A method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology

Abstract

The present invention discloses a method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology. According to the climate type zoning data, vegetation type zoning data, soil type zoning data, and geomorphic type zoning data published by the state, the ecological restoration area is divided into different ecological types; hydrological analysis and vegetation community clustering analysis are carried out on the areas where each ecological type is located, and each ecological type is further subdivided into different evaluation units; using remote sensing technology, the ecosystem quality of all evaluation units is calculated from four aspects: ecosystem structure, function, stability, and human disturbance intensity; the evaluation units of each ecological type are sorted in descending order of ecosystem quality, and the evaluation units with ecosystem quality in the top t% (5 ≤ t ≤ 10) are taken as the reference ecosystem of this ecological type. The present invention uses remote sensing technology, without the need for on-site investigation, and can quickly and accurately select a reference ecosystem for the area undergoing ecological restoration and formulate the goals of ecological restoration.

Description

Technical Field

[0001] The present invention relates to a method for selecting a reference ecosystem, and more particularly to a method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology, belonging to the field of ecological restoration technology. Background Art

[0002] In recent years, China has carried out or plans to carry out a number of ecological restoration projects, including major projects for ecological protection and restoration in the Qinghai-Tibet Plateau ecological barrier area, major projects for ecological protection and restoration in the key ecological areas of the Yellow River, major projects for ecological protection and restoration in the key ecological areas of the Yangtze River, and major projects for ecological protection and restoration of the national coastal zone, etc.

[0003] Before ecological restoration, it is necessary to formulate the goals of ecological restoration, that is, to what extent the various indicators of the ecosystem (such as vegetation coverage, biodiversity, productivity, etc.) need to be restored. At the same time, the formulated goals can also be used as the basis for judging whether the ecological restoration project can pass the acceptance. Therefore, it is necessary to set a reference ecosystem and use the reference ecosystem as a template for the ecological restoration effect. The reference ecosystem needs to have good structural and functional properties, and have a certain anti-interference ability and stability, and is hardly affected by human activities at the same time. Ecological restoration should take the reference ecosystem as the goal and restore the quality of the ecosystem in the restoration area to the level of the reference area.

[0004] China has a vast territory and a wide range of ecological restoration projects. It is unrealistic to select a reference ecosystem by means of ground surveys. Therefore, how to scientifically select a reference ecosystem is of great significance for the implementation of major ecological restoration projects in China. Summary of the Invention

[0005] Aiming at the problems existing in the above-mentioned prior art, the present invention provides a method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology, realizing scientific and convenient selection of a reference ecosystem and formulating the acceptance basis for ecological restoration projects.

[0006] To achieve the above object, the present invention provides the following technical solution: A method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology, comprising the following steps:

[0007] Step 1, dividing the ecological restoration area into different ecological types according to climate characteristics, vegetation characteristics, soil characteristics, and geomorphic characteristics;

[0008] Step 2, performing hydrological analysis and vegetation community clustering analysis on the areas where each ecological type is located, and further dividing each ecological type into different evaluation units;

[0009] Step 3: Using remote sensing images, calculate the ecosystem quality of all evaluation units from four aspects: the structure, function, stability of the ecosystem, and the intensity of human disturbance.

[0010] Step 4: Sort the evaluation units of each ecological type in descending order of ecosystem quality, and select the evaluation units with the top t% (5 ≤ t ≤ 10) of ecosystem quality as the reference ecosystem of this ecological type.

[0011] Furthermore, when dividing ecological types in Step 1, download the published climate type zoning data, vegetation type zoning data, soil type zoning data, and geomorphic type zoning data, and overlay the above data in the same spatial coordinate system to obtain different climate-vegetation-soil-geomorphology combination types, thereby dividing the ecological restoration area into different ecological types.

[0012] Furthermore, when dividing evaluation units in Step 2, first, based on the digital elevation model, conduct a standardized hydrological analysis of the areas where each ecological type is located to obtain a spatial distribution map of catchment areas; then, based on remote sensing images, conduct clustering of the vegetation community types in the areas where each ecological type is located to obtain a spatial distribution map of vegetation community types; finally, overlay the spatial distribution map of catchment areas with the spatial distribution map of vegetation community types to obtain hydrological-community type evaluation units.

[0013] Furthermore, the formula for calculating ecosystem quality in Step 3 is as follows:

[0014] EQ = a × ES + b × EF + c × EST + d × D

[0015] In the formula, EQ is the ecosystem quality, ES is the ecosystem structure, EF is the ecosystem function, EST is the ecosystem stability, D is the distance to the nearest disturbance source, and a, b, c, and d are weight factors with values of 0.4, 0.2, 0.2, and 0.2 respectively; each pixel in the calculation result has an attribute value.

[0016] The calculation method of ecosystem structure is as follows: ES = a1 × Cov + a2 × Bio

[0017] In the formula, Cov is the vegetation coverage, Bio is the biodiversity, and a1 and a2 are weight factors with both values of 0.5. The vegetation coverage and biodiversity are calculated from the remote sensing images of July and August of the most recent year and are standardized to the range of 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value.

[0018] The calculation method of ecosystem function is as follows: EF = b1 × NPP + b2 × SMC

[0019] In the formula, NPP is the net primary productivity, SMC is the soil moisture content, b1 and b2 are weight factors, both with a value of 0.5. The net primary productivity and soil moisture content are calculated from the remote sensing images of July and August in the most recent year, and are standardized to the range of 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value;

[0020] The calculation method of ecosystem stability is as follows: EST = c1 × Cov_ST + c2 × NPP_ST

[0021] In the formula, Cov_ST is the stability of vegetation coverage, NPP_ST is the stability of net primary productivity, c1 and c2 are weight factors, both with a value of 0.5;

[0022] ST is the stability of vegetation coverage or net primary productivity. The calculation method of stability is as follows:

[0023]

[0024] In the formula, mean is the average value of vegetation coverage or net primary productivity in the past five years, std is the standard deviation of vegetation coverage or net primary productivity in the past five years, Cov_mean is the average value of vegetation coverage in the most recent year, and Cov is the vegetation coverage in the most recent year; when the vegetation coverage in the most recent year is greater than or equal to the average value of the current year's vegetation coverage, calculate normally; when it is less than the average value, the result is directly assigned a value of 0; the vegetation coverage and net primary productivity are calculated from the remote sensing images of July and August each year, and the calculation results are standardized to the range of 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value;

[0025] The human disturbance intensity is determined by the distance of the pixel from the nearest disturbance source. The disturbance sources include residential areas, industrial and mining areas, and grazing points. The measurement method is the distance from the pixel center to the geometric center of the disturbance source. The calculation result is standardized to the range of 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value.

[0026] Furthermore, when calculating the ecosystem quality in step three, in order to reflect the overall situation of the evaluation unit and facilitate comparison between evaluation units, according to the structural index, functional index, stability index, and human disturbance intensity index of the ecosystem, first calculate the ecosystem quality of each pixel according to the formula EQ = a × ES + b × EF + c × EST + d × D, and then take the average value of the ecosystem quality of all pixels in the evaluation unit as the final ecosystem quality of the evaluation unit.

[0027] Compared with the prior art, the present invention first divides ecological types through climate characteristics, vegetation characteristics, soil characteristics, and geomorphic characteristics, and then further subdivides the hydrological-vegetation community assessment unit through hydrological analysis and vegetation community clustering, thereby ensuring the universality and operability of the method. Through a large number of studies, the present invention selects to evaluate the quality of the ecosystem from four aspects: ecosystem structure, function, stability, and human disturbance intensity, which can meet the scientificity, comprehensiveness, and operability of the evaluation results. By selecting the assessment unit with the highest ecosystem quality, the reference ecosystem is determined. The reference ecosystem can be used as the goal of the ecological restoration project to evaluate whether the results of the ecological restoration meet the standards. At the same time, the present invention fully utilizes remote sensing technology and does not require ground surveys, which can save a large amount of labor costs and time costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 is a flowchart of the present invention.

[0029] Figure 2 is a schematic diagram of dividing ecological types in an embodiment of the present invention.

[0030] Figure 3 is a schematic diagram of the spatial distribution of catchments in an embodiment of the present invention.

[0031] Figure 4 is a schematic diagram of the spatial distribution of vegetation community types in an embodiment of the present invention.

[0032] Figure 5 is a schematic diagram of the hydrological-vegetation community type assessment unit in an embodiment of the present invention.

[0033] Figure 6 is a schematic diagram of the assessment unit being divided into 20 grades according to the ecosystem quality in an embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0034] The present invention will be further described below with reference to the accompanying drawings.

[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0036] The following embodiments take the ecological restoration area of Shendong Coalfield at the junction of Shanxi, Shaanxi, and Inner Mongolia provinces in China as the implementation object, and the ecological restoration area is 127 km 2 . Due to large-scale coal mining, the ecological environment in this area has deteriorated severely and urgent ecological restoration is needed. Therefore, it is necessary to first determine the reference ecosystem for ecological restoration.

[0037] As Figure 1 shown, the present invention provides a technical solution for a method of selecting a reference ecosystem for an ecological restoration area based on remote sensing technology.

[0038] First, divide ecological types. According to climate characteristics, vegetation characteristics, soil characteristics, and geomorphic characteristics, divide the ecological restoration area into different ecological types; download climate type zoning data, vegetation type zoning data, soil type zoning data, and geomorphic type zoning data from the Resource and Environment Science and Data Center of the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences (https: / / www.resdc.cn), and overlay the downloaded data in GIS software to obtain various climate-vegetation-soil-geomorphology combination types, so as to divide the ecological restoration area into different ecological types. Through actual operation, the area is divided into 3 ecological types, including mid-temperate zone-temperate steppe-grassland aeolian sandy soil-middle altitude hilly area, mid-temperate zone-temperate steppe-calcareous rocky soil-middle altitude hilly area, and mid-temperate zone-temperate steppe-alluvial soil-middle altitude hilly area. The division results are as Figure 2 shown. The soil characteristics of each ecological type are different from each other but have relative consistency within. Since different soil environments will give birth to different ecosystems. Therefore, different ecological types cannot share the same reference ecosystem, and different reference ecosystems should be selected for different ecological types in the ecological restoration area.

[0039] Secondly, divide evaluation units. Conduct hydrological analysis and vegetation community clustering analysis on the areas where each ecological type is located, and further subdivide each ecological type into different evaluation units; obtain a digital elevation model through the method of unmanned aerial vehicle (UAV) aerial photogrammetry. The spatial resolution of the digital elevation model is 5 cm, and the acquisition time of the UAV images is July 3, 2022; use the hydrological analysis function of GIS software, and through standard processes such as filling depressions, flow direction analysis, flow analysis, extracting river networks, river linking, and calculating watersheds, obtain the spatial distribution map of catchment areas in the areas where each ecological type is located, as Figure 3 shown. Then, based on the GF-1 remote sensing images on July 7, 2022, use the object-oriented classification function of ENVI software to segment and merge each ecological type, divide different vegetation community types, and obtain the spatial distribution map of vegetation community types, as Figure 4 shown. Finally, use the intersection function of GIS software to overlay the spatial distribution map of catchment areas and the spatial distribution map of vegetation community types to obtain evaluation units divided according to hydrological information and vegetation community types, as Figure 5As shown. After statistics, 1,517 evaluation units are classified into ecological type one, 10,354 evaluation units into ecological type two, and 1,275 evaluation units into ecological type three. Each evaluation unit is an ecosystem. Then, the ecosystem quality of all evaluation units is calculated, and a reference ecosystem is selected.

[0040] Third, calculate the ecosystem quality. Using remote sensing images, calculate the ecosystem quality of all evaluation units from four aspects: the structure, function, stability, and human disturbance intensity of the ecosystem.

[0041] The formula for calculating the ecosystem quality is as shown in Equation (1):

[0042] EQ = a×ES + b×EF + c×EST + d×D (1);

[0043] In Equation (1), EQ is the ecosystem quality, ES is the ecosystem structure, EF is the ecosystem function, EST is the ecosystem stability, D is the distance to the nearest disturbance source, and the value ranges of ES, EF, EST, and D are 0 - 1. a, b, c, and d are weight factors, with values of 0.4, 0.2, 0.2, and 0.2 respectively. Use the raster calculator of GIS software to complete the calculation of Equation (1). Each pixel in the calculation result has an attribute value, and the value range is between 0 - 1.

[0044] The ecosystem structure is obtained by weighted summation of the vegetation coverage and biodiversity. The calculation method is as shown in Equation (2):

[0045] ES = a1×Cov + a2×Bio (2);

[0046] In Equation (2), Cov is the vegetation coverage, Bio is the biodiversity, and a1 and a2 are weight factors, both with values of 0.5. The vegetation coverage and biodiversity are calculated from the GF-1 remote sensing image on July 7, 2022. Among them, the vegetation coverage is calculated using the pixel dichotomy model, and the biodiversity is calculated using the remote sensing spectral variation coefficient and standardized to the range of 0 - 1 using the min-max method. Use the raster calculator of GIS software to complete the calculation of Equation (2). Each pixel in the calculation result has an attribute value.

[0047] The ecosystem function is obtained by the weighted sum of the production capacity and the water conservation capacity. Among them, the production capacity is represented by the net primary productivity, and the water conservation capacity is represented by the soil moisture content. The calculation method is as shown in Equation (3):

[0048] EF = b1 × NPP + b2 × SMC (3);

[0049] In Equation (3), NPP is the net primary productivity, SMC is the soil moisture content, b1 and b2 are weight factors, and their values are both 0.5. The net primary productivity and the soil moisture content are calculated from the GF-1 remote sensing image on July 7, 2022, and the remote sensing index method is used for both. The calculation results are standardized to the range of 0 - 1 using the min-max method. The calculation of Equation (3) can be completed using the raster calculator of GIS software, and each pixel in the calculation results has an attribute value.

[0050] The ecosystem stability is obtained by the weighted sum of the structural stability and the functional stability. Among them, the structural stability is represented by the stability of the vegetation coverage, and the functional stability is represented by the stability of the net primary productivity. The calculation method is as shown in Equation (4):

[0051] EST = c1 × Cov_ST + c2 × NPP_ST (4);

[0052] In Equation (4), Cov_ST is the stability of the vegetation coverage, NPP_ST is the stability of the net primary productivity, c1 and c2 are weight factors, and their values are both 0.5. The calculation of Equation (4) can be completed using the raster calculator of GIS software, and each pixel in the calculation results has an attribute value;

[0053] ST is the stability of the vegetation coverage or the net primary productivity. The calculation method of the stability is as shown in Equation (5):

[0054]

[0055] In Equation (5), mean is the average value of the vegetation coverage or the net primary productivity in the past five years (from 2018 to 2022, downloading one GF-1 image in July each year), std is the standard deviation of the vegetation coverage or the net primary productivity in the past five years, Cov_mean is the average value of the vegetation coverage on July 7, 2022, and Cov is the vegetation coverage on July 7, 2022. When Cov is greater than or equal to Cov_mean, calculate normally; when it is less than Cov_mean, the result is directly assigned a value of 0. The calculation results are standardized to the range of 0 - 1 using the min-max method. The calculation of Equation (5) can be completed using the raster calculator of GIS software, and each pixel in the calculation results has an attribute value.

[0056] The intensity of human disturbance is determined by the distance of the pixel from the nearest disturbance source, where the disturbance sources include settlements, industrial and mining areas, and grazing points. The measurement method is the distance from the center of the pixel to the geometric center of the disturbance source. The calculation results are standardized to between 0 and 1 using the min-max method, and each pixel in the calculation results has an attribute value.

[0057] In the GIS software, use the zonal statistics function to calculate the average value of all pixel values within the evaluation unit as the ecosystem quality of the evaluation unit.

[0058] Fourth, extract the reference ecosystem. Considering the large area of the region where this embodiment is located, the evaluation units with the top 5% ecosystem quality are extracted as the reference ecosystem. Using the reclassification tool of the GIS software, sort the evaluation units of each ecological type in ascending order of ecosystem quality and divide them into 20 grades by the quantile method. As Figure 6 shown, select the evaluation units with the 20th grade ecosystem quality as the reference ecosystem for this ecological type. That is, select the evaluation units with the top 5% ecosystem quality as the reference ecosystem for this ecological type. If this invention is applied to a region with a small area, the selection interval of the reference ecosystem can be considered to be expanded (5 ≤ t ≤ 10) according to the on-site situation.

[0059] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be encompassed within the present invention. Any reference signs in the claims should not be regarded as limiting the claimed rights.

[0060] The above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any minor modifications, equivalent replacements, and improvements made to the above embodiments based on the technical essence of the present invention should be included within the protection scope of the technical solution of the present invention.

Claims

1. A method for selecting a reference ecosystem in an ecological restoration area based on remote sensing technology, characterized in that, Including the following steps: Step 1: Divide the ecological restoration area into different ecological types according to climate characteristics, vegetation characteristics, soil characteristics, and geomorphic characteristics; Step 2: Conduct hydrological analysis and vegetation community clustering analysis on the areas where each ecological type is located, and further subdivide each ecological type into different evaluation units; Step 3: Use remote sensing images to calculate the ecological system quality of all evaluation units from four aspects: ecological system structure, function, stability, and human disturbance intensity; The formula for calculating the ecological system quality in Step 3 is as follows: ； In the formula, EQ is the ecological system quality, ES is the ecological system structure, EF is the ecological system function, EST is the ecological system stability, D is the distance to the nearest disturbance source, and a, b, c, and d are weight factors with values of 0.4, 0.2, 0.2, and 0.2 respectively; each pixel in the calculation result has an attribute value; The calculation method of the ecological system structure is as follows: ； In the formula, Cov is the vegetation coverage, Bio is the biodiversity, and a1 and a2 are weight factors with values of 0.

5. The vegetation coverage and biodiversity are calculated from the remote sensing images of July and August of the most recent year and are standardized to 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value; The calculation method of the ecological system function is as follows: ； In the formula, NPP is the net primary productivity, SMC is the soil moisture content, and b1 and b2 are weight factors with values of 0.

5. The net primary productivity and soil moisture content are calculated from the remote sensing images of July and August of the most recent year and are standardized to 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value; The calculation method of the ecological system stability is as follows: ； In the formula, Cov_ST is the stability of the vegetation coverage, NPP_ST is the stability of the net primary productivity, and c1 and c2 are weight factors with values of 0.5; ST is the stability of the vegetation coverage or the net primary productivity, and the calculation method of the stability is as follows: ； In the formula, mean is the average value of the vegetation coverage or the net primary productivity in the past five years, std is the standard deviation of the vegetation coverage or the net primary productivity in the past five years, Cov_mean is the average value of the vegetation coverage in the most recent year, Cov is the vegetation coverage in the most recent year. When the vegetation coverage in the most recent year is greater than or equal to the average value of the current year's vegetation coverage, calculate normally; when it is less than the average value, the result is directly assigned 0; the vegetation coverage and the net primary productivity are calculated from the remote sensing images of July and August of each year, and the calculation results are standardized to 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value; The human disturbance intensity is determined by the distance of the pixel to the nearest disturbance source. The disturbance sources include residential areas, industrial and mining areas, and grazing points. The measurement method is the distance from the pixel center to the geometric center of the disturbance source. The calculation result is standardized to 0 - 1 using the min-max method. Each pixel in the calculation result has an attribute value; Step 4: Sort the evaluation units of each ecological type in descending order of ecosystem quality, and select the evaluation units with the top t% (5 ≤ t ≤ 10) of ecosystem quality as the reference ecosystem of this ecological type.

2. The method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology according to claim 1, characterized in that When dividing ecological types in Step 1, download the published climate type zoning data, vegetation type zoning data, soil type zoning data, and geomorphic type zoning data, overlay the above data in the same spatial coordinate system to obtain different climate-vegetation-soil-geomorphology combination types, and thus divide the ecological restoration area into different ecological types.

3. The method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology according to claim 1, characterized in that, When dividing evaluation units in Step 2, first, based on the digital elevation model, conduct a standardized hydrological analysis of the areas where each ecological type is located to obtain a spatial distribution map of catchment areas; then, based on remote sensing images, conduct clustering of vegetation community types in the areas where each ecological type is located to obtain a spatial distribution map of vegetation community types; finally, overlay the spatial distribution map of catchment areas with the spatial distribution map of vegetation community types to obtain hydrological-community type evaluation units.

4. The method for selecting a reference ecosystem for an ecological restoration area based on remote sensing technology according to claim 1, characterized in that, When calculating the ecosystem quality in the third step, according to the structural index, functional index, stability index and human disturbance intensity index of the ecosystem, first according to the formula ; Calculate the ecosystem quality of each pixel, and then take the average value of the ecosystem quality of all pixels within the evaluation unit as the final ecosystem quality of this evaluation unit.

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