Evaluation method for mountain orchid rice producing area ecosystem based on multi-source satellite remote sensing

Abstract

The invention provides a mountain orchid rice producing area ecosystem evaluation method based on multi-source satellite remote sensing. The method comprises the following steps: S101, acquiring remote sensing image data of a mountain orchid rice producing area by using a satellite remote sensing technology; s102, performing preprocessing operation on the remote sensing image data of the mountain orchid rice producing area to obtain preprocessed remote sensing image data of the mountain orchid rice producing area; s103, on the basis of the preprocessed remote sensing image data of the mountain orchid rice producing area, interpreting and obtaining ecological system classification data of the mountain orchid rice producing area by adopting an object-oriented classification method; s104, performing statistical analysis on the classification data of the ecological system of the mountain orchid rice producing area to obtain the area of each type of ecological system; and S105, performing ecological system service value evaluation on the mountain orchid rice producing area based on various ecological system areas. According to the method, remote sensing image data and ecosystem classification data can be accurately obtained, and the service value function of the mountain orchid rice producing area is shown.

Description

Technical Field

[0001] The present invention relates to the field of satellite remote sensing technology, and in particular to a method for evaluating an ecosystem of a mountain rice producing area based on multi-source satellite remote sensing. Background Art

[0002] my country is a major grain producer, and rice is the country's largest grain crop. The rice planting area is about 30 million hectares, so the rice field ecosystem is also a part of our human survival. Due to the lack of awareness of environmental protection in the past and the frequent use of chemical additives such as fertilizers and pesticides that damage the ecological environment, the rice field ecosystem has also suffered certain damage. Therefore, there is an urgent need to accurately evaluate the changes in the rice field ecosystem based on a complete and unified rice field ecosystem service value assessment method, so as to raise people's awareness of ecological environment protection, pay attention to the sustainable use of ecology, and promote regional sustainable development. Summary of the invention

[0003] In view of this, the object of the present invention is to provide a method for assessing the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing, so as to solve or at least partially solve the above-mentioned problems existing in the prior art.

[0004] To achieve the above-mentioned purpose, the present invention provides a method for evaluating the ecosystem of a mountain rice producing area based on multi-source satellite remote sensing, the method comprising the following steps:

[0005] S101. Use satellite remote sensing technology to obtain remote sensing image data of Shanlan rice producing areas;

[0006] S102, performing a preprocessing operation on the remote sensing image data of the Shanlan rice producing area to obtain the preprocessed remote sensing image data of the Shanlan rice producing area;

[0007] S103, based on the pre-processed remote sensing image data of the Shanlan rice producing area, using an object-oriented classification method to interpret and obtain the classification data of the ecosystem of the Shanlan rice producing area;

[0008] S104. Statistically analyze the ecosystem classification data of Shanlan rice production areas to obtain the area of ​​each type of ecosystem;

[0009] S105. Based on the area of ​​various ecosystems, an assessment of the ecosystem service value of the Shanlan rice producing area is conducted.

[0010] Furthermore, the preprocessing operation includes radiation calibration, atmospheric correction, geometric correction and image data fusion.

[0011] Further, S21, radiation calibration: converting the brightness gray value of the remote sensing image data of the Shanlan rice producing area into a radiation brightness value;

[0012] S22, Atmospheric Correction: Convert the radiance value into the actual reflectivity of the surface;

[0013] S23, geometric correction: eliminating the distortion error of the remote sensing image data of the Shanlan rice producing area after the pre-processing in S22, performing geographic coordinate positioning on the remote sensing image data of the Shanlan rice producing area, and obtaining real coordinate information;

[0014] S24, image data fusion: Based on steps S21 to S23, the HIS transformation fusion method is used to fuse the remote sensing image data of the Shanlan rice producing area.

[0015] Further, S31, segmenting the pre-processed remote sensing image data of the Shanlan rice producing area into a plurality of entity units of the image objects;

[0016] S32, segmenting the image object entity unit to obtain multi-spatial feature values ​​of the image object;

[0017] S33. Analyze the multi-spatial feature values ​​of the image objects, establish a classification system for multi-feature image objects, and obtain classification data of the ecosystem in the Shanlan rice producing area.

[0018] Furthermore, the areas of various ecosystems include mountain rice planting area, forest area, shrub area, grassland area and wetland area.

[0019] Furthermore, the ecosystem service value assessment includes economic and cultural service value, positive ecological service value and negative ecological service value.

[0020] Furthermore, the economic and cultural service value is the sum of the economic value of the primary products produced by the rice fields and the landscape cultural service value;

[0021] The positive ecological service values ​​include gas regulation, climate regulation, water conservation, water purification, soil conservation and maintenance of biodiversity;

[0022] Negative ecosystem service values ​​include greenhouse gas emissions and agrochemical pollution.

[0023] Compared with the prior art, the present invention has the following beneficial effects:

[0024] The present invention can obtain accurate remote sensing image data and ecosystem classification data by preprocessing remote sensing image data and interpreting it using an object-oriented classification method. Then, by conducting an ecosystem service value assessment on the Shanlan rice producing area, the service value function of the Shanlan rice producing area can be more intuitively reflected, and the changes in the ecosystem service value function of the Shanlan rice producing area can be accurately displayed. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A schematic flow chart of a method for evaluating an ecosystem in a Shanlan rice producing area provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The enumerated embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0028] This embodiment provides a method for evaluating the ecosystem of a mountain rice producing area based on multi-source satellite remote sensing, the method comprising the following steps:

[0029] like Figure 1 As shown, the present invention provides a method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing, comprising:

[0030] S101. Use satellite remote sensing technology to obtain remote sensing image data of Shanlan rice producing areas.

[0031] S102, performing a preprocessing operation on the remote sensing image data of the Shanlan rice producing area to obtain the preprocessed remote sensing image data of the Shanlan rice producing area.

[0032] The pre-processing operation comprises the following steps:

[0033] S21, radiation calibration: convert the brightness gray value of the remote sensing image data of the Shanlan rice producing area into a radiation brightness value, or convert the recorded DN value (remote sensing image pixel brightness value) into an apparent reflectance. The conversion between the DN value and the radiation brightness value is:

[0034] L λ = k·DN+c

[0035] Among them, L λ is the radiance value of band λ, k and c are gain and offset respectively. The conversion between radiance value and apparent reflectance is:

[0036]

[0037] Among them, ρ λ is the atmospheric apparent reflectivity, d is the average distance between the sun and the earth, ESUN λ is the solar irradiance and θ is the solar altitude angle.

[0038] S22. Atmospheric correction: The process of converting the above radiance into the actual surface reflectance, eliminating the radiation error caused by the atmospheric image, and reflecting the true surface reflectance of the surface.

[0039] S23. Geometric correction: Eliminating the distortion error of the remote sensing image data of the mountain orchid rice production area after the preprocessing of S22, performing geographic coordinate positioning on the remote sensing image data of the mountain orchid rice production area, and obtaining the true coordinate information.

[0040] S24. Image data fusion: Based on the steps of S21 - S23, the IHS transform fusion method is used to perform fusion operations on the remote sensing image data of the mountain orchid rice production area.

[0041] Specifically, for the remote sensing image data stored in RGB format, its color information and brightness information are fused together. Although various colors can be conveniently displayed, it is impossible to distinguish various colors with a fixed threshold. However, for the remote sensing image data stored in HIS format, the color information and brightness information can be distinguished. Color separation processing in the HIS space can be independent of brightness, and various colors can be effectively separated using a fixed threshold.

[0042] The specific steps of IHS transform fusion are as follows:

[0043] (1) Perform IHS transform on the remote sensing image data to obtain I brightness, H hue, and S saturation images;

[0044] (2) Replace the obtained I with the panchromatic band image I';

[0045] (3) Perform IHS inverse transform on I', H, and S to generate fused remote sensing image data, defined as:

[0046]

[0047] Among them, V1 and V2 are intermediate variables in the color transformation, and r, g, and b are the red, green, and blue primary colors in the RGB color system. When g >= b, C = 0; when g < b, C = π.

[0048] S103. Based on the preprocessed remote sensing image data of the mountain orchid rice production area, using an object - oriented classification method, interpret and obtain the ecosystem classification data of the mountain orchid rice production area.

[0049] The object - oriented classification method includes the following steps:

[0050] S31. Segment the preprocessed remote sensing image data of the mountain orchid rice production area into multiple entity units of image objects, and classify different ground objects in the image to achieve a better classification effect.

[0051] S32, segmenting the entity units of the image object, and obtaining multi-spatial feature values ​​of the image object by using the feature attribute information such as spatial geometry, texture and spectrum of the image object.

[0052] S33. Analyze the multi-spatial feature values ​​of the image objects, establish a classification system for multi-feature image objects, and obtain classification data of the ecosystem in the Shanlan rice producing area.

[0053] S104. Statistically analyze the ecosystem classification data of Shanlan rice producing areas to obtain the area of ​​each type of ecosystem.

[0054] The areas of various ecosystems include ecosystem classification data such as mountain rice planting area, forest area, shrub area, grassland area and wetland area.

[0055] S105. Based on the area of ​​various ecosystems, an assessment of the ecosystem service value of the Shanlan rice producing area is conducted.

[0056] The ecosystem service value assessment includes economic and cultural service value, positive ecosystem service value and negative ecosystem service value;

[0057] (1) Economic and cultural service value: It is the sum of the economic value of the primary products of rice field production and the landscape cultural service value. The primary products produced by the rice field ecosystem include mountain rice and straw. Mountain rice is the source of food for humans, and straw can be used as a raw material for papermaking, fiber products and animal feed, etc., and has a certain economic value. The landscape cultural service value is calculated using the results reference method with the mountain rice planting area as the calculation standard. The mountain rice producing area in Qiongzhong County is used as the calculation standard to calculate the landscape cultural service value. The unit is: Yuan / hm 2 / year. The economic value of primary products produced by rice fields is calculated using the market value method and is defined as:

[0058] V F =TPV F -TPC F

[0059] V S =Q S *0.706*P S

[0060] Among them, V F is the total income of Shanlan rice production (10,000 yuan), V S is the value of straw resources (10,000 yuan), TPV F is the market value of Shanlan rice production (10,000 yuan), which can be calculated from Shanlan rice production (t) and Shanlan rice market price (yuan / kg -1 ) shows that TPC F is the production cost of Shanlan rice (10,000 yuan), which can be calculated by the Shanlan rice planting area (hm2 ) and unit area production cost (yuan / hm2) 2 ) It is concluded that Q S is the straw yield (t), which is derived from the Shanlan rice yield (t) and the rice production straw-grain ratio. The effective utilization rate of straw in my country is 70.6%, P S Market price of straw products (yuan / kg -1 );

[0061] (2) Positive ecological service value: gas regulation, climate regulation, water conservation, water purification, soil conservation and maintenance of biodiversity;

[0062] Gas regulation: The gas regulation of the ecosystem in the Shanlan rice production area is the sum of the values ​​of fixing CO2, releasing O2 and absorbing harmful gases, among which the value of fixing CO2 is the average value of the calculation results of the Swedish carbon tax method and the afforestation cost method; the value of releasing O2 is the average value of the calculation results of the oxygen production industry cost method and the afforestation cost method; the value of absorbing harmful gases includes the absorption of dust, sulfur dioxide (SO2), nitrogen oxides (NOX) and hydrogen fluoride (HF);

[0063] Fixed CO2 is defined as:

[0064] V CO2 =Q W *P CO2 *C CO2 *M

[0065] Among them, V CO2 is the value of fixed CO2 (10,000 yuan), Q W is the dry matter mass of Shanlan rice production (t), P CO2 is the average of the carbon sequestration price calculated by the Swedish carbon tax method and the afforestation cost method, C CO2 is the carbon content in CO2, M is the mass of CO2 required to produce 1g of dry matter of Shanlan rice (g);

[0066] The release of O2 is defined as:

[0067] V O2 =Q W *P O2 *N

[0068] Among them, V O2 is the value of releasing O2 (10,000 yuan), Q W is the dry matter mass of Shanlan rice production (t), P O2 It is the average price of producing O2 calculated by the oxygen production industry cost method and the afforestation cost method, and N is the mass (g) of O2 released for every gram of dry matter produced by Shanlan rice.

[0069] Climate regulation: In summer, the transpiration of rice plants and the evaporation of water in rice fields will absorb the heat from the surrounding environment, lower the temperature of the surrounding air, and alleviate the "heat island effect". The value of climate regulation can be measured by the benefits of rural residents saving on the use of air conditioners, which is defined as:

[0070] V T =H T *d*h*x*P T

[0071] Among them, V T is the climate regulation value (ten thousand yuan), H T is the number of rural households in the Shanlan rice producing area, d is the number of days with assumed summer temperature drop, h is the assumed daily temperature drop time, x is the temperature drop number, P T is the residential electricity price (yuan).

[0072] Water conservation: During the growth of Shanlan rice, its roots are covered by water most of the time, which reflects the good water retention of the rice field. The value of water conservation in the rice field is replaced by the amount of water infiltrated into the soil multiplied by the price of agricultural water, and is defined as:

[0073] V S =Q S *P S

[0074] Q S =A*I R

[0075] Among them, V S is the water conservation value (ten thousand yuan), Q S is the amount of water infiltrating into the paddy field (m 3 ), P S is the agricultural water price (yuan / m 3 ), A is the planting area of ​​mountain rice (hm 2 ), I R is the soil infiltration rate.

[0076] Water purification: The treatment of sewage by the rice field ecosystem includes not only physical purification processes of adsorption and sedimentation, but also chemical purification processes of oxidation and reduction decomposition. The value of rice field water purification is replaced by the purification cost of rural domestic sewage and is defined as:

[0077] V R =Q R *β*C R

[0078] Among them, V R is the paddy field water purification value, β is the domestic sewage purification coefficient, Q R is the volume of domestic sewage, C R It is the cost of domestic sewage purification.

[0079] Soil conservation: The rice field ecosystem has soil conservation functions such as intercepting sediment, preventing soil erosion and increasing soil organic matter. The value of this function is measured by the difference between the input and output of soil organic matter multiplied by the market price of organic fertilizer. The organic matter in the paddy field soil mainly comes from the sedimentation of the roots of mountain rice and the straw left in the rice field after the mountain rice is harvested. At the same time, mountain rice and soil microorganisms will consume soil organic matter, and the consumption is mainly calculated through the CO2 and CH4 emissions of the two.

[0080] Maintaining biodiversity: Rice fields not only provide food for humans, but also serve as an ecological environment for plants, animals and soil microorganisms to survive. The value of this service is calculated using the results reference method, referring to the Shanlan rice producing area in Qiongzhong County, and using the area of ​​various ecosystems in the Shanlan rice producing area as the calculation standard to calculate the value of maintaining biodiversity. The unit is: yuan / hm 2 / Year.

[0081] (3) Negative ecological service value: greenhouse gas emissions and agricultural chemical pollution;

[0082] Greenhouse gas emissions: Greenhouse gases emitted by rice field ecosystems to the atmosphere mainly include CH4, N2O and CO2. The present invention converts the negative values ​​of CH4 and N2O emitted by rice field ecosystems into the negative value of CO2 emissions, that is, 1.00kg CH4 has the same greenhouse effect as 24.50kg CO2, and 1.00kg N2O has the same greenhouse effect as 320.00kg CO2. The negative value of greenhouse gas emissions from rice fields is the average value of the calculation results of the Swedish carbon tax method and the afforestation cost method, and is defined as:

[0083] V G =P CO2 *(E CO2 +25E CH4 +298E N2O )*C CO2 +(T N *E N +T P *E P +T K *E K )

[0084] Among them, V G is the negative value of greenhouse gas emissions from rice fields, P CO2 It is the average of the carbon sequestration price calculated by the Swedish carbon tax law and the afforestation cost method. Through the global warming potential (GWP), CH4 and N2O are converted into the negative value of CO2. The GWP of CH4 and N2O are 25 and 298 respectively. CO2 、ECH4 and E N2O are the emissions of CO2, CH4 and N2O respectively, T N , T P and T K The use of nitrogen, phosphorus and potassium fertilizers per unit area of ​​Shanlan rice (kg / hm 2 ), E N 、E P and E K are greenhouse gases emitted during the production of nitrogen, phosphorus and potash fertilizers, respectively. CO2 is the carbon content in CO2.

[0085] Agrochemical pollution: The use of chemical fertilizers in the cultivation of Shanlan rice can easily cause eutrophication of the surrounding soil and water bodies. The application of pesticides may cause soil and air pollution, while endangering the biodiversity of the rice field ecosystem. This negative value is calculated by multiplying the pollution cost caused by agrochemicals by the Shanlan rice planting area, and is defined as:

[0086] V N =C N *A*Q N

[0087] Among them, V N is the negative value of agricultural chemical pollution, C N is the pollution cost of agricultural chemicals, A is the area of ​​rice cultivation, Q N It is the amount of chemical fertilizer applied to the Shanlan rice planting area.

[0088] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. On the contrary, any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for assessing the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing, characterized in that: include: S101. Use satellite remote sensing technology to obtain remote sensing image data of Shanlan rice producing areas; S102, performing a preprocessing operation on the remote sensing image data of the Shanlan rice producing area to obtain the preprocessed remote sensing image data of the Shanlan rice producing area; S103, based on the pre-processed remote sensing image data of the Shanlan rice producing area, using an object-oriented classification method to interpret and obtain the classification data of the ecosystem of the Shanlan rice producing area; S104. Statistically analyze the ecosystem classification data of Shanlan rice production areas to obtain the area of ​​each type of ecosystem; S105. Based on the area of ​​various ecosystems, an assessment of the ecosystem service value of the Shanlan rice producing area is conducted.

2. The method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing according to claim 1, characterized in that: In step S102, the preprocessing operation includes radiometric calibration, atmospheric correction, geometric correction and image data fusion.

3. The method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing according to claim 2 is characterized in that: In step S102, the preprocessing operation includes the following steps: S21, radiation calibration: converting the brightness gray value of the remote sensing image data of the Shanlan rice producing area into a radiation brightness value; S22, Atmospheric Correction: Convert the radiance value into the actual reflectivity of the surface; S23, geometric correction: eliminating the distortion error of the remote sensing image data of the Shanlan rice producing area after the pre-processing in S22, performing geographic coordinate positioning on the remote sensing image data of the Shanlan rice producing area, and obtaining real coordinate information; S24, image data fusion: Based on steps S21 to S23, the IHS transformation fusion method is used to fuse the remote sensing image data of the Shanlan rice producing area.

4. The method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing according to claim 1, characterized in that: In step S103, an object-oriented classification method is used to interpret and obtain the classification data of the ecosystem of the mountain rice producing area, including the following steps: S31, dividing the pre-processed remote sensing image data of the Shanlan rice producing area into a plurality of entity units of the image objects; S32, segmenting the image object entity unit to obtain multi-spatial feature values ​​of the image object; S33. Analyze the multi-spatial feature values ​​of the image objects, establish a classification system for multi-feature image objects, and obtain classification data of the ecosystem in the Shanlan rice producing area.

5. The method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing according to claim 1, characterized in that: The areas of various ecosystems include mountain rice planting area, forest area, shrub area, grassland area and wetland area.

6. The method for evaluating the ecosystem of mountain rice producing areas based on multi-source satellite remote sensing according to claim 1, characterized in that: The ecosystem service value includes economic and cultural service value, positive ecological service value and negative ecological service value.

7. The method for evaluating the ecosystem of the rice producing area based on multi-source satellite remote sensing according to claim 6 is characterized in that: The economic and cultural service value is the sum of the economic value of the primary products produced by the rice fields and the landscape cultural service value; The positive ecological service values ​​include gas regulation, climate regulation, water conservation, water purification, soil conservation and maintenance of biodiversity; Negative ecosystem service values ​​include greenhouse gas emissions and agrochemical pollution.

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