A forest area environment monitoring system based on multi-source data fusion

Abstract

The application discloses a kind of forest area environmental monitoring systems of multi-source data fusion, it is related to the technical field of data analysis, including division module, calculation module and correction module, division module calculates overlapping area, sets reverse factor, calculation module calculates vegetation index and growth rate, fitting growth potential surface, correction module calculates the vigor value of sub-region, corrects the time interval of sub-region.The application corrects competition effect by reverse factor, eliminates the overestimation deviation of NDVI, growth potential surface integrates multiple factors, improves monitoring accuracy, adaptive sampling reduces invalid monitoring, saves remote sensing resources and computing cost, illumination radius dynamically tracks crown competition boundary, time interval correction reflects phenology rhythm, accurately captures growth inflection point, integrates finite element analysis, illumination competition model and adaptive sampling in forestry monitoring, and reverse factor provides a calculable index for quantifying forest community competition intensity, from uniform monitoring to process-driven monitoring.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and in particular to a forest area environmental monitoring system that integrates multi-source data. Background Technology

[0002] In recent years, by integrating satellite, drone and ground observation data, dynamic monitoring of forest resources has been achieved. Bird monitoring PTZ cameras equipped with lightweight AI can autonomously cruise, intelligently identify species and generate distribution heat maps. The self-organizing network technology solves the problem of no electricity and no network in the core area, and realizes automatic transmission of high-definition images in the field. LoRaWAN sensors, together with satellite gateways, have a large coverage radius, long battery life, localized processing of high-frequency data, reduced transmission energy consumption, and ensure the operation of core functions in weak network environments.

[0003] Currently, Chinese invention patent CN120031676A discloses a system and method for constructing a forest pest early warning model. This method re-corrects the initial monitoring intensity of each patch through influencing factors, periodically analyzes the real-time data of all patches to obtain the overall performance index of the monitored forest area, and combines the overall performance index with dynamic judgment rules to analyze whether the current monitoring intensity of all patches needs to be optimized and adjusted. Based on the analysis results, a personalized plan is dynamically generated for each patch, and the personalized plan is mapped to the monitoring forest area early warning model for display. However, the related technology only calculates the overall performance index based on vegetation coverage, ignoring the overlap effect caused by different tree crown diameters existing in the same area. This makes the vegetation coverage indicator ineffective, which is not conducive to the mobility and accuracy of forest area environmental monitoring and has certain limitations. Summary of the Invention

[0004] The technical problem solved by this invention is that related technologies only calculate the overall performance index based on vegetation coverage, ignoring the overlapping effect caused when trees with different crown diameters exist in the same area. This makes the vegetation coverage index ineffective, which is not conducive to the mobility and accuracy of forest area environmental monitoring and has certain limitations.

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a forest area environmental monitoring system with multi-source data fusion, comprising a segmentation module, a calculation module, and a correction module; The partitioning module divides the area into sub-regions, calculates the light radius corresponding to any vegetation according to the preset calculation nodes and the latitude of the sub-regions, calculates the overlapping area based on the light radius of the plants, and sets the inverse factor based on the overlapping area. The computation node is represented as a point in time; The calculation module calculates the vegetation index based on the normalized vegetation index formula, and calculates the growth rate based on the vegetation index and the time interval between adjacent monitoring time points within the monitoring period. Based on natural data within the time interval, accumulated temperature and precipitation are calculated, and a growth potential surface is fitted based on growth rate, accumulated temperature, precipitation, and inverse factor. The correction module calculates the growth potential value of the sub-region based on the growth potential surface, and corrects the time interval of the sub-region based on the growth potential value.

[0006] As a preferred embodiment of the multi-source data fusion forest environment monitoring system described in this invention, the computing node is configured with setting logic, which matches the crown diameter data sequence corresponding to the plant species within the monitoring period according to the monitoring period, and draws a circle with the plant seed position as the center and the crown diameter data as the radius based on the crown diameter data at the same monitoring time point, with the monitoring time points distributed within the monitoring period. Determine whether the centers of the circles at the monitoring time point overlap. If so, select monitoring time points in reverse chronological order and repeatedly draw circles until the centers of the monitoring time points no longer overlap, then set the monitoring time point as a calculation node. If not, then set the monitoring time point as the calculation node; The logic for setting the monitoring period is as follows: match the growth cycle of the plant species, sort the growth cycles in descending order, and set the growth cycle with the largest value as the monitoring period.

[0007] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, a calculation logic is configured for the overlapping area corresponding to the sub-region. The calculation logic includes obtaining the interaction time interval and the independent time interval according to the calculation node. Within an independent time interval, the overlapping area of ​​the sub-regions is set to 0; Within the interaction time interval, calculate the sub-overlap area corresponding to each plant, and set the sum of the sub-overlap areas corresponding to each plant as the overlap area. Obtain the current time point and compare it with the calculation node; If the current time point is earlier than or equal to the computing node, then the time period between the current time point and the computing node is set as an independent time interval, and the time period after the computing node is set as an interactive interval. If the current time point is later than the calculation node, then the time period after the current time point is divided into the interaction time interval.

[0008] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, the calculation logic of the illumination radius includes: obtaining the latitude corresponding to the geometric center point of the sub-region, retrieving the effective radius formula of the FON ellipse influence circle, inputting the latitude corresponding to the geometric center point of the sub-region into the formula, and obtaining the illumination radius. During the interaction time interval, determine whether any plant is independent. If it is, set the sub-overlap area of ​​the plant to 0. If not, determine whether the plant is an occluded plant. If the plant is an occluded plant, the sub-overlap area corresponding to the plant is calculated according to the first algorithm; if the plant is not an occluded plant, the sub-overlap area corresponding to the plant is set to 0. Iterate through the sub-overlapping areas corresponding to each plant, calculate the sum of the sub-overlapping areas, and set this sum as the overlapping area of ​​the sub-region.

[0009] As a preferred embodiment of the multi-source data fusion forest environment monitoring system described in this invention, the logic for determining whether a plant is independent includes drawing a circle in the sub-rectangle corresponding to the sub-region, with the plant's location as the center and the light radius as the radius of the circle. Select any circle corresponding to a plant and determine whether the circle intersects with any other circle. If there is no intersection, the plant is determined to be independent; if there is an intersection, the plant is determined to be not independent, and it is determined whether the plant is a shaded plant. The logic for determining whether a plant is an occluded plant includes: obtaining the circle in the rectangle corresponding to the current time point when setting the calculation node, cropping the sub-rectangle part corresponding to the sub-region, selecting the position of the plant, and determining whether the circle corresponding to the plant is at the top of the layer; If the plant is at the top of the layer, it is determined that the plant is not an obscured plant; if it is not at the top of the layer, it is determined that the plant is an obscured plant.

[0010] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, the first algorithm includes obtaining the average light intensity of the forest area at the current time point. Obtain the light radius corresponding to the plant, and set plants whose light radii overlap with the plant's as related plants; Compare the effective radius of any related plant with that of the plant in question. Set the effective radius with the smaller value as r and the effective radius with the larger value as R. Calculate the distance between the positions of the related plant and the plant in question using the Euclidean distance formula, and denote this distance as d. Obtain the intersection point of the circles corresponding to the light radii of these two plants. Connect the centers of the circles corresponding to these two plants to the intersection point to obtain the central angle between the two plants. Denote the central angle corresponding to R as . ,Will The corresponding central angle is denoted as ; Calculate the shading area between the two plants based on d, R, r, and the shading area calculation expression; Iterate through all the related plants of the plant to obtain the shading area corresponding to each related plant; Select any relevant plant, determine the relationship between the height of the relevant plant and the height of the current plant, and delete or retain the shading area corresponding to the relevant plant. Calculate the sum of the retained shading areas and set the sum of the retained shading areas as the sub-overlap area of ​​the plant.

[0011] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, the inverse factor is represented as follows: ,in, The overlapping area is... The area is a rectangle. It is a constant.

[0012] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, the expression for calculating the growth rate is as follows: ; in, For growth rate, This represents the difference in vegetation index between adjacent monitoring time points. This represents the absolute value operation, where t is the interval between any two adjacent monitoring time points within the monitoring period, and adjacent means that they are adjacent in time sequence. Natural data includes daily average maximum temperature, daily average minimum temperature, and daily average rainfall; The formula for calculating accumulated temperature is: ; in, For accumulated temperature, Let be the average daily maximum temperature on the j-th day of the time interval. Let be the average daily minimum temperature on the j-th day of the time interval. Let j be the day of the time interval; The formula for calculating precipitation is: ; in, For precipitation, Let be the average daily rainfall on day j within the time interval.

[0013] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, a growth potential surface is fitted using a high-order polynomial regression method. The expression for the growth potential surface is, ; in, These are accumulated temperature and precipitation, respectively. The maximum value of the fitting order for the accumulated temperature. The maximum value of the fitting order for precipitation is... Let be the regression coefficients for accumulated temperature of order k and precipitation of order l. For the k-th order accumulated temperature, First-order precipitation.

[0014] As a preferred embodiment of the multi-source data fusion forest area environmental monitoring system described in this invention, the calculation logic of the growth value includes selecting any sub-interval, calculating the growth rate at the current time point, and recording it as the actual growth rate. Based on the growth potential surface, the growth rate with the largest value and the growth rate with the smallest value are obtained; Calculate the first difference between the actual growth rate and the smallest growth rate, and calculate the second difference between the largest growth rate and the smallest growth rate. Calculate the ratio of the first difference to the second difference, and set this ratio as the growth potential value; Obtain the time interval corresponding to the sub-region, calculate the product of the time interval and the growth potential value, and set the product as the time interval of the sub-region after the current time point.

[0015] The beneficial effects of this invention are as follows: by correcting the competition effect through the inverse factor, the overestimation bias of NDVI is eliminated; the growth potential surface integrates multiple factors to improve monitoring accuracy; adaptive sampling reduces invalid monitoring, saving remote sensing resources and computing costs; the illumination radius dynamically tracks the boundary between canopy competition; the time interval correction reflects phenological rhythms; the growth inflection point is accurately captured; finite element analysis, illumination competition model, and adaptive sampling are integrated into forestry monitoring; the inverse factor provides a calculable index for quantifying the intensity of competition in forest communities; and the monitoring shifts from uniform monitoring to process-driven monitoring. Attached Figure Description

[0016] Figure 1 This is a basic flowchart of a forest area environmental monitoring system that integrates multi-source data, as provided in one embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0018] It should be understood that the step numbers used herein are for ease of description only and are not intended to limit the order in which the steps are performed. It should also be understood that the terminology used in this specification is for the purpose of describing specific embodiments only and is not intended to limit the invention.

[0019] As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0021] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0022] Example, refer to Figure 1 As an embodiment of the present invention, a forest area environmental monitoring system with multi-source data fusion is provided, including a segmentation module, a calculation module and a correction module; The partitioning module divides the area into sub-regions, calculates the light radius corresponding to any vegetation according to the preset calculation nodes and the latitude of the sub-regions, calculates the overlapping area based on the light radius of the plants, and sets the inverse factor based on the overlapping area. The computation node is represented as a point in time; The calculation module calculates the vegetation index based on the normalized vegetation index formula, and calculates the growth rate based on the vegetation index and the time interval between adjacent monitoring time points within the monitoring period. Based on natural data within the time interval, accumulated temperature and precipitation are calculated, and a growth potential surface is fitted based on growth rate, accumulated temperature, precipitation, and inverse factor. The correction module calculates the growth potential value of the sub-region based on the growth potential surface, and corrects the time interval of the sub-region based on the growth potential value.

[0023] More preferably, this invention corrects the competition effect through a reverse factor, eliminates the overestimation bias of NDVI, integrates multiple factors through the growth potential surface to improve monitoring accuracy, reduces invalid monitoring through adaptive sampling, saves remote sensing resources and computing costs, dynamically tracks the boundary between canopy competition through the illumination radius, and reflects phenological rhythms through time interval correction, accurately capturing growth inflection points. It integrates finite element analysis, illumination competition model, and adaptive sampling into forestry monitoring, and the reverse factor provides a calculable index for quantifying the intensity of competition in forest communities, shifting from uniform monitoring to process-driven monitoring.

[0024] For each sub-region, there is a partitioning logic. The partitioning logic includes: projecting the curved plane containing the soil of the forest area onto a two-dimensional plane using a projection method; converting the projection result of the soil into a rectangle using a method to convert irregular shapes into regular shapes; setting a dividing frame based on the common factor of the length and the common factor of the width of the rectangle; dividing the forest area into N sub-regions based on the dividing frame; and automatically numbering the sub-regions. More preferably, a three-dimensional model of the forest area is obtained, and the curved plane where the soil is located in the three-dimensional model of the forest area is extracted. The plane where the elevation is equal to the average elevation value of the curved plane is set as the projection plane. The vertical downward direction is selected as the projection direction. The curved plane where the soil is located is projected onto the projection plane. The projection result is recorded as the soil plane. The soil plane is transformed into a rectangle by filling and segmenting methods, and the rectangle satisfies the first constraint condition. The first constraint is that the difference between the area of ​​the rectangle and the area of ​​the soil plane reaches a minimum. Get the length and width of the rectangle, and construct the dividing frame by taking any common factor of the length and any common factor of the width. Divide the rectangle into N sub-rectangles with partition box dimensions, and the sub-rectangles satisfy the second constraint condition. After the division is completed, each sub-region is obtained. The second constraint is expressed as follows: any two sub-rectangles do not overlap, and the sum of the areas of the sub-rectangles is equal to the sum of the areas of the rectangles. The sub-rectangles are assigned numbers, which are natural numbers. This application does not limit the numbering order of the sub-rectangles; that is, the sub-rectangles can be numbered according to any of the existing numbering techniques.

[0025] For computing nodes, there is a configuration logic. Select any sub-region, obtain the plant species and soil data in the sub-region, set the monitoring period, match the crown diameter data sequence corresponding to the plant species in the monitoring period according to the monitoring period, and draw a circle with the plant seed position as the center and the crown diameter data as the radius based on the crown diameter data at the same monitoring time point. The monitoring time points are distributed within the monitoring period. Determine whether the centers of the circles at the monitoring time point overlap. If so, select monitoring time points in reverse chronological order and repeatedly draw circles until the centers of the monitoring time points no longer overlap, then set the monitoring time point as a calculation node. If not, then set the monitoring time point as the calculation node; The logic for setting the monitoring period is as follows: match the growth cycle of the plant species, sort the growth cycles in descending order, and set the growth cycle with the largest value as the monitoring period.

[0026] More preferably, the plant species is represented as the variety name of the plant; Soil data include pH value, organic matter content, nitrogen, phosphorus and potassium content, moisture content and heavy metal ion concentration.

[0027] More preferably, a plant database is retrieved, any plant species is input into the plant database, and the growth cycle corresponding to that plant species is matched. The growth cycle is expressed as the time period from seed germination to the completion of the first flowering and fruiting of the mature plant. By traversing each plant species, the growth cycle corresponding to each plant species is obtained.

[0028] More preferably, the application scenario of this application is to monitor forest areas with mixed tree species from the time of planting. As the trees grow, there may be situations where the crown diameter of dwarf trees is blocked by other trees. By setting the computing nodes, it is possible to distinguish the time points when the trees are not blocked. This is beneficial for subsequent execution of different effective radius algorithms based on the relationship between the time points and the computing nodes, so as to adapt to the monitoring of forest areas at different growth time points. This solves the shortcomings of the existing technology in adjusting the monitoring frequency due to tree occlusion, and greatly improves the monitoring efficiency of forest areas.

[0029] More preferably, the logic for matching the crown diameter data sequence corresponding to the plant species within the monitoring period according to the monitoring period includes setting plant growth simulation parameters in the plant growth simulation software, including plant species, soil data, initial simulation morphology, temperature sequence, humidity sequence, light intensity sequence, and carbon dioxide concentration sequence corresponding to the latitude and longitude of the forest area, setting the initial simulation morphology to seed, setting the data acquisition time interval to the initial monitoring frequency, setting the total running time to the monitoring period, running the plant growth simulation software, and generating the crown diameter sequence of the plant species under the set environmental parameters. The coronal diameter sequence is represented as follows: coronal diameter is collected once at each initial monitoring frequency, in chronological order. The temperature, humidity, light intensity, and carbon dioxide concentration sequences corresponding to the latitude and longitude of the forest area are represented as the average values ​​of the daily measured data for the corresponding latitude and longitude in the forest area meteorological database. For example, on April 12, the historical daily average measured temperatures were 23, 22, 21, 20, 19, 18, 24, ... with an average of 21.5. Therefore, the temperature corresponding to April 12 in the plant growth simulation parameters is 21.5.

[0030] More preferably, the point where the plant seed is located on the curved plane where the soil is located is obtained, and this point is projected onto a rectangle, and the projected point is recorded as the target point; Establish a coordinate system for the rectangle, with the bottom left corner of the rectangle as the origin, the length direction adjacent to the origin as the x-axis, and the width direction connected to the origin as the y-axis, to construct a two-dimensional coordinate system, and make the number of coordinate points inside the rectangle distributed in the first quadrant reach the maximum value. Obtain the coordinates of the target point in the rectangular coordinate system and denote them as the center of the circle.

[0031] More preferably, the initial monitoring time point and the initial monitoring frequency are obtained, where the monitoring time point = initial monitoring time point + n × initial monitoring frequency, and n is a natural number.

[0032] For the overlapping area corresponding to the sub-region, there is a calculation logic configured. The calculation logic includes obtaining the interaction time interval and the independent time interval based on the calculation node. Within an independent time interval, the overlapping area of ​​the sub-regions is set to 0; Within the interaction time interval, calculate the sub-overlap area corresponding to each plant, and set the sum of the sub-overlap areas corresponding to each plant as the overlap area. Obtain the current time point and compare it with the calculation node; If the current time point is earlier than or equal to the computing node, then the time period between the current time point and the computing node is set as an independent time interval, and the time period after the computing node is set as an interactive interval. If the current time point is later than the calculation node, then the time period after the current time point is divided into the interaction time interval; More preferably, this application only monitors the time after the current time point, and the data of the time points before the current time point are not included in the real-time monitoring and calculation. Therefore, the starting point of the interaction time interval and the independent time is the current time point.

[0033] More preferably, the overlapping area of ​​this application is calculated for any monitoring time point. That is, the overlapping area may be different for different monitoring time points, and the inverse factor may also be different.

[0034] The calculation logic for the illumination radius includes obtaining the latitude corresponding to the geometric center point of the sub-region, retrieving the effective radius formula of the FON elliptical influence circle, inputting the latitude corresponding to the geometric center point of the sub-region into the formula, and obtaining the illumination radius. During the interaction time interval, determine whether any plant is independent. If it is, set the sub-overlap area of ​​the plant to 0. If not, determine whether the plant is an occluded plant. If the plant is an occluded plant, the sub-overlap area corresponding to the plant is calculated according to the first algorithm; if the plant is not an occluded plant, the sub-overlap area corresponding to the plant is set to 0. Iterate through the sub-overlapping areas corresponding to each plant, calculate the sum of the sub-overlapping areas, and set the sum as the overlapping area of ​​the sub-region. More preferably, the effective radius formula of the FON elliptical influence circle is expressed as follows: ; in, For the radius of illumination, It is the minor semi-axis of the ellipse. The latitude of the geometric center point of the sub-region is given in the formula for the effective radius. The constant is the value corresponding to different plants. Different values ​​indicate different crown diameters. The smaller the value.

[0035] The logic for determining whether a plant is independent includes drawing a circle in the sub-rectangle corresponding to the sub-region, with the plant's position as the center and the light radius as the radius of the circle; Select any circle corresponding to a plant and determine whether the circle intersects with any other circle. If there is no intersection, the plant is determined to be independent; if there is an intersection, the plant is determined to be not independent, and it is determined whether the plant is a shaded plant. The logic for determining whether a plant is an occluded plant includes: obtaining the circle in the rectangle corresponding to the current time point when setting the calculation node, cropping the sub-rectangle part corresponding to the sub-region, selecting the position of the plant, and determining whether the circle corresponding to the plant is at the top of the layer; If the plant is at the top of the layer, it is determined that the plant is not an obscured plant; if it is not at the top of the layer, it is determined that the plant is an obscured plant.

[0036] The first algorithm includes obtaining the average light intensity of the forest area at the current time point. Obtain the light radius corresponding to the plant, and set plants whose light radii overlap with the plant's as related plants; Compare the effective radius of any related plant with that of the plant in question. Set the effective radius with the smaller value as r and the effective radius with the larger value as R. Calculate the distance between the positions of the related plant and the plant in question using the Euclidean distance formula, and denote this distance as d. Obtain the intersection point of the circles corresponding to the light radii of these two plants. Connect the centers of the circles corresponding to these two plants to the intersection point to obtain the central angle between the two plants. Denote the central angle corresponding to R as . ,Will The corresponding central angle is denoted as ; Calculate the shading area between the two plants based on d, R, r, and the shading area calculation expression; Iterate through all the related plants of the plant to obtain the shading area corresponding to each related plant; Select any relevant plant and determine whether the height of the relevant plant is greater than the height of the plant at the current moment. If the height of the relevant plant is greater than the height of the plant, retain the shading area corresponding to the relevant plant. If the height of the relevant plant is less than or equal to the height of the plant, delete the shading area corresponding to the relevant plant. Calculate the sum of the remaining shading areas and set the sum of the remaining shading areas as the sub-overlap area of ​​the plant. The expression for calculating the shading area is: ; in, The corresponding shading area for these two plants. It is a constant.

[0037] The inverse factor is represented as, ,in, The overlapping area is... The area is a rectangle. It is a constant; More preferably, the overlapping area is proportional to the inverse factor, that is, the larger the overlapping area, the greater the degree of inhibition of plant growth.

[0038] The expression for calculating the growth rate is: ; in, For growth rate, This represents the difference in vegetation index between adjacent monitoring time points. This represents the absolute value operation, where t is the interval between any two adjacent monitoring time points within the monitoring period, and adjacent means that they are adjacent in time sequence. Natural data includes daily average maximum temperature, daily average minimum temperature, and daily average rainfall; More preferably, the natural data is obtained by analyzing the historical natural data corresponding to the forest area, calculating the average value of the historical natural data corresponding to the forest area within the time interval, and setting it as the natural data.

[0039] The formula for calculating accumulated temperature is: ; in, For accumulated temperature, Let be the average daily maximum temperature on the j-th day of the time interval. Let be the average daily minimum temperature on the j-th day of the time interval. Let j be the day of the time interval; The formula for calculating precipitation is: ; in, For precipitation, Let be the average daily rainfall on day j within the time interval.

[0040] More preferably, the normalized vegetation index formula is expressed as follows: ; in, The vegetation index, This is the reflectance value of near-infrared waves. This represents the reflectance value of infrared light waves.

[0041] More preferably, this application is applied to forest area monitoring combining shrubs, trees, herbaceous plants and vines. The near-infrared emission band is distributed in the range of 760~2500nm, preferably three narrowband channels with center wavelengths of 940nm, 1250nm and 1650nm. The infrared emission band is distributed in the range of 630~690nm, preferably a narrowband channel with a center wavelength of 650nm. The spectral response bandwidth of each channel is less than or equal to 30nm, and the signal-to-noise ratio is greater than or equal to 55dB.

[0042] The growth potential surface was fitted using a high-order polynomial regression method. The expression for the growth potential surface is, ; in, These are accumulated temperature and precipitation, respectively. The maximum value of the fitting order for the accumulated temperature. The maximum value of the fitting order for precipitation is... Let be the regression coefficients for accumulated temperature of order k and precipitation of order l. For the k-th order accumulated temperature, First-order precipitation.

[0043] More preferably, Preferably 2, The preferred value is 3.

[0044] More preferably, the surfaces obtained through regression analysis are the maximum and minimum surfaces of plant growth, representing the theoretical maximum and minimum values ​​of plant growth rate under specific accumulated temperature and precipitation conditions, respectively. These surfaces allow for an intuitive understanding of the range of plant growth potential under different climatic conditions, thus providing a theoretical basis for subsequent monitoring and evaluation. The maximum and minimum surfaces provide a theoretical basis for the potential range of plant growth.

[0045] The calculation logic for growth potential includes selecting any sub-interval, calculating the growth rate at the current time point, and recording it as the actual growth rate. Based on the growth potential surface, the growth rate with the largest value and the growth rate with the smallest value are obtained; Calculate the first difference between the actual growth rate and the smallest growth rate, and calculate the second difference between the largest growth rate and the smallest growth rate. Calculate the ratio of the first difference to the second difference, and set this ratio as the growth potential value; Obtain the time interval corresponding to the sub-region, calculate the product of the time interval and the growth potential value, and set the product as the time interval of the sub-region after the current time point.

[0046] More preferably, this invention corrects the competition effect through a reverse factor, eliminates the overestimation bias of NDVI, integrates multiple factors through the growth potential surface to improve monitoring accuracy, reduces invalid monitoring through adaptive sampling, saves remote sensing resources and computing costs, dynamically tracks the boundary between canopy competition through the illumination radius, and reflects phenological rhythms through time interval correction, accurately capturing growth inflection points. It integrates finite element analysis, illumination competition model, and adaptive sampling into forestry monitoring, and the reverse factor provides a calculable index for quantifying the intensity of competition in forest communities, shifting from uniform monitoring to process-driven monitoring.

[0047] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0048] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the protection scope of the present invention.

Claims

1. A forest area environmental monitoring system that integrates multi-source data, characterized in that, It includes a partitioning module, a calculation module, and a correction module; The partitioning module divides the area into sub-regions, calculates the light radius corresponding to any vegetation according to the preset calculation nodes and the latitude of the sub-regions, calculates the overlapping area based on the light radius of the plants, and sets the inverse factor based on the overlapping area. The computation node is represented as a point in time; The calculation module calculates the vegetation index based on the normalized vegetation index formula, and calculates the growth rate based on the vegetation index and the time interval between adjacent monitoring time points within the monitoring period. Based on natural data within the time interval, accumulated temperature and precipitation are calculated, and a growth potential surface is fitted based on growth rate, accumulated temperature, precipitation, and inverse factor. The correction module calculates the growth potential value of the sub-region based on the growth potential surface, and corrects the time interval of the sub-region based on the growth potential value.

2. The forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, For the computing nodes, there is a configuration logic that matches the crown diameter data sequence corresponding to the plant species within the monitoring period according to the monitoring period. Based on the crown diameter data at the same monitoring time point, a circle is drawn with the plant seed position as the center and the crown diameter data as the radius. The monitoring time points are distributed within the monitoring period. Determine whether the centers of the circles at the monitoring time point overlap. If so, select monitoring time points in reverse chronological order and repeatedly draw circles until the centers of the monitoring time points no longer overlap, then set the monitoring time point as a calculation node. If not, then set the monitoring time point as the calculation node; The logic for setting the monitoring period is as follows: match the growth cycle of the plant species, sort the growth cycles in descending order, and set the growth cycle with the largest value as the monitoring period.

3. The forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, For the overlapping area corresponding to the sub-region, there is a calculation logic configured. The calculation logic includes obtaining the interaction time interval and the independent time interval based on the calculation node. Within an independent time interval, the overlapping area of ​​the sub-regions is set to 0; Within the interaction time interval, calculate the sub-overlap area corresponding to each plant, and set the sum of the sub-overlap areas corresponding to each plant as the overlap area. Obtain the current time point and compare it with the calculation node; If the current time point is earlier than or equal to the computing node, then the time period between the current time point and the computing node is set as an independent time interval, and the time period after the computing node is set as an interactive interval. If the current time point is later than the calculation node, then the time period after the current time point is divided into the interaction time interval.

4. The forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, The calculation logic for the illumination radius includes obtaining the latitude corresponding to the geometric center point of the sub-region, retrieving the effective radius formula of the FON elliptical influence circle, inputting the latitude corresponding to the geometric center point of the sub-region into the formula, and obtaining the illumination radius. During the interaction time interval, determine whether any plant is independent. If it is, set the sub-overlap area of ​​the plant to 0. If not, determine whether the plant is an occluded plant. If the plant is an occluded plant, the sub-overlap area corresponding to the plant is calculated according to the first algorithm; if the plant is not an occluded plant, the sub-overlap area corresponding to the plant is set to 0. Iterate through the sub-overlapping areas corresponding to each plant, calculate the sum of the sub-overlapping areas, and set this sum as the overlapping area of ​​the sub-region.

5. A forest area environmental monitoring system based on multi-source data fusion as described in claim 4, characterized in that, The logic for determining whether a plant is independent includes drawing a circle in the sub-rectangle corresponding to the sub-region, with the plant's position as the center and the light radius as the radius of the circle; Select any circle corresponding to a plant and determine whether the circle intersects with any other circle. If there is no intersection, the plant is determined to be independent; if there is an intersection, the plant is determined to be not independent, and it is determined whether the plant is a shaded plant. The logic for determining whether a plant is an occluded plant includes: obtaining the circle in the rectangle corresponding to the current time point when setting the calculation node, cropping the sub-rectangle part corresponding to the sub-region, selecting the position of the plant, and determining whether the circle corresponding to the plant is at the top of the layer; If the plant is at the top of the layer, it is determined that the plant is not an obscured plant; if it is not at the top of the layer, it is determined that the plant is an obscured plant.

6. The forest area environmental monitoring system based on multi-source data fusion as described in claim 4, characterized in that, The first algorithm includes obtaining the average light intensity of the forest area at the current time point. Obtain the light radius corresponding to the plant, and set plants whose light radii overlap with the plant's as related plants; Compare the effective radius of any related plant with that of the plant in question. Set the effective radius with the smaller value as r and the effective radius with the larger value as R. Calculate the distance between the positions of the related plant and the plant in question using the Euclidean distance formula, and denote this distance as d. Obtain the intersection point of the circles corresponding to the light radii of these two plants. Connect the centers of the circles corresponding to these two plants to the intersection point to obtain the central angle between the two plants. Denote the central angle corresponding to R as . ,Will The corresponding central angle is denoted as ; Calculate the shading area between the two plants based on d, R, r, and the shading area calculation expression; Iterate through all the related plants of the plant to obtain the shading area corresponding to each related plant; Select any relevant plant, determine the relationship between the height of the relevant plant and the height of the current plant, and delete or retain the shading area corresponding to the relevant plant. Calculate the sum of the retained shading areas and set the sum of the retained shading areas as the sub-overlap area of ​​the plant.

7. A forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, The inverse factor is represented as, ,in, The overlapping area is... The area is a rectangle. It is a constant.

8. A forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, The expression for calculating the growth rate is: ; in, For growth rate, This represents the difference in vegetation index between adjacent monitoring time points. This represents the absolute value operation, where t is the interval between any two adjacent monitoring time points within the monitoring period, and adjacent means that they are adjacent in time sequence. Natural data includes daily average maximum temperature, daily average minimum temperature, and daily average rainfall; The formula for calculating accumulated temperature is: ; in, For accumulated temperature, Let be the average daily maximum temperature on the j-th day of the time interval. Let be the average daily minimum temperature on the j-th day of the time interval. Let j be the day of the time interval; The formula for calculating precipitation is: ; in, For precipitation, Let be the average daily rainfall on day j within the time interval.

9. A forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, The growth potential surface was fitted using a high-order polynomial regression method. The expression for the growth potential surface is, ; in, These are accumulated temperature and precipitation, respectively. The maximum value of the fitting order for the accumulated temperature. The maximum value of the fitting order for precipitation is... Let be the regression coefficients for accumulated temperature of order k and precipitation of order l. For the k-th order accumulated temperature, First-order precipitation.

10. A forest area environmental monitoring system based on multi-source data fusion as described in claim 1, characterized in that, The calculation logic for growth potential includes selecting any sub-interval, calculating the growth rate at the current time point, and recording it as the actual growth rate. Based on the growth potential surface, the growth rate with the largest value and the growth rate with the smallest value are obtained; Calculate the first difference between the actual growth rate and the smallest growth rate, and calculate the second difference between the largest growth rate and the smallest growth rate. Calculate the ratio of the first difference to the second difference, and set this ratio as the growth potential value; Obtain the time interval corresponding to the sub-region, calculate the product of the time interval and the growth potential value, and set the product as the time interval of the sub-region after the current time point.

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