A land greening system data information management method

Abstract

The present application relates to the technical field of land greening data management, in particular to a land greening system data information management method, comprising: arranging an ecological perception network composed of multiple source sensors in a target administrative region to collect vegetation physiology and soil environment data; carrying out denoising, interpolation preprocessing, standardization and coordinate system conversion in a data processing center to form a standardized basic ecological data set. Based on the data set, an attribute library containing multi-dimensional information such as tree species is constructed with a single plant or a reforestation plot as the smallest management unit, a dynamic three-dimensional green volume voxel model is generated in a geographic information system to reflect the spatial distribution of land greening resources. The model is used to calculate the carbon fixation and oxygen release potential values of different functional divisions, and a planning decision engine is called to generate suggestions for replanting or reforming in low potential value areas. The method effectively improves the data information processing efficiency, calls the planning decision engine to generate land greening implementation suggestions, and quickly and dynamically updates the land greening system data information.

Description

Technical Field

[0001] This invention relates to the field of land greening data management technology, and in particular to a method for managing data information based on a land greening system. Background Technology

[0002] Currently, the management of data information in the national land greening system mainly adopts a combination of traditional manual surveys and single-sensor data collection. Data on vegetation growth and soil environment are manually recorded, and this is supplemented by simple remote sensing image analysis to form basic national land greening data archives. Initial labeling and management of national land greening resources are then completed using two-dimensional geographic maps. This approach suffers from insufficient comprehensiveness and real-time performance in data collection, and data processing involves only simple filtering. It lacks systematic denoising, interpolation preprocessing, standardization, and coordinate system conversion of the raw data, failing to create standardized basic ecological datasets and thus hindering the need for refined management of national land greening resources.

[0003] Existing management technologies often use large areas as the dividing standard, lacking precise control over individual plants or small afforestation plots. They fail to construct a multi-dimensional attribute system encompassing tree species, forest age, stand density, and site conditions, resulting in an inaccurate capture of the spatial distribution characteristics of national greening resources, achieving only a rough, planar representation. Furthermore, ecological value assessments rely heavily on empirical estimations, lacking a precise accounting method corresponding to the spatial distribution of national greening resources. Assessment results are disconnected from greening planning decisions, making it impossible to formulate specific and implementable replanting or renovation recommendations for areas with low carbon sequestration and oxygen release potential. This hinders precise and scientific management of national greening resources and fails to meet the practical needs of refined management and scientific planning for national greening. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a data information management method based on the national land greening system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a method for managing data information based on a land greening system, comprising: Within the geographical space of the target administrative region, an ecological sensing network consisting of multi-source sensors is deployed. This ecological sensing network is responsible for collecting surface vegetation physiological data and soil environmental data. The raw data collected by the ecological sensing network is transmitted to the data processing center, where the data processing center performs noise reduction, interpolation preprocessing, standardization, and coordinate system transformation on the data to form a standardized basic ecological dataset. Based on the standardized basic ecological dataset, a multi-dimensional attribute database is constructed, which includes tree species type, forest age, forest stand density and site conditions. The multi-dimensional attribute database takes a single plant or afforestation plot as the smallest management unit. Using the information in the multidimensional attribute library, a dynamic three-dimensional green voxel model is generated in the geographic information system. The three-dimensional green voxel model reflects the spatial distribution of land greening resources. Using the three-dimensional green volume voxel model, the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region are calculated, and the carbon sequestration and oxygen release potential values ​​are stored as key indicators in the ecological value assessment table. Based on the ecological value assessment table, the planning decision engine is invoked. The planning decision engine, in conjunction with the preset land greening coverage rate target, generates a list of replanting or renovation suggestions for low-potential areas.

[0006] As a further aspect of the present invention, the ecological sensing network transmits the collected raw data to a data processing center, where the data processing center performs noise reduction, interpolation preprocessing, standardization, and coordinate system transformation on the data to form a standardized basic ecological dataset, including: Receive a mixed data stream uploaded by the ecological sensing network, which includes multispectral images, soil temperature and humidity, and leaf area index; The multispectral image is subjected to cloud masking to remove invalid pixels caused by weather interference, and the remaining pixels are radiometrically calibrated. For the missing values ​​of soil temperature and humidity, a time-series-based linear interpolation method was used to fill them in, and cross-validation was performed using observations from neighboring stations. The coordinate systems of data from different sources are uniformly converted to the national geodetic coordinate system, and differential correction is performed on the data collected by all mobile terminals based on the location of the reference station in the ecological sensing network. The data, after denoising, interpolation, and skew correction, is formatted according to a predefined field structure to generate the standardized basic ecological dataset.

[0007] As a further aspect of the present invention, based on the standardized basic ecological dataset, a multi-dimensional attribute library is constructed, including tree species type, forest age, stand density, and site conditions, comprising: Image recognition is performed on the standardized basic ecological dataset to extract the crown outline and texture features of individual plants, and the tree species type and forest age of the individual plants are inverted by combining historical archive data. Based on the inverted individual plant information and combined with the canopy closure data measured by the ecological sensing network, the local stand density centered on the individual plant is calculated. Using the elevation, aspect, and soil pH data contained in the standardized basic ecological dataset, the site condition level of the individual plant is determined by a lookup table method. The tree species type, tree species, forest age, calculated stand density, determined site condition level, and spatial coordinates of the individual plant are all written into the multidimensional attribute database to form a complete attribute record.

[0008] As a further aspect of the present invention, a dynamic three-dimensional green volume voxel model is generated in a geographic information system using information from the multidimensional attribute library, including: The spatial coordinates, tree height, and crown width of all individual plants are extracted from the multidimensional attribute library, wherein the tree height data is obtained by lidar scanning in the ecological sensing network. Within the computational grid set by the geographic information system, cubic units, or voxels, are generated with the spatial coordinates of a single plant as the origin, its crown width as the base, and its tree height as the height. Based on the tree species information of a single plant, the corresponding green volume coefficient per unit volume is found in the preset green volume conversion coefficient table and assigned to the voxel; Voxels with different green volume coefficients are superimposed and fused to form a three-dimensional green volume voxel model that intuitively displays the distribution of green space. The three-dimensional green volume voxel model supports historical backtracking along a time axis.

[0009] As a further aspect of the present invention, the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region are calculated using the aforementioned three-dimensional green volume voxel model, and these carbon sequestration and oxygen release potential values ​​are stored as key indicators in an ecological value assessment table, including: The three-dimensional green volume voxel model is spatially divided according to administrative divisions or urban functional areas to obtain several independent analysis units; For each analysis unit, the total green amount of all voxels within it is calculated to obtain the total green amount value of the analysis unit; Based on the total green volume value, and combined with the carbon sequestration and oxygen release capacity parameters corresponding to the tree species information carried by each voxel, the theoretical total carbon sequestration and oxygen release of the analysis unit is calculated. A time decay factor is introduced to correct the theoretical total carbon sequestration and oxygen release to reflect the changes in the plant growth cycle. The corrected result is then recorded as the carbon sequestration and oxygen release potential value of the analysis unit in the ecological value assessment table.

[0010] As a further aspect of the present invention, based on the ecological value assessment table, a planning decision engine is invoked. This planning decision engine, combined with a preset national green coverage rate target, generates a list of replanting or renovation suggestions for low-potential areas, including: Read the carbon sequestration and oxygen release potential values ​​of each analysis unit recorded in the ecological value assessment table, and perform a correlation analysis with the current land green coverage rate of the analysis unit; The analysis unit is divided into four quadrants: high potential high energy region, high potential low energy region, low potential high energy region, and low potential low energy region, among which the low potential low energy region is marked as the key area of ​​focus; Retrieve site condition data for the key areas of interest and screen candidate tree species that are suitable for growth under the site conditions and have high carbon sequestration capacity from the plant susceptibility database. Based on the preset national greening coverage target, the amount of new green space needed in the key areas of concern is calculated, and the planting quantity and layout of candidate tree species are determined accordingly, generating the list of proposed replanting or renovation.

[0011] As a further aspect of the present invention, it also includes: breaking down the list of replanting or renovation suggestions into specific engineering tasks and issuing them to the construction process monitoring platform, which records the entire process data from the arrival of seedlings to the final acceptance. The construction process monitoring platform will transmit the data after acceptance to update the multidimensional attribute library and the three-dimensional green volume voxel model, thus completing a data loop. The proposed replanting or renovation list is broken down into specific engineering tasks and distributed to the construction process monitoring platform. This platform records data from the arrival of seedlings to final acceptance, including: Analyze the proposed list of replanting or renovation suggestions, and transform the requirements regarding tree species, quantity, and layout into specific procurement plans and planting operation guidelines; Assign a unique engineering task code to the procurement plan and planting operation instructions, and bind the engineering task code to the spatial location in the suggestion list; During construction, photos of seedling varieties, planting hole dimensions, and installation status of support facilities are collected via mobile terminals, and the data is associated with the corresponding project task code. When the project is completed, all process data under the project task code will be compiled to form an electronic file containing construction details, which will be stored in the construction process monitoring platform.

[0012] As a further aspect of the present invention, the construction process monitoring platform transmits the data after acceptance to update the multidimensional attribute library and the three-dimensional green volume voxel model, including: Obtain electronic files of the accepted projects from the construction process monitoring platform, and extract information such as seedling varieties, actual planting coordinates, and acceptance time. The extracted seedling variety and coordinate information, combined with the actual tree height and crown width obtained from the ecological sensing network, are inserted as a new record into the multidimensional attribute library. Trigger the recalculation mechanism of the three-dimensional green volume voxel model, add voxels to the model with the same number as the current replanting or modification, and set the coordinates, size and green volume coefficient of the new voxels to be consistent with the records in the electronic archive. The 3D green volume voxel model was re-rendered using the updated data to keep the model's state synchronized with the actual greening status on the ground.

[0013] As a further aspect of the present invention, after generating the three-dimensional green voxel model, a health assessment step is also included: The latest vegetation index data for each voxel is continuously acquired from the ecological sensing network. The vegetation index data is used to characterize the chlorophyll content and water status of the leaves. The obtained vegetation index data is compared with the health standard values ​​of the same tree species and forest age to calculate a health deviation degree. When the health deviation exceeds the set warning threshold, the voxel is automatically highlighted in the geographic information system, and a warning work order containing the specific location and anomaly type is generated. The warning work order is pushed to the construction process monitoring platform, where maintenance personnel perform targeted restoration work based on the warning work order, and the work results are sent back to update the multi-dimensional attribute library.

[0014] As a further aspect of the present invention, social participation data is also integrated when constructing the multidimensional attribute library, including: Open a public reporting interface to allow citizens to submit clues about the protection of ancient and famous trees or acts of destroying or occupying green spaces through a mobile application; The clues are manually reviewed and verified on-site. The verified information is then converted into structured social participation data, which includes the latitude and longitude of the location involved, the type of event, and the status of the process. The latitude and longitude information in the social participation data is matched with the geographic information system to find the corresponding individual plant or afforestation plot, and the event type is added as a special attribute to the corresponding record in the multidimensional attribute library. When generating the list of replanting or renovation suggestions, if there is unprocessed social participation data in a certain area, the planning operation for the unprocessed area will be suspended until the social participation data is processed.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: Using individual plants or afforestation plots as the smallest management unit, a multi-dimensional attribute database is constructed, including tree species type, forest age, stand density, and site conditions. Based on a standardized basic ecological dataset collected by an ecological sensing network and cleaned and registered, a dynamic three-dimensional green volume voxel model is generated in the geographic information system. This model can accurately reflect the three-dimensional spatial distribution characteristics of greening resources, breaking the limitation of conventional technologies that can only achieve a two-dimensional display of greening resources. It makes the spatial distribution details of greening resources clearly traceable, realizing the transformation of greening resources from extensive management to refined control. This solves the problems of extensive management units and inaccurate depiction of greening spatial distribution in conventional technologies.

[0016] The carbon sequestration and oxygen release potential of different functional zones within the target administrative region is calculated using a three-dimensional green volume voxel model. This potential value is then stored as a key indicator in the ecological value assessment table. The planning decision engine is then invoked, and combined with the preset national green coverage rate target, a list of replanting or renovation suggestions for low-potential areas is generated. This achieves precise integration of ecological value accounting and greening planning decisions, breaking the disconnect between ecological value assessment and planning decisions in conventional technologies. It enables greening planning suggestions to accurately match the actual needs of low-potential areas, avoiding the problems of lack of specificity and inability to be implemented in conventional technologies. This achieves closed-loop management of the entire process from greening data collection, processing, and assessment to decision-making. Attached Figure Description

[0017] Figure 1 This is a flowchart of a data information management method based on a land greening system as described in this invention; Figure 2 Flowchart for building a multidimensional attribute library; Figure 3 A graph showing the changes in carbon sequestration potential at different stages of the national greening system; Figure 4 A graph showing the correlation between green coverage rate and carbon sequestration potential of a unit of land; Figure 5 This is a time-series change graph of 24-hour ecological sensing data. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0019] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0020] See Figure 1 Within the geographic space of the target administrative region, an ecological sensing network composed of multi-source sensors is deployed. This network is responsible for collecting surface vegetation physiological data and soil environmental data. The ecological sensing network transmits the collected raw data to a data processing center, where the data undergoes denoising, interpolation preprocessing, standardization, and coordinate system transformation to form a standardized basic ecological dataset. Based on this standardized basic ecological dataset, the system constructs a multi-dimensional attribute database including tree species type, forest age, stand density, and site conditions. The multi-dimensional attribute database uses individual plants or afforestation plots as the smallest management unit. Using the information in the multi-dimensional attribute database, a dynamic three-dimensional green volume voxel model is generated in the geographic information system. This model can intuitively reflect the spatial distribution of national greening resources. Through the three-dimensional green volume voxel model, the system calculates the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region and stores this value as a key indicator in the ecological value assessment table. Based on the ecological value assessment table, the planning decision engine is invoked. This engine, combined with the preset national green coverage rate target, generates a list of suggestions for replanting or renovation in low-potential areas, thereby completing the transformation from data to management decisions.

[0021] In one embodiment of the present invention, the method deploys an ecological sensing network composed of multi-source sensors within the geographic space of the target administrative region. This network is responsible for collecting surface vegetation physiological data and soil environmental data. The ecological sensing network transmits the collected raw data to a data processing center, which performs noise reduction, interpolation preprocessing, standardization, and coordinate system transformation on the data to form a standardized basic ecological dataset. Based on the standardized basic ecological dataset, the system constructs a multi-dimensional attribute database including tree species type, forest age, stand density, and site conditions. The multi-dimensional attribute database uses a single plant or afforestation plot as the smallest management unit. Subsequently, using the information in the multi-dimensional attribute database, a dynamic three-dimensional green volume voxel model is generated in the geographic information system. This model can intuitively reflect the spatial distribution of national greening resources. Through the three-dimensional green volume voxel model, the system calculates the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region and stores this value as a key indicator in the ecological value assessment table. Finally, based on the ecological value assessment table, the planning decision engine is invoked. This engine, combined with the preset national green coverage rate target, generates a list of replanting or renovation suggestions for low-potential areas, thereby completing the transformation from data to management decisions.

[0022] In practical implementation, after the ecological sensing network composed of multi-source sensors completes data acquisition, the network transmits the collected raw data to the data processing center. The data processing center receives a mixed data stream from the ecological sensing network, including multispectral images, soil temperature and humidity, and leaf area index. Cloud masking is performed on the multispectral images to remove invalid pixels caused by weather interference. In some embodiments, the masking process identifies cloud pixels based on specific band reflectance differences in the multispectral images and marks pixels identified as clouds as invalid. Radiometric calibration is performed on the remaining valid pixels, converting the raw digital quantization values ​​recorded by the sensors into physically meaningful reflectance or radiance values ​​to enhance data comparability and accuracy. Missing soil temperature and humidity values ​​are filled using a time-series-based linear interpolation method, and cross-validation is performed using observations from neighboring stations to ensure data continuity and reliability. The time-series-based linear interpolation method can be expressed as the formula:

[0023] in: This represents the interpolated value at time t. and These represent the observations at the previous and next valid time points, respectively. and This refers to the corresponding time point. In practical implementation, when soil temperature data from a sensor is missing at a certain time, the missing value is calculated using the most recent valid observations from that sensor before and after the missing time, based on the formula mentioned above. The calculated interpolated value is then used to fill the gap. This can be understood as cross-validation using observations from neighboring stations, which involves comparing the interpolated data sequence with data sequences from neighboring stations during the same time period, calculating the correlation or difference between the two. If the correlation is below a set threshold or the difference exceeds the allowable range, the interpolated value for the corresponding time period is marked as suspicious, and a secondary check is initiated, or a weighted average of neighboring stations is used for correction. The coordinate systems of data from different sources are uniformly converted to the national geodetic coordinate system. Based on the location of the base station in the ecological sensing network, differential correction is performed on all mobile data collected, eliminating positioning errors and achieving accurate spatial registration of multi-source data. In practical implementation, the base station is a fixed sensor station with known precise geographic coordinates. The positioning information continuously observed by the base station deviates from the actual coordinates. This deviation is calculated in real time and sent as a correction parameter to the mobile data acquisition device.

[0024] It is understandable that the unified coordinate system transformation to the national geodetic coordinate system involves converting the geographic coordinate information of all sensor data, regardless of whether the original coordinate system used is WGS-84, CGCS2000, or a local independent coordinate system, into the target national geodetic coordinate system, such as CGCS2000, through a preset transformation parameter model. The data, after denoising, interpolation, and correction processing, is then formatted according to a predefined field structure. These predefined fields include, but are not limited to, sensor number, acquisition time, geographic coordinates, data type, and numerical value, thereby generating the standardized basic ecological dataset. In some embodiments, the predefined field structure is a fixed database table structure, where each processed data item is filled into the corresponding field according to its category. For example, the sensor number field stores a code identifying the sensor, the acquisition time field stores the UTC time of data acquisition, and the geographic coordinate field stores longitude, latitude, and altitude information.

[0025] In one embodiment of the present invention, after the standardized basic ecological dataset is generated, the system constructs a multidimensional attribute database based on the standardized basic ecological dataset, including tree species type, forest age, stand density, and site conditions. See also... Figure 2The process involves image recognition of a standardized basic ecological dataset, extracting the crown contour and texture features of individual plants. Specifically, the image recognition process uses multispectral images from the standardized basic ecological dataset. The algorithm identifies continuous patches of vegetation in the images and delineates the crown polygons of individual plants using edge detection and segmentation techniques. The tree species type and stand age of individual plants are then inverted using historical archive data, which may include records of national greening projects over the years, seedling procurement lists, or previous survey records. In some embodiments, tree species type inversion is achieved by comparing the extracted crown contour shape and texture features with a pre-established tree species spectral-morphological feature library, while stand age inversion is estimated through regression analysis of crown diameter, tree height, and planting years recorded in historical archives. Based on the inverted individual plant information and canopy closure data measured by the ecological sensing network, the local stand density centered on the individual plant is calculated. The local stand density can be calculated based on the ratio of the number of plants to the crown area within a specific radius, using the following formula:

[0026] Where: D represents the stand density within a circular area with radius R centered on the target plant, N represents the total number of individual plants identified within this circular area, and R is a preset analysis radius, such as 5 meters or 10 meters. Using the elevation, aspect, and soil pH data contained in the standardized basic ecological dataset, the site condition level of an individual plant is determined by a lookup table method. This lookup table method relies on a pre-established site classification standard, which defines site condition level codes corresponding to different elevation ranges, aspect types, and soil pH ranges. For example, an elevation of 300-500 meters, a sunny slope, and a pH of 6.5-7.5 correspond to "Site Class II".

[0027] While constructing a multi-dimensional attribute database, the system also integrates social participation data. This integration process includes opening a public reporting interface, allowing citizens to submit clues about the protection of ancient and famous trees or acts of destroying or occupying green spaces via a mobile application. Optionally, the mobile application provides form filling, location marking, and photo upload functions, allowing citizens to report the specific location and protection status of ancient and famous trees, or to take and upload photos and locations of acts of destroying or occupying green spaces. The clues undergo manual review and on-site verification, converting verified information into structured social participation data. In practice, manual review includes judging the rationality of the reported information and the authenticity of the photos, while on-site verification involves management personnel conducting on-site investigations based on the reported location. The structured social participation data includes the latitude and longitude of the location involved, the event type, and the processing status. Event types include "reporting ancient trees" and "destroying green spaces," while processing statuses include "pending verification," "processed," and "invalid report." The latitude and longitude information in the structured social participation data is matched with a geographic information system to find the corresponding individual plants or afforestation plots. In some embodiments, matching is achieved by calculating the spatial distance between the reported latitude and longitude and the center coordinates of the polygons of plants or afforestation plots recorded in the multidimensional attribute database, and identifying the record with the smallest distance as the matching object. The event type is then added as a special attribute to the corresponding record in the multidimensional attribute database; this attribute record includes information such as "Social Participation - Event Type: Ancient Tree Reporting". Finally, the inverted tree species type, tree species, forest age, calculated stand density, determined site condition level, integrated social participation data, and the spatial coordinates of individual plants are all written into the multidimensional attribute database to form a complete attribute record.

[0028] In one embodiment of the present invention, after the multidimensional attribute library is constructed, the system uses the information in the multidimensional attribute library to generate a dynamic three-dimensional green volume voxel model in the geographic information system. This process extracts the spatial coordinates, tree height, and crown width data of all individual plants from the multidimensional attribute library, where the tree height data is obtained through lidar scanning in the ecological sensing network. Within the computational grid set by the geographic information system, a cubic unit, i.e., a voxel, is generated with the spatial coordinates of the individual plant as the origin, the crown width of the individual plant as the base, and the tree height of the individual plant as the height. In a specific implementation, the crown width data of the individual plant is used to determine the side length of the base of the cubic unit. Assuming the crown width data is recorded as the average crown diameter, the base of the voxel is a square with a side length equal to the average crown diameter, and the height of the voxel is the tree height. Based on the tree species information of the individual plant, the corresponding unit volume green volume coefficient is looked up in a preset green volume conversion coefficient table, and this coefficient is assigned to the voxel. In some embodiments, the preset green volume conversion coefficient table is a database table containing fields for "tree species name" and "green volume coefficient per unit volume," such as a coefficient of 1.2 for "camphor tree" and 1.0 for "ginkgo." The green volume coefficient per unit volume represents the leaf area and other green volume indicators of a tree species per unit volume of plant tissue. Voxels with different green volume coefficients are superimposed and fused in three-dimensional space to form a three-dimensional green volume voxel model that intuitively displays the distribution of green space. The three-dimensional green volume voxel model supports historical backtracking along a timeline. Optionally, the superimposition and fusion process includes accumulating the green volume coefficients of spatially overlapping voxels and visually rendering the voxels, using different colors or transparency to represent the levels of green volume coefficients. The historical backtracking function is implemented by calling voxel model snapshots generated at different time points stored in the database.

[0029] Using a three-dimensional green volume voxel model, the system calculates the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region. The calculation involves spatially dividing the three-dimensional green volume voxel model according to administrative divisions or urban functional zones to obtain several independent analysis units. In specific implementation, spatial division utilizes vector boundary files in a geographic information system, such as street boundaries or polygons, to perform spatial mask analysis on the three-dimensional green volume voxel model, dividing the model into multiple parts consistent with the boundaries; each part is an independent analysis unit. For each analysis unit, the total green volume of all voxels within it is calculated to obtain the total green volume value of the analysis unit. The formula for calculating the total green volume value is:

[0030] Where: G represents the total green value of the analysis unit, and n represents the total number of voxels contained in the analysis unit. This represents the volume of the i-th voxel. This represents the green volume coefficient assigned to the i-th voxel per unit volume. Based on the total green volume value, combined with the carbon sequestration and oxygen release capacity parameters corresponding to the tree species information carried by each voxel, the theoretical total carbon sequestration and oxygen release of the analysis unit is calculated. In some embodiments, the carbon sequestration and oxygen release capacity parameters are obtained from another preset parameter table and are associated with the tree species, such as the parameter "Annual carbon sequestration per unit green volume (kg)". The theoretical total carbon sequestration and oxygen release is calculated by multiplying the total green volume value by the corresponding parameter. A time decay factor is introduced to correct the theoretical total carbon sequestration and oxygen release to reflect changes in the plant growth cycle. It can be understood that the time decay factor is a coefficient set based on the plant growth curve model, which is related to the plant's stand age and is used to simulate changes in the plant's carbon sequestration efficiency at different growth stages. The corrected result is entered as the carbon sequestration and oxygen release potential value of the analysis unit into the ecological value assessment table.

[0031] See Figure 3 This is a map showing the changes in carbon sequestration potential at different stages of the national land greening system. It illustrates the trends in carbon sequestration potential values ​​for five functional zones across the five stages of the national land greening system's construction, reflecting the value enhancement process from data collection to final assessment. In the data collection stage, the initial summary of raw sensory data revealed the greatest differences in potential values ​​among zones, with ecological protection areas and parks already demonstrating their natural greening advantages. In the data processing stage, noise reduction and interpolation improved data quality, resulting in a slight increase in potential values ​​for all zones and enhanced data reliability. The construction of a multi-dimensional attribute library incorporated dimensions such as tree species type, forest age, stand density, and site conditions, further differentiating the potential values ​​of each zone. The refined data from residential and commercial areas began to release their value. After the generation of the three-dimensional green volume voxel model, the spatial distribution of green volume was visualized, and the three-dimensional green volume value of ecological protection areas and parks was fully quantified. With the introduction of time decay factors and tree species carbon sequestration parameters in the carbon sequestration potential assessment, the final potential values ​​were determined. Ecological protection areas remained the core carbon sequestration areas, while residential and commercial areas showed the most significant improvements after human intervention.

[0032] In one embodiment of the present invention, after the ecological value assessment table is generated, the system invokes the planning decision engine based on the ecological value assessment table. The planning decision engine reads the carbon sequestration and oxygen release potential values ​​of each analysis unit recorded in the ecological value assessment table and performs a correlation analysis with the current land green coverage rate of the analysis unit. It can be understood that the land green coverage rate is the area percentage data obtained by back-calculation from previous remote sensing image interpretation or three-dimensional green volume voxel model. The analysis unit is divided into four quadrants: high potential and high energy zone, high potential and low energy zone, low potential and high energy zone, and low potential and low energy zone, where the low potential and low energy zone is marked as a key area of ​​concern. In specific implementation, the division process uses the carbon sequestration and oxygen release potential value of each analysis unit in the ecological value assessment table as the X-axis and the land green coverage rate of each analysis unit as the Y-axis, sets a high potential threshold and a high coverage threshold, divides the scatter plot into four quadrants, and the analysis units falling in the low potential and low coverage quadrants are identified as low potential and low energy zones and automatically marked as key areas of concern. Retrieve site condition data for the key areas of interest and screen candidate tree species suitable for growth under the given site conditions and possessing high carbon sequestration capacity from a plant adaptability database. In some embodiments, the plant adaptability database records the adaptability of different tree species to site conditions such as altitude, slope aspect, and soil pH, as well as their carbon sequestration capacity per unit of green volume. Based on the preset national green coverage rate target, calculate the required increase in green volume for the key areas of interest and determine the planting quantity and layout of candidate tree species accordingly, generating a list of replanting or renovation recommendations. It is understood that the preset national green coverage rate target is a target value set in the city's overall plan, for example, increasing it from the current 30% to 35%. Calculate the total green volume required for the increased green volume:

[0033] Where: T represents the total amount of new green space needed, and A represents the area of ​​the key focus region. This indicates the target land green coverage rate. This indicates the current green coverage rate of the land. This represents the baseline green volume coefficient per unit area. The planning decision engine determines the planting quantity based on the calculated total green volume value T and the average green volume contribution per tree of the candidate tree species. It then combines this with a spatial layout algorithm to generate planting location suggestions, forming a list of replanting or renovation recommendations. See Table 1 for a simplified example of this recommendation list.

[0034] Table 1: Example of a Recommendation List Analysis Unit Number Current carbon sequestration potential Current land green coverage rate Target land green coverage rate Replanting alternative tree species Recommended quantity Spatial layout pattern A-01 Low 25% 35% camphor 50 Scattered planting A-02 Low 28% 35% ginkgo 30 Determinant B-05 Low 20% 35% Chinese scholar tree 80 Group planting The method also includes breaking down the replanting or renovation suggestion list into specific engineering tasks. The breakdown process involves parsing the replanting or renovation suggestion list, converting the requirements regarding tree species, quantity, and layout into specific procurement plans and planting operation instructions. The procurement plan includes the required seedling varieties, specifications, quantities, and budget information, while the planting operation instructions include the specific coordinates of the planting points, planting hole dimensions, planting depth, and other technical requirements. A unique engineering task code is assigned to each procurement plan and planting operation instruction, and this code is linked to the spatial location in the suggestion list. During construction, photos of seedling varieties, planting hole dimensions, and the installation status of support facilities are collected via mobile terminals, and the collected data is associated with the corresponding engineering task code. In practice, the mobile terminal has a dedicated application installed; construction personnel scan the QR code of the engineering task code, upload on-site photos, and fill in data under the corresponding task. Upon project completion, all process data under the engineering task code is compiled into an electronic archive containing construction details.

[0035] See Figure 4 This is a correlation analysis chart showing the relationship between the unit's green coverage rate and carbon sequestration potential, displaying the comparison between the normalized green coverage rate, carbon sequestration potential, and target green coverage rate for 10 analysis units. Currently, only A-04 and A-06 have green coverage rates close to the target value (0.35), while the other 8 units have not met the standard, indicating significant room for improvement in the overall greening construction of the region. A-03, A-05, A-07, and A-09 have significantly higher carbon sequestration potential than the average, but their green coverage rates are far below the target, making them core areas for priority replanting and increasing green volume. A-01, A-02, and A-08 have both low carbon sequestration potential and low green coverage rates, requiring the selection of suitable high-carbon-sequestration tree species based on site conditions and systematic transformation. A-04 is close to the target; maintaining the current green volume and optimizing the tree species structure are necessary to further release its carbon sequestration potential. While A-06 and A-10 meet the national green coverage rate standards, their carbon sequestration potential is insufficient. They need to explore their ecological value by replacing trees with those that have high carbon sequestration potential and increasing forest density.

[0036] In one embodiment of the present invention, after construction is completed, the construction process monitoring platform transmits the accepted data back to update the multidimensional attribute library and the three-dimensional green volume voxel model. The update process obtains the electronic archives of the accepted project tasks from the construction process monitoring platform and extracts information such as seedling variety, actual planting coordinates, and acceptance time from the electronic archives. In specific implementation, the electronic archives are stored in the database of the construction process monitoring platform in the form of a structured data table. The system queries the records corresponding to the project task codes and extracts fields such as "seedling variety," "planting longitude," "planting latitude," and "acceptance date." The extracted seedling variety and coordinate information, combined with the actual tree height and crown width at the corresponding location obtained from the ecological sensing network, are inserted as a new record into the multidimensional attribute library. The actual tree height and crown width obtained from the ecological sensing network can be the latest measurement values ​​obtained within the same growing season after project acceptance, through supplementary scanning of the planting point using lidar or drones. The recalculation mechanism of the 3D green volume voxel model is triggered, adding voxels to the model with the same number as the current replanting or modification, and setting the coordinates, dimensions, and green volume coefficient of the new voxels to match the records in the electronic archive. In some embodiments, the recalculation mechanism refers to calling the calculation module that generates the 3D green volume voxel model, inputting the newly inserted plant records from the multidimensional attribute library, and recalculating and updating the 3D model according to the voxel generation logic. The updated data is then used to re-render the 3D green volume voxel model, ensuring that the state of the 3D green volume voxel model is synchronized with the actual greening status. The re-rendering includes adding, modifying, or deleting corresponding voxel graphic elements in the 3D visualization interface.

[0037] After generating the three-dimensional green volume voxel model, the method also includes a health diagnosis step. This step continuously acquires the latest vegetation index data for each voxel location from the ecological sensing network. The vegetation index data characterizes the chlorophyll content and water status of leaves. In practice, the latest vegetation index data, such as the normalized vegetation index (NVI), is periodically collected and calculated by multispectral sensors in the ecological sensing network. This data is correlated with the spatial location of each voxel in the three-dimensional green volume voxel model. The acquired vegetation index data is compared with the health standard values ​​for the same tree species and forest age to calculate a health deviation. The health standard values ​​are pre-determined through experiments or historical data statistics, representing the normal range of vegetation indices for different tree species and growth stages under healthy conditions. The formula for calculating the health deviation is:

[0038] Where: B represents the degree of health deviation. This represents the current vegetation index data value obtained from the ecological sensing network. This represents the health standard value for the same tree species and forest age. When the health deviation exceeds the set warning threshold, the voxel is automatically highlighted in the geographic information system, and a warning work order containing the specific location and anomaly type is generated. In some embodiments, the set warning threshold is a percentage, such as 20%. When the calculated health deviation B is greater than 0.2, a warning is triggered. The warning work order includes fields such as "Warning Voxel ID," "Location Coordinates," "Associated Tree Species," "Current Vegetation Index," "Health Standard Value," "Calculated Deviation," and "Suggested Verification Items." The warning work order is pushed to the construction process monitoring platform, where maintenance personnel perform targeted rejuvenation operations based on the warning work order. Rejuvenation operations include, but are not limited to, irrigation, fertilization, and pest and disease control. Optionally, the construction process monitoring platform assigns the warning work order to a specific person in charge, who receives the task via a mobile terminal and processes it on-site. The results of the operation will be fed back to update the multidimensional attribute database. For example, after the rejuvenation operation is completed, the treatment measures and treatment time will be recorded, and this information will be added as a status update to the corresponding plant attribute record in the multidimensional attribute database to form a data closed loop of monitoring-early warning-maintenance.

[0039] See Figure 5 This is a 24-hour time-series map of ecological sensing data, showcasing the temporal changes of core environmental parameters during the data collection phase of the national land greening system. These parameters include soil temperature, soil moisture, leaf area index (LAI), and normalized difference vegetation index (NDVI), reflecting the dynamic response relationship between vegetation and the soil environment throughout the day. During the period of rising soil temperature, soil moisture decreased synchronously, reflecting the temperature-driven soil moisture evaporation process. LAI and NDVI maintained high fluctuations throughout the day, closely coinciding with the period of photosynthetically active radiation, reflecting the diurnal physiological activity of vegetation. All parameters showed continuous and smooth changes, without significant jumps or missing values, indicating that the denoising and interpolation processes during the data processing phase were effective and the data was highly reliable. Fluctuations in the NDVI can serve as an early warning signal for vegetation health; deviations from the standard values ​​for the same tree species and age will trigger the calculation of health deviation.

[0040] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for managing data information based on a national land greening system, characterized in that, The method includes: Within the geographical space of the target administrative region, an ecological sensing network consisting of multi-source sensors is deployed. This ecological sensing network is responsible for collecting surface vegetation physiological data and soil environmental data. The raw data collected by the ecological sensing network is transmitted to the data processing center, where the data processing center performs noise reduction, interpolation preprocessing, standardization, and coordinate system transformation on the data to form a standardized basic ecological dataset. Based on the standardized basic ecological dataset, a multi-dimensional attribute database is constructed, which includes tree species type, forest age, forest stand density and site conditions. The multi-dimensional attribute database takes a single plant or afforestation plot as the smallest management unit. Using the information in the multidimensional attribute library, a dynamic three-dimensional green volume voxel model is generated in the geographic information system. The three-dimensional green volume model reflects the spatial distribution of land greening resources. Using the three-dimensional green volume voxel model, the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region are calculated, and the carbon sequestration and oxygen release potential values ​​are stored as key indicators in the ecological value assessment table. Based on the ecological value assessment table, the planning decision engine is invoked. The planning decision engine, in conjunction with the preset land greening coverage rate target, generates a list of replanting or renovation suggestions for low-potential areas.

2. The method for managing data information based on the land greening system as described in claim 1, characterized in that, The raw data collected by the ecological sensing network is transmitted to the data processing center, where the data processing center performs noise reduction, interpolation preprocessing, standardization, and coordinate system transformation on the data to form a standardized basic ecological dataset, including: Receive a mixed data stream uploaded by the ecological sensing network, which includes multispectral images, soil temperature and humidity, and leaf area index; The multispectral image is subjected to cloud masking to remove invalid pixels caused by weather interference, and the remaining pixels are radiometrically calibrated. For the missing values ​​of soil temperature and humidity, a time-series-based linear interpolation method was used to fill them in, and cross-validation was performed using observations from neighboring stations. The coordinate systems of data from different sources are uniformly converted to the national geodetic coordinate system, and differential correction is performed on the data collected by all mobile terminals based on the location of the reference station in the ecological sensing network. The data, after denoising, interpolation, and skew correction, is formatted according to a predefined field structure to generate the standardized basic ecological dataset.

3. The data information management method based on the land greening system as described in claim 2, characterized in that, Based on the standardized basic ecological dataset, a multidimensional attribute database is constructed, including tree species type, forest age, stand density, and site conditions, including: Image recognition is performed on the standardized basic ecological dataset to extract the crown outline and texture features of individual plants, and the tree species type and forest age of the individual plants are inverted by combining historical archive data. Based on the inverted individual plant information and combined with the canopy closure data measured by the ecological sensing network, the local stand density centered on the individual plant is calculated. Using the elevation, aspect, and soil pH data contained in the standardized basic ecological dataset, the site condition level of the individual plant is determined by a lookup table method. The tree species type, tree species, forest age, calculated stand density, determined site condition level, and spatial coordinates of the individual plant are all written into the multidimensional attribute database to form a complete attribute record.

4. The method for managing data information based on the land greening system as described in claim 3, characterized in that, Using the information in the aforementioned multidimensional attribute library, a dynamic three-dimensional green volume voxel model is generated in the geographic information system, including: The spatial coordinates, tree height, and crown width of all individual plants are extracted from the multidimensional attribute library, wherein the tree height data is obtained by lidar scanning in the ecological sensing network. Within the computational grid set by the geographic information system, cubic units, or voxels, are generated with the spatial coordinates of a single plant as the origin, its crown width as the base, and its tree height as the height. Based on the tree species information of a single plant, the corresponding green volume coefficient per unit volume is found in the preset green volume conversion coefficient table and assigned to the voxel. Voxels with different green volume coefficients are superimposed and fused to form a three-dimensional green volume voxel model that intuitively displays the distribution of green space. The three-dimensional green volume voxel model supports historical backtracking along a time axis.

5. The method for managing data information based on the land greening system as described in claim 4, characterized in that, Using the aforementioned three-dimensional green volume voxel model, the carbon sequestration and oxygen release potential values ​​of different functional zones within the target administrative region are calculated, and these potential values ​​are stored as key indicators in the ecological value assessment table, including: The three-dimensional green volume voxel model is spatially divided according to administrative divisions or urban functional areas to obtain several independent analysis units; For each analysis unit, the total green amount of all voxels within it is calculated to obtain the total green amount value of the analysis unit; Based on the total green volume value, and combined with the carbon sequestration and oxygen release capacity parameters corresponding to the tree species information carried by each voxel, the theoretical total carbon sequestration and oxygen release of the analysis unit is calculated. A time decay factor is introduced to correct the theoretical total carbon sequestration and oxygen release to reflect the changes in the plant growth cycle. The corrected result is then recorded as the carbon sequestration and oxygen release potential value of the analysis unit in the ecological value assessment table.

6. The method for managing data information based on the national land greening system as described in claim 5, characterized in that, Based on the ecological value assessment table, the planning decision engine is invoked. This engine, combined with a preset national green coverage rate target, generates a list of replanting or renovation suggestions for low-potential areas, including: Read the carbon sequestration and oxygen release potential values ​​of each analysis unit recorded in the ecological value assessment table, and perform a correlation analysis with the current land green coverage rate of the analysis unit; The analysis unit is divided into four quadrants: high potential high energy region, high potential low energy region, low potential high energy region, and low potential low energy region, among which the low potential low energy region is marked as the key area of ​​focus; Retrieve site condition data for the key areas of interest and screen candidate tree species that are suitable for growth under the site conditions and have high carbon sequestration capacity from the plant susceptibility database. Based on the preset national greening coverage target, the amount of new green space needed in the key areas of concern is calculated, and the planting quantity and layout of candidate tree species are determined accordingly, generating the list of proposed replanting or renovation.

7. A method for managing data information based on a land greening system as described in claim 6, characterized in that, Also includes: The list of replanting or renovation suggestions is broken down into specific engineering tasks and distributed to the construction process monitoring platform, which records the entire process data from the arrival of seedlings to final acceptance. The construction process monitoring platform will transmit the data after acceptance to update the multidimensional attribute library and the three-dimensional green volume voxel model, thus completing a data loop. The proposed replanting or renovation list is broken down into specific engineering tasks and distributed to the construction process monitoring platform. This platform records data from the arrival of seedlings to final acceptance, including: Analyze the proposed list of replanting or renovation suggestions, and transform the requirements regarding tree species, quantity, and layout into specific procurement plans and planting operation guidelines; Assign a unique engineering task code to the procurement plan and planting operation instructions, and bind the engineering task code to the spatial location in the suggestion list; During construction, photos of seedling varieties, planting hole dimensions, and installation status of support facilities are collected via mobile terminals, and the data is associated with the corresponding project task code. When the project is completed, all process data under the project task code will be compiled to form an electronic file containing construction details, which will be stored in the construction process monitoring platform.

8. The method for managing data information based on the land greening system as described in claim 7, characterized in that, The construction process monitoring platform will transmit the data after acceptance to update the multidimensional attribute library and the three-dimensional green volume voxel model, including: Obtain electronic files of the accepted projects from the construction process monitoring platform, and extract information such as seedling varieties, actual planting coordinates, and acceptance time. The extracted seedling variety and coordinate information, combined with the actual tree height and crown width obtained from the ecological sensing network, are inserted as a new record into the multidimensional attribute library. Trigger the recalculation mechanism of the three-dimensional green volume voxel model, add voxels to the model with the same number as the current replanting or modification, and set the coordinates, size and green volume coefficient of the new voxels to be consistent with the records in the electronic archive. The 3D green volume voxel model was re-rendered using the updated data to keep the model's state synchronized with the actual greening status on the ground.

9. A method for managing data information based on a land greening system as described in claim 8, characterized in that, After generating the three-dimensional green voxel model, a health assessment step is also included: The latest vegetation index data for each voxel is continuously acquired from the ecological sensing network. The vegetation index data is used to characterize the chlorophyll content and water status of the leaves. The obtained vegetation index data is compared with the health standard values ​​of the same tree species and forest age to calculate a health deviation degree. When the health deviation exceeds the set warning threshold, the voxel is automatically highlighted in the geographic information system, and a warning work order containing the specific location and anomaly type is generated. The warning work order is pushed to the construction process monitoring platform, where maintenance personnel perform targeted restoration work based on the warning work order, and the work results are sent back to update the multi-dimensional attribute library.

10. A method for managing data information based on a land greening system as described in claim 9, characterized in that, In constructing the multidimensional attribute library, social participation data was also integrated, including: Open a public reporting interface to allow citizens to submit clues about the protection of ancient and famous trees or acts of destroying or occupying green spaces through a mobile application; The clues are manually reviewed and verified on-site. The verified information is then converted into structured social participation data, which includes the latitude and longitude of the location involved, the type of event, and the status of the process. The latitude and longitude information in the social participation data is matched with the geographic information system to find the corresponding individual plant or afforestation plot, and the event type is added as a special attribute to the corresponding record in the multidimensional attribute library. When generating the list of replanting or renovation suggestions, if there is unprocessed social participation data in a certain area, the planning operation for the unprocessed area will be suspended until the social participation data is processed.

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