Land space planning implementation evaluation and early warning system for multi-source remote sensing data coupling

Abstract

The invention relates to the field of territorial planning, in particular to a territorial space planning implementation evaluation and early warning system for multi-source remote sensing data coupling, which integrates multi-source data through a remote sensing surveying and mapping module, automatically identifies and extracts multi-dimensional feature data, and automatically compares the multi-dimensional feature data with a planning target, so that subjective deviation caused by human intervention is avoided; the method also achieves the synchronization and precise verification of multiple planning elements, achieves the coupling of multi-source remote sensing data, the automatic proofreading analysis and the total element coverage of evaluation, and also achieves the calculation of the standard growth rate and the recognition of the standard change types through the introduction of a timeliness evaluation module, not only pays attention to the result of single evaluation, but also achieves the recognition of the standard change types through the comparative analysis of adjacent time periods. And the crossing from static evaluation to dynamic trend early warning is realized, and sufficient early warning is ensured.

Description

Technical Field

[0001] This invention relates to the field of land planning, specifically to a land spatial planning implementation assessment and early warning system based on multi-source remote sensing data coupling. Background Technology

[0002] With the establishment and improvement of the national spatial planning system, the routine and precise monitoring, evaluation and early warning of the implementation of the plan has become a key link to ensure the realization of the planning objectives. In the existing technology, the evaluation of the implementation of the plan mostly relies on manual field surveys, statistical annual reports and comparative analysis of limited remote sensing images. Referring to the technical solution of patent application CN202510328302X, multi-source environmental monitoring data is used to improve the accuracy of monitoring and evaluation.

[0003] However, its data sources are singular and the update cycle is long, resulting in serious lag in the assessment results, which cannot meet the needs of dynamic supervision. Similarly, the assessment process relies heavily on manual interpretation and processing, which is inefficient and subjective, making it difficult to guarantee the objectivity and consistency of the assessment results. Moreover, conventional assessment systems mostly focus on static, single-element compliance judgments, such as only checking whether the scale of construction land exceeds the standard, lacking comprehensive and trend analysis of the coordinated implementation of multiple planning elements, and even more unable to capture and warn of the dynamic changes in the implementation effect. Therefore, this invention proposes a solution. Summary of the Invention

[0004] This invention integrates multi-source data through a remote sensing mapping module, automatically identifies and extracts multi-dimensional feature data such as terrain, buildings, and greening, and automatically compares it with planning targets. This not only avoids subjective biases caused by human intervention but also achieves synchronous and accurate verification of multiple planning elements. It realizes full-element coverage of coupling and automated calibration analysis and evaluation of multi-source remote sensing data. At the same time, by introducing a timeliness assessment module, it not only focuses on the results of a single assessment but also calculates the compliance growth rate and identifies the types of compliance changes through comparative analysis of adjacent time periods. This achieves a leap from static assessment to dynamic trend early warning and generates dynamic early warnings in a timely manner, ensuring that the warnings have sufficient lead time. Therefore, this invention proposes a land spatial planning implementation assessment and early warning system based on multi-source remote sensing data coupling.

[0005] The objective of this invention can be achieved through the following technical solution: a land spatial planning implementation assessment and early warning system for multi-source remote sensing data coupling, including a remote sensing mapping module, wherein the remote sensing mapping module is used to acquire multi-source remote sensing data and to identify and analyze the multi-source remote sensing data to obtain feature data for verification;

[0006] A planning port interface module, which obtains land planning information through the cloud;

[0007] The verification and analysis module acquires feature data and land planning information for verification, compares the feature data and land planning information, and obtains the land implementation compliance rate.

[0008] The timeliness assessment module obtains land planning information through the cloud, extracts progress information from the land planning information, and compares the progress information with the real-time compliance rate of the land to obtain the progress assessment result.

[0009] The assessment and early warning module performs comprehensive calculations based on the real-time compliance and progress assessment results of the land to obtain a real-time land rating. Based on the land implementation rating, it is classified into different levels of early warning and outputs the classified early warnings through the network.

[0010] In a preferred embodiment of the present invention, the remote sensing and mapping module identifies the following data: terrain identification data, building-specific identification data, and greening identification data. The terrain identification data includes terrain height and water area, the building-specific identification data includes building height and building density, and the greening identification data includes greening area and greening type.

[0011] The remote sensing and mapping module performs coordinate system registration on different remote sensing data to obtain comprehensive ground mapping data.

[0012] As a preferred embodiment of the present invention, the remote sensing and mapping module obtains feature data for verification by analyzing comprehensive ground surveying data as follows: it extracts settlement velocity and water area change ratio from terrain identification data, obtains building scale from building specificity identification data, and obtains green coverage rate, green change rate, and green species library from greening identification data.

[0013] In a preferred embodiment of the present invention, the planning port docking module acquires land planning information, which includes building planning, settlement control planning, water area planning and greening planning, and each plan includes planning objectives and planning implementation time.

[0014] In a preferred embodiment of the present invention, the process by which the verification and analysis module compares the feature data and land planning information used for verification is as follows:

[0015] S1: By comparing and determining whether the terrain settlement rate is within the set settlement control plan, the settlement is judged to be qualified or abnormal.

[0016] S2: By comparing the building scale and building plan, determine whether the building is normal or abnormal;

[0017] S3: By comparing the water area planning and the proportion of water area changes, determine whether the water area is normal or abnormal. Abnormal water area includes water area shrinkage or water area flooding.

[0018] S4: By comparing greening planning and greening identification data, the results of the judgment are obtained respectively: greening meets the standards or is insufficient, greening shrinks or expands, and greening species are single or qualified.

[0019] S5: The calibration and analysis module performs statistics on normal and abnormal results, calculates the proportion of normal results in the total results, and obtains the land implementation compliance rate of the region.

[0020] In a preferred embodiment of the present invention, the calibration and analysis module sends the land implementation compliance rate to the calibration and evaluation platform, which then forwards it to the evaluation and early warning module. After obtaining the land implementation compliance rate, the evaluation and early warning module compares the land implementation compliance rate with multiple set threshold levels to determine the level to which the land implementation compliance rate belongs, and generates early warning signals of different levels according to the level.

[0021] In a preferred embodiment of the present invention, after the verification analysis module sends the land implementation compliance rate to the verification evaluation platform each time, the timeliness evaluation module obtains and records the land implementation compliance rate through the verification platform, and records the time of obtaining the land implementation compliance rate each time.

[0022] In a preferred embodiment of the present invention, the timeliness assessment module compares the compliance rates of adjacent land parcels to obtain progress assessment results. These progress assessment results include the compliance rate growth rate and the types of compliance changes. Specifically:

[0023] The timeliness assessment module calculates the difference in compliance levels of adjacent land, and uses the result of the difference calculation as the growth rate. The growth rate is divided into positive compliance growth rate and negative compliance growth rate.

[0024] The timeliness assessment module obtains all the types of normal results in the compliance of adjacent land, compares them, and records the different types of results in the comparison as compliance change types.

[0025] The timeliness assessment module sends the compliance growth rate and the types of compliance changes to the assessment and early warning module.

[0026] In a preferred embodiment of the present invention, when the evaluation and early warning module obtains the negative growth rate of compliance, it generates a dynamic early warning. After generating the dynamic early warning, the evaluation and early warning module generates early warnings for the missing categories in the categories of compliance changes.

[0027] Compared with the prior art, the beneficial effects of the present invention are:

[0028] 1. In this invention, the remote sensing and mapping module integrates multi-source data such as optical and radar data, automatically identifies and extracts multi-dimensional feature data such as terrain, buildings, and greening, and automatically compares them with the planning targets obtained by the planning port interface module. This not only avoids subjective bias caused by human intervention, but also achieves synchronous and accurate verification of planning elements such as settlement control, building scale, water area changes, and greening status. Finally, through the quantitative indicator of land implementation compliance, it realizes the coupling, automated calibration analysis, and full-element coverage of multi-source remote sensing data.

[0029] 2. In this invention, by introducing a timeliness assessment module, not only is the result of a single assessment considered, but also the compliance rate of land implementation over time is recorded. Comparative analysis of adjacent time periods is conducted to calculate the compliance growth rate and identify the types of compliance changes. This achieves a leap from static assessment to dynamic trend early warning, enabling the system to keenly capture the dynamic trend of deteriorating implementation effects and generate dynamic early warnings in a timely manner, ensuring that the early warnings have sufficient lead time.

[0030] 3. In this invention, the comprehensive land compliance rate is compared with multiple threshold levels to generate early warning signals of different levels, thereby realizing hierarchical risk management. At the same time, when faced with dynamic early warnings, the system can further correlate and output specific types of compliance changes, directly pointing out the problem. This makes the early warning information not only have a warning function, but also accurately locate the problem, greatly improving the pertinence and decision-making efficiency of regulatory actions, and significantly enhancing the pertinence and decision support effectiveness of early warning information. Attached Figure Description

[0031] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings.

[0032] Figure 1 This is a system block diagram of the present invention;

[0033] Figure 2 This is a system flowchart of the present invention. Detailed Implementation

[0034] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0035] Example 1: Please refer to Figure 1 - Figure 2As shown, the land spatial planning implementation assessment and early warning system for multi-source remote sensing data coupling includes a remote sensing mapping module, a planning port docking module, a verification and analysis module, a timeliness assessment module, and an assessment and early warning module.

[0036] The remote sensing and mapping module can acquire multi-source remote sensing data, including optical remote sensing data, radar remote sensing data, hyperspectral remote sensing data, and lidar remote sensing data. By using multi-source data in a coordinated manner, it can effectively overcome the limitations of a single data source in terms of weather, time phase, and resolution. For example, radar data can penetrate clouds and rain to make up for the lack of optical data and ensure the continuity of monitoring; lidar data provides high-precision three-dimensional information, laying the foundation for the verification of fine indicators such as building volume ratio, thus forming an all-weather, three-dimensional data sensing network.

[0037] The remote sensing and mapping module identifies the acquired remote sensing data, including terrain identification data, building-specific identification data, and greening identification data. Specifically, terrain identification data includes terrain height and water area; building-specific identification data includes building height and building density; and greening identification data includes greening area and greening species. Based on the ability to identify multiple elements simultaneously, the system can simultaneously acquire land cover, three-dimensional morphology, and ecological component information in a single processing, avoiding the data inconsistencies and time asynchrony problems caused by itemized surveys in traditional methods, and providing a unified and coordinated data foundation for subsequent comprehensive assessment.

[0038] The remote sensing and mapping module performs coordinate system registration on different remote sensing data, thereby registering the terrain identification data, building-specific identification data, and greening identification data. This allows for the simultaneous acquisition of terrain identification data, building-specific identification data, and greening identification data for a region, which are then recorded as comprehensive ground mapping data for that region. Under a unified spatiotemporal reference, this enables precise spatial correlation of geographic elements with different attributes, forming a "digital twin" that can fully represent the current state of the region. This allows subsequent analysis to be based on a real and comprehensive spatial scene.

[0039] The remote sensing and mapping module analyzes comprehensive ground survey data, extracts settlement velocity and water area change ratio from terrain identification data, obtains building scale from building specificity identification data, and obtains green coverage rate, green change rate and green species library from greening identification data. The analysis results are recorded as feature data for verification.

[0040] The planning port interface module acquires land planning information, which includes building planning, settlement control planning, water area planning, and greening planning. Each plan contains planning objectives and implementation timelines. By structurally reading planning objectives and timelines, an authoritative evaluation standard is established for subsequent automatic comparison, ensuring the legality and compliance of the assessment work. This is the logical premise for achieving automated assessment.

[0041] After obtaining land planning information, the verification and analysis module compares the feature data used for verification with the land planning information. Specifically:

[0042] The settlement rate is compared to determine whether it is within the set settlement control plan. If it is within the settlement control plan, the settlement is deemed qualified. If the settlement rate is outside the settlement control plan, the settlement is deemed abnormal.

[0043] By comparing the building size with the building plan, if the building size conforms to the building plan, the building is judged to be normal; if the building size exceeds the building plan, the building is judged to be abnormal.

[0044] By comparing the water area planning and the water area change ratio, if the water area change ratio is within the set water area planning range, the water area is judged to be normal; if the water area change ratio exceeds the set water area planning range, the water area is judged to be abnormal. Water area abnormality includes water area shrinkage or water area flooding.

[0045] By comparing the greening plan, greening coverage rate, greening change rate, and greening species database, the results of the judgments are obtained respectively: greening meets the standards or is insufficient, greening shrinks or expands, and greening species are single or qualified.

[0046] The verification and analysis module will count settlement compliance, normal building conditions, normal water area conditions, and greening compliance as normal results, and will count abnormal settlement, abnormal building conditions, abnormal water area conditions, and insufficient greening as abnormal results.

[0047] The verification and analysis module statistically analyzes normal and abnormal results, calculates the proportion of normal results in the total results, and obtains the land implementation compliance rate of the region.

[0048] The verification and analysis module sends the land implementation compliance rate to the verification and evaluation platform, which then forwards it to the evaluation and early warning module. After obtaining the land implementation compliance rate, the evaluation and early warning module compares the land implementation compliance rate with multiple set threshold levels to determine the level to which the land implementation compliance rate belongs, and generates early warning signals of different levels according to the level. The multiple threshold levels include at least three levels: low, medium, and high. The early warning signals corresponding to each threshold level are high-risk warning, low-risk warning, and no warning, respectively, thereby completing the evaluation of the planning implementation effect.

[0049] By setting preset threshold levels, the system can automatically respond differently to different levels of implementation deviations. For example, it can initiate emergency inspections for high-risk warning areas, focus on low-risk warning areas, and reduce the frequency of inspections for areas without warnings. This effectively optimizes the allocation of regulatory resources, concentrates management efforts on the most critical areas, and realizes the transformation from homogeneous supervision to intelligent and precise supervision.

[0050] Example 2: Please refer to Figure 1 - Figure 2 As shown, after the verification and analysis module sends the land implementation compliance rate to the verification and evaluation platform each time, the timeliness evaluation module obtains and records the land implementation compliance rate through the verification platform, and records the time of obtaining the land implementation compliance rate each time, thus giving the system the ability to remember. By continuously recording the evaluation results each time, a time series dataset of the planning implementation status is constructed, laying the data foundation for dynamic analysis.

[0051] The timeliness assessment module compares the compliance rates of adjacent land parcels to obtain progress assessment results. These results include the compliance rate growth rate and the types of changes in compliance. Specifically:

[0052] The timeliness assessment module records the compliance rate of adjacent land as the original compliance rate and the new compliance rate according to the acquisition time. Then, it calculates the difference between the new compliance rate and the original compliance rate and uses the result of the difference calculation as the growth rate. If the new compliance rate is greater than or equal to the original compliance rate, it is recorded as a positive compliance growth rate. If the original compliance rate is greater than the new compliance rate, it is recorded as a negative compliance growth rate.

[0053] The timeliness assessment module obtains all normal results in the compliance level of adjacent land and compares them. It records the missing types that appear in the original compliance level but not in the new compliance level, and records the new types that appear in the new compliance level but not in the original compliance level. The timeliness assessment module records the missing types and the new types as compliance change types.

[0054] The timeliness assessment module sends the compliance growth rate and the types of compliance changes to the assessment and early warning module;

[0055] The assessment and early warning module generates a dynamic early warning when it detects a negative growth rate in compliance with the target, but does not react when it detects a positive growth rate in compliance with the target.

[0056] After generating a dynamic warning, the assessment and early warning module will generate a warning for the missing category among the categories of compliance changes.

[0057] The dynamic early warning logic forms the core of the system's forward-looking early warning function, upgrading simple status quo assessment to judgment of development trends. When the system issues a dynamic early warning and specifies the type of deficiency, it can clearly warn of different implementation problems existing in different areas, thereby obtaining early warning information that combines trend judgment and problem identification, which greatly improves the system's early warning lead time and accuracy.

[0058] Thresholds, preset values, preset ranges, etc. are set for result comparison and analysis to determine whether they are good or bad. The value of these thresholds is determined by a combination of large-scale model analysis of sample data and human experience. They can also be adjusted appropriately based on seasonal or common-sense influences.

[0059] Furthermore, the settings for weighting ratios, influence factors, etc., are based on the magnitude of each parameter's influence on the results. The specific values ​​are allocated to ultimately reflect the impact on the results. The settings for input and storage are also determined by a combination of large-scale model analysis of sample data and human experience. Appropriate adjustments can also be made based on seasonal or rational influence conditions.

[0060] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A land space planning implementation evaluation and early warning system oriented to multi-source remote sensing data coupling, characterized in that, The remote sensing surveying and mapping module is configured to acquire multi-source remote sensing data, and to perform identification analysis on the multi-source remote sensing data to obtain feature data for verification. The planning port docking module is configured to acquire land planning information through the cloud. The proofreading and analysis module is configured to acquire the feature data for verification and the land planning information, and to compare the feature data and the land planning information to obtain a land implementation compliance degree. The timeliness evaluation module is configured to acquire land planning information through the cloud, to extract progress information in the land planning information, to compare the progress information with a real-time land compliance degree, and to obtain a progress evaluation result. The evaluation and early warning module is configured to perform comprehensive calculation on the real-time land compliance degree and the progress evaluation result to obtain a real-time land rating, to perform grading based on the land implementation rating, to obtain graded early warnings of different levels, and to output the graded early warnings through a network.

2. The land space planning implementation evaluation and early warning system oriented to multi-source remote sensing data coupling according to claim 1, characterized in that, The remote sensing surveying and mapping module is configured to identify terrain identification data, building specificity identification data, and greening identification data, wherein the terrain identification data includes terrain height and water area, the building specificity identification data includes building height and building density, and the greening identification data includes greening area and greening types. The remote sensing surveying and mapping module is configured to perform coordinate system registration on different remote sensing data to obtain comprehensive ground surveying and mapping data.

3. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, The remote sensing surveying and mapping module is configured to analyze the comprehensive ground surveying and mapping data to obtain the feature data for verification, including extracting a subsidence speed and a water area change ratio from the terrain identification data, obtaining a building scale from the building specificity identification data, and obtaining a greening coverage rate, a greening change rate, and a greening type library from the greening identification data.

4. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, The planning port docking module is configured to acquire land planning information, wherein the land planning information includes building planning, subsidence control planning, water area planning, and greening planning, and each type of planning includes a planning target and a planning implementation time.

5. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, The proofreading and analysis module is configured to compare the feature data for verification and the land planning information, including: S1: determining whether a terrain subsidence speed is within a set subsidence control planning to determine whether subsidence is qualified or abnormal; S2: comparing a building scale with building planning to determine whether a building is normal or abnormal; S3: comparing a water area planning with a water area change ratio to determine whether a water area is normal or abnormal, wherein water area abnormality includes water area shrinkage or water area flooding; S4: comparing greening planning with greening identification data to determine whether greening is qualified or insufficient, whether greening is shrinking or expanding, and whether greening types are single or qualified; S5: the proofreading and analysis module is configured to count normal results and abnormal results, to calculate a proportion of the normal results in total results, and to obtain a land implementation compliance degree of an area.

6. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, The correction analysis module sends the land implementation compliance scale to the correction evaluation platform, which is then forwarded to the evaluation warning module. After obtaining the land implementation compliance scale, the evaluation warning module compares it with the set threshold levels, determines the level to which the land implementation compliance scale belongs, and generates different levels of warning signals according to the level.

7. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, After the correction analysis module sends the land implementation compliance scale to the correction evaluation platform each time, the timeliness evaluation module obtains the land implementation compliance scale through the correction platform and records it, and records the time of obtaining the land implementation compliance scale each time.

8. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, The timeliness evaluation module compares adjacent land implementation compliance scales to obtain progress evaluation results, including compliance growth rate and compliance change type. Specifically: The timeliness evaluation module calculates the difference between adjacent land implementation compliance scales, and uses the result of the difference calculation as the growth rate. The growth rate is divided into compliance positive growth rate and compliance negative growth rate. The timeliness evaluation module obtains the types of all normal results in adjacent land implementation compliance scales and compares them. Different result types in the comparison are recorded as compliance change types. The timeliness evaluation module sends the compliance growth rate and compliance change type to the evaluation warning module.

9. The multi-source remote sensing data coupling-oriented land space planning implementation evaluation and early warning system according to claim 1, characterized in that, When the evaluation warning module obtains the compliance negative growth rate, it generates a dynamic warning. After generating the dynamic warning, the evaluation warning module generates a warning for the missing type in the compliance change type.

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