Blockchain-based flood detention basin ecological compensation execution traceability processing method and system

Abstract

The present application relates to the technical field of performing tracing, in particular to a flood storage area ecological compensation execution tracing processing method and system based on a block chain, comprising the following steps: extracting remote sensing data to generate a delay factor list, identifying an ecological trigger node to generate a calibrated node data group, constructing an account path structure to extract a boundary node, generating a permission mapping and a responsibility signature block, and writing into a responsibility tracking chain structure area. In the present application, the compensation disbursement behavior is logically accounted for through the time stamp and the hash record, the node tracking and continuity inspection of the fund disbursement path are realized, the time jump is identified and the boundary node is calibrated, then the operation permission matching is performed in combination with the contract permission table, the responsibility tracking structure chain is constructed step by step, the responsibility binding of the fund behavior node and the whole process signature trace of the disbursement behavior are effectively realized, the authenticity discrimination ability and the operation responsibility tracing ability of the compensation execution are enhanced, and the verification precision and the process integrity of the fund execution path are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of execution tracing, and in particular to a blockchain-based flood storage area ecological compensation execution tracing processing method and system. BACKGROUND

[0002] The technical field of execution tracing mainly focuses on the dynamic monitoring, credible verification and historical restoration of the whole life cycle of policy execution, fund flow, resource allocation and other processes, covering chain management of multiple links such as data collection, event recording, contract execution and result feedback. This field widely uses core technologies such as blockchain, smart contract, multi-source data fusion, distributed ledger and consensus mechanism to realize the automatic processing, compliance verification and whole-process traceability of various execution behaviors. Its technical core lies in building an operation chain that is tamper-proof, verifiable and traceable, ensuring that the responsibility of key nodes can be defined, the operation can be proved, and the process can be supervised, so as to improve the transparency, credibility and response efficiency of governance behavior. Execution tracing technology is suitable for government governance, financial expenditure, ecological compensation, supply chain management, digital justice and other industry scenarios, and has an important supporting role in national supervision, social credit system construction and cross-subject collaborative management.

[0003] Among them, the ecological compensation execution tracing processing method for flood storage area is aimed at building an ecological compensation execution closed-loop mechanism suitable for the ecological governance scene of flood storage area. By integrating remote sensing monitoring, ecological index modeling and blockchain smart contract, it realizes the whole-process on-chain tracing and dynamic regulation of the ecological compensation fund distribution process. Its purpose is to improve the execution efficiency and verifiability of ecological compensation behavior in flood storage area, ensure that compensation is based on clear standards, is quantifiable, contract execution is automated, and fund flow is traceable, and ultimately realize the precise coupling between ecological governance effect and financial incentive mechanism, and enhance the standardization, transparency and continuous effectiveness of governance.

[0004] Traditional tracing methods do not build a clear time sequence response mapping mechanism between monitoring nodes and fund allocation nodes, resulting in a lack of time logic-based node identification method in compensation triggering and fund path verification, which makes it difficult to accurately locate the responsible node when there is a time sequence disturbance in remote sensing monitoring, and also makes it difficult to verify the authority range based on operation records, so that the responsibility division and boundary control in the fund allocation process lack structured support, reducing the ability to identify abnormal situations in the fund allocation chain. SUMMARY

[0005] The purpose of the present application is to solve the shortcomings in the prior art, and to propose a blockchain-based flood storage area ecological compensation execution tracing processing method and system.

[0006] In order to achieve the above object, the application adopts the following technical scheme: the blockchain-based flood storage and detention area ecological compensation execution tracing processing method comprises the following steps:

[0007] S1: obtain the remote sensing grid data of the flood storage and detention area, calculate the response time difference of the normalized vegetation index value in the corresponding grid, compare the time difference of each parameter offset time, select the data combination with the largest response offset period as the lag factor combination, and generate a vegetation response delay factor list;

[0008] S2: call the vegetation response delay factor list, retrieve the normalized vegetation index change sequence in the corresponding lag period, compare the normalized vegetation index change rate and the river flow fluctuation frequency of each sequence, identify the effective node, and generate a contract trigger calibration node data group;

[0009] S3: based on the contract trigger calibration node data group, call the contract execution hash record set and node state log in the compensation fund allocation record on the blockchain, perform logical reconciliation comparison between the time period and the execution node, filter the path sequence, and generate an ecological compensation reconciliation chain path structure;

[0010] S4: call the ecological compensation reconciliation chain path structure, identify the boundary node through the maximum time jump threshold and the allocation classification consistency judgment, record the path segment and the head and tail node mapping table after verification, and generate a compensation section boundary node index set.

[0011] As a further scheme of the application, the vegetation response delay factor list includes a normalized vegetation index change lag period, a water body disturbance response lag time and a surface runoff intensity action time window, the contract trigger calibration node data group includes a vegetation state boundary value, a wetland flow mutation point time and a grid position number, the ecological compensation reconciliation chain path structure includes a fund allocation trigger number, an execution node time index and a fund type path mapping value, and the compensation section boundary node index set includes a path segment number, a node operation state code group and a closed boundary node identifier.

[0012] As a further scheme of the application, the vegetation response delay factor list acquisition step is specifically:

[0013] S101: obtain the remote sensing grid data of the flood storage and detention area, and perform time synchronization processing on three types of data in the corresponding spatial position according to the land surface temperature, water body disturbance frequency and surface runoff intensity of multiple time periods, structure the time series data under the same grid number, and record the change trend and change amplitude of each type of parameter in the continuous time range, to generate a grid time series data set;

[0014] S102: Based on the grid time series data set, the normalized vegetation index value sequence consistent with the spatial position is selected, the change time point between the normalized vegetation index value sequence of each grid and the corresponding land surface temperature, water body disturbance frequency and surface runoff intensity change sequence is compared, the vegetation response time offset corresponding to each influence factor is calculated, and a vegetation response time difference reference table is generated;

[0015] S103: According to the vegetation response time difference reference table, the data combination with the maximum offset period value in each response time offset is judged, the corresponding grid number, influence factor name and lag period value are extracted, the offset period is sorted and an index structure is constructed, and a vegetation response delay factor list is obtained.

[0016] As a further scheme of the present application, the contract trigger calibration node data set obtaining step specifically comprises:

[0017] S201: The vegetation response delay factor list is called, the normalized vegetation index time series data in the lag period range is retrieved according to each group of lag factors, the normalized vegetation index sequence corresponding to each monitoring grid number is matched in time length cutting, and a mapping relationship between the grid number and the cut vegetation sequence is established, a lag vegetation index sequence set is obtained;

[0018] S202: According to the lag vegetation index sequence set, the adjacent time sequence change value in each normalized vegetation index change sequence is obtained, the normalized vegetation index change rate between adjacent time points is calculated, the change rate value is compared with the river flow change frequency in the same time period, the absolute offset value of the NDVI change rate and the flow fluctuation difference value is obtained, and the node with an absolute offset value greater than the offset reference difference value is extracted as a change inflection point. The grid number and time index corresponding to the inflection point are screened, a rate offset reversal node set is generated;

[0019] S203: According to the rate offset reversal node set, it is judged whether each reversal point satisfies the vegetation index activation rule in the ecological compensation contract, the nodes satisfying the activation condition are screened and marked with the corresponding grid number and unit runoff change value, the mapping index of node data and compensation trigger record is established, and a contract trigger calibration node data set is generated.

[0020] As a further scheme of the present application, the formula for calculating the absolute offset value of the NDVI change rate and the flow fluctuation difference value is specifically:

[0021] ;

[0022] Wherein, The absolute offset difference value between NDVI and flow disturbance response rate is represented by The absolute offset difference value between NDVI and flow disturbance response rate is represented by monitoring the normalized vegetation index value in the grid cell at the time, representing the monitoring the normalized vegetation index value in the grid cell at the time, representing the time value at the time, representing the time value at the time, representing the normalized value of river flow at the monitoring location at the time, representing the normalized value of river flow at the monitoring location at the time, representing the normalized value of river channel disturbance energy level at the monitoring section at the time, representing the constant adjustment parameter in the logarithmic function term.

[0023] As a further scheme of the present application, the acquiring step of the ecological compensation reconciliation chain path structure is specifically:

[0024] S301: Based on the contract trigger designated node data set, according to the monitoring grid number and the time stamp sequence, the contract execution hash record set and the node state log in the block chain platform are queried, the fund allocation type field, the active node address and the allocation response start and end time in the allocation record are extracted for each data item, the structured data record list is established, and the allocation associated field data table is generated;

[0025] S302: According to the allocation associated field data table, the allocation response time period of each fund allocation record and the time stamp of the corresponding active node are compared, the time difference value is calculated and compared with the set time difference value threshold, it is judged whether the fund allocation type field and the active node type identifier are consistent, the node path that satisfies the time continuity and the type consistency at the same time is screened, and the matching node path sequence set is acquired;

[0026] S303: In the matching node path sequence set, the allocation path chain structure is constructed according to the time stamp sequence, and the node hash address and the allocation confirmation identifier associated with the corresponding path section are recorded, the path number, the start and end time and the associated data field are integrated, and the ecological compensation reconciliation chain path structure is generated.

[0027] As a further scheme of the present application, the acquiring step of the compensation section boundary node index set is specifically:

[0028] S401: According to the path section number and the first and last node identifier, the node state code, the state transition direction flag and the fund response type code of each node in the path are extracted, the three data are constructed into a triple structure and archived according to the time sequence, and the path section triple data set is generated.

[0029] S402: Based on the path segment triplet dataset, obtain the mapping value of the timestamp difference between adjacent nodes, the status code jump amplitude and the fund response type code, call the fund confirmation cycle and transfer direction identifier value between adjacent nodes, calculate and obtain the continuity offset index of the node pair, determine whether the continuity offset index value exceeds the set continuity boundary benchmark value, mark the boundary nodes for node pairs that exceed the threshold, and generate a node continuity offset index group.

[0030] The specific formula for obtaining the continuity offset index of the node pair is as follows:

[0031] ;

[0032] in, Indicates the first To the The continuity offset index between path nodes Indicates the first The status code value of each node. Indicates the first The status code value of each node. Indicates the first The timestamp value of each node. Indicates the first The timestamp value of each node. Indicates the first The normalized value corresponding to the funding response type code of each node. Indicates the first The normalized value of the path jump direction exponent for each node. Indicates the first The perturbation value of the contract activation cycle of each node. is the base of the natural logarithm;

[0033] S403: Based on the node continuity offset index group, according to the boundary node index marked as continuity break point, combined with the path segment number and the first and last node identification information, record the correspondence of valid path segment boundary nodes, establish a one-to-one mapping record table between path segment number and first and last node number, and generate a compensation section boundary node index set.

[0034] As a further aspect of the present invention, the method further includes the following steps:

[0035] S5: Based on the compensation section boundary node index set, record the permission overstepping flag for the overstepping behavior node, read the signature private key address identifier, operation timestamp and call event log hash digest corresponding to the node, and sequentially concatenate the three data items to form a behavior signature block structure. After adding the role level and authorization scope, write them sequentially into the responsibility tracking chain structure area to generate the flood storage and detention area responsibility signature traceability structure set.

[0036] The responsibility signature traceability structure set of the flood storage area is specifically a responsibility signature value, a role permission level identifier, and path node binding information.

[0037] As a further scheme of the present application, the obtaining step of the responsibility signature traceability structure set of the flood storage area is specifically:

[0038] S501: Based on the compensation section boundary node index set, according to the contract role permission comparison set provided in the path segment information and the node role table, extract the operation instruction type code and the permission value in each node operation record, call the preset permission mapping rule in the operation instruction permission corresponding table, judge whether each operation instruction exceeds the role permission value range corresponding to the node, mark the nodes with permission out-of-range and add the permission out-of-range flag field, and generate a permission out-of-range state identifier list;

[0039] S502: According to the permission out-of-range state identifier list, read the permission out-of-range flag state field node by node, for the nodes with operation records, extract the signature private key address identifier, operation timestamp and call event log hash digest of the corresponding node, connect the three data in the order of private key address, operation time and event hash, and construct the behavior signature unit by using the standard byte splicing method to obtain the behavior signature block structure sequence;

[0040] S503: Call the behavior signature block structure sequence, generate a signature block data structure for each node, according to the previous node behavior signature block recorded in the path segment information, construct a signature chain through a bidirectional hash docking mechanism, add the role level value field and the authorized range code field of each node, sequentially write the structure unit with additional information into the responsibility tracking chain structure area, and establish the responsibility signature traceability structure set of the flood storage area.

[0041] The flood storage area ecological compensation execution traceability processing system based on a blockchain is used to implement the above-mentioned flood storage area ecological compensation execution traceability processing method based on a blockchain, and the system comprises:

[0042] The response lag analysis module obtains the flood storage area remote sensing grid data, calculates the response time difference of the normalized vegetation index value in the corresponding grid, compares the time difference of each parameter by comparing the offset time of each parameter, selects the data combination with the largest response offset period as the lag factor combination, and generates a vegetation response delay factor list;

[0043] The trigger trajectory recognition module calls the vegetation response delay factor list, retrieves the normalized vegetation index change sequence in the corresponding lag period, compares the normalized vegetation index change rate and the river flow fluctuation frequency for each sequence, identifies the effective nodes, and generates a contract trigger calibration node data group.

[0044] The contract triggering calibration node data set is triggered by the reconciliation path analysis module, the contract execution hash record set in the compensation fund disbursement record on the blockchain and the node state log are called, the logical reconciliation comparison between the time period and the execution node is carried out, the path sequence is screened, and the ecological compensation reconciliation chain path structure is generated;

[0045] The closed boundary identification module calls the ecological compensation reconciliation chain path structure, identifies the boundary node through the maximum time jump threshold and the disbursement classification consistency judgment, records the path segment and the head and tail node mapping table after verification, and generates the compensation section boundary node index set;

[0046] The responsibility identification encapsulation module records the permission boundary sign of the out-of-bound behavior node based on the compensation section boundary node index set, reads the signature private key address identification, operation timestamp and call event log hash digest corresponding to the node, sequentially splices the three data to form the behavior signature block structure, sequentially writes the role level and authorized range into the responsibility tracking chain structure area, and generates the detention basin responsibility signature tracing structure set.

[0047] Compared with the prior art, the advantages and positive effects of the present application are that:

[0048] In the present application, by acquiring remote sensing grid data and introducing time series parameters such as land surface temperature, water body disturbance frequency and surface runoff intensity, a vegetation response delay factor list is constructed using the response time difference, the intersection of the normalized vegetation index and the flow fluctuation frequency is identified to identify the ecological trigger node and extract effective monitoring data, the compensation disbursement behavior is logically reconciled with the timestamp and hash record, the node tracking and continuity verification of the fund disbursement path are realized, the time jump is identified and the boundary node is calibrated, the operation permission matching is carried out in combination with the contract permission table, the operation log is extracted and the responsibility signature block containing time, signature and behavior digest is generated, the responsibility tracking structure chain is constructed step by step, the responsibility binding of the fund behavior node and the whole process signature trace and chain tracing of the disbursement behavior are effectively realized, the real-time discrimination ability and operation responsibility tracing ability of the compensation execution are enhanced, and the verification accuracy and process integrity of the fund execution path are improved. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced as follows. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0050] Figure 1 The workflow schematic diagram of the present application is shown in the figure.

[0051] Figure 2 System flowchart of the present application. DETAILED DESCRIPTION

[0052] The technical solutions in the present application will be described below with reference to the drawings.

[0053] In the embodiments of the present application, the words such as "example", "for example" are used to represent an example, illustration or description. Any embodiment or design scheme described as "example" in the present application should not be interpreted as more preferred or more advantageous than other embodiments or design schemes. Rather, the word "example" is intended to present the concept in a specific manner. In addition, in the embodiments of the present application, the meaning expressed by "and / or" can be both, or can be one of the two.

[0054] In the embodiments of the present application, "image" and "picture" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent. "Of", "corresponding" and "corresponding" can be used interchangeably at times. It should be pointed out that when the distinction is not emphasized, the meanings expressed are consistent.

[0055] In the embodiments of the present application, sometimes the subscript such as W1 can be written in the form of non-subscript such as W1. When the distinction is not emphasized, the meanings expressed are consistent.

[0056] In order to make the technical problems, technical solutions and advantages of the present application clearer, specific embodiments will be described in detail below with reference to the drawings.

[0057] Please refer to Figure 1 The present application provides a technical solution: a flood storage and detention area ecological compensation execution traceability processing method based on a block chain, comprising the following steps:

[0058] S1: Obtain the remote sensing grid data of the flood storage and detention area, extract the land surface temperature, water body disturbance frequency and surface runoff intensity in a continuous time period, combine the three types of data according to the grid position and time sequence, calculate the response time difference of the normalized vegetation index value in the corresponding grid, compare the time difference by offsetting the time of each parameter, select the data combination with the largest response offset period as the lag factor combination, and generate a list of vegetation response delay factors;

[0059] Land surface temperature represents the thermal radiation temperature of the ground, derived from remote sensing data products such as MODIS; water body disturbance frequency is the number of water bodies appearing or disappearing in the statistical unit area, used to evaluate the degree of hydrological disturbance; land surface runoff intensity is estimated by models such as SWAT or TRMM data, representing the trend of runoff per unit area; the normalized vegetation index calculation formula is (NIR-RED) / (NIR+RED), where NIR is the near-infrared band reflectivity and RED is the red light band reflectivity, used to measure changes in vegetation coverage.

[0060] S2: Call the vegetation response delay factor list, according to each set of lag factors, retrieve the normalized vegetation index change sequence in the corresponding lag period, compare the normalized vegetation index change rate with the river flow fluctuation frequency for each sequence, extract the intersection point of the rate inversion point and the flow mutation point, judge whether it is an ecological trigger node in the contract condition, identify the effective node according to the vegetation index activation rule, record the corresponding monitoring grid number and unit runoff change, and generate a contract trigger calibration node data set;

[0061] The normalized vegetation index change rate is the change rate of the normalized vegetation index per unit time, reflecting the vegetation recovery trend; the river flow fluctuation frequency can be calculated from the flow velocity monitoring station data, reflecting the hydrological disturbance behavior of the flood storage and detention area river channel; the unit runoff change is the change value of the runoff at the grid scale within the time window, which is commonly used to couple ecological hydrological processes;

[0062] S3: Based on the contract trigger calibration node data set, according to the recorded monitoring grid number and time stamp sequence, call the contract execution hash record set and node state log in the compensation fund disbursement record on the blockchain, extract the fund disbursement type field, active node address and disbursement response time period, perform logical reconciliation comparison between the time period and the execution node, and use the time difference threshold and disbursement type consistency identifier to filter the path sequence, and generate an ecological compensation reconciliation chain path structure;

[0063] The contract execution hash record set is a set of transaction hash values stored in the smart contract activation in the blockchain, used to track the execution order of the contract; the node state log is an operation log and node state value record structure for each blockchain transaction; the fund disbursement type field is an encoding structure representing the type of ecological compensation behavior, such as according to the vegetation recovery metric, wetland hydrological restoration metric division;

[0064] S4: Call the ecological compensation reconciliation chain path structure, according to the path segment number and first and last node identifier, extract the node state code, state transition direction flag and fund response type code, perform continuity judgment between operations in the path, identify the boundary node through the maximum time jump threshold and disbursement classification consistency judgment, record the path segment and first and last node mapping table after verification, and generate a compensation section boundary node index set;

[0065] The node state code represents the function or authority corresponding to each node in the contract execution;

[0066] S5: Based on the compensation section boundary node index set, according to the path segment information and the contract role authority provided in the role table, match the mapping rule between the operation instruction type code and the authority value in the node operation record, record the authority out-of-boundary flag of the out-of-boundary behavior node, and perform responsibility binding signature processing on each node. Read the corresponding signature private key address identifier, operation timestamp and call event log hash digest, sequentially splice the three data to form a behavior signature block structure, connect the hash chain with the previous node behavior signature, and sequentially write the role level and authorized range into the responsibility tracking chain structure area. Generate a set of flood storage and detention area responsibility signature trace structure;

[0067] The vegetation response delay factor list includes the normalized vegetation index change lag period, water body disturbance response lag time and surface runoff intensity action time window. The contract trigger calibration node data set includes the vegetation state boundary value, wetland flow mutation point time and grid position number. The ecological compensation reconciliation chain path structure includes the fund allocation trigger number, execution node time index and fund type path mapping value. The compensation section boundary node index set includes the path segment number, node operation state code group and closed boundary node identifier. The flood storage and detention area responsibility signature trace structure set specifically includes the responsibility signature value, role authority level identifier and path node binding information.

[0068] The acquisition step of the vegetation response delay factor list is specifically:

[0069] S101: Acquire the flood storage and detention area remote sensing grid data, and perform time synchronization processing on the three types of data at the corresponding spatial position according to the land surface temperature, water body disturbance frequency and surface runoff intensity of multiple time periods. Structure the time series data under the same grid number, and record the change trend and change amplitude of each type of parameter in the continuous time range to generate a grid time series data set;

[0070] To obtain the land surface temperature, water body disturbance frequency and surface runoff intensity of different time periods in the flood storage and detention area remote sensing grid data, first set the grid number system based on the remote sensing image source, divide the area range with a spatial resolution of 250 meters, extract the MODIS land surface temperature image , extract the water body spectrum after disturbance from Sentinel-1 and perform multi-period ratio processing, calculate the grid surface runoff intensity combined with TRMM or GPM satellite-borne precipitation data and terrain data, then align the grids with the same number vertically according to the time labels of each type of data image, synchronize the data according to the timestamp sequence, arrange the temperature sequence, water body disturbance frequency sequence and surface runoff intensity sequence under each grid number in turn by constructing a three-dimensional array form, and form The time series matrix of the dimension, for example, the grid number is At this point, the 7-day land surface temperature is , the water body disturbance frequency is , the runoff intensity is converted to unit area , when calculating the daily change rate of the above three parameters, the change amplitude is obtained by dividing the difference between every two days by the time interval, then the change trend array is constructed according to the direction of the change amplitude, for change trend classification, the absolute value of the change amplitude is less than is a stable segment, the change amplitude is greater than or equal to is a growth segment, and less than or equal to is a decline segment, and the threshold value is derived from the statistical analysis of the average annual change rate in the remote sensing monitoring data in the past three years, and is set according to the quantile value, in the stable interference intensity region, this amplitude can effectively divide the background and abnormal trend, the calculation process is to set the change rate data sample to , after calculating the interquartile range, the upper quartile value is taken as the change amplitude threshold, and each continuous trend information is mapped to the structured result set to obtain the grid time series data set;

[0071] S102: Based on the grid time series data set, select the normalized vegetation index value sequence consistent with the spatial position, compare the normalized vegetation index value sequence of each grid with the change time point between the corresponding land surface temperature, water body disturbance frequency and surface runoff intensity change sequence, calculate the vegetation response time offset corresponding to the influence factor, and generate a vegetation response time difference table;

[0072] Based on the grid time series data set, select the normalized vegetation index value sequence consistent with the spatial position, in this process, first extract value from the same period of remote sensing data source, set the numbering method consistent with the grid for position mapping processing, then align the numbered sequence with the time sequence of the above three parameters of temperature, water body disturbance frequency and surface runoff intensity, record the position time stamp of the change trend mutation in each parameter sequence, and judge the corresponding change point time position, and the corresponding offset is the response time offset, and the comparison process is performed once for each grid, for example: in the grid numbered , the water body disturbance frequency mutates at the 4th day, and changes at the 6th day, so the offset is 2 days, record such offset in sequence, fill in the table according to the parameter dimension, calculate the corresponding response time difference value of each parameter in each grid, and use the time stamp difference calculation formula All response time offset amounts are constructed into a two-dimensional index structure, and in the mutation judgment, the mutation recognition threshold is set to be greater than The threshold is set based on the average of the standard deviation of the difference value change of each factor data before and after the sample set. In the example, if the disturbance frequency change is , it is not identified as a mutation, otherwise it is marked as a mutation point, and the result is recorded as a vegetation response time difference table;

[0073] S103: According to the vegetation response time difference table, determine the data combination with the largest offset period value in each response time offset amount, extract the corresponding grid number, influence factor name and lag period value, sort them by offset period size and construct an index structure, and obtain a vegetation response delay factor list;

[0074] According to the vegetation response time difference table, determine the driving factor corresponding to the maximum response time offset value in each row of data, extract the corresponding grid number, factor name and corresponding lag period value, and sort all data by lag period value. Before sorting, the period unit needs to be unified, and 1 day is set as the basic unit for unified conversion. For example, if the lag period in a record is 48 hours, it is converted to 2 days. After unifying all values, construct a lag period ascending list, then construct an index structure for the sorted results. Use a structure to mark the grid number, driving factor identifier, and lag period number of each item. Three-field composite index, further forming a queryable list set structure. In implementation, if multiple factors have the same lag period, sort them according to the initial value, and in the auxiliary sorting, set the sorting weight as the lag period , initial value weight , and the sorting index is , where , are the normalized sorting positions of the lag period and value in the entire sample, and the weight setting is based on the variance contribution ratio of the contribution of the two factors in the overall volatility. The initial field is added for subsequent filtering, and the vegetation response delay factor list is finally obtained.

[0075] The steps for obtaining the contract trigger calibration node data set are as follows:

[0076] S201: Call the vegetation response delay factor list, retrieve the normalized vegetation index time series data within the lag period range according to each lag factor, match the normalized vegetation index sequence corresponding to each monitoring grid number with the lag period value, and establish a mapping relationship between the grid number and the vegetation sequence after cutting, to obtain a lag vegetation index sequence set.

[0077] To retrieve the hysteresis period value from the vegetation response delay factor list, first determine the raster number of each record entry in the list. and its corresponding lag period value Perform a traversal extraction operation on the number. For entries with a lag period of 10 days, the entry with the number [number] is retrieved from the vegetation index database. The NDVI sequence is obtained, and the data is indexed based on the data recording time. Selecting a data window that moves backwards 10 days creates a fixed-time series with daily intervals. The specific content extracted is as follows: Then, regarding the number The operations are performed sequentially, and if the lag period value of a certain number is... If the value is 12, then perform the same operation, adjusting the starting point of the cutoff to... Start, then stitch to The data is structured into 12-day segments. All operations are performed based on the existence of a complete time series in the original database. If a time gap exists in a particular entry, that entry must be removed to avoid data inconsistency leading to incorrect response decisions. Subsequently, each entry is... The extracted vegetation index vector is mapped and bound to it to construct a key-value structure, where the key is the ID number. The value is a fixed-length NDVI vector. Finally, all numbered mapping structures are assembled to obtain a mapping hash table structure with the number as the index and the NDVI vector as the value. This structure is the set of lagged vegetation index sequences obtained in this step.

[0078] S202: Based on the lag vegetation index sequence set, obtain the adjacent time series change values ​​in each normalized vegetation index change sequence, calculate the normalized vegetation index change rate between adjacent time points, compare the change rate value with the river flow change frequency in the same time period, calculate the absolute offset value of the difference between the NDVI change rate and the flow fluctuation, extract the nodes whose absolute offset value is greater than the offset benchmark difference as change inflection points, filter the raster number and time index corresponding to the inflection point, and generate a rate offset inversion node set;

[0079] The specific formula for calculating the absolute offset value of the difference between the NDVI change rate and the flow fluctuation is as follows:

[0080] ;

[0081] in, This represents the absolute offset difference between NDVI and the flow disturbance response rate. Indicates the first Continuously monitor the normalized vegetation index (NDI) values ​​within the raster cells. Indicates the first monitoring the normalized vegetation index value in the grid cell at the time, representing the time value at the time, representing the time value at the time, representing the time value at the time, monitoring the normalized value of river flow at the location at the time, monitoring the normalized value of river flow at the location at the time, representing the time value at the time, representing the constant adjustment parameter in the logarithmic function term;

[0082] According to the lag vegetation index sequence set, the NDVI time series data under each number is selected, and the NDVI values at adjacent two times are obtained, which are set as , the NDVI change rate in the interval is calculated, and the operation is the difference divided by the interval days: , for example, if , , the time interval is 5 days, then the NDVI rate is 0.01, the normalized river flow data in the time period is extracted, the change rate is calculated in the same difference and time ratio form, and then the disturbance energy level normalization value at the time in the monitoring section is combined to perform natural logarithmic transformation. In order to prevent the risk of non-derivative of logarithmic function caused by extremely small disturbance energy level, set , the combination transformation factor is , and after multiplying the flow rate value, the disturbance response estimation value of NDVI is constructed. Finally, the absolute value of the difference between the NDVI change rate value and the estimation value is obtained to obtain the offset amplitude, using the formula:

[0083] ;

[0084] wherein, is the difference value of NDVI change response and flow disturbance, , is the NDVI normalization value, , is the adjacent time point, , is the flow normalization value, is the disturbance energy level normalization value, is the constant to prevent the failure of logarithmic function;

[0085] Formula operation logic explanation: the first term is the true vegetation change rate, the second term is the estimated rate based on hydrological disturbance, and the difference between the two represents the degree of adaptation between vegetation response and flow behavior. The absolute value form is used to capture the degree of deviation, and the larger the value, the more serious the disconnection between vegetation and hydrology, reflecting the expected range of ecological compensation triggering;

[0086] The advantage of the formula is that by introducing the disturbance energy level term and combining with the logarithmic nonlinear processing method, the NDVI response deviation in the small disturbance stage can be highlighted, the weak but critical response nodes can be identified, and the sensitivity of the overall response mechanism can be improved;

[0087] Offset reference difference setting explanation: set the offset threshold , which is an important basis for identifying deviation behavior nodes in the system. The value is derived from the results obtained from statistical analysis of the historical responses of multiple flood storage and detention areas. When the NDVI response rate and flow fluctuation offset difference are greater than 0.08, it is considered as a potential ecological turning point, and the corresponding data node is marked in the abnormal behavior list;

[0088] Example calculation: if the data at a certain time is as follows: 、 、 、 、 、 、 , then the calculation is as follows:

[0089] ;

[0090] The results show that does not exceed the offset threshold , which does not constitute a turning point behavior. If the threshold is exceeded, the time period is included in the identification node;

[0091] Filter all data points that satisfy , extract their corresponding numbers and time indexes, and generate a set of rate offset reversal nodes.

[0092] S203: According to the rate offset reversal node set, determine whether each reversal node meets the vegetation index activation rule in the ecological compensation contract, filter the nodes that meet the activation condition and mark the corresponding grid number and unit runoff change value, establish the mapping index of node data and compensation trigger record, and generate the contract trigger calibration node data group.

[0093] According to the rate offset reversal node set, determine whether each node meets the activation rule in the ecological compensation contract. The rule is: within the time window corresponding to the node, the NDVI value needs to be monotonically increasing in the next three time periods, and the increment of each time period is not less than 0.015. If the current grid number If the reverse node is located at time , the value between needs to be checked to see if it meets , If the above conditions are met, the node is considered a potential activation node, and the corresponding unit runoff change value is further extracted, with unit runoff defined as the change in river flow divided by the monitoring grid area. If the grid area is 1 square kilometer and the river flow increases from 1.1 cubic meters per second to 1.6 cubic meters per second, the unit runoff change is 0.5 cubic meters per second per square kilometer. Then the grid number, time index and corresponding unit runoff change value of the activation node are recorded in the mapping structure table, with the key being the node number and the value being a composite structure containing unit runoff value and time index information. After the table is summarized, the contract trigger calibration node data set is generated.

[0094] The acquisition steps of the ecological compensation account chain path structure are as follows:

[0095] S301: Based on the contract trigger calibration node data set, the contract execution hash record set and node state log in the blockchain platform are queried according to the monitoring grid number and time stamp sequence, the fund allocation type field, activation node address and allocation response start and end time in the allocation record are extracted for each data item, a structured data record list is established, and an allocation associated field data table is generated;

[0096] Based on the monitoring grid number and time stamp sequence in the contract trigger calibration node data set, the grid number and time stamp contained in each record in the data set are first obtained, the corresponding contract execution hash record set is found in the query interface of the blockchain platform, the transaction log related to the node in the hash record is located through the grid number and time stamp, the hash value field in the chain data structure is called to quickly index, and the complete allocation record of the contract is extracted, including the fund type field triggered by the allocation action trigger address field , allocation response start and end time , if any field in the record is missing, skip processing the entry, ensure the integrity of the structure, and extract the state change item consistent with the grid number from the node state log, check the consistency of the block height, address hash and time index information recorded in the log entry, perform data splicing on the legal item, and sequentially build the fund allocation field, active address field, response time field and other information into structured key-value data records. The field name is used as the key, and the corresponding value is used as the value to form a JSON-style or equivalent structure. The list is filled in order, with each record as a row in the table. All structured data records are integrated and sorted in ascending order of timestamp to build a two-dimensional table data structure with uniform fields, time alignment and consistent data items. The table is named the allocation associated field data table.

[0097] S302: According to the allocation associated field data table, compare the allocation response time period of each fund allocation record with the timestamp of the corresponding active node, calculate the time difference and compare it with the set time difference threshold, judge whether the fund allocation type field and the active node type identifier are consistent, filter the node path that satisfies the time continuity and type consistency at the same time, and obtain the matching node path sequence set;

[0098] According to the allocation associated field data table, read the allocation response start and end time of each allocation record , compare it with the timestamp of the active node corresponding to the record , calculate the time difference between the response interval and the active time point , the judgment condition is whether it falls within interval, where is the time difference threshold, if set to 2 days, only records with active node time point within 2 days before and after the allocation response window are allowed to be determined as valid time matching, after successful time matching, compare the fund allocation type field with the active node type identifier , the identifier value is defined as a three-byte structure code, for example, the fund allocation type code is "101" indicating vegetation restoration, and the active node type code is "101" indicating a first-level contract role match, if both are consistent, it is considered as type consistent, if any field is empty or not matched, skip the record, filter out the record that satisfies the time period continuity and type identifier consistency at the same time, for the records that pass the judgment, according to the path identifier field they belong to, if multiple records have the same path identifier value, they are grouped into the same path group, finally select the path segment structure that meets the double conditions in all path groups, mark the path number and start and end node time, extract the path number, node sequence and confirmation flag, and obtain the matching node path sequence set after summarizing.

[0099] S303: Call the matching node path sequence set, construct the allocation path chain structure in the order of timestamp, and record the node hash address and allocation confirmation identification associated with the corresponding path segment, integrate the path number, start and end time and associated data field, and generate the ecological compensation reconciliation chain path structure;

[0100] Call the path node number information in the matching node path sequence set, process each path segment in the order of path number, read the node number sequence under each path , according to the timestamp field corresponding to each node, sort it in ascending order from early to late, and verify the continuity of the time interval between adjacent nodes based on the order, and construct the directed chain structure for the nodes that pass the verification, the hash address of the first node as the starting node address field, the hash address of the second node as the end node field, and read its fund allocation confirmation identification field , sequentially hang up in order to build a chain structure representation of the complete path segment, maintain the path segment number , first and last timestamp, node number, state confirmation result of each node, node address, fund status flag, and combine them into a five-tuple structure, write them into the main path data table structure in a unified format, and add node participation address, authorized role level information field and allocation type field to each path segment, append these fields to the tail of the path segment structure to form the complete information body of the chain path, and collect all path segment data sets into the main chain structure index data structure table, finally generate the ecological compensation reconciliation chain path structure.

[0101] The acquisition step of the compensation section boundary node index set is specifically:

[0102] S401: Call the ecological compensation reconciliation chain path structure, extract the node state code, state transition direction flag and fund response type code of each node in the path according to the path segment number and the first and last node identification, construct a three-tuple structure with the three data and archive them in chronological order, and generate a path segment three-tuple data set;

[0103] The process involves calling the path segment numbers and first / last node identifiers from the ecological compensation reconciliation chain structure, selecting the path segment information marked by each path segment number, reading the intermediate node information contained in each path segment from the path chain structure, and sequentially extracting the three field values ​​bound to each node: status code, status transition direction flag, and fund response type code. For each node, a triplet format data consisting of these three data items is constructed, and the node timestamp record field is bound to this triplet. These are then archived and arranged sequentially in chronological order to form a time-series data structure. For example, during the construction process, the path segment numbering... If the node number sequence in P202 is N101, N102, and N103, then read the data of each node, extract the status code of node N101 as 3, the direction flag as positive, the fund response type code as 0, and the timestamp as 1683456000 seconds, and construct a triple (3, positive, 0). Sort all triples in ascending order by node timestamp, and group them with path segment numbers. Finally, using the path segment number as the retrieval field, organize the node triple data in each segment into a standard structure and form a list structure to generate the path segment triple dataset.

[0104] S402: Based on the path segment triplet dataset, obtain the mapping value of the timestamp difference between adjacent nodes, the status code jump amplitude and the fund response type code, call the fund confirmation cycle and transfer direction identifier value between adjacent nodes, calculate and obtain the continuity offset index of the node pair, determine whether the continuity offset index value exceeds the set continuity boundary benchmark value, mark the boundary nodes for node pairs that exceed the threshold, and generate a node continuity offset index group.

[0105] The specific formula for calculating the continuity offset index of node pairs is as follows:

[0106] ;

[0107] in, Indicates the first To the The continuity offset index between path nodes Indicates the first The status code value of each node. Indicates the first The status code value of each node. Indicates the first The timestamp value of each node. Indicates the first The timestamp value of each node. Indicates the first The normalized value corresponding to the funding response type code of each node. Indicates the first The normalized value of the path jump direction exponent for each node. Indicates the first contract activation period perturbation value of the node, the state code difference value between the and nodes, the square of the time interval between the and nodes, the fund response perturbation normalization item of the node under the influence of the perturbation period is the base of the natural logarithm;

[0108] According to the node pairs in the path segment triple data set, a continuity verification process is constructed, the state code value, timestamp value, fund response type code, path jump direction index and contract activation perturbation value of each pair of adjacent nodes are extracted, and the following formula is introduced as the calculation basis of the key indicators:

[0109]

[0110] In this formula, reflects the state code change amplitude between adjacent nodes, and the absolute value ensures that the change direction does not affect the amplitude strength evaluation; the square root value of the jump direction index, which adjusts the path direction perturbation strength and reflects the path stability; the denominator item represents the square of the time interval, which is intended to significantly amplify the offset when the nodes are too dense, highlighting the continuity anomaly point; the second item introduces a logical function to normalize and modulate the fund response perturbation, where is the contract activation period perturbation value of the node, and if the perturbation value increases, the normalization coefficient will decrease, reflecting the time dispersion degree of the fund confirmation response.

[0111] For example, in a certain path segment, adjacent nodes N201 and N202 have state codes of 5 and 9, respectively, corresponding to , the state jump amplitude is 4; the node timestamps are 1683450000 seconds and 1683450300 seconds, respectively, i.e. seconds; the path direction perturbation index value is 1.44, i.e. ; the fund response type code normalization value is , and the contract activation perturbation value is . Substitute each value into the formula to calculate:

[0112]

[0113] The final continuity offset indicator is about 0.529. If the system sets the continuity boundary reference value as 0.45, then the​​​​ has exceeded the boundary threshold, it is determined that there is a continuous abnormal jump behavior.

[0114] The calculation logic of the continuity offset indicator is to aggregate the path offset parameters of multiple dimensions into a unified quantitative indicator: the higher the value, the more severe the state change that occurs in the path between the node and its previous node, the more inconsistent the fund response and time rhythm, and the weaker the path continuity or the breaking point. This indicator not only integrates time disturbance, state change, and fund characteristics, but also has threshold determination capability, effectively screening unstable links in the ecological compensation chain.

[0115] The advantage of the formula is that by introducing the contract activation period disturbance value The normalization of the fund type item and the non-linear processing of the path direction index item enable the calculation result to comprehensively reflect the non-equilibrium fluctuations of path behavior, thereby avoiding the dilution effect of time series on state disturbance in node continuity testing.

[0116] The results show that the node pair (N201→N202) has an offset degree greater than the boundary value, which should be considered as a breaking point in the chain path. It is marked and written into the structure, and the node continuity offset indicator group is generated.

[0117] S403: Based on the node continuity offset indicator group, according to the boundary node index marked as a continuity breaking point, combined with the path segment number and the head and tail node identification information, record the effective path segment boundary node correspondence, establish a one-to-one mapping record table of path segment number and head and tail node number, and generate a set of compensation section boundary node indexes;

[0118] According to the node number and breaking state marker in each record of the node continuity offset indicator group, the path segment structure is modified, the head and tail node numbers are read in the order of node timestamp, and the association table is constructed with the original path segment number. In actual execution, for example, the continuity breaking nodes in the path segment number P303 are marked as N405 and N409, the system identifies them as boundary nodes and records the start and end time information and the corresponding node hash address, finally constructs the corresponding mapping record between the path segment P303 and N405, N409, and generates a boundary node information table in the compensation responsibility chain segment. All path segment boundary mapping items are grouped in turn to generate a set of compensation section boundary node indexes.

[0119] The acquisition steps of the detention basin responsibility signature trace structure set are:

[0120] S501: Based on the compensation section boundary node index set, according to the contract role permission set provided in the path segment information and the node role table, the operation instruction type code and the permission value in each node operation record are extracted, the preset permission mapping rule in the operation instruction permission corresponding table is called, it is judged whether each operation instruction exceeds the role permission value range corresponding to the node, the nodes with permission out of range are marked and the permission out of range flag field is added, and a permission out of range state identification list is generated;

[0121] Based on the compensation section boundary node index set, each path segment number and its first and last node identification item in the index set are read, the matching structure in the path segment information and the node role table is called, the node role identification value field and its binding role permission value in the role permission set are extracted according to the node number, and the operation record left by the node in the blockchain execution log is further retrieved. The operation instruction type code recorded in the operation record is extracted, and the operation instruction permission mapping rule table is called to identify the permission level value corresponding to the instruction type code. The permission level value and the role permission value field corresponding to the node in the contract role permission set are compared, and when the instruction permission value exceeds the upper limit of the role permission value, the node operation state is marked as permission out of range, and the permission out of range result is written into the node permission flag field, forming the out of range flag field array. In the processing process, for example, the role permission value of node number N508 is 4, and the instruction type code corresponding permission level is 6, then the node will be judged as an out of range node, and the permission out of range flag bit in its record structure is assigned a value of 1. After the system completes the permission verification and flag field assignment of all nodes, the record items are sorted according to the node number sequence, and the permission out of range state identification list is generated.

[0122] S502: According to the permission out of range state identification list, read the permission out of range flag state field node by node, for the nodes with operation records, extract the signature private key address identification, operation timestamp and call event log hash digest of the corresponding node, connect the three data in the order of private key address, operation time and event hash, and construct the behavior signature unit by using the standard byte splicing method to obtain the behavior signature block structure sequence;

[0123] According to the generated permission boundary state identifier list, all node records in the list are read in sequence, and the permission boundary flag field value of each node is retrieved item by item. Whether it is a boundary or not, the node is subjected to behavior data splicing processing. The private key address identifier field, contract call operation timestamp field and event log hash value field bound to each node are called, and a standardized byte-level connection operation is performed in a predetermined splicing order, that is, the private key address field is at the front end, the operation timestamp field is in the middle, and the event hash field is at the tail, to form the behavior signature structure unit of the node. In the operation example, for example, the private key address of node N605 is 0xA8B7, the operation timestamp is 1683456600 seconds, and the event log hash value is 0x3E9F...A22. The corresponding behavior signature splicing structure is a concatenated byte stream: [0xA8B7|1683456600|0x3E9F...A22]. The byte sequence standard and length padding logic set by the blockchain data structure operation protocol are called in the splicing process to ensure the uniformity and readability of different source fields. Finally, all node signature structures are collected in timestamp order to form a list structure, and an action signature block structure sequence is obtained.

[0124] S503: Call the action signature block structure sequence, generate a signature block data structure for each node, and build a signature chain through a bidirectional hash docking mechanism according to the previous node action signature block recorded in the path segment information, append the role level value field and the authorization range code field of each node, and sequentially write the structure unit with the appended information into the responsibility tracking chain structure area to establish the responsibility signature tracing structure set of the flood storage and detention area;

[0125] Call all structure units in the action signature block structure sequence, build a responsibility signature chain structure for each node, and generate a signature chain connection field by taking the current signature block and the previous signature block as hash input sources based on the generated behavior signature block of the previous node read from the path segment information. The node role level field and the authorization range code field are appended as extended information structures in each signature block to form a node responsibility unit data format containing four key fields. In the docking process, for example, the current node is N710 and the previous node is N709. The signature block hash value of N709 and the behavior signature block of N710 are jointly used to generate the docking hash value of the current link segment and serve as the chain connection structure header. The appended fields such as the role level of 2 and the authorization range code of A7F2 are integrated and written into the signature chain structure area. Each path segment is sequentially written during execution to finally form a complete data chain table containing full-path signature tracking, and a responsibility signature tracing structure set of the flood storage and detention area is established.

[0126] The blockchain-based detention basin ecological compensation execution traceability processing system is used for executing the blockchain-based detention basin ecological compensation execution traceability processing method, and the system comprises.

[0127] The response lag analysis module obtains the detention basin remote sensing grid data, calculates the response time difference of the normalized vegetation index value in the corresponding grid, compares the time difference of each parameter offset time, selects the data combination with the maximum response offset period as the lag factor combination, and generates a vegetation response delay factor list;

[0128] The trigger trajectory identification module calls the vegetation response delay factor list, retrieves the normalized vegetation index change sequence in the corresponding lag period, compares the normalized vegetation index change rate and the river flow fluctuation frequency for each sequence, identifies the effective node, and generates a contract trigger calibration node data set;

[0129] The reconciliation path analysis module, based on the contract trigger calibration node data set, calls the contract execution hash record set and node state log in the compensation fund allocation record on the blockchain, performs logical reconciliation comparison between the time period and the execution node, filters the path sequence, and generates an ecological compensation reconciliation chain path structure;

[0130] The closed boundary identification module calls the ecological compensation reconciliation chain path structure, identifies the boundary node through the maximum time jump threshold and the allocation classification consistency judgment, records the path segment and the head and tail node mapping table after verification, and generates a compensation section boundary node index set;

[0131] The responsibility identification encapsulation module records the boundary behavior node based on the compensation section boundary node index set, reads the signature private key address identifier, operation timestamp and call event log hash digest corresponding to the node, sequentially splices the three data to form a behavior signature block structure, and sequentially writes the role level and authorized range into the responsibility tracking chain structure area to generate a detention basin responsibility signature traceability structure set.

[0132] It should be understood that the term "and / or" herein is only a description of the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist together, and B exists alone, where A and B can be singular or plural. In addition, the character " / " herein generally represents an "or" relationship between the front and rear associated objects, but can also represent an "and / or" relationship, which can be understood in the context.

[0133] In the present application, "at least one" means one or more, and "multiple" means two or more. "At least one of the following" or the like means any combination of the items, including a single item or any combination of multiple items. For example, at least one of a, b, or c can mean a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, and c can be single or multiple.

[0134] It should be understood that the size of the sequence number of the above-mentioned processes does not mean the order of execution in various embodiments of the present application. The execution order of the processes should be determined according to their functions and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0135] Those of ordinary skill in the art can realize that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be realized in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0136] Those skilled in the art can clearly understand that, for the convenience and brevity of the description, the specific working processes of the devices, apparatuses and units described above can refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

[0137] In several embodiments provided by the present application, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely schematic, for example, the division of the units is only a logical function division, and actual implementation can have another division manner, for example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed units can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0138] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, i.e. they can be located in one place or distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the present embodiment.

[0139] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit.

[0140] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the present application that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0141] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas, characterized in that: Includes the following steps: S1: Obtain remote sensing grid data of flood storage and detention areas, calculate the response time difference of the normalized vegetation index value within the corresponding grid, compare the time difference of each parameter's offset time, select the data combination with the largest response offset period as the lag factor combination, and generate a list of vegetation response delay factors. S2: Call the vegetation response delay factor list, retrieve the normalized vegetation index change sequence within the corresponding lag period, compare the normalized vegetation index change rate with the river flow fluctuation frequency for each sequence, identify valid nodes, and generate a contract trigger calibration node data group. S3: Based on the contract triggering and node data group, call the contract execution hash record set and node status log in the compensation fund disbursement record on the blockchain, perform logical reconciliation comparison between time period and execution node, filter path sequence, and generate ecological compensation reconciliation chain path structure. S4: Call the ecological compensation reconciliation chain path structure, identify boundary nodes by judging the consistency between the maximum time jump threshold and the payment classification, record the verified path segment and the first and last node mapping table, and generate the compensation segment boundary node index set.

2. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 1, characterized in that, The vegetation response delay factor list includes the normalized vegetation index change lag period, water body disturbance response lag time, and surface runoff intensity effect time window. The contract trigger calibration node data group includes vegetation state boundary values, wetland flow mutation point time, and raster location number. The ecological compensation reconciliation chain path structure includes fund disbursement trigger number, execution node time index, and fund type path mapping value. The compensation segment boundary node index set includes path segment number, node operation status code group, and closed boundary node identifier.

3. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 2, characterized in that, The specific steps for obtaining the vegetation response delay factor list are as follows: S101: Acquire remote sensing grid data of flood storage and detention areas. Based on land surface temperature, water disturbance frequency and surface runoff intensity at multiple time periods, perform time synchronization processing on the three types of data at their corresponding spatial locations. Combine the time series data under the same grid number in a structured manner and record the changing trend and magnitude of each type of parameter within a continuous time range to generate a grid time series dataset. S102: Based on the raster time series dataset, select the normalized vegetation index value sequence that is consistent with the spatial location, compare the normalized vegetation index value sequence of each raster with the change time points of the corresponding land surface temperature, water disturbance frequency and surface runoff intensity change sequences, calculate the vegetation response time offset corresponding to the influencing factors, and generate a vegetation response time difference comparison table. S103: Based on the vegetation response time difference reference table, determine the data combination with the largest offset period value in each response time offset, extract the corresponding raster number, influencing factor name and lag period value, sort them according to the offset period size and construct an index structure to obtain the vegetation response delay factor list.

4. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 3, characterized in that, The specific steps for obtaining the contract trigger calibration node data group are as follows: S201: Call the vegetation response delay factor list, retrieve the normalized vegetation index time series data within the lag period range according to each group of lag factors, perform time-truncation matching between the normalized vegetation index sequence corresponding to each monitoring grid number and the lag period value, and establish a mapping relationship between the grid number and the truncated vegetation sequence to obtain the lag vegetation index sequence set. S202: Based on the lag vegetation index sequence set, obtain the adjacent time series change values ​​in each normalized vegetation index change sequence, calculate the normalized vegetation index change rate between adjacent time points, compare the change rate value with the river flow change frequency in the same time period, calculate the absolute offset value of the difference between the NDVI change rate and the flow fluctuation, extract the nodes whose absolute offset value is greater than the offset benchmark difference as change inflection points, filter the raster number and time index corresponding to the inflection point, and generate a rate offset inversion node set; S203: Based on the rate offset reversal node set, determine whether each reversal point meets the vegetation index activation rules in the ecological compensation contract, filter nodes that meet the activation conditions and mark the corresponding raster number and unit runoff change value, establish a mapping index between node data and compensation trigger records, and generate a contract trigger calibration node data group.

5. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 4, characterized in that, The formula for obtaining the absolute offset value of the difference between the NDVI change rate and the flow fluctuation is as follows: ； in, This represents the absolute offset difference between NDVI and the flow disturbance response rate. Indicates the first Continuously monitor the normalized vegetation index (NDI) values ​​within the raster cells. Indicates the first Continuously monitor the normalized vegetation index (NDI) values ​​within the raster cells. Indicates the first The time value at any given moment Indicates the first The time value at any given moment Indicates the first The normalized value of river flow at the constantly monitored location. Indicates the first The normalized value of river flow at the constantly monitored location. Indicates the first The normalized value of the river channel disturbance energy level is monitored at all times. This represents the constant adjustment parameter in the logarithmic function term.

6. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 5, characterized in that, The specific steps for obtaining the ecological compensation reconciliation chain path structure are as follows: S301: Based on the contract trigger calibration node data group, according to the monitoring grid number and timestamp sequence, query the contract execution hash record set and node status log in the blockchain platform, extract the fund disbursement type field, activation node address and disbursement response start and end time from the disbursement record for each data item, establish a structured data record list, and generate a disbursement-related field data table; S302: Based on the payment association field data table, compare the payment response time period of each fund payment record with the timestamp of the corresponding activation node, calculate the time difference and compare it with the set time difference threshold, determine whether the fund payment type field is consistent with the activation node type identifier, filter the node paths that simultaneously meet the time continuity and type consistency, and obtain the matching node path sequence set. S303: Call the matching node path sequence set, construct the payment path chain structure in the order of timestamps, record the node hash address and payment confirmation identifier associated with the corresponding path segment, integrate the path number, start and end time and associated data fields, and generate the ecological compensation reconciliation chain path structure.

7. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 6, characterized in that, The specific steps for obtaining the boundary node index set of the compensation section are as follows: S401: Call the ecological compensation reconciliation chain path structure, extract the node status code, state transition direction flag and fund response type code of each node in the path according to the path segment number and the first and last node identifiers, construct the three data into a triplet structure and archive it according to the time series to generate the path segment triplet dataset; S402: Based on the path segment triplet dataset, obtain the mapping value of the timestamp difference between adjacent nodes, the status code jump amplitude and the fund response type code, call the fund confirmation cycle and transfer direction identifier value between adjacent nodes, calculate and obtain the continuity offset index of the node pair, determine whether the continuity offset index value exceeds the set continuity boundary benchmark value, mark the boundary nodes for node pairs that exceed the threshold, and generate a node continuity offset index group. The specific formula for obtaining the continuity offset index of the node pair is as follows: ； in, Indicates the first To the The continuity offset index between path nodes Indicates the first The status code value of each node. Indicates the first The status code value of each node. Indicates the first The timestamp value of each node. Indicates the first The timestamp value of each node. Indicates the first The normalized value corresponding to the funding response type code of each node. Indicates the first The normalized value of the path jump direction exponent for each node. Indicates the first The perturbation value of the contract activation cycle of each node. is the base of the natural logarithm; S403: Based on the node continuity offset index group, according to the boundary node index marked as continuity break point, combined with the path segment number and the first and last node identification information, record the correspondence of valid path segment boundary nodes, establish a one-to-one mapping record table between path segment number and first and last node number, and generate a compensation section boundary node index set.

8. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 7, characterized in that, The method further includes the following steps: S5: Based on the compensation section boundary node index set, record the permission overstepping flag for the overstepping behavior node, read the signature private key address identifier, operation timestamp and call event log hash digest corresponding to the node, and sequentially concatenate the three data items to form a behavior signature block structure. After adding the role level and authorization scope, write them sequentially into the responsibility tracking chain structure area to generate the flood storage and detention area responsibility signature traceability structure set. The specific structure set for tracing responsibility signatures in flood storage and detention areas consists of responsibility signature values, role and permission level identifiers, and path node binding information.

9. The blockchain-based method for tracing and processing the implementation of ecological compensation in flood storage and detention areas according to claim 8, characterized in that, The specific steps for obtaining the responsibility signature traceability structure set for the flood storage and detention area are as follows: S501: Based on the compensation section boundary node index set, according to the path segment information and the contract role permission comparison set provided in the node role table, extract the operation instruction type code and permission value in each node operation record, call the preset permission mapping rule in the operation instruction permission correspondence table, determine whether each operation instruction exceeds the role permission value range corresponding to the node, mark the node with permission out of bounds and add a permission out of bounds flag field, and generate a permission out of bounds status identifier list. S502: According to the permission out-of-bounds status identifier list, read the permission out-of-bounds flag status field node by node. For nodes with operation records, extract the signature private key address identifier, operation timestamp and call event log hash digest of the corresponding node. Connect the three data items in the order of private key address, operation time and event hash, and construct the behavior signature unit using the standard byte concatenation method to obtain the behavior signature block structure sequence. S503: Invoke the behavior signature block structure sequence, for the signature block data structure generated for each node, construct a signature chain through a bidirectional hash docking mechanism based on the behavior signature block of the previous node recorded in the path segment information, attach the role level numerical field and authorization range code field of each node, and write the structure unit with the additional information into the responsibility tracking chain structure area in sequence to establish the responsibility signature traceability structure set of the flood storage and detention area.

10. A blockchain-based traceability system for ecological compensation implementation in flood storage and detention areas, characterized in that: The system is used to implement the blockchain-based traceability processing method for ecological compensation execution in flood storage and detention areas as described in any one of claims 1-9, and the system includes: The response lag analysis module acquires remote sensing grid data of flood storage and detention areas, calculates the response time difference of the normalized vegetation index value within the corresponding grid, compares the time difference of the offset time of each parameter, selects the data combination with the largest response offset period as the lag factor combination, and generates a list of vegetation response delay factors. The trigger trajectory recognition module calls the vegetation response delay factor list, retrieves the normalized vegetation index change sequence within the corresponding lag period, compares the normalized vegetation index change rate with the river flow fluctuation frequency for each sequence, identifies valid nodes, and generates a contract trigger calibration node data group. The reconciliation path analysis module, based on the contract triggering and labeling node data group, calls the contract execution hash record set and node status log in the compensation fund disbursement record on the blockchain to perform logical reconciliation comparison between time periods and execution nodes, filter path sequences, and generate an ecological compensation reconciliation chain path structure. The closed boundary identification module calls the ecological compensation reconciliation chain path structure, identifies boundary nodes by judging the consistency of the maximum time jump threshold and the payment classification, records the verified path segment and the first and last node mapping table, and generates a compensation segment boundary node index set. The responsibility identification encapsulation module records the permission overstepping flag for overstepping behavior nodes based on the compensation section boundary node index set. It reads the signature private key address identifier, operation timestamp and call event log hash digest corresponding to the node, and concatenates the three data items in sequence to form a behavior signature block structure. After adding the role level and authorization scope, it writes them sequentially into the responsibility tracking chain structure area to generate the flood storage and detention area responsibility signature traceability structure set.

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