CN-122022174-A - Ecological product value analysis method and system based on multi-source data fusion

CN122022174ACN 122022174 ACN122022174 ACN 122022174ACN-122022174-A

Abstract

The invention discloses an ecological product value analysis method and system based on multi-source data fusion, which relate to the technical field of ecological product value analysis, and divide original ecological data into two-dimensional space grid units according to fixed scales through space grid construction and index units, so that automatic mapping from an actual geographic coordinate system to an analysis grid unit is realized, the multi-source data has a unified projection basis in space, the problems that the spatial references of the multi-source data in original ecological assessment are inconsistent and the results are difficult to transversely compare are solved, and a strict space organization structure is provided for subsequent ecological supply modeling. In the process of mapping the ecological index to the grid unit, the system designs a mechanism for solving average filling of multiple observation points and a mechanism for solving invalid units based on neighborhood interpolation, so that the problem of uneven distribution of the observation points or local missing of the remote sensing data influenced by shielding in field sampling is effectively solved, and the integrity and analysis reliability of the space expression matrix are improved.

Inventors

SONG YOUTAO
ZHANG HAOMING
ZHANG PENG
XIAO FEIFEI
WANG LI
SHAO SIYAO
WANG MENGFAN

Assignees

天津科技大学

Dates

Publication Date: 20260512
Application Date: 20260202

Claims (10)

1. The ecological product value analysis system based on multi-source data fusion is characterized by comprising a heterogeneous ecological factor data acquisition module, an index dimension unified mapping module, a space unit unified analysis module, a multi-dimensional index fusion response construction module, a unified ecological supply index construction module and a region comparability output and analysis module; The heterogeneous ecological factor data acquisition module acquires ecological data of forests through an acquisition sensor and an acquisition device and fits the ecological data into a multi-source data set DW; The index dimension unified mapping module performs cleaning and standardization processing on the multi-source data set DW to obtain an ecological data set SW; the space unit unified analysis module maps the ecological data set SW into the consistent space segmentation units to construct a space expression matrix M; The multidimensional index fusion response construction module fuses the ecological indexes of the space expression matrix M and constructs an ecological supply response function ψeco; the unified ecological supply index construction module constructs a unified ecological supply expression value psisup (i, j) based on an ecological supply response function psieco; The regional comparability output and analysis module performs regional statistical analysis on all the ecological supply expression values psisup (i, j), obtains an output result supporting transverse comparison, and feeds back.
2. The ecological product value analysis system based on multi-source data fusion according to claim 1, wherein the heterogeneous ecological factor data acquisition module comprises a structural response parameter acquisition unit and a productivity and hydrologic response acquisition unit; the structure response parameter acquisition unit acquires vegetation environment data of a forest through a sensor, wherein the vegetation environment data comprise a rainfall interception rate Ri (x, y) of a surface layer, a relative humidity flux response coefficient Hs (x, y) and a surface stability disturbance index Dstab (x, y); the rainfall interception rate Ri (x, y) of the surface layer is acquired through a standard rainfall gauge and a rainfall collector under the crown of the forest; the relative humidity flux response coefficient Hs (x, y) is acquired through an SHT series humidity sensor array installed in a forest; The surface stability disturbance index Dstab (x, y) is acquired through a LiDAR three-dimensional terrain scanner and a soil profile actual measurement tool; The hydrologic response acquisition unit acquires the water maintenance and carbon fixation capacity of the forest ecological system through acquisition equipment, wherein the acquisition equipment comprises a soil capillary water reaction period Tmc (x, y) and a net primary productivity NPP (x, y); The soil capillary water reaction period Tmc (x, y) is acquired through a TDR/FDR soil moisture sensor; The method for acquiring the net primary productivity NPP (x, y) comprises the steps of firstly acquiring the efficiency of converting sunlight into organic matters by plants to acquire light energy utilization efficiency, then deducing a photosynthesis factor through NDVI (New energy density vi), then acquiring photosynthesis effective radiation amount through satellite remote sensing or ground meteorological observation data, and finally multiplying the light energy utilization efficiency, the photosynthesis factor and the photosynthesis effective radiation amount to acquire the net primary productivity NPP (x, y); and fitting the obtained rainfall interception rate Ri (x, y) of the earth surface layer, the relative humidity flux response coefficient Hs (x, y), the soil capillary water reaction period Tmc (x, y), the net primary productivity NPP (x, y) and the earth surface stability disturbance index Dstab (x, y) to obtain a multi-source dataset DW.
3. The system for analyzing the value of the ecological product based on multi-source data fusion according to claim 2, wherein the index dimension unified mapping module comprises a multi-dimension tolerance driving cleaning unit and a dimensionless mapping unit; The multi-scale tolerance driving cleaning unit cleans the multi-source data set DW to obtain a cleaning data set CW; the cleaning comprises trend-drift mixed abnormal point identification and ecological continuity response jump detection; The trend-drift mixed abnormal point identification processing mode is that for each parameter in the multi-source data set DW, a local sliding window sequence is constructed, and local gradient variation rate is calculated; The local gradient mutation rate is obtained by firstly determining a space position point, then setting a neighborhood window of 5X 5 grid around the space position point, then calculating absolute difference value of each point of the neighborhood window, specific data value and the data value of the center point, and finally, adding all the difference values together and dividing the sum of the difference values by the total effective point in the neighborhood to obtain the local gradient mutation rate; When the local gradient variation rate is larger than a preset variation rate threshold value, marking the spatial position points as spatial abnormal drift points; The processing mode of the ecological continuity response jump detection is that slope response curvature analysis is carried out on the time sequence of the space position points, and whether single-point jump behavior exists is judged; Firstly, continuously observing data in a multi-source data set DW at a space position, acquiring continuous data values, analyzing the change speed of the group of continuous data values to acquire a first derivative, and then acquiring a second derivative, namely curvature; When the curvature has a large abnormal value in a fixed period, the non-ecological disturbance exists, and rejection and interpolation substitution are carried out.
4. The system for analyzing the value of the ecological product based on the multi-source data fusion as recited in claim 3, wherein the dimensionless mapping unit performs dimensionless processing on the cleaning data set CW to obtain an ecological data set SW; Dimensionless processing eliminates the dimensionality of data by introducing a median dominant bidirectional mapping mechanism, and specifically comprises the steps of constructing a distribution kernel function range and executing median symmetric expansion normalization; The processing mode for constructing the distribution kernel function range is as follows: S1, acquiring quartile information of data in a cleaning data set CW, wherein a first quartile (Q1) represents that 25% of the data is smaller than the data, a third quartile (Q3) represents that 75% of the data is smaller than the data, and subtracting the first quartile from the third quartile to acquire a quartile distance; S2, constructing a reasonable value range, and respectively expanding the quartile spacing to 1.5 times on the two sides based on the third quartile and the first quartile; Expanding downwards to obtain a lower boundary, wherein the first quartile is subtracted by 1.5 times of the quartile interval; Expanding upwards to obtain an upper boundary, wherein the upper boundary is the third quartile plus 1.5 times of quartile spacing; the interval between the upper boundary and the lower boundary is a reasonable distribution range; the processing mode of executing the median symmetric expansion normalization is that the data in a reasonable distribution range is normalized by a relative median deviation ratio method, and the dimension of the data is eliminated.
5. The system for analyzing the value of the ecological product based on multi-source data fusion of claim 4, wherein the space unit unified analysis module comprises a space grid construction and index unit and an index filling and matrix expression unit; the space grid construction and index unit performs grid division on a research area of the forest in a fixed scale to construct a two-dimensional space grid G (i, j); each two-dimensional spatial grid G (i, j) corresponds to an actual geographic coordinate range [ (xi, xi+Δx), (yj, yj+Δy) ] Wherein Deltax and Deltay represent the actual physical lengths of the grid in the x and y directions respectively; mapping each data point (x, y) coordinate in the ecological dataset SW into a corresponding two-dimensional spatial grid G (i, j) matching logic is as follows: ; Where (x 0, y 0) represents the start coordinates of the analysis region, Representing a downward rounding function; the index filling and matrix expression unit maps the data in the ecological data set SW to a two-dimensional space grid G (i, j) according to a space index table to generate a space expression matrix M; the space expression matrix M is established by judging whether the coordinate position belongs to a two-dimensional space grid G (i, j) according to the corresponding relation of the geographic coordinate position (x, y) in the ecological data set SW; When the geographic coordinate position (x, y) belongs to the two-dimensional space grid G (i, j), assigning data corresponding to the geographic coordinate position (x, y) to a corresponding matrix position, and establishing a space expression matrix M; When a plurality of coordinate points exist in the two-dimensional space grid G (i, j), the data of all the coordinate points are subjected to mean value calculation and then are filled into the corresponding matrix positions, and when the two-dimensional space grid G (i, j) has no effective observation points, the completion is performed on the basis of the data of the space neighborhood, so that a complete space expression matrix M is generated.
6. The ecological product value analysis system based on multi-source data fusion according to claim 5, wherein the multi-dimensional index fusion response construction module comprises an ecological factor coupling structure generation unit and a fusion response function construction unit; The ecological factor coupling structure generating unit carries out structure recombination on the space expression matrix M to construct a plurality of ecological factors, including a hydrological regulation factor Qhd, a biological influence factor QPr and a structural stability regulation factor Qst; the hydrologic regulation factor Qhd is obtained by the following formula: ; Wherein Qhd (i, j) represents a hydrologic regulation factor at the space grid (i, j), MRi (i, j) represents a surface layer rainfall cut-off rate at the space grid (i, j), MHs (i, j) represents a relative humidity flux response coefficient at the space grid (i, j), MTmc (i, j) represents a soil capillary water reaction period at the space grid (i, j), and ex represents a minimum constant; The biological influence factor Qpr is obtained by the following formula: ; Where Qpr (i, j) represents the biological impact factor at spatial grid (i, j), MNPP (i, j) represents the net primary productivity at spatial grid (i, j); The structural stability adjustment factor Qst is obtained by the following formula: ; Wherein Qst (i, j) represents a structural stability adjustment factor at the spatial grid (i, j), ln represents a logarithmic function, MDstab (i, j) represents a surface stability disturbance index at the spatial grid (i, j); The fusion response function construction unit combines the acquired hydrological regulation factor Qhd, biological influence factor QPr and structural stability regulation factor Qst to acquire an ecological supply response function ψeco; The ecological supply response function ψeco is obtained by multiplying the three of the hydrological adjustment factor Qhd, the biological influence factor Qpr, and the structural stability adjustment factor Qst.
7. The system for analyzing the value of the ecological product based on the multi-source data fusion according to claim 6, wherein the unified ecological supply index constructing module comprises a structure adjustment factor calculating unit and a unified supply index outputting unit; The structure adjustment factor calculation unit acquires the terrain elevation at the two-dimensional space grid G (i, j), marks Ev (i, j), introduces a space neighborhood omega (i, j) and calculates a micro-terrain variation delta topo; the microtopography variability Δtopo is obtained by the following formula: Where Δtopo (i, j) represents the micro-terrain variability at the spatial grid (i, j), ev (u, v) represents the elevation of the neighborhood grid; Mapping the obtained micro-terrain variation rate delta topo into an adjustment coefficient phi (i, j) through an exponential adjustment structure; the adjustment coefficient Φ (i, j) is obtained by the following formula: Φ(i,j)=1+λ×tanh(Δtopo(i,j)); where tan h represents the hyperbolic tangent function and λ represents the adjustment factor.
8. The system for analyzing the value of the ecological product based on the multi-source data fusion as recited in claim 7, wherein the unified supply index output unit combines the ecological supply response function ψeco with the adjustment coefficient Φ (i, j) to obtain an ecological supply expression value ψsup (i, j); the eco-feed expression value ψsup (i, j) is obtained by multiplying the eco-feed response function ψeco by the adjustment coefficient Φ (i, j).
9. The system for analyzing the value of the ecological product based on multi-source data fusion according to claim 8, wherein the regional comparability output and analysis module comprises a regional supply statistic extraction unit and a regional supply statistic extraction unit; the regional supply statistics extraction unit carries out aggregation treatment on the ecological supply expression values psisup (i, j) according to the ecological functional region boundary, extracts basic statistics indexes of each region, including regional supply mean value and variation coefficient CV, and provides a quantifiable data basis for transverse comparison The regional supply average value is obtained by calculating the average value of ecological supply expression values psisup (i, j) of any region; the coefficient of variation CV is obtained by dividing the standard in any region by the region supply average value; The transverse supply difference feedback unit carries out transverse parallel analysis on the statistical indexes of the multiple areas, builds a supply comparison function and a grading feedback logic between the areas, and acquires a supply grade classification function L; the supply level classification function L is obtained by matching in the following manner When the ecological supply expression value psi < sup (i, j) is larger than a preset high supply judgment threshold value TH and the variation coefficient CV is smaller than a preset upper judgment threshold value CH, the supply grade classification function L represents one class, and is high in supply; When the preset low supply judgment threshold TL is smaller than or equal to the ecological supply expression value psisup (i, j) and smaller than or equal to the preset high supply judgment threshold TH, the supply grade classification function L represents two kinds of medium supply, the ecological supply function is sound but has fluctuation, and small-range ecological restoration and degenerated land treatment are performed aiming at local supply low-value points; when the ecological supply expression value ψsup (i, j) is smaller than a preset low supply judgment threshold value TL and the variation coefficient CV is larger than a preset lower judgment threshold value CL, the supply grade classification function L represents three types, namely low supply, the ecological system is degraded and has no service function, and the ecological restoration engineering is preferentially implemented as an ecological management key area.
10. The ecological product value analysis method based on multi-source data fusion is applied to the ecological product value analysis system based on multi-source data fusion as claimed in any one of claims 1 to 9, and is characterized by comprising the following steps: Firstly, acquiring ecological data of a forest through an acquisition sensor and an acquisition device by an heterogeneous ecological factor data acquisition module, and fitting the ecological data into a multi-source data set DW; Step two, cleaning and standardizing the multi-source data set DW by using an index dimension unified mapping module to obtain an ecological data set SW; mapping the ecological data set SW into a consistent space segmentation unit by a space unit unified analysis module to construct a space expression matrix M; A multidimensional index fusion response construction module fuses ecological indexes of the space expression matrix M to construct an ecological supply response function ψeco; Step five, a unified ecological supply index construction module constructs a unified ecological supply expression value psisup (i, j) based on an ecological supply response function psieco; Step six, the regional comparability output and analysis module performs regional statistical analysis on all the ecological supply expression values psisup (i, j), obtains an output result supporting transverse comparison, and feeds back the output result.

Description

Ecological product value analysis method and system based on multi-source data fusion Technical Field The invention relates to the technical field of ecological product value analysis, in particular to an ecological product value analysis method and system based on multi-source data fusion. Background The invention relates to the field of ecological environment monitoring and ecological value evaluation, in particular to a quantitative evaluation direction of an ecological system service function, and more particularly, the method is suitable for structural identification and value expression of ecological product supply capacity in natural ecological units such as forests, grasslands and the like. In the traditional ecological assessment technology, the ecological services such as carbon sink, water conservation, soil conservation and the like are often estimated in a single-factor calculation mode, unified and structured expression of ecological supply capacity is difficult to form, and the wide development of trans-regional comparison of ecological resources, ecological compensation partition and multi-element value conversion application is limited. In the prior art, ecological product value assessment has relied on individual modeling or estimation of certain ecological functions, such as representing forest land carbon sequestration values in terms of carbon fixation, and water conservation capacity in terms of soil water content. However, there are often coupling relationships such as structural linkage, resource sharing, and spatial overlapping between the ecological services, and a single index cannot reflect the comprehensive structural performance of the supply capability of the ecological system. Especially in forest or grassland areas, because the ecological process has time accumulation and space heterogeneity, neglecting the multi-factor structure combination can lead to the fragmentation of the evaluation result, has no transverse comparability, and is difficult to support the overall configuration of actual resources and the formulation of partition management strategies. The root cause of the above problem is that the existing system lacks a collaborative modeling and structural quantity fusion mechanism for multi-source ecological factors. Once the ecological service functions are evaluated in isolation, even if the ecological service functions have similar supply capacities, the ecological service functions are difficult to transversely compare through unified standards, so that key links such as ecological function division, ecological compensation pricing and ecological performance assessment are affected. Disclosure of Invention Aiming at the defects of the prior art, the invention provides an ecological product value analysis method and system based on multi-source data fusion, and solves the problems in the background art. The ecological product value analysis system based on multi-source data fusion comprises a heterogeneous ecological factor data acquisition module, an index dimension unified mapping module, a space unit unified analysis module, a multi-dimensional index fusion response construction module, a unified ecological supply index construction module and a regional comparability output and analysis module; The heterogeneous ecological factor data acquisition module acquires ecological data of forests through an acquisition sensor and an acquisition device and fits the ecological data into a multi-source data set DW; The index dimension unified mapping module performs cleaning and standardization processing on the multi-source data set DW to obtain an ecological data set SW; the space unit unified analysis module maps the ecological data set SW into the consistent space segmentation units to construct a space expression matrix M; The multidimensional index fusion response construction module fuses the ecological indexes of the space expression matrix M and constructs an ecological supply response function ψeco; the unified ecological supply index construction module constructs a unified ecological supply expression value psisup (i, j) based on an ecological supply response function psieco; The regional comparability output and analysis module performs regional statistical analysis on all the ecological supply expression values psisup (i, j), obtains an output result supporting transverse comparison, and feeds back. Preferably, the heterogeneous ecological factor data acquisition module comprises a structural response parameter acquisition unit and a productivity and hydrologic response acquisition unit; the structure response parameter acquisition unit acquires vegetation environment data of a forest through a sensor, wherein the vegetation environment data comprise a rainfall interception rate Ri (x, y) of a surface layer, a relative humidity flux response coefficient Hs (x, y) and a surface stability disturbance index Dstab (x, y); the rainfall interception rate Ri (x,