CN114358615A - Dynamic grass and livestock balance monitoring method - Google Patents
Dynamic grass and livestock balance monitoring method Download PDFInfo
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Abstract
The invention provides a dynamic livestock and grass balance monitoring method which comprises the steps of obtaining theoretical livestock carrying capacity through remote sensing monitoring, obtaining actual livestock carrying capacity through ground monitoring, and verifying overload degree. The technical scheme of the invention can be accurate to the bearing capacity of each housekeeper contracted with the grassland and to the housekeeper, and is fair; the influence of artificial law enforcement can be eliminated when the grass livestock is supervised to be balanced, and fairness and sense are reflected; in addition, the method is favorable for monitoring the degradation condition of the grassland and protecting the ecological environment of the grassland.
Description
Technical Field
The invention relates to a monitoring method, in particular to a dynamic grass and livestock balance monitoring method.
Background
In order to protect, build and reasonably utilize grassland, maintain and improve ecological environment and promote sustainable development of animal husbandry, according to the grassland law of the people's republic of China, the state sets up a forage and livestock balance management method. Means that the total amount of available forage feed available to a grassland user or a contract operator through grassland and other approaches is dynamically balanced with the amount of forage feed required by the livestock to be fed, in a certain period of time, in order to maintain the virtuous cycle of the grassland ecosystem.
The grass-livestock balance system is a basic system for grassland management and ecological protection in China, but the aim of 'grass-livestock balance' is difficult to achieve in implementation. The grass and livestock balance management can directly influence the authority-dividing relationship between managers and producers at present, and the practical grass and livestock balance management system has certain limitation. As a grassland management system taking regulation and control of livestock carrying capacity as a core, the livestock overload rate of national key natural grassland reaches 31.2 percent. As a measure for ecological protection of grasslands, the phenomena of deterioration, desertification, salinization and stony desertification of the grasslands in China are still serious. This situation requires countermeasures against the problems of the system in its formulation and implementation. There are several major drawbacks.
1. Nowadays, the grass-livestock balance management system in China is defined according to the average productivity of grasslands in flag county areas, and one sheep unit can be cultivated in unit area. The types of grassland of a flag county area can be various, each type of grassland is different, the overground productivity is different, the bearing capacity of the grassland contracted by each farmer is different, and the unit of sheep cultivated in the unit area of each farmer is different.
2. The bearing capacity of the grassland specified in the 'grass and livestock balance management method' is a fixed numerical value all the time, the influence of the rich and poor years on the productivity of the grassland is not considered, and the bearing capacity of the grassland is high, poor and low in the grassland probably in one year with good rainwater. There is no annual dynamic load capacity variation.
3. On the supervision of the grass and livestock balance, the pasturing forbidding, the pasturing and the grass and livestock balance subsidy are directly related to the grass and livestock balance. At present, sheep are counted by a manual method, the grass-livestock balance execution must be implemented to the scale of a herdsman, but due to the heterogeneity and fluctuation of grass field resources, the accurate measurement of grass yield on the scale of the herdsman by the existing means is almost impossible. In addition, the herdsman can question the reasonableness of the stock carrying capacity standard formulated by the government according to own experience and the need of living beings. Hence, the herdsmen are penalized for unfairness based on such a criterion that is disputed itself.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a dynamic grass and livestock balance monitoring method which is accurate and fair, can improve law enforcement efficiency and is beneficial to protecting grassland ecology, and the method specifically comprises the following steps:
the invention discloses a dynamic grass and livestock balance monitoring method which is characterized by comprising the following steps:
(1) collecting high-resolution remote sensing data, processing the high-resolution remote sensing data to form image data, and interpreting and automatically identifying land use types, grassland types and subclasses by using application software;
(2) calculating NDVI of grasslands of different shepherds according to the image data in the step (1), performing regression analysis according to the NDVI data and the biomass on the field survey ground, establishing an estimation model, and performing a grass yield data map layer in a reverse mode;
(3) overlapping the boundary line of the grassland of the herdsman, and calculating the theoretical livestock carrying capacity of the herdsman by using the grass production data in the step (2) and referring to the calculation of the reasonable livestock carrying capacity of the agricultural industry standard NY/T635-2015 of the people's republic of China;
(4) the seasonal dynamics and the feed intake dynamics of a pasture field of a pasture user are measured by internal and external comparison by applying a 'cage covering method', the seasonal dynamics of the pasture field of the pasture user are obtained at the same time, the grazing intensity of the pasture field is calculated, the actual livestock carrying capacity of the pasture user with large grazing intensity (the utilization rate of the pasture is more than 50%) is obtained by investigation, and the actual livestock carrying capacity is compared with the theoretical livestock carrying capacity data in the step (3) to verify the overload degree;
the grazing strength and the aboveground biomass are measured according to the calculation of the reasonable livestock carrying capacity of the natural grassland of the agricultural industry standard NY/T635-2015 of the people's republic of China.
Further, the NDVI data was calculated using NDVI ═ (B4-B3)/(B4+ B3); b4 shows a remote sensing image near-infrared band, and B3 shows a remote sensing image red light band.
Further, the spatial resolution of the high-resolution remote sensing data in the step (1) is 2 meters.
Further, the step (1) of collecting high-resolution remote sensing data and processing the collected high-resolution remote sensing data to form image data specifically comprises the following steps: remote sensing data of 6, 7, 8 and 9 months per year are used. The remote sensing base map is formed by inlaying remote sensing image data of the same month in the period 4, and monthly image data are formed after radiation correction, atmospheric correction and cutting.
Further, the software in step (1) comprises ENVI.
Further, the cage covering method in the step (4) means that a small fence of 5m × 5m is placed in a grazing field, and grazing is not performed in the fence.
Further, the inner diameter of the iron ring on the enclosure of the cage method in the step (4) is 30mm, and the length of the iron ring is 100 mm.
And (3) further, the upper part and the lower part of the enclosure of the cage method in the step (4) are reinforced by welding transverse iron rods.
The invention provides a dynamic grass and livestock balance monitoring method. The method has the following beneficial effects:
1. the bearing capacity of each housekeeper contracted the meadow is accurate, and the bearing capacity of each housekeeper contracted the meadow is accurate, so that the method is fair. How many sheep units are bred in each household has scientific basis.
2. The influence of artificial law enforcement is eliminated when the grass and livestock are supervised and balanced, and fairness and justice are reflected.
3. The method has the advantages that the livestock are drafted, the grassland change condition of each herdsman is monitored, the law enforcement can be effectively carried out, and the law enforcement efficiency is improved. The law enforcement efficiency can be improved by more than 90%. (originally, 2-3 law enforcement officers are required to go to shepherd family and count sheep one by one, and the sheep are checked only by watching which overload is serious according to the remote sensing satellite film, and the sheep are not required to be counted by each family) the method helps to monitor the degradation condition of the grassland and protect the ecology of the grassland.
Drawings
FIG. 1 is a grassland estimated production model for inverting a grass production data map layer; wherein the grassland estimation model is Y498 x2X is more than or equal to +30.5x 0 and less than 0.35 (the left side of the figure 1); 1295x of Y2917x + 2710.35 ≦ x ≦ 1 (right side of FIG. 1); wherein Y is the biomass on the grassland and the unit is g/m2(ii) a x is the grassland NDVI value.
Fig. 2 is a diagram of pasture utilization rate distribution according to the invention.
FIG. 3 is a aboveground biomass distribution plot according to the present invention.
Fig. 4 is a schematic view of a ground monitoring pen.
Fig. 5 shows the dimensions of the rail and components.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention. The experimental methods without specifying specific conditions in the following examples were selected according to the conventional methods and conditions, or according to the commercial instructions.
The data analysis method of the invention comprises the following steps:
vegetation growth data: the vegetation growth is calculated according to a normalized vegetation index (NDVI) by adopting a formula (1) NDVI ═ (B4-B3)/(B4+ B3), (wherein B4 represents a near infrared band of a remote sensing image, B3 represents a red light band of the remote sensing image, the NDVI value is between [ -1,1], the larger the NDVI is, the higher the vegetation coverage is.)
Meadow utilization data: and according to the local grass mowing time node, obtaining remote sensing images before and after the time node, calculating an NDVI value, and determining a grass mowing field according to the characteristic that the NDVI value is rapidly reduced after grass mowing.
Coverage data: formula (2) fc ═ (NDVI-NDVIsoil)/(NDVIveg-NDVIsoil), where: NDVIsoil is the NDVI value of bare soil or vegetation-free covered areas; NDVIveg then represents the NDVI value of the pel that is completely covered by vegetation.
Biomass data: the normalized vegetation index (NDVI) has strong positive correlation with biomass, so that regression analysis is carried out according to NDVI data and field investigation biomass, a vegetation estimation relation model is determined according to the R-square value, and an aboveground biomass data map layer is inverted.
Stock carrying capacity data: according to technical parameters such as biomass data, actual grazing days, daily feed of livestock and the like, and according to national agricultural industry standard 'calculation of reasonable livestock carrying capacity on natural grassland' NY _ T635-2015.
Grassland utilization intensity data: monitoring was carried out by 2 methods: 1. the ground measurement and comparison of the utilization conditions of the grazing grassland inside and outside the fence by the 'cage covering method'; 2. and (3) comparing the biomass of various pastures (which are not fed by livestock and are only used for grass mowing, namely, all types of grasslands and grass prototypes) by using high-resolution remote sensing combined with ground production measurement data to obtain the feed intake of the pasture, wherein the ratio of the feed intake (the reserved grass output after the livestock outside the fence eat) to the grass output of the pasture is the grassland utilization rate of the region.
Example 1
A dynamic livestock balance monitoring method comprising:
firstly, remote sensing monitoring:
remote sensing data of 6, 7, 8 and 9 months per year are used. The remote sensing base map is formed by inlaying same-month remote sensing image data in the period 4, monthly image data are formed after radiation correction, atmospheric correction and cutting, and land use types, grassland classes and subclasses are interpreted and automatically identified by applying software such as ENVI; calculating NDVI of different pasture grasslands according to the image data, performing regression analysis according to the NDVI data and the biomass on the field survey ground, establishing an estimated yield model (figure 1), and inverting a grass yield data map layer; and overlapping the boundary line of the grassland of the herd, and calculating the theoretical livestock carrying capacity of the herd according to the indexes such as the grass yield data, the actual grazing days, the daily food consumption of livestock, the area of various grasslands of the grassland of the herd and the like. The theoretical livestock carrying capacity is calculated according to the agricultural industry standard of the people's republic of China (NY/T635-2015 natural grassland reasonable livestock carrying capacity).
Secondly, ground monitoring:
the seasonal dynamics and the feed intake dynamics of a grazing land of a grazing household are measured by comparing the inside and the outside of a 'cage covering method' (a small fence of 5m multiplied by 5m is placed in the grazing land, grazing is not performed in the fence), the seasonal dynamics of the grassland without grazing pressure is obtained at the same time, the grazing intensity of the grazing land is calculated, the actual livestock carrying capacity of the grazing household with high grazing intensity is obtained by investigation, and the overload degree is verified by comparing the actual livestock carrying capacity with the remote sensing estimated theoretical livestock carrying capacity data. The grazing intensity refers to the agricultural industry standard of the people's republic of China (NY/T635-2015 calculation of reasonable animal carrying capacity of natural grasslands), the pasture utilization rate is 50% -60% of light overload, 60% -70% of moderate overload and more than 70% of severe overload.
The above ground monitoring is mainly based on a sample area survey. On the field investigation route, sample plots are mainly laid in representative types, including representative grassland types (warm meadow grassland, warm desert grassland, warm grassland desertification, warm desertification and the like) and grassland types (plain hill meadow grassland subclass, mountain meadow grassland subclass, sandy grassland subclass and the like), and a plurality of small fences are enclosed by applying a 'cage method' to determine the seasonal dynamics and the feed intake dynamics of vegetation in and out of the comparison fences.
1 main plant species description sample prescription and a seed and yield determination sample prescription are randomly arranged in a sample plot, and 2 non-seed and yield determination sample prescriptions are randomly arranged in the sample plot. The sample plot table mainly records longitude and latitude, altitude, grassland types, grassland sub-types, grassland types, topographic features, soil texture, grassland utilization modes, grassland utilization strength and other information.
The method mainly comprises the steps of recording the names of main plant species, the coverage, height, grass yield and other indexes of a community, measuring the grass yield, cutting the overground part of the community on the ground level, drying and weighing the dry weight.
Example 2
Establishment of regression analysis model
Selecting sampling points (such as grasslands of different farmers), selecting a farmer grazing grassland in the inner Mongolia Wula cover area, performing regression analysis according to NDVI data and biomass on the field investigation ground, establishing an estimated yield model, and performing a grass yield data map layer in a reverse manner (fig. 1).
The method for measuring the aboveground biomass refers to the calculation of the reasonable livestock carrying capacity of the agricultural industry standard NY/T635-2015 of the people's republic of China.
When x is not less than 0.35 and not more than 1, regression analysis is carried out according to the data in the table 1, and Y is 1295x2917x +271 (right side of FIG. 1), wherein Y is biomass on grassland in g/m2(ii) a x is the grassland NDVI value.
TABLE 1
Claims (9)
1. A dynamic herd balance monitoring method, comprising:
(1) collecting high-resolution remote sensing data, processing the high-resolution remote sensing data to form image data, and interpreting and automatically identifying land use types, grassland types and subclasses by using application software;
(2) calculating NDVI of grasslands of different shepherds according to the image data in the step (1), performing regression analysis according to the NDVI data and the biomass on the field survey ground, establishing an estimation model, and performing a grass yield data map layer in a reverse mode;
(3) overlapping the boundary line of the grassland of the herdsman, and calculating the theoretical livestock carrying capacity of the herdsman by using the grass production data in the step (2) and referring to the reasonable livestock carrying capacity of the agricultural industry standard NY/T635-2015 of the people's republic of China;
(4) the seasonal dynamics and the feed intake dynamics of a pasture field of a pasture user are measured by internal and external comparison by applying a 'cage covering method', the seasonal dynamics of the grassland without the grazing pressure is obtained at the same time, the grazing intensity of the pasture field is calculated, the actual livestock carrying capacity of the pasture user with the pasture utilization rate of more than 50% is obtained by investigation, and the actual livestock carrying capacity is compared with the theoretical livestock carrying capacity data in the step (3) to verify the overload degree;
the grazing strength and the aboveground biomass are measured according to the calculation of the reasonable livestock carrying capacity of the natural grassland of the agricultural industry standard NY/T635-2015 of the people's republic of China.
2. A dynamic forage balance monitoring method according to claim 1 wherein the spatial resolution of the high resolution remote sensing data of step (1) is 2 metres.
3. The dynamic livestock balance monitoring method according to claim 1, wherein the step (1) of collecting high-resolution remote sensing data and processing the collected high-resolution remote sensing data to form image data specifically comprises the following steps: remote sensing data of 6, 7, 8 and 9 months per year are used. The remote sensing base map is formed by inlaying remote sensing image data of the same month in the period 4, and monthly image data are formed after radiation correction, atmospheric correction and cutting.
4. A dynamic livestock balancing monitoring method according to claim 1, wherein the software in step (1) comprises ENVI.
5. The dynamic herd balance monitoring method according to claim 1, wherein said NDVI data is calculated using NDVI ═ (B4-B3)/(B4+ B3); b4 shows a remote sensing image near-infrared band, and B3 shows a remote sensing image red light band.
6. The dynamic livestock balance monitoring method of claim 1, wherein said assessment model is Y498 x2+30.5x 0≤x＜0.35；Y＝1295x2-917x + 2710.35 ≦ x ≦ 1; wherein Y is the biomass on the grassland and the unit is g/m2(ii) a x isGrassland NDVI values.
7. The dynamic livestock balance monitoring method of claim 1, wherein the caging in step (4) means placing a small 5m x 5m pen in the grazing area, and no grazing is performed in the pen.
8. The dynamic livestock balance monitoring method of claim 6, wherein said iron ring of said caging enclosure of step (4) has an inner diameter of 30mm and a length of 100 mm.
9. The dynamic livestock balance monitoring method of claim 6, wherein the upper and lower parts of the enclosure of the caging process in step (4) are reinforced by welding transverse iron rods.
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| CN116431952B (en) * | 2023-03-22 | 2024-01-30 | 中国地质大学（北京） | Grassland ecological monitoring method and system based on artificial intelligence |
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