Automatic accurate estimation method for total production value of forest ecosystem based on remote sensing technology

Abstract

The invention relates to the technical field of forest total production value estimation, and discloses a forest ecosystem total production value automatic accurate estimation method based on a remote sensing technology, which comprises the following steps: acquiring a real-time positioning signal of remote sensing acquisition equipment, acquiring a to-be-estimated forest map from a geographic information database, and displaying the real-time positioning signal on the map; meteorological parameters and forest characteristic parameters of a to-be-estimated forest are acquired through remote sensing acquisition equipment, and the ground estimation model performs preliminary estimation on the total production value of the forest ecosystem through the meteorological parameters and the forest characteristic parameters; collecting landform characteristics of the map, judging whether the preliminary estimation result is corrected or not according to the landform characteristics, and adjusting the preliminary estimation result according to the landform characteristics if the preliminary estimation result needs to be corrected; and storing the adjusted estimation result, and displaying a dynamic fluctuation graph of the adjusted estimation result on a visual device. The method is accurate and reliable in estimation of the total production value of the forest ecosystem.

Description

Technical Field

[0001] The present invention relates to the technical field of forest gross product estimation, and in particular to an automatic and accurate estimation method for the gross product of a forest ecosystem based on remote sensing technology. Background Art

[0002] Remote sensing technology is a method of obtaining information about objects or the environment through detection equipment (such as satellites, drones, airplanes, etc.) without direct contact with the object being measured. This technology is mainly used to observe and analyze various natural phenomena on the earth's surface and in its atmosphere. Remote sensing technology is widely used in areas such as environmental monitoring, resource surveys, disaster assessments, and climate research. Gross Primary Productivity (GPP) refers to the total amount of carbon fixed by a forest ecosystem through photosynthesis over a certain period of time. It represents the process by which plants absorb carbon dioxide (CO2) from the atmosphere and convert it into organic matter, and is a key link in the carbon cycle of forest ecosystems.

[0003] Existing technologies often rely on ground surveys and traditional monitoring methods, which are affected by factors such as human interference, sample size limitations, and uneven geographical coverage, resulting in large uncertainties in the estimation results. Traditional methods require a lot of manpower, material resources, and time for data collection and estimation, which makes the estimation process cumbersome and time-consuming, and it is difficult to meet the needs of fast, efficient, and accurate estimation.

[0004] Therefore, it is necessary to provide an automatic and accurate estimation method for the gross domestic product of forest ecosystems based on remote sensing technology to solve the problem that the estimation of the gross domestic product of forest ecosystems in the existing technology is not efficient and accurate enough. Summary of the invention

[0005] In view of this, the present invention proposes an automatic and accurate estimation method for the gross domestic product of forest ecosystems based on remote sensing technology, aiming to solve the problem that the estimation of the gross domestic product of forest ecosystems in the prior art is not efficient and accurate enough and the cost is high.

[0006] The present invention proposes an automatic and accurate estimation method for the gross domestic product of forest ecosystems based on remote sensing technology, comprising:

[0007] Acquire a real-time positioning signal of a remote sensing acquisition device, obtain a forest map to be estimated from a geographic information database, and display the real-time positioning signal on the map;

[0008] The meteorological parameters and forest characteristic parameters of the forest to be estimated are collected by remote sensing collection equipment, and the ground estimation model makes a preliminary estimate of the gross domestic product of the forest ecosystem through the meteorological parameters and forest characteristic parameters; wherein the meteorological parameters include the temperature of the day, the precipitation of the day and the sunshine duration of the day; and the forest characteristic parameters include the normalized vegetation index, the leaf area index and the plant cover density;

[0009] Collecting the geomorphic features of the map, judging whether to correct the preliminary estimated result according to the geomorphic features, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the geomorphic features; wherein the geomorphic features include terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height;

[0010] The adjusted estimation results are stored, and a dynamic fluctuation graph of the adjusted estimation results is displayed on a visual device.

[0011] Furthermore, the step of obtaining the real-time positioning signal of the remote sensing acquisition device, obtaining the forest map to be estimated from the geographic information database, and displaying the real-time positioning signal on the map includes:

[0012] Configuring a positioning module on the remote sensing acquisition device, communicating the positioning module with a ground estimation model, and obtaining a position signal of the positioning module;

[0013] The forest map to be estimated is evenly divided into a number of unit grids according to coordinates and equal areas, and the position signal is matched with the divided forest map, and a unique number or identifier is assigned to each unit grid;

[0014] The ground estimation model receives and interprets the location signal from the remote sensing acquisition equipment, extracting the real-time longitude, latitude and altitude information;

[0015] Using coordinate conversion and matching algorithms, the received location signal is matched with the grid cells divided on the map, and the grid cell where the location signal is located is determined according to the latitude and longitude of the location signal;

[0016] The position of the remote sensing acquisition device is dynamically updated on the map, and the grid unit where the remote sensing acquisition device is located is marked, and the current coordinates, altitude and corresponding grid unit number of the device are displayed on the map.

[0017] Furthermore, the meteorological parameters and forest characteristic parameters of the forest to be estimated are collected by remote sensing collection equipment, and the ground estimation model makes a preliminary estimation of the gross production value of the forest ecosystem through the meteorological parameters and forest characteristic parameters, including:

[0018] The gross value of forest ecosystem production is preliminarily estimated using the following formula:

[0019] GPP=(S×D×0.24)×(α×NDVI+β)×∈max×{1 / [1+e -k(T-Topt) ]}×[P / (P+P0)]×[LAI / (1+LAI)]×CD;

[0020] ∈max=∈c×∈a×∈b;

[0021] In the above formula, GPP is the preliminary estimated gross forest ecosystem production, unit: gCm 2 d -1 ; S is the solar radiation constant, S = 1361W / m 2 ; D is the sunshine duration of the day in hours; 0.24 = 1 / 2*0.48, 1 / 2 is the conversion of total solar radiation into photosynthetically active radiation accounting for 50%, 0.48 is the conversion of W / m 2 Convert to MJ / m 2 coefficient; α and β are empirical coefficients, α = 1.2, β = -0.1; NDVI is the normalized difference vegetation index; ∈max is the maximum light energy utilization rate, ∈c is the maximum light energy utilization rate under astronomical conditions, ∈c ranges from [1.5-2.5], unit: gCMJ- 1 ; ∈a is the utilization correction coefficient under the temperature and moisture of the day, and the value range of ∈a is [0.2, 1.0]; ∈b is the correction coefficient under the vegetation condition, and the value range of ∈b is [0.5, 1.0]; T is the temperature of the day, unit: ℃; Topt is the optimal temperature for photosynthesis, Topt = 25℃; k is the temperature sensitivity coefficient, k = 0.05; P is the precipitation of the day, unit: mm; P0 is the water saturation constant, and the value range of P0 is [5, 10], unit: mm; LAI is the leaf area index; CD is the plant cover density.

[0022] Furthermore, judging whether to correct the preliminary estimation result according to the landform feature includes:

[0023] Determine whether to revise the preliminary estimate based on the terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height;

[0024] Based on the judgment results, the preliminary estimated results are corrected according to terrain slope, terrain aspect, altitude, convexity and concavity and vegetation height.

[0025] Further, judging whether to correct the preliminary estimated result according to the landform feature, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the landform feature, further includes:

[0026] If the terrain slope is less than or equal to 5°, the result of the preliminary estimation is not adjusted and the result of the preliminary estimation is used as the first estimation value GPP1;

[0027] If the terrain slope is greater than 5°, the result of the preliminary estimation is adjusted and the adjusted value is used as the first estimated value GPP1;

[0028] The formula for correcting the initial estimate based on terrain slope is:

[0029] GPP1 = GPP × (1 + CF1);

[0030] In the above formula, GPP1 is the value after a correction of the preliminary estimated gross forest ecosystem product, that is, the first estimated value; GPP is the preliminary estimated gross forest ecosystem product; CF1 is the correction coefficient determined according to the slope category, where the value range of CF1 is [0, 0.3];

[0031] If the terrain slope is greater than or equal to 5° and less than 15°, the result of the preliminary estimation is adjusted, and the value range of CF1 is [0.05, 0.15]. For every 1° increase in slope, CF1 increases by 0.01;

[0032] If the terrain slope is greater than or equal to 15°, the result of the preliminary estimation is adjusted, and the value range of CF1 is (0.15, 0.3], and for every 1° increase in slope, CF1 increases by 0.03.

[0033] Further, judging whether to correct the preliminary estimated result according to the landform feature, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the landform feature, further includes:

[0034] The first estimated value GPP1 is adjusted according to the terrain slope to obtain a second estimated value GPP2. The calculation formula of the second estimated value GPP2 is:

[0035] Southward slope aspect: GPP2 = GPP1 × (1 + CFsouth);

[0036] North slope aspect: GPP2 = GPP1 × (1 + CFnorth);

[0037] East slope aspect: GPP2 = GPP1 × (1 + CFeast);

[0038] Westward slope aspect: GPP2 = GPP1 × (1 + CFwest);

[0039] In the above formula, GPP2 is the value after secondary correction of the preliminary estimated gross forest ecosystem product, that is, the second estimated value; GPP1 is the first estimated value; CFsouth is the south slope correction coefficient, ranging from [0.10, 0.15]; CFnorth is the north slope correction coefficient, ranging from [-0.10, -0.15]; CFeast is the east slope correction coefficient, ranging from [0.05, 0.10]; CFwest is the west slope correction coefficient, ranging from [0.05, 0.10];

[0040] If the terrain slope is between two directions, the average of the values ​​of the two directions after secondary correction of the preliminary estimated gross forest ecosystem production is taken as the second estimated value GPP2;

[0041] If there are multiple terrain slopes in the terrain area, the average of the values ​​of the preliminary estimated gross forest ecosystem product of several slopes after secondary correction is taken as the second estimated value GPP2.

[0042] Further, judging whether to correct the preliminary estimated result according to the landform feature, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the landform feature, further includes:

[0043] A first preset altitude A1 and a second preset altitude A2 are preset, and the first preset altitude A1 is lower than the second preset altitude A2;

[0044] If the altitude is lower than the first preset altitude A1, the second estimated value GPP2 is not adjusted, and the second estimated value GPP2 is used as the third estimated value GPP3;

[0045] If the altitude is greater than or equal to the first preset altitude A1 and less than or equal to the second preset altitude A2, the second estimated value GPP2 is corrected by the first adjustment coefficient to obtain a third estimated value GPP3;

[0046] If the altitude is greater than or equal to the second preset altitude A1, the second estimated value GPP2 is corrected by the second adjustment coefficient to obtain a third estimated value GPP3;

[0047] The first adjustment coefficient is smaller than the second adjustment coefficient.

[0048] Further, judging whether to correct the preliminary estimated result according to the landform feature, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the landform feature, further includes:

[0049] A first preset concavity B1 and a second preset concavity B2 are preset, and the first preset concavity B1 is smaller than the second preset concavity B2;

[0050] If the concavity is smaller than the first preset concavity B1, the third estimated value GPP3 is not adjusted, and the third estimated value GPP3 is used as the fourth estimated value GPP4;

[0051] If the concavity is greater than or equal to the first preset concavity B1 and less than or equal to the second preset concavity B2, the third estimated value GPP3 is corrected by the first adjustment coefficient to obtain a fourth estimated value GPP4;

[0052] If the concavity is greater than or equal to the second preset concavity B2, the third estimated value is corrected by the second adjustment coefficient to obtain a value after four corrections, thereby obtaining a fourth estimated value GPP4;

[0053] The first adjustment coefficient is smaller than the second adjustment coefficient.

[0054] Further, judging whether to correct the preliminary estimated result according to the landform feature, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the landform feature, further includes:

[0055] A first vegetation height value C1 is preset, and if the vegetation height is lower than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, and the fourth estimated value GPP4 is used as the final gross production value;

[0056] If the vegetation height is higher than the first vegetation height value C1, the fourth estimated value GPP4 is adjusted, and the adjusted fourth estimated value GPP4 is used as the final gross production value.

[0057] Furthermore, if the vegetation height is higher than the first height value C1, the fourth estimated value GPP4 is adjusted, and the adjusted fourth estimated value GPP4 is used as the final gross production value, including:

[0058] The fourth estimated value GPP4 is adjusted according to the vegetation height, and the adjusted fourth estimated value GPP4 is used as the final gross production value. The calculation formula is:

[0059] GPP5 = GPP4 × (1 + CF3);

[0060] In the above formula, GPP5 is the value after five corrections of the preliminary estimated gross forest ecosystem product, that is, the fifth estimated value; GPP4 is the fourth estimated value; CF3 is the correction coefficient determined according to the vegetation height, where the value range of CF5 is [-0.2, 0];

[0061] Preset a second vegetation height value C2;

[0062] If the vegetation height is less than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, that is, CF5 = 0;

[0063] If the vegetation height is greater than the first vegetation height value C1 and less than or equal to the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is [-0.05, -0.10];

[0064] If the vegetation height is greater than the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is (-0.10, -0.20].

[0065] Compared with the prior art, the present invention has the following beneficial effects:

[0066] The automatic and accurate estimation method of forest ecosystem gross product based on remote sensing technology can achieve accurate GPP evaluation by integrating real-time positioning signals, meteorological parameters and forest characteristic parameters. The acquisition of real-time positioning signals and the display of forest maps in the geographic information database make the estimation process accurate in position and spatially consistent; the meteorological parameters (temperature, precipitation, sunshine duration) and forest characteristic parameters (normalized vegetation index, leaf area index, plant cover density) collected by remote sensing acquisition equipment provide comprehensive data support for the preliminary and accurate estimation of GPP; when correcting the preliminary estimation results, the geomorphic characteristics are considered: slope, aspect, altitude, convexity and concavity and vegetation height, thereby improving the accuracy and reliability of the estimation; finally, the adjusted results are stored and their dynamic fluctuation graphs are displayed on visual devices, making the monitoring and analysis of changes in forest ecosystem productivity more intuitive and convenient; this method not only improves the accuracy of the data, but also improves the real-time response capability to changes in forest ecosystems, and has important practical application value for ecological management and protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0068] Figure 1 A flowchart of a method for automatically and accurately estimating the gross domestic product of a forest ecosystem based on remote sensing technology provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0069] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0070] In some embodiments of the present application, see Figure 1 As shown, this embodiment provides an automatic and accurate estimation method for the gross domestic product of a forest ecosystem based on remote sensing technology, comprising the following steps:

[0071] S100, obtaining a real-time positioning signal of a remote sensing acquisition device, obtaining a forest map to be estimated from a geographic information database, and displaying the real-time positioning signal on the map;

[0072] S200, collecting meteorological parameters and forest characteristic parameters of the forest to be estimated through remote sensing collection equipment, and the ground estimation model makes a preliminary estimate of the gross domestic product of the forest ecosystem through the meteorological parameters and forest characteristic parameters; wherein the meteorological parameters include the temperature of the day, the precipitation of the day and the sunshine duration of the day; the forest characteristic parameters include the normalized vegetation index, the leaf area index and the plant cover density;

[0073] S300, collecting geomorphic features of the map, and judging whether to correct the preliminary estimated result according to the geomorphic features, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the geomorphic features; wherein the geomorphic features include terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height;

[0074] S400: storing the adjusted estimation result, and displaying a dynamic fluctuation graph of the adjusted estimation result on a visual device.

[0075] It can be understood that the automatic estimation method of the gross product of forest ecosystem based on remote sensing technology of the present invention can achieve accurate GPP evaluation by integrating real-time positioning signals, meteorological parameters and forest characteristic parameters. The acquisition of real-time positioning signals and the display of forest maps in the geographic information database make the estimation process have position accuracy and spatial consistency; the meteorological parameters (temperature, precipitation, sunshine duration of the day) and forest characteristic parameters (normalized vegetation index, leaf area index, plant cover density) collected by remote sensing acquisition equipment provide comprehensive data support for the preliminary and accurate estimation of GPP; when correcting the preliminary estimation results, the landform characteristics are considered: slope, slope aspect, altitude, convexity and concavity and vegetation height, thereby improving the accuracy and reliability of the estimation; finally, the adjusted results are stored and their dynamic fluctuation graphs are displayed on visual devices, making the monitoring and analysis of changes in forest ecosystem productivity more intuitive and convenient; this method not only improves the accuracy of the data, but also improves the real-time response capability to changes in forest ecosystems, and has important practical application value for ecological management and protection. Preferably, the remote sensing acquisition equipment includes satellites, drones and aircraft.

[0076] In some embodiments of the present application, obtaining a real-time positioning signal of a remote sensing acquisition device, obtaining a forest map to be estimated from a geographic information database, and displaying the real-time positioning signal on a map includes:

[0077] Configure a positioning module on the remote sensing acquisition device, communicate the positioning module with the ground estimation model, and obtain the position signal of the positioning module;

[0078] The forest map to be estimated is evenly divided into a number of unit grids according to coordinates and equal areas, and the location signal is matched with the divided forest map, and a unique number or identifier is assigned to each unit grid;

[0079] The ground estimation model receives and interprets the location signal from the remote sensing acquisition equipment, extracting the real-time longitude, latitude and altitude information;

[0080] Use coordinate conversion and matching algorithms to match the received location signal with the grid cells divided on the map, and determine the grid cell where the location signal is located based on its latitude and longitude;

[0081] The location of the remote sensing acquisition device is dynamically updated on the map, and the grid unit where the remote sensing acquisition device is located is marked, and the current coordinates, altitude and corresponding grid unit number of the device are displayed on the map.

[0082] It can be understood that accurate GPP estimation is achieved by configuring a positioning module on the remote sensing acquisition device and communicating it with the ground estimation model to obtain a real-time location signal and match the signal with the forest map in the geographic information database; this method first divides the forest map evenly into multiple grid cells and assigns a unique number to each grid. Subsequently, through coordinate conversion and matching algorithms, the real-time longitude, latitude and altitude information is matched with the map grid, ensuring the accuracy and real-time nature of positioning, dynamically updating the location of the remote sensing acquisition device, and marking the grid cell where the device is located and its detailed coordinates and altitude information on the map, providing clear spatial positioning and data visualization, which not only improves the accuracy of the estimation, but also enhances the real-time monitoring capability, making the management and analysis of forest ecosystems more scientific and efficient.

[0083] In some embodiments of the present application, meteorological parameters and forest characteristic parameters of the forest to be estimated are collected by remote sensing collection equipment, and the ground estimation model makes a preliminary estimate of the gross production value of the forest ecosystem through the meteorological parameters and forest characteristic parameters, including:

[0084] The gross value of forest ecosystem production is preliminarily estimated using the following formula:

[0085] GPP=(S×D×0.24)×(α×NDVI+β)×∈max×{1 / [1+e -k(T-Topt) ]}×[P / (P+P0)]×[LAI / (1+LAI)]×CD;

[0086] ∈max=∈c×∈a×∈b;

[0087] In the above formula, GPP is the preliminary estimated gross forest ecosystem production, unit: gCm 2 d -1 ; S is the solar radiation constant, S = 1361W / m 2 ; D is the sunshine duration of the day in hours; 0.24 = 1 / 2*0.48, 1 / 2 is the conversion of total solar radiation into photosynthetically active radiation accounting for 50%, 0.48 is the conversion of W / m 2 Convert to MJ / m 2 coefficient; α and β are empirical coefficients, α = 1.2, β = -0.1; NDVI is the normalized difference vegetation index; ∈max is the maximum light energy utilization rate, ∈c is the maximum light energy utilization rate under astronomical conditions, ∈c ranges from [1.5-2.5], unit: gCMJ- 1; ∈a is the utilization correction coefficient under the temperature and moisture of the day, and the value range of ∈a is [0.2, 1.0]; ∈b is the correction coefficient under the vegetation condition, and the value range of ∈b is [0.5, 1.0]; T is the temperature of the day, unit: ℃; Topt is the optimal temperature for photosynthesis, Topt = 25℃; k is the temperature sensitivity coefficient, k = 0.05; P is the precipitation of the day, unit: mm; P0 is the water saturation constant, and the value range of P0 is [5, 10], unit: mm; LAI is the leaf area index; CD is the plant cover density.

[0088] It can be understood that the use of the above formula to make a preliminary estimate of the gross domestic product of the forest ecosystem combines a variety of key meteorological and forest characteristic parameters, and has significant advantages. In the formula, the main factors affecting the forest GPP are fully integrated by considering solar radiation, sunshine duration, vegetation index, light energy utilization, daily temperature, precipitation, leaf area index and plant cover density. Specifically, the formula takes into account the conversion efficiency of photosynthetically active radiation, the impact of environmental conditions on light energy utilization, the optimization effect of temperature on photosynthesis, and the role of water and plant cover, thereby providing a more accurate GPP estimate. In addition, ∈max combines astronomical conditions, daily temperature and vegetation conditions to make the estimation results more in line with actual conditions. Through this comprehensive approach, the changes in the productivity of forest ecosystems can be more accurately reflected, providing strong data support for forest management and ecological research. Preferably, the ground estimation model is a formula for calculating GPP.

[0089] In some embodiments of the present application, judging whether to correct the preliminary estimation result according to the landform characteristics includes:

[0090] Determine whether to revise the preliminary estimate based on the terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height;

[0091] Based on the judgment results, the preliminary estimated results are corrected according to terrain slope, terrain aspect, altitude, convexity and concavity and vegetation height.

[0092] It can be understood that by considering the terrain slope, aspect, altitude, convexity and concavity, and vegetation height in turn to determine whether to correct the GPP, the accuracy and reliability of the estimation results can be significantly improved. First, by correcting according to the terrain slope, the influence of light and meteorological conditions caused by terrain changes can be corrected, thereby more accurately reflecting forest productivity. Next, considering the terrain aspect can further adjust the influence caused by changes in light angles to ensure the comprehensiveness of the estimation results. Finally, the consideration of vegetation height can correct the shielding effect of tall vegetation on light and radiation, making the results more realistic. The comprehensive application of these factors for correction enables the estimation of GPP to more comprehensively reflect the influence of terrain and vegetation conditions on forest productivity, improve the accuracy and practical application value of the data, and provide a more reliable basis for forest management and ecological research.

[0093] In some embodiments of the present application, whether to correct the preliminary estimated result is determined according to the landform features. If it is determined that correction is required, the preliminary estimated result is adjusted according to the landform features, which further includes:

[0094] If the terrain slope is less than or equal to 5°, the result of the preliminary estimation is not adjusted and is used as the first estimation value GPP1;

[0095] If the terrain slope is greater than 5°, the preliminary estimated result is adjusted and the adjusted value is used as the first estimated value GPP1;

[0096] The formula for correcting the initial estimate based on terrain slope is:

[0097] GPP1 = GPP × (1 + CF1);

[0098] In the above formula, GPP1 is the value after a correction of the preliminary estimated gross forest ecosystem product, that is, the first estimated value; GPP is the preliminary estimated gross forest ecosystem product; CF1 is the correction coefficient determined according to the slope category, where the value range of CF1 is [0, 0.3];

[0099] If the terrain slope is greater than or equal to 5° and less than 15°, the preliminary estimate is adjusted, and the value range of CF1 is [0.05, 0.15]. For every 1° increase in slope, CF1 increases by 0.01;

[0100] If the terrain slope is greater than or equal to 15°, the preliminary estimate is adjusted and the value range of CF1 is (0.15, 0.3], where CF1 increases by 0.03 for every 1° increase in slope.

[0101] It can be understood that the scheme of correcting GPP according to terrain slope greatly improves the accuracy and reliability of the estimate by adjusting the preliminary estimate results through precise correction coefficients. Specifically, when the terrain slope is less than or equal to 5°, the slope has little effect on the estimate results, so no adjustment is required. However, when the slope exceeds 5°, the slope has a significant impact on light and meteorological conditions, and the GPP needs to be adjusted. For areas with slopes between 5° and 15°, the correction factor increases linearly with the increase in slope to gradually adapt to the impact of terrain on productivity. For areas where the slope increase is greater than 1, the correction factor is increased by a larger amount to more fully compensate for the impact of slope on the estimate results. This refined correction method can effectively take into account the different effects of terrain on light and meteorological conditions, thereby providing a more accurate assessment of forest productivity and facilitating better forest management and ecological monitoring.

[0102] In some embodiments of the present application, whether to correct the preliminary estimated result is determined according to the landform features. If it is determined that correction is required, the preliminary estimated result is adjusted according to the landform features, which further includes:

[0103] The first estimated value GPP1 is adjusted according to the terrain slope to obtain the second estimated value GPP2. The calculation formula of the second estimated value GPP2 is:

[0104] Southward slope aspect: GPP2 = GPP1 × (1 + CFsouth);

[0105] North slope aspect: GPP2 = GPP1 × (1 + CFnorth);

[0106] East slope aspect: GPP2 = GPP1 × (1 + CFeast);

[0107] Westward slope aspect: GPP2 = GPP1 × (1 + CFwest);

[0108] In the above formula, GPP2 is the value after secondary correction of the preliminary estimated gross forest ecosystem product, that is, the second estimated value; GPP1 is the first estimated value; CFsouth is the south slope correction coefficient, ranging from [0.10, 0.15]; CFnorth is the north slope correction coefficient, ranging from [-0.10, -0.15]; CFeast is the east slope correction coefficient, ranging from [0.05, 0.10]; CFwest is the west slope correction coefficient, ranging from [0.05, 0.10];

[0109] If the terrain slope is between two directions, the average of the values ​​of the two directions after secondary correction of the preliminary estimated gross forest ecosystem product is taken as the second estimated value GPP2;

[0110] If there are multiple terrain slopes in the terrain area, the average of the values ​​of the preliminary estimated gross forest ecosystem product of several slopes after secondary correction is taken as the second estimated value GPP2.

[0111] It can be understood that by further correcting the first estimated value GPP1 according to the terrain slope aspect, the accuracy and practicality of the estimation result can be significantly improved. Different corrections are made to the south, north, east and west slope aspects to ensure that the specific influences of light and meteorological conditions in each direction are accurately reflected. The correction coefficients for the south slope aspect and the north slope aspect take into account the photosynthesis efficiency under different light conditions, while the correction coefficients for the east and west slope aspects take into account the impact of sunlight changes on GPP. For situations where the terrain slope aspect is between two directions or there are multiple slope aspects, by taking the average of the secondary correction values, the influence of different slope aspects can be better integrated to ensure the comprehensive accuracy of the estimation results. This multi-level correction method makes the estimation of forest GPP closer to the actual situation and helps to provide more accurate forest management and ecological monitoring data.

[0112] In some embodiments of the present application, whether to correct the preliminary estimated result is determined according to the landform features. If it is determined that correction is required, the preliminary estimated result is adjusted according to the landform features, which further includes:

[0113] A first preset altitude A1 and a second preset altitude A2 are preset, and the first preset altitude A1 is lower than the second preset altitude A2;

[0114] If the altitude is lower than the first preset altitude A1, the second estimated value GPP2 is not adjusted, and the second estimated value GPP2 is used as the third estimated value GPP3;

[0115] If the altitude is greater than or equal to the first preset altitude A1 and less than or equal to the second preset altitude A2, the second estimated value GPP2 is corrected by the first adjustment coefficient to obtain a third estimated value GPP3;

[0116] If the altitude is greater than or equal to the second preset altitude A1, the second estimated value GPP2 is corrected by the second adjustment coefficient to obtain a third estimated value GPP3;

[0117] The first adjustment coefficient is smaller than the second adjustment coefficient.

[0118] It can be understood that this embodiment has multiple advantages by presetting the first preset altitude A1 and the second preset altitude A2 to hierarchically process the estimation of the gross domestic product of forest ecosystems at different altitudes. First, through staged adjustments, unnecessary corrections to the estimated values ​​in low-altitude areas are avoided, thereby improving the efficiency and accuracy of the estimation. Secondly, the application of different adjustment coefficients in different altitude intervals helps to more accurately reflect the complexity of forest ecosystems in high-altitude areas, because the environmental conditions in high-altitude areas often have a more significant impact on the gross domestic product. Through this hierarchical adjustment method, it is possible to ensure the simplified processing of estimates in low-altitude areas, and provide more refined corrections for high-altitude areas, ultimately obtaining a more accurate estimate of the gross domestic product of forest ecosystems.

[0119] In some embodiments of the present application, whether to correct the preliminary estimated result is determined according to the landform features. If it is determined that correction is required, the preliminary estimated result is adjusted according to the landform features, which further includes:

[0120] A first preset concavity B1 and a second preset concavity B2 are preset, and the first preset concavity B1 is smaller than the second preset concavity B2;

[0121] If the concavity is less than the first preset concavity B1, the third estimated value GPP3 is not adjusted, and the third estimated value GPP3 is used as the fourth estimated value GPP4;

[0122] If the concavity is greater than or equal to the first preset concavity B1 and less than or equal to the second preset concavity B2, the third estimated value GPP3 is corrected by the first adjustment coefficient to obtain a fourth estimated value GPP4;

[0123] If the concavity is greater than or equal to the second preset concavity B2, the third estimated value is corrected by the second adjustment coefficient to obtain a value after four corrections, thereby obtaining a fourth estimated value GPP4;

[0124] The first adjustment coefficient is smaller than the second adjustment coefficient.

[0125] It can be understood that the present invention sets a threshold to determine whether to make a correction, thereby avoiding excessive adjustment of the estimation results in areas with flat terrain or small changes, thereby improving the efficiency and accuracy of the calculation. Secondly, for complex terrain with large unevenness, the impact of different terrain conditions on the gross domestic product of forest ecosystems can be more flexibly dealt with through graded adjustment coefficients (first adjustment coefficient and second adjustment coefficient). Since the second adjustment coefficient is higher than the first adjustment coefficient, it can more carefully reflect the degree of influence of areas with large terrain changes on the gross domestic product of the ecosystem, which not only ensures simplified processing of flat areas, but also provides accurate correction for complex terrain, so that the estimation results are more in line with the actual terrain characteristics.

[0126] In some embodiments of the present application, whether to correct the preliminary estimated result is determined according to the landform features. If it is determined that correction is required, the preliminary estimated result is adjusted according to the landform features, which further includes:

[0127] A first vegetation height value C1 is preset, and if the vegetation height is lower than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, and the fourth estimated value GPP4 is used as the final gross production value;

[0128] If the vegetation height is higher than the first vegetation height value C1, the fourth estimated value GPP4 is adjusted, and the adjusted fourth estimated value GPP4 is used as the final gross production value.

[0129] In some embodiments of the present application, if the vegetation height is higher than the first height value C1, the fourth estimated value GPP4 is adjusted, and when the adjusted fourth estimated value GPP4 is used as the final gross production value, it includes:

[0130] The fourth estimated value GPP4 is adjusted according to the vegetation height, and the adjusted fourth estimated value GPP4 is used as the final gross production value. The calculation formula is:

[0131] GPP5 = GPP4 × (1 + CF3);

[0132] In the above formula, GPP5 is the value after five corrections of the preliminary estimated gross forest ecosystem product, that is, the fifth estimated value; GPP4 is the fourth estimated value; CF3 is the correction coefficient determined according to the vegetation height, where the value range of CF5 is [-0.2, 0];

[0133] Preset a second vegetation height value C2;

[0134] If the vegetation height is less than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, that is, CF5 = 0;

[0135] If the vegetation height is greater than the first vegetation height value C1 and less than or equal to the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is [-0.05, -0.10];

[0136] If the vegetation height is greater than the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is (-0.10, -0.20].

[0137] It is understandable that this application does not need to adjust the estimated value for low vegetation areas, which reduces unnecessary calculations and improves efficiency. Secondly, when the vegetation height exceeds the first vegetation height value C1, an accurate negative adjustment is made according to the specific height to ensure that the estimated results in high vegetation density areas are more practical. Through the hierarchical correction coefficient CF3, this method can effectively capture the inhibitory effect of vegetation height on photosynthesis and ecosystem production efficiency, so that the final gross domestic product more accurately reflects the impact of vegetation at different heights on productivity. In addition, this hierarchical processing mechanism ensures the flexibility and accuracy of the calculation, and is particularly suitable for estimating the gross domestic product of complex ecosystems.

[0138] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0139] The present application is described with reference to flowcharts and / or block diagrams of methods, devices (systems) and computer program products according to embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0140] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0141] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0142] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An automatic and accurate estimation method for the gross domestic product of forest ecosystems based on remote sensing technology, characterized in that: include: Acquire a real-time positioning signal of a remote sensing acquisition device, obtain a forest map to be estimated from a geographic information database, and display the real-time positioning signal on the map; The meteorological parameters and forest characteristic parameters of the forest to be estimated are collected by remote sensing collection equipment, and the ground estimation model makes a preliminary estimate of the gross domestic product of the forest ecosystem through the meteorological parameters and forest characteristic parameters; wherein the meteorological parameters include the temperature of the day, the precipitation of the day and the sunshine duration of the day; and the forest characteristic parameters include the normalized vegetation index, the leaf area index and the plant cover density; Collecting the geomorphic features of the map, judging whether to correct the preliminary estimated result according to the geomorphic features, and if it is judged that correction is needed, adjusting the preliminary estimated result according to the geomorphic features; wherein the geomorphic features include terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height; The adjusted estimation results are stored, and a dynamic fluctuation graph of the adjusted estimation results is displayed on a visual device.

2. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 1 is characterized in that: The method of obtaining a real-time positioning signal of a remote sensing acquisition device, obtaining a forest map to be estimated from a geographic information database, and displaying the real-time positioning signal on the map includes: Configuring a positioning module on the remote sensing acquisition device, communicating the positioning module with a ground estimation model, and obtaining a position signal of the positioning module; The forest map to be estimated is evenly divided into a number of unit grids according to coordinates and equal areas, and the position signal is matched with the divided forest map, and a unique number or identifier is assigned to each unit grid; The ground estimation model receives and interprets the location signal from the remote sensing acquisition equipment, extracting the real-time longitude, latitude and altitude information; Using coordinate conversion and matching algorithms, the received location signal is matched with the grid cells divided on the map, and the grid cell where the location signal is located is determined according to the latitude and longitude of the location signal; The position of the remote sensing acquisition device is dynamically updated on the map, and the grid unit where the remote sensing acquisition device is located is marked, and the current coordinates, altitude and corresponding grid unit number of the device are displayed on the map.

3. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 2 is characterized in that: The meteorological parameters and forest characteristic parameters of the forest to be estimated are collected by remote sensing collection equipment, and the ground estimation model makes a preliminary estimation of the gross production value of the forest ecosystem through the meteorological parameters and forest characteristic parameters, including: The gross value of forest ecosystem production is preliminarily estimated using the following formula: GPP=(S×D×0.24)×(α×NDVI+β)×∈max×{1 / [1+e -k(T-Topt) ]}× [P / (P+P0)]×[LAI / (1+LAI)]×CD; ∈max=∈c×∈a×∈b; In the above formula, GPP is the preliminary estimated gross forest ecosystem production, unit: gCm 2 d - 1; S is the solar radiation constant, S = 1361W / m 2 ; D is the sunshine duration of the day in hours; 0.24 = 1 / 2*0.48, 1 / 2 is the conversion of total solar radiation into photosynthetically active radiation accounting for 50%, 0.48 is the conversion of W / m 2 Convert to MJ / m 2 coefficient; α and β are empirical coefficients, α=1.2, β=-0.1; NDVI is the normalized vegetation index; ∈max is the maximum light energy utilization rate, ∈c is the maximum light energy utilization rate under astronomical conditions, ∈c ranges from [1.5-2.5], unit: gCMJ-1; ∈a is the utilization correction coefficient under the temperature and moisture of the day, ∈a ranges from [0.2, 1.0]; ∈b is the correction coefficient under vegetation conditions, ∈b ranges from [0.5, 1.0]; T is the temperature of the day, unit: ℃; Topt is the optimal temperature for photosynthesis, Topt=25℃; k is the temperature sensitivity coefficient, k=0.05; P is the precipitation of the day, unit: mm; P0 is the water saturation constant, P0 ranges from [5, 10], unit: mm; LAI is the leaf area index; CD is the plant cover density.

4. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 3 is characterized in that: The determining whether to correct the preliminary estimation result according to the landform feature includes: Determine whether to revise the preliminary estimate based on the terrain slope, terrain aspect, altitude, convexity and concavity, and vegetation height; Based on the judgment results, the preliminary estimated results are corrected according to terrain slope, terrain aspect, altitude, convexity and concavity and vegetation height.

5. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 4 is characterized in that: The determining whether to correct the preliminary estimated result according to the landform feature, and if it is determined that correction is required, adjusting the preliminary estimated result according to the landform feature, further includes: If the terrain slope is less than or equal to 5°, the result of the preliminary estimation is not adjusted and the result of the preliminary estimation is used as the first estimation value GPP1; If the terrain slope is greater than 5°, the result of the preliminary estimation is adjusted and the adjusted value is used as the first estimated value GPP1; The formula for correcting the initial estimate based on terrain slope is: GPP1 = GPP × (1 + CF1); In the above formula, GPP1 is the value after a correction of the preliminary estimated gross forest ecosystem product, that is, the first estimated value; GPP is the preliminary estimated gross forest ecosystem product; CF1 is the correction coefficient determined according to the slope category, where the value range of CF1 is [0, 0.3]; If the terrain slope is greater than or equal to 5° and less than 15°, the result of the preliminary estimation is adjusted, and the value range of CF1 is [0.05, 0.15]. For every 1° increase in slope, CF1 increases by 0.01; If the terrain slope is greater than or equal to 15°, the result of the preliminary estimation is adjusted, and the value range of CF1 is (0.15, 0.3], and for every 1° increase in slope, CF1 increases by 0.

03.

6. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 5 is characterized in that: The determining whether to correct the preliminary estimated result according to the landform feature, and if it is determined that correction is required, adjusting the preliminary estimated result according to the landform feature, further includes: The first estimated value GPP1 is adjusted according to the terrain slope to obtain a second estimated value GPP2. The calculation formula of the second estimated value GPP2 is: Southward slope aspect: GPP2 = GPP1 × (1 + CFsouth); North slope aspect: GPP2 = GPP1 × (1 + CFnorth); East slope aspect: GPP2 = GPP1 × (1 + CFeast); Westward slope aspect: GPP2 = GPP1 × (1 + CFwest); In the above formula, GPP2 is the value after secondary correction of the preliminary estimated gross forest ecosystem product, that is, the second estimated value; GPP1 is the first estimated value; CFsouth is the south slope correction coefficient, ranging from [0.10, 0.15]; CFnorth is the north slope correction coefficient, ranging from [-0.10, -0.15]; CFeast is the east slope correction coefficient, ranging from [0.05, 0.10]; CFwest is the west slope correction coefficient, ranging from [0.05, 0.10]; If the terrain slope is between two directions, the average of the values ​​of the two directions after secondary correction of the preliminary estimated gross forest ecosystem production is taken as the second estimated value GPP2; If there are multiple terrain slopes in the terrain area, the average of the values ​​of the preliminary estimated gross forest ecosystem product of several slopes after secondary correction is taken as the second estimated value GPP2.

7. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 6 is characterized in that: The determining whether to correct the preliminary estimated result according to the landform feature, and if it is determined that correction is required, adjusting the preliminary estimated result according to the landform feature, further includes: A first preset altitude A1 and a second preset altitude A2 are preset, and the first preset altitude A1 is lower than the second preset altitude A2; If the altitude is lower than the first preset altitude A1, the second estimated value GPP2 is not adjusted, and the second estimated value GPP2 is used as the third estimated value GPP3; If the altitude is greater than or equal to the first preset altitude A1 and less than or equal to the second preset altitude A2, the second estimated value GPP2 is corrected by the first adjustment coefficient to obtain a third estimated value GPP3; If the altitude is greater than or equal to the second preset altitude A1, the second estimated value GPP2 is corrected by the second adjustment coefficient to obtain a third estimated value GPP3; The first adjustment coefficient is smaller than the second adjustment coefficient.

8. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 7 is characterized in that: The determining whether to correct the preliminary estimated result according to the landform feature, and if it is determined that correction is required, adjusting the preliminary estimated result according to the landform feature, further includes: A first preset concavity B1 and a second preset concavity B2 are preset, and the first preset concavity B1 is smaller than the second preset concavity B2; If the concavity is smaller than the first preset concavity B1, the third estimated value GPP3 is not adjusted, and the third estimated value GPP3 is used as the fourth estimated value GPP4; If the concavity is greater than or equal to the first preset concavity B1 and less than or equal to the second preset concavity B2, the third estimated value GPP3 is corrected by the first adjustment coefficient to obtain a fourth estimated value GPP4; If the concavity is greater than or equal to the second preset concavity B2, the third estimated value is corrected by the second adjustment coefficient to obtain a value after four corrections, thereby obtaining a fourth estimated value GPP4; The first adjustment coefficient is smaller than the second adjustment coefficient.

9. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 8 is characterized in that: The determining whether to correct the preliminary estimated result according to the landform feature, and if it is determined that correction is required, adjusting the preliminary estimated result according to the landform feature, further includes: A first vegetation height value C1 is preset, and if the vegetation height is lower than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, and the fourth estimated value GPP4 is used as the final gross production value; If the vegetation height is higher than the first vegetation height value C1, the fourth estimated value GPP4 is adjusted, and the adjusted fourth estimated value GPP4 is used as the final gross production value.

10. The automatic and accurate estimation method of the gross domestic product of forest ecosystem based on remote sensing technology according to claim 9 is characterized in that: If the vegetation height is higher than the first height value C1, the fourth estimated value GPP4 is adjusted, and the adjusted fourth estimated value GPP4 is used as the final gross production value, including: The fourth estimated value GPP4 is adjusted according to the vegetation height, and the adjusted fourth estimated value GPP4 is used as the final gross production value. The calculation formula is: GPP5 = GPP4 × (1 + CF3); In the above formula, GPP5 is the value after five corrections of the preliminary estimated gross forest ecosystem product, that is, the fifth estimated value; GPP4 is the fourth estimated value; CF3 is the correction coefficient determined according to the vegetation height, where the value range of CF5 is [-0.2, 0]; Preset a second vegetation height value C2; If the vegetation height is less than or equal to the first vegetation height value C1, the fourth estimated value GPP4 is not adjusted, that is, CF5 = 0; If the vegetation height is greater than the first vegetation height value C1 and less than or equal to the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is [-0.05, -0.10]; If the vegetation height is greater than the second vegetation height value C2, the fourth estimated value GPP4 is adjusted, and the value range of CF3 is (-0.10, -0.20].

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