specifically includes: performing spectral analysis on the current remote sensing image based on the spectral band corresponding to the preset land category, and allocating pixels of the current remote sensing image matched by the spectral analysis to the land category; and merging pixels belonging to the same land category and connected into the same land unit.

[0065] Among them, the current remote sensing image can be spectrally analyzed by the maximum likelihood classification method. First, the spectral information under each preset land category is used to construct a corresponding data set; then, based on the normal distribution assumption, the mean vector and covariance matrix of each data set are calculated respectively, and the probability density function corresponding to the spectral information under each land category is constructed according to the mean variance and covariance matrix; then, for each pixel in the current remote sensing image, its likelihood value belonging to each land category is calculated respectively, and the pixel corresponding to the current remote sensing image is matched according to the likelihood value.

[0066] The probability density function is as follows:

[0067]

[0068] Among them, X is the spectral information, μ is the mean vector of X, Y is the covariance matrix of X, det(Y) is the determinant of the covariance matrix Y, and Y -1 is the inverse matrix of the covariance matrix Y.

[0069] Step S102: Perform spatial analysis on each of the land units to determine the attribute information corresponding to each of the land units and a first matching degree between the attribute information and the preset temporary building land attribute.

[0070] In step S102, the spatial analysis is performed on each of the land units to determine the attribute information corresponding to each of the land units, specifically including: extracting the geometric features of each of the land units; superimposing the land units with a preset human factor layer based on the geometric features, and marking the land units whose intersection areas after superposition are greater than a preset intersection area threshold with corresponding artificial structure labels; and determining the attribute information corresponding to each of the land units based on the query index corresponding to the artificial structure label.

[0071] The geometric features may include the shape (such as rectangle, circle, irregular shape, etc.), area size, perimeter, direction and other information of the land unit. Then, based on these geometric features, the land unit is superimposed with the preset artificial factor layer. Assuming that the preset artificial factor layer contains the planned building range in a specific area, when the geometric range of a land unit overlaps with these building ranges, it is necessary to further determine the size of the intersection area. If the superimposed intersection area is larger than the preset intersection area threshold, the land unit is marked as the corresponding artificial structure label. For example, the preset intersection area threshold is 50% of the land unit area. When the intersection area between a land unit and the building range reaches 60% of its own area, it will be marked as an artificial structure label.

[0072] Man-made structure tags include urban infrastructure buildings (such as residences, shopping malls, hospitals, schools, etc.), transportation buildings (such as airports, railway stations, ports, etc.), entertainment buildings (such as cinemas, museums, parks, stadiums, etc.), infrastructure buildings (such as roads, bridges, tunnels, etc.), agricultural buildings (greenhouses, livestock sheds, barns, etc.), administrative buildings (such as courts, police stations, town halls, etc.) and religious buildings (temples, churches, etc.), as well as some other types of man-made structure tags.

[0073] Correspondingly, the human factor layer includes the urban basic building layer, the transportation building layer, the entertainment building layer, the infrastructure building layer, the agricultural building layer, the administrative building layer and the religious building layer, etc.

[0074] After determining the man-made structure label of each land unit, the corresponding attribute information can be extracted according to the query indicators corresponding to each land type. For example, for the urban basic building layer, the query indicators can be building density, building height, etc.; for the transportation building layer, the indicators may include road grade and traffic flow; for the entertainment building layer, the building scale and service scope can be considered; for the infrastructure building layer, the coverage and service capacity of the facilities can be considered; for the agricultural building layer, the scale and type of breeding or planting facilities can be considered; for the administrative building layer, the administrative level and service population can be considered; for the religious building layer, the scale and frequency of religious activities can be considered.

[0075] Temporary buildings are usually small in size, relatively simple in appearance, with a relatively random layout and loose building density. The surrounding environment lacks complete urban supporting facilities and is usually built in a short time. The materials used to build temporary buildings are mostly pre-made parts made of metal plates, wood or plastic films. For example, the mobile houses built by railway workers along the railway, temporary bridges built temporarily for traffic or transportation during bridge construction, etc.

[0076] Whether the compared land unit is temporary construction land can be determined by comparing the temporary construction land attributes with multiple information types such as appearance characteristics, material characteristics, time characteristics, surrounding environment, land area and building density in the attribute information corresponding to each land unit.

[0077] Temporary buildings usually exist while permanent buildings are being constructed and are demolished after the permanent buildings are completed. In order to determine the planning of the land for temporary buildings after the demolition of the temporary buildings, the land units occupied by the permanent buildings near the temporary buildings must also be included in the scope of the temporary building land block.

[0078] Step S103: marking the land unit whose first matching degree exceeds the preset first matching degree threshold as a reference land unit, merging at least another adjacent land unit with the reference land unit as the center to generate a land block to be determined, and determining a second matching degree between the land block to be determined and the land attribute of the temporary building;

[0079] Step S104: Mark the undetermined land block whose second matching degree exceeds the preset second matching degree threshold as a temporary construction land block, and determine the temporary construction land type of the temporary construction land block according to the land category of the land unit contained in the temporary construction land block.

[0080] In step S103 and step S104, the reference land unit is the land unit occupied by the temporary building. When merging adjacent land units, according to the overlapping length of the contour lines between the adjacent land unit and the reference land unit, the land unit with the longest overlapping contour line is preferentially selected for merging, and then the adjacent land unit and the reference land unit are taken together as the land block to be determined. If the second matching degree between the attribute of the land block to be determined and the attribute of the temporary building land exceeds the preset second matching degree threshold, then the merging of the adjacent land units is accepted, and the adjacent land units are also marked with the label information of the temporary building land block. If the second matching degree between the attribute of the land block to be determined and the attribute of the temporary building land is less than or equal to the preset second matching degree threshold, then the merging of the adjacent land units is not accepted, and another adjacent land unit is merged again in the order of overlapping contour lines and re-compared with the second matching degree threshold until the adjacent land units near the reference land unit are merged in turn and the comparison is completed. The temporary construction land block is a collection of land units marked with label information of the temporary construction land block, and the land type of the temporary construction land block can be determined according to the land type of each land unit in the temporary construction land block.

[0081] Furthermore, due to the fact that temporary buildings are dispersed to a certain extent, that is, there are multiple related temporary buildings during the construction of the same batch of construction projects, and there is a certain distance between the two temporary buildings in space, in order to avoid identifying the land blocks where multiple temporary buildings are located as multiple unrelated temporary building land blocks when determining the temporary building land blocks, this embodiment merges the divided temporary building land blocks again, thereby merging multiple related temporary building land blocks into a complete temporary building land block, avoiding missing relevant information in the process of urban land planning analysis.

[0082] The divided temporary construction land blocks are merged again, so that multiple related temporary construction land blocks are merged into a complete temporary construction land block, which specifically includes the following steps: two temporary construction land blocks that are close to each other but not adjacent are positively buffered at a preset distance to obtain two positive buffer land blocks after the contours are enlarged; if the two positive buffer land blocks after the contours are enlarged have an intersection, it indicates that the temporary construction land blocks corresponding to the two positive buffer land blocks may be associated; then the geographic space data of the two temporary construction land blocks are analyzed for similarity and a similarity result is obtained. When the similarity result is greater than a preset similarity threshold, it indicates that the two temporary construction land blocks are associated, and the two temporary construction land blocks and other land blocks sandwiched between the two temporary construction land blocks are merged into a complete temporary construction land block. If the two positive buffer land blocks after the contours are enlarged do not have an intersection, it indicates that the temporary construction land blocks corresponding to the two positive buffer land blocks may not be associated.

[0083] Step S200: Call the historical planning data of the temporary building land block, and determine at least one target planning time interval of the temporary building land block based on the historical planning data; the target planning time interval includes a time segment between a first historical time node and a second historical time node located after the first historical time node.

[0084] In step S200, the historical planning data refers to the project planning data of the planned construction project in the building land block, such as the location, purpose, area, start time and end time of the declared building, etc. Among them, the first historical time node is the start time node of the planning project, and the second historical time node is the end time node of the planning project.

[0085] Determining at least one target planning time interval of the temporary construction land block based on the historical planning data specifically includes: determining a planning project of the temporary construction land block in the historical planning data, and using the start and end time of the planning project as the target planning time interval.

[0086] Step S300: Determine the geographic space change degree of the temporary construction land block according to the first historical geographic space data of the temporary construction land block at the first historical time node and the second historical geographic space data at the second historical time node.

[0087] Geospatial data refers to data associated with a geographic spatial location, which describes the characteristics, location and relationship of spatial objects within the target city. Usually, geospatial data includes vector data, raster data and attribute data. Vector data is composed of geometric objects such as points, lines, and surfaces, such as the boundaries of roads, rivers, administrative divisions, etc.; raster data uses pixels or grid units as basic units; attribute data describes non-spatial information related to geospatial objects, such as land use type, purpose of buildings, etc. The first historical geospatial data and the second historical geospatial data of this embodiment mainly include vector data and attribute data of temporary building land blocks. The vector data is used to determine whether the spatial object in the temporary building land block is a temporary building, and its land use type is determined based on the attribute information.

[0088] Among them, according to the first historical geographic spatial data of the temporary construction land block at the first historical time node and the second historical geographic spatial data at the second historical time node, the geographic spatial change degree of the temporary construction land block is determined, specifically including: determining the geographic spatial change degree between the first historical geographic spatial data and the second historical geographic spatial data according to a preset loss function.

[0089] The formula of the loss function is:

[0090]

[0091] Wherein, L is the degree of geographic spatial change between the first historical geographic spatial data and the second historical geographic spatial data; X is the first historical geographic spatial data; and Y is the second historical geographic spatial data.

[0092] Step S400: When the geographic space change degree is lower than a preset geographic space change threshold, determining whether the temporary construction land block is an abnormal land block based on the historical remote sensing image of the target city at the second historical time node and the current remote sensing image.

[0093] Usually, temporary buildings will be demolished after the completion of the planned construction project of their corresponding construction. However, due to their use value or ornamental value, some temporary buildings are not demolished, but are transformed into temporary buildings or semi-permanent buildings with extended periods. This embodiment can effectively identify the temporary building land blocks where temporary buildings have not been demolished by comparing the geospatial change degree of the temporary building land blocks with the preset geospatial change threshold, and determine that the reason why the temporary buildings have not been demolished is caused by unconventional reasons based on the historical remote sensing images and current remote sensing images of the temporary building land blocks (for example, a temporary factory is transformed into an exhibition hall for tourist check-ins, and a temporary hospital cabin is transformed into a sub-designated hospital), and mark the temporary building land blocks where the temporary buildings have not been demolished for these unconventional reasons as abnormal land blocks.

[0094] The historical remote sensing image and the current remote sensing image include the temporary building land block and a land block adjacent to the temporary building land block; determining whether the temporary building land block is an abnormal land block according to the historical remote sensing image of the target city at the second historical time node and the current remote sensing image specifically includes:

[0095] Step S401: In the historical remote sensing image, taking the boundary line of the temporary construction land block as a reference, performing negative buffer processing of a preset distance on the temporary construction land block and obtaining a negative buffer area, and performing mask processing on the negative buffer area to obtain a masked historical remote sensing image of the temporary construction land block;

[0096] In step S401, due to the fact that temporary buildings are dispersed to a certain extent, that is, there are multiple associated temporary building blocks in the same batch of construction projects, and there is a certain distance between the two temporary building blocks in space. In the masked historical remote sensing image, other land blocks between the associated temporary building blocks and located in the negative buffer area can be ablated by masking the negative buffer area.

[0097] Step S402: inputting the masked historical remote sensing image into a preset image restoration model for restoration, thereby obtaining a restored remote sensing image.

[0098] Step S403: When the similarity between the restored remote sensing image and the current remote sensing image is less than a preset similarity threshold, the temporary building land block is determined to be an abnormal land block.

[0099] In step S402 and step S403, when the temporary building blocks on both sides of the negative buffer area are associated, the image restoration model will also generate associated temporary building groups in the negative buffer area when restoring the masked historical remote sensing image, thereby connecting the temporary building blocks on both sides. When the temporary building blocks on both sides of the negative buffer area are not associated, the image restoration model restores the image of the negative buffer area according to conventional reasons, so that the restored remote sensing image has a large overlap with the current remote sensing image, that is, the similarity between the restored remote sensing image and the current remote sensing image is high. When the similarity between the restored remote sensing image and the current remote sensing image is low and less than the preset similarity threshold, the temporary building land block can be determined as an abnormal land block.

[0100] Before inputting the covered historical remote sensing image into a preset image restoration model for restoration to obtain a restored remote sensing image, the method also includes: constructing an image restoration sample data set; the image restoration sample data set includes remote sensing images of multiple non-demolished temporary buildings at different time nodes and non-demolished planning information of the non-demolished temporary buildings; based on the image restoration sample data set, training the image restoration model through a neural network model.

[0101] The image restoration sample dataset contains remote sensing images of various temporary buildings that have not been demolished at different time points and planning information of temporary buildings that have not been demolished. For example, the iron houses that have not been demolished along the railway are used as power distribution rooms for railway inspection equipment, exhibition sheds used for exhibitions are converted into vegetable markets, and temporary fences are reinforced with concrete to become semi-permanent fences.

[0102] Based on the image restoration sample data set, the image restoration model is trained by a neural network model, which can be achieved by the following method: dividing the image restoration sample data set into training samples and test samples according to a preset ratio; determining a primary restoration model based on the training samples, and generating an evaluation index based on the test samples; when the evaluation index is within the preset evaluation index range, determining that the primary prediction model is an image restoration model; if the evaluation index is not within the preset evaluation index range, returning to the step of dividing the ultrasound image sample data set into training samples and test samples according to the preset ratio.

[0103] The target variable is defined as "the difference between the restored remote sensing image and the remote sensing image at different time nodes", and the "remote sensing image" and "non-demolition planning information" are used as feature variables to construct the objective function. The classification model is used to perform multiple rounds of iterative training on the training samples and generate a new objective function. Each round of iteration generates a new residual. The residual of the previous round of prediction is fitted in the new round of iteration, which can improve the accuracy of the neural network model, solve the optimal value of the final objective function, and train the neural network model based on the optimal value.

[0104] Step S500: When it is determined that the temporary construction land block is an abnormal land block, the temporary construction land block is subjected to association analysis with land blocks corresponding to the same land type as the temporary construction land block.

[0105] In step S500, after determining that the temporary construction land block is an abnormal land block, the geospatial data of the temporary construction land block is extracted to perform association analysis for the land blocks corresponding to the same land type as the temporary construction land type. The geospatial data includes multiple indicators such as spatial distribution characteristics, time change trends, attribute feature comparisons, and surrounding environmental impacts. Among them, the spatial distribution characteristics refer to the distribution relationship between the abnormal land block and other normal blocks of the same type in the geographic space, whether there is an aggregated or discrete pattern. The time change trend refers to the comparison of changes at different time points. Attribute feature comparison refers to the difference relationship between the abnormal land block and other normal blocks of the same type, such as the building structure, use, and other attribute information. The surrounding environmental impact refers to the environmental factors around the abnormal land block, such as the impact of traffic conditions, infrastructure, policy planning, etc. on it, and is compared with the surrounding environmental impacts of other blocks. When other land blocks of the same type are similar to the abnormal land block in geospatial data, the attribute information of the temporary construction land block corresponding to the abnormal land block can be used as an analysis reference for the same land type.

[0106] To summarize, in an urban land planning analysis method based on remote sensing images in the present embodiment, by analyzing the current remote sensing images of the target city, the temporary building land blocks and the corresponding temporary building land types of the target city can be determined, and combined with the historical planning data and historical geographic spatial data of the temporary building land blocks, it can be determined whether the temporary building land blocks are land blocks where temporary buildings have not been demolished under abnormal circumstances, so that the attribute information of the temporary building land blocks marked as abnormal land blocks can be used as an analysis reference for the same land type.

[0107] This embodiment also provides a GIS-based urban land planning analysis system, including: a processor and a memory; wherein the memory stores a computer program, and the computer program is used to be loaded by the processor and execute the above-mentioned urban land planning analysis method based on remote sensing images.

[0108] Based on the same inventive concept as the above embodiments, this embodiment also provides a computer-readable storage medium, which stores instructions for the processor to load and execute the urban land planning analysis method based on remote sensing images as described above.

[0109] In the embodiments of the mobile terminal and computer-readable storage medium provided in the present application, all technical features of the above-mentioned control method embodiments are included, and the expansion and explanation content of the specification are basically the same as those of the above-mentioned method embodiments, which will not be repeated here.

[0110] The embodiment of the present application further provides a computer program product, which includes a computer program code. When the computer program code runs on a computer, the computer executes the methods in the above various possible implementation modes.

[0111] An embodiment of the present application also provides a chip, including a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that a device equipped with the chip executes the methods in various possible implementation modes as described above.

[0112] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0113] In the present application, the same or similar terminology concepts, technical solutions and / or application scenario descriptions are generally described in detail only the first time they appear. When they appear again later, they are generally not repeated for the sake of brevity. When understanding the technical solutions and other contents of the present application, for the same or similar terminology concepts, technical solutions and / or application scenario descriptions that are not described in detail later, reference can be made to the previous related detailed descriptions.

[0114] In the present application, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0115] The various technical features of the technical solution of the present application can be arbitrarily combined. In order to make the description concise, not all possible combinations of the various technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of the present application.

[0116] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment method can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product is stored in a storage medium as above, including several instructions for a terminal device to execute the method of each embodiment of the present application. The above is only a preferred embodiment of the present application, and the patent scope of the present application is not limited thereto. All equivalent structures or equivalent process transformations made by using the contents of the present application specification and the drawings, or directly or indirectly used in other related technical fields, are similarly included in the patent protection scope of the present application. It should be noted that each embodiment in this specification is described in a progressive manner, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0117] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the attached claims.

Claims

1. A method for analyzing urban land planning based on remote sensing images, characterized in that: include: Determine, based on the current remote sensing image of the target city, a temporary construction land block of the target city and a temporary construction land type of the temporary construction land block; Retrieving historical planning data of the temporary construction land block, and determining at least one target planning time interval of the temporary construction land block based on the historical planning data; The target planning time interval includes a time segment between a first historical time node and a second historical time node located after the first historical time node; Determining the geospatial change degree of the temporary construction land block according to the first historical geospatial data of the temporary construction land block at the first historical time node and the second historical geospatial data at the second historical time node; specifically comprising: determining the geospatial change degree between the first historical geospatial data and the second historical geospatial data according to a preset loss function; Among them, the formula of the loss function is: Wherein, L is the degree of geographic spatial change between the first historical geographic spatial data and the second historical geographic spatial data; X is the first historical geographic spatial data; Y is the second historical geographic spatial data; When the geographic space change degree is lower than a preset geographic space change threshold, determining whether the temporary construction land block is an abnormal land block according to the historical remote sensing image of the target city at the second historical time node and the current remote sensing image; When it is determined that the temporary construction land block is an abnormal land block, the temporary construction land block is subjected to association analysis with a land block corresponding to the same land type as the temporary construction land block.

2. The urban land planning analysis method based on remote sensing images according to claim 1 is characterized in that: The determining of the temporary construction land block of the target city and the land type of the temporary construction land block based on the current remote sensing image of the target city specifically includes: Allocating pixels of the current remote sensing image of the target city to preset land categories, and dividing the target city into a plurality of land units; the land categories include land cover categories and land use categories; Performing spatial analysis on each of the land units to determine attribute information corresponding to each of the land units and a first matching degree between the attribute information and a preset temporary building land attribute; Marking a land unit whose first matching degree exceeds a preset first matching degree threshold as a reference land unit, merging at least another adjacent land unit with the reference land unit as the center to generate a land block to be determined, and determining a second matching degree between the land block to be determined and the land attribute of the temporary building; The to-be-determined land block whose second matching degree exceeds a preset second matching degree threshold is marked as a temporary construction land block, and the temporary construction land type of the temporary construction land block is determined according to the land category of the land units contained in the temporary construction land block.

3. The urban land planning analysis method based on remote sensing images according to claim 2 is characterized in that: The allocating pixels of the current remote sensing image of the target city to preset land categories and dividing the target city into a plurality of land units specifically includes: Based on the spectral band corresponding to the preset land category, spectral analysis is performed on the current remote sensing image, and pixels matched by the spectral analysis of the current remote sensing image are assigned to the land category; The pixels belonging to the same land category and connected are merged into the same land unit.

4. The urban land planning analysis method based on remote sensing images according to claim 2 is characterized in that: The performing of spatial analysis on each of the land units to determine the attribute information corresponding to each of the land units specifically includes: extracting geometric features of each of said land units; Based on the geometric features, the land unit is superimposed with a preset human factor layer, and the land unit whose intersection area after superposition is greater than a preset intersection area threshold is marked with a corresponding artificial structure label; The attribute information corresponding to each of the land units is determined based on the query index corresponding to the man-made structure tag.

5. The urban land planning analysis method based on remote sensing images according to claim 1 is characterized in that: The determining of at least one target planning time interval of the temporary construction land block based on the historical planning data specifically includes: The planning project of the temporary building land block in the historical planning data is determined, and the start and end time of the planning project is used as the target planning time interval.

6. The urban land planning analysis method based on remote sensing images according to any one of claims 1 to 5, characterized in that: The historical remote sensing image and the current remote sensing image include the temporary construction land block and a land block adjacent to the temporary construction land block; and determining whether the temporary construction land block is an abnormal land block based on the historical remote sensing image of the target city at the second historical time node and the current remote sensing image specifically includes: In the historical remote sensing image, taking the boundary line of the temporary construction land block as a reference, performing negative buffer processing of a preset distance on the temporary construction land block and obtaining a negative buffer area, and performing mask processing on the negative buffer area to obtain a masked historical remote sensing image of the temporary construction land block; Inputting the masked historical remote sensing image into a preset image restoration model for restoration, thereby obtaining a restored remote sensing image; When the similarity between the restored remote sensing image and the current remote sensing image is less than a preset similarity threshold, the temporary building land block is determined to be an abnormal land block.

7. The urban land planning analysis method based on remote sensing images according to claim 6 is characterized in that: Before inputting the masked historical remote sensing image into a preset image restoration model for restoration to obtain a restored remote sensing image, the method further includes: Constructing an image restoration sample data set; the image restoration sample data set includes remote sensing images of multiple temporary buildings that have not been demolished at different time nodes and non-demolished planning information of the temporary buildings that have not been demolished; Based on the image restoration sample data set, the image restoration model is trained by a neural network model.

Images