A forest resource long-term fixed monitoring sample plot sampling and construction method

Abstract

The application provides a forest resource long-term fixed monitoring sample plot sampling and construction method.The forest resource long-term fixed monitoring sample plot sampling method comprises the following steps: step A1: a regional vegetation distribution map is made on a regional scale by taking a regional map and a boundary, and combining existing forest community distribution data; step A2: the regional map is divided into grids according to the number and density of the monitoring sample plots; and step A3: the number of the monitoring sample plots of each forest type is determined according to the regional vegetation distribution map made in step A1 and the actual needs of scientific research or production work.The forest resource long-term fixed monitoring sample plot sampling and construction method has the advantages that representative fixed monitoring sample plots can be arranged more conveniently, and the goal of accurate forest resource monitoring can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of forest resource monitoring, and particularly relates to a sampling and construction method of long-term fixed monitoring sample plots of forest resources. BACKGROUND

[0002] Forest resource monitoring is a work of periodic and positioning observation analysis and evaluation on the quantity, quality, spatial distribution and utilization status of forest resources. It is the basic work of forest resource management and supervision. The establishment of long-term fixed monitoring sample plots can realize periodic, quantitative and standardized monitoring of forest resources, timely grasp the current situation and dynamic changes of forest resources, and predict the development trend of forest resources, so as to provide basic data support for scientific research and technology research of forestry, and provide decision basis for scientific management of forestry.

[0003] The national forest resource survey mainly includes the national forest resource continuous survey (class I survey) and the forest resource planning and design survey (class II survey). The class I survey generally takes sampling survey as the basis for work, and the sampling method is usually mechanical sampling point distribution. The class II survey requires the quantity and quality of the surveyed forest resources to be implemented to the forest sub-compartment, and its accuracy is higher than that of the class I survey.

[0004] Under the background of the implementation of the double carbon strategy by the state, it is very important to accurately know the bottom line of forest resources. In scientific research and production survey work, in order to more accurately grasp the resource situation, forestry workers often set up fixed monitoring sample plots in regional scales, such as a province or a city, to monitor the dynamic changes of forest resources. In some non-large forest areas, the forest is patchy distributed, and the types of patchy forest are quite different. The fixed monitoring sample plots set up by using the traditional mechanical point distribution and typical sampling method cannot guarantee the representativeness, and cannot achieve the goal of accurate forest resource monitoring. It is difficult to realize the comprehensive investigation in the unit of forest sub-compartment, and the class II survey data are not easy to obtain or are difficult to use due to the confidentiality.

[0005] Therefore, it is necessary to provide a new sampling and construction method of long-term fixed monitoring sample plots of forest resources to solve the above technical problems. SUMMARY

[0006] The technical problem solved by the present application is to provide a sampling and construction method of long-term fixed monitoring sample plots of forest resources, which can more conveniently set up a representative fixed monitoring sample plot and achieve the goal of accurate forest resource monitoring.

[0007] To solve the above technical problems, the sampling method of long-term fixed monitoring sample plots of forest resources provided by the present application comprises the following steps: step A1: making a vegetation distribution map on a regional scale according to a regional map, a boundary and existing forest community distribution data;

[0008] Step A2: According to the number and density of monitoring sample plots, the regional map is grid divided;

[0009] Step A3: Based on the vegetation distribution map at the regional scale prepared in step A1, and combined with the actual needs of scientific research or production work, the number of monitoring sample plots for each forest type is determined;

[0010] Then, on the regional vegetation distribution map prepared in step A1, random sampling is performed for each forest type, and preset fixed monitoring sample plot points are determined.

[0011] For forest types with fewer distribution patches on the vegetation map than the number of monitoring points to be extracted, preset fixed monitoring sample plot points are determined for all distribution patches of the forest type;

[0012] Step A4: Using remote sensing data and products, random sampling is performed on grid spaces that show no forest distribution on the regional vegetation map prepared in step A1, but show forest distribution on remote sensing data and products, and preset monitoring points are determined. The sampling proportion or grid coverage rate can be consistent with that in step A3;

[0013] Step A5: Field investigation, using the geographic coordinate positions of the preset fixed monitoring sample plot points, go to all preset fixed monitoring sample plot points for field investigation, determine whether the sample plots can be set up according to the actual situation of the investigation, and determine the point positions where fixed monitoring sample plots can be set up.

[0014] Step A6: Statistically determine the fixed monitoring sample plot points determined in step A5, for the preset fixed monitoring sample plot points where the number of points where fixed monitoring sample plots can be set up exceeds the required number of points, all of them can be retained, or a random number of points required can be extracted;

[0015] Step A7: Based on the work of step A6, determine the final point positions where fixed monitoring sample plots are to be built, mark them on the regional map, and prepare a point position basic information table to prepare for the construction and investigation of fixed monitoring sample plots in the later stage.

[0016] Preferably, in step A2, the grid size is determined according to the area of the region and the actual needs in the grid division, and the grid size includes 50km*50km, 20km*20km, 10km*10km and 5km*5km spatial grid.

[0017] Preferably, in step A3, the number of monitoring sample plots is a specific number for each forest type; or the number of monitoring sample plots for each forest type is determined by using stratified sampling method according to the proportion;

[0018] The preset fixed monitoring sample plot arrangement points are set according to 120%-150% of the actual demand point quantity, so as to avoid the situation that after some preset fixed monitoring sample plot arrangement points that cannot construct sample plots are removed, the quantity is insufficient;

[0019] In addition, in random sampling, the same forest type in each spatial grid is sampled only once in principle;

[0020] For the forest type whose distribution patch on the vegetation map is less than the quantity of the monitoring points to be sampled, preset fixed monitoring sample plot arrangement points are arranged in all distribution patches of the forest type.

[0021] Preferably, the above-mentioned preset fixed monitoring sample plot arrangement points are randomly located in the patch of the forest type distribution on the regional vegetation map, and the geographic coordinate position of the point is obtained.

[0022] Preferably, in step A6, for the preset fixed monitoring sample plot arrangement points that can construct fixed monitoring sample plots, the quantity of the preset fixed monitoring sample plot arrangement points is equal to the quantity of the demand points; for the preset fixed monitoring sample plot arrangement points that can construct fixed monitoring sample plots, the quantity of the preset fixed monitoring sample plot arrangement points is less than the quantity of the demand points; if the quantity of the demand points is a hard requirement, two or more monitoring points are arranged in the patch that can construct sample plots and has a larger forest distribution area, and the monitoring points do not coincide and are separated by a distance.

[0023] Preferably, in step A7, the point basic information table includes position information and a forest type.

[0024] The application further provides a forest resource long-term fixed monitoring sample plot construction method, which comprises the following steps:

[0025] Step B1: sample plot position selection: the sample plot is set as close as possible to the center position or the most representative site of the forest distribution area of the monitoring point in the sample plot to be constructed, and in principle, the sample plot is avoided to be set at the edge;

[0026] Step B1: sample plot setting: after the sample plot construction position is selected, the sample plot original point is determined, and then the four edges of the sample plot are determined by using RTK; the edge length of the sample plot can be determined according to the monitoring demand and target and in combination with the actual situation of the forest resource distribution of the monitoring point.

[0027] Step B1: sample plot marking: the stakes are inserted into the four corner points of the sample plot, the stakes are generally cement stakes or glass fiber reinforced plastic stakes, and after the burying is completed, the stakes can be long-term preserved and become the permanent markers of the fixed monitoring sample plot.

[0028] Compared with the related art, the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application has the following beneficial effects:

[0029] The application provides a forest resource long-term fixed monitoring sample plot sampling and construction method, which is suitable for forest resource monitoring of a large regional scale and patchy distribution of forest resources, especially under the condition that basic information is lacking and the forest resource bottom line and distribution of the region are unclear, can more conveniently arrange representative fixed monitoring sample plots, and can achieve the goal of accurate forest resource monitoring. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 A certain provincial administrative region map in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application;

[0031] Figure 2 A certain provincial vegetation distribution map in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application;

[0032] Figure 3 A monitoring point distribution map preset according to the certain provincial vegetation distribution map in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application;

[0033] Figure 4 A 30-meter fine surface cover product of a certain province in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application;

[0034] Figure 5 Supplemental preset points combined with the 30-meter fine surface cover product of the space and time institute in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application;

[0035] Figure 6 A regional patchy forest resource fixed monitoring sample plot preset point distribution map in an embodiment of the forest resource long-term fixed monitoring sample plot sampling and construction method provided by the application. DETAILED DESCRIPTION

[0036] The application will be further described below in combination with the drawings and embodiments.

[0037] The forest resource long-term fixed monitoring sample plot sampling and construction method of the regional scale patchy forest resources provided by the application specifically comprises the following steps.

[0038] I. Monitoring sample plot sampling method

[0039] Step A1: Taking a regional map and boundary, using the forest community distribution recorded in the “People's Republic of China 1:1 million vegetation map” (the vegetation map is a commonly used and referenced map recognized at present, with the development of science and technology, a 1:500,000 vegetation map is being drawn, and in the future, a higher precision vegetation map will be available, at which time the latest map can be used) to make a vegetation distribution map on a regional scale.

[0040] Step A2: The regional map is gridded according to the number and density of monitoring plots. For example, it is divided into a spatial grid of 50 km*50 km, 20 km*20 km, 10 km*10 km, or even 5 km*5 km. The grid size can be determined according to the area of the region and actual needs.

[0041] Step A3: Based on the vegetation distribution map at the regional scale prepared in step A1, and combined with the actual needs of scientific research or production work, determine the number of monitoring plots for each forest type, for example, 10 monitoring points for each forest type; or use stratified sampling method to determine the number of monitoring points for each forest type according to the proportion.

[0042] Then on the regional vegetation distribution map prepared in step A1, randomly sample each forest type and preset the fixed monitoring plot layout points. Due to the difference between the vegetation distribution map and the actual distribution of forest resources, in order to ensure that the number of final fixed monitoring plot layout points can meet the monitoring needs, the preset points can be set at 120%-150% of the actual number of points, to avoid the situation that after removing some preset points that cannot be built into plots, the number is insufficient. In addition, when randomly sampling, the same forest type in each spatial grid is sampled only once in principle.

[0043] For forest types with fewer distribution patches on the vegetation map than the number of monitoring points to be extracted, preset points are set for all distribution patches of the forest type.

[0044] All the above preset points are randomly located within the patches of the forest type distribution on the regional vegetation map. The geographic coordinate position of the point can be obtained by analyzing software such as ArcGIS.

[0045] To ensure the coverage and representativeness of sampling at the regional scale, the preset points in this step can cover the gridded space divided in step A2, for example, the coverage of the preset points on the gridded space with forest vegetation distribution should not be less than 60%.

[0046] Step A4: Use remote sensing data and products, such as the "Global 30-meter Surface Cover Fine Classification Product" regularly released by the Innovation Institute of Aerospace Information of the Chinese Academy of Sciences, to supplement and improve the vegetation distribution at the regional scale. For grid spaces that show no forest distribution on the regional vegetation map prepared in step A1, but show forest distribution on remote sensing data and products, randomly sample and preset monitoring points. The sampling proportion or grid coverage can be consistent with step A3.

[0047] Step A5: On-site investigation. Using the geographical coordinate position of the preset point, go to all preset points for on-site investigation, and determine whether a sample plot can be set up according to the actual situation of the investigation, and determine the point position where the fixed monitoring sample plot can be set up.

[0048] Step A6: Statistics of the fixed monitoring sample plot construction point determined in step A5. For the number of preset points where the fixed monitoring sample plot can be constructed, if the number of preset points is more than the number of required points, all of them can be reserved (because the more samples, the higher the accuracy), or a random number of points can be selected; for the number of preset points where the fixed monitoring sample plot can be constructed, if the number of preset points is equal to the number of required points, all of them are reserved. For the number of preset points where the fixed monitoring sample plot can be constructed, if the number of preset points is less than the number of required points, all of them are reserved, and if the number of required points is a hard requirement, two or more monitoring points can be set up in the patch where the sample plot can be constructed and the forest distribution area is large, and the monitoring points do not overlap and are separated by a distance.

[0049] Step A7: According to the work of step A6, determine the final point position of the fixed monitoring sample plot construction, mark it on the regional map, and make a point position basic information table (including position information, forest type, etc.), to prepare for the later fixed monitoring sample plot construction and investigation.

[0050] Specific examples are shown in Figures 1-6 , wherein, Figure 1 is a provincial administrative region map; Figure 2 is a vegetation distribution map of a certain province; Figure 3 is a monitoring point distribution map preset according to the vegetation distribution map of a certain province; Figure 4 is a 30-meter fine surface cover product of a certain province provided by the Aerospace Institute; Figure 5 is a combination of the 30-meter fine surface cover product of the Aerospace Institute to supplement the preset point (black dot); Figure 6 is a regional patch forest resource fixed monitoring sample plot preset point distribution map; finally, according to Figure 6 on-site investigation, complete the work of steps A6 and A7 above, and determine the final fixed monitoring sample plot construction point.

[0051] II. Monitoring sample plot construction method

[0052] Step B1: Sample plot location selection. In the monitoring point where the sample plot is to be constructed, the sample plot should be set as close as possible to the center position of the forest distribution area of the monitoring point or the most representative section, and in principle, the sample plot should be set at the edge. The habitat in the sample plot, especially the terrain and soil, should be as consistent as possible and representative of the monitoring point.

[0053] Step B2: sample site setting. After selecting the sample site construction location, the sample site origin is determined first, and then the four sides of the sample site are determined using RTK. The sample site side length can be determined according to the monitoring requirements and targets, combined with the actual distribution of the monitoring points of forest resources, for example, the projection side length is 30m*30m, 50m*50m, 10m*100m, etc. The determination of the sample site boundary and corner point can be realized by the point lofting and line lofting method of RTK. The specific operation method of RTK is not described again.

[0054] Generally, when setting a fixed monitoring sample site, the southwest corner is taken as the origin. However, in a non-continuous patchy forest, especially when the patchy forest resources are distributed on a hillside, it is not easy to set the southwest corner as the origin, and the operability is not strong. Therefore, the present application proposes that when setting the sample site, facing the hillside, the corner point at the lower left corner of the sample site is taken as the origin, and the bottom side of the sample site is set in principle parallel to the contour line of the hillside, and the side is set perpendicular to the contour line. This way of setting the sample site is more operational and representative, and it is also convenient for future regular monitoring review.

[0055] Step B3: sample site marking. The stakes are inserted at the four corner points of the sample site, and the stakes are generally made of cement piles or glass steel piles. After the burial is completed, it can be preserved for a long time and become the permanent marker of the fixed monitoring sample site. If the sample site area is large, such as 100m*100m, the sample site can be further divided into small sample plots, for example, 20m*20m sample plots. At each 20m node, a stake can be buried for marking, so as to facilitate the investigation work of the monitoring sample site.

[0056] After completing the basic investigation of the forest sample site, VR technology can be used to take real scenes at each corner point of the sample site (including each 20m node for large sample sites), form a VR video library, and integrate it into a monitoring data management system. While realizing quantitative monitoring, the actual situation in the forest monitoring sample site can be directly observed, which provides a basis for decision-making of forest management.

[0057] Compared with the related art, the forest resource long-term fixed monitoring sample site sampling and construction method provided by the present application has the following beneficial effects:

[0058] The present application provides a forest resource long-term fixed monitoring sample site sampling and construction method, which is suitable for forest resource monitoring of non-continuous and patchy distribution of forest resources on a larger regional scale, especially under the condition that there is a lack of basic information and the forest resource bottom number and distribution of the region are unclear. The method can more conveniently lay out a representative fixed monitoring sample site and achieve the goal of precise forest resource monitoring.

[0059] The above merely illustrates the embodiments of the present application, and is not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process conversion, or direct or indirect application in other related technical fields, which is made according to the content of the present application, shall be included in the patent protection scope of the present application.

Claims

1. A sampling method for long-term fixed monitoring plots of forest resources, characterized in that, Includes the following steps: Step A1: Using regional maps and boundaries, combined with existing forest community distribution data, create a vegetation distribution map at the regional scale; Step A2: Divide the regional map into a grid according to the required number and density of monitoring sample plots; Step A3: Based on the regional vegetation distribution map prepared in Step A1, and in combination with the actual needs of scientific research or production work, determine the number of monitoring plots to be set up for each forest type. Then, on the regional-scale vegetation distribution map created in step A1, random sampling is performed for each forest type, and fixed monitoring plots are pre-set. For forest types where the number of distribution patches on the vegetation map is less than the number of monitoring points to be extracted, fixed monitoring plots are pre-set for all distribution patches of that forest type. Step A4: Using remote sensing data and products, for grid spaces where the vegetation map of the area created in Step A1 shows no forest distribution, but the remote sensing data and products show forest distribution, random sampling is performed, and monitoring points are preset; the sampling ratio or grid coverage can be consistent with that in Step A3. Step A5: Field survey. Using the geographical coordinates of the preset fixed monitoring plot locations, conduct a field survey of all preset fixed monitoring plot locations. Based on the actual survey results, determine whether a plot can be set up and identify the locations where fixed monitoring plots can be set up. Step A6: Count the proposed fixed monitoring sites determined in Step A5. If the number of preset fixed monitoring sites exceeds the required number of sites, all sites can be retained, or the required number of sites can be randomly selected. Step A7: Based on the work done in Step A6, determine the final locations of the fixed monitoring plots, mark them on the regional map, and create a basic information table of the plot locations to prepare for the later construction and investigation of the fixed monitoring plots.

2. The sampling method for long-term fixed monitoring plots of forest resources according to claim 1, characterized in that, In step A2, the grid size is determined based on the area and actual needs during the gridded spatial division. The grid sizes include 50km*50km, 20km*20km, 10km*10km and 5km*5km spatial grids.

3. The sampling method for long-term fixed monitoring plots of forest resources according to claim 1, characterized in that, In step A3, the number of monitoring plots is the specific number set up for each forest type; or the number of monitoring plots set up for each forest type is determined proportionally using a stratified sampling method. The number of pre-set fixed monitoring plots should be set at 120%-150% of the actual required number to avoid insufficient quantity after some pre-set fixed monitoring plots that cannot be used for plot construction are removed later. In addition, during random sampling, the same forest type is sampled only once within each spatial grid. For forest types where the number of distribution patches on the vegetation map is less than the number of monitoring points to be extracted, fixed monitoring plots will be pre-set for all distribution patches of that forest type.

4. The sampling method for monitoring plots according to claim 3, characterized in that, The aforementioned preset fixed monitoring plots are randomly located within patches of forest type distribution on the regional vegetation map, and the geographic coordinates of these plots are obtained through analysis using geographic information system software.

5. The sampling method for long-term fixed monitoring plots of forest resources according to claim 1, characterized in that, In step A6, if the number of preset fixed monitoring points for establishing fixed monitoring plots is equal to the required number of points, all points are retained; if the number of preset fixed monitoring points for establishing fixed monitoring plots is less than the required number of points, all points are retained; if the required number of points is a rigid requirement, two or more monitoring points are set up in patches where plots can be established and the forest distribution area is large, with the monitoring points not overlapping and separated by a distance.

6. The sampling method for long-term fixed monitoring plots of forest resources according to claim 1, characterized in that, In step A7, the basic information table of the location includes location information and forest type.

7. A method for constructing long-term fixed monitoring plots for forest resources determined using the sampling method for long-term fixed monitoring plots as described in any one of claims 1-6, characterized in that, Includes the following steps: Step B1: Selection of sample plot location: At the monitoring point where the sample plot is to be established, the sample plot should be set up as close as possible to the center of the forest distribution area of ​​the monitoring point or the most representative area. In principle, sample plots should be avoided on the edge. Step B1: Sample plot setup: After selecting the sample plot location, first determine the sample plot origin, and then use RTK to determine the four sides of the sample plot. The side length of the sample plot can be determined according to the monitoring needs and objectives, combined with the actual distribution of forest resources at the monitoring points. Step B1: Plot marking: Using stakes inserted at the four corners of the plot, the stakes are generally made of cement or fiberglass. After installation, they can be preserved for a long time and become permanent markers for fixed monitoring plots.

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