CN-121234190-B - Multi-objective optimization method, device, storage medium and equipment for natural protection area resources

CN121234190BCN 121234190 BCN121234190 BCN 121234190BCN-121234190-B

Abstract

The invention relates to a multi-target optimizing method, a device, a storage medium and equipment for resources in a natural protection area, which are used for realizing the prediction of overground biomass data and plant crude protein data in the target natural protection area by utilizing a pre-trained prediction model through acquiring multi-source remote sensing data in the target natural protection area, acquiring optimal planning information of the target protection area according to biological data, overground biomass data, plant crude protein data, decision targets and constraint conditions of the target natural protection area based on a second generation non-dominant ordering genetic algorithm, providing data support for planning of herd structures, wild animal numbers and artificial grassland planting information in the target protection area, solving the balance problem of balancing a plurality of targets of human habitat-grassland-wild animal-livestock in the natural protection area, and promoting sustainable development of the natural protection area.

Inventors

XU YIMING
Qin Yunmeng
DONG SHIKUI
Che Yunling
YU DIAN
CAO JIAYOU
WANG YOUHUI

Assignees

北京林业大学

Dates

Publication Date: 20260508
Application Date: 20250918

Claims (9)

1. The multi-objective optimization method for the natural protection area resources is characterized by comprising the following steps of: Acquiring biological data and multisource remote sensing data of a target natural protection area, wherein the biological data comprises grassland data, livestock data and wild animal data; Acquiring the above-ground biomass data and the plant crude protein data of a target natural protection area according to the multi-source remote sensing data and a pre-trained prediction model; obtaining a decision target and constraint conditions of a target natural protection area, wherein the decision target comprises a grassland ecological environment optimization target, and the constraint conditions comprise pasture production constraint and grass-livestock balance constraint; The grassland ecological optimization objective includes minimizing grassland resource pressure: ), Wherein, the For the purpose of grassland resource pressure, For the number of the last year columns of each livestock, Feeding food to the aboveground organisms of each livestock; For the number of the respective wild animals, For daily feed intake of each wild animal, For grazing days for k-type natural grasslands, when k=1, the grazing days for the corresponding warm-season natural grasslands are 153 days, and when k=2, the grazing days for the corresponding cold-season natural grasslands are 212 days; The pasture production constraint is used for constraining the slaughtering rate of the corresponding herd to be kept within a set range: , wherein, And Is the upper and lower limits of the out-rate; the grass-animal balance constraints include natural grass utilization constraints and artificial grass natural constraints, The natural grassland utilization constraint is used to constrain the forage demand of livestock to match the forage output of the grassland resource for each season: , , Wherein, the Is the number of the annual stock columns of various domestic animals, Is the number of various wild animals, and the number of the wild animals is the number of the wild animals, Daily feed intake for various domestic and wild animals in the kth natural grassland; For grazing days for k-type natural grasslands, when k=1, the grazing days for the corresponding warm-season natural grasslands are 153 days, and when k=2, the grazing days for the corresponding cold-season natural grasslands are 212 days; the available grassland area for k types of natural grasslands, k=1 being a warm season pasture and k=2 being a cold season pasture; is the aboveground biomass of k-type natural grasslands, For various areas where artificial grasslands are planted, For the single production of each artificial grass land, Is the area of the peripheral support region; The natural constraint of the artificial grassland is the constraint of artificial grass planting land: , Wherein, the To purchase the quantity of hay; the area of the grass planting land is artificially planted; the dry grass yield of artificial grass planting land, The daily hay amount of the livestock is fed, Days for cold season supplementary feeding; based on a second generation non-dominant ranking genetic algorithm, constructing a grass-livestock balance model based on nutrition according to biological data of the target natural protection area, aboveground biomass data, plant crude protein data, the decision target and the constraint condition, and obtaining optimal planning information of the target natural protection area, wherein the optimal planning information comprises a herd structure, the number of wild animals and artificial grassland planting information, and the method comprises the following steps: constructing an optimal dynamic balance of nutrient supply and body requirements: , , Wherein, the For daily crude protein demand in various domestic and wild animals in natural grasslands of the k-th type, Crude protein amount of pasture available for natural pasture; for daily acidic wash fiber demand in a variety of domestic and wild animals in a type k natural grass, The amount of pasture acid wash fiber available for a natural pasture; Based on the available grassland amount and the actual demand of livestock and wild animals, the spatial distribution of the unbalanced grassland area and the supplementary feeding amount required for achieving the forage supply and demand balance are calculated: , , Wherein, the Unbalanced aboveground biomass for grasslands in warm seasons or cold seasons, Daily actual demand for aboveground biomass in warm or cold seasons for domestic animals and wild animals, The theoretical availability of biomass on land for warm or cold season grasslands, The unbalanced crude protein amount of grassland warm season or cold season grasses and animals, Daily actual demand for warm or cold season crude proteins for domestic animals and wild animals, The crude protein provided for warm or cold season grassland biomass theoretically may be provided in amounts.
2. The method for multi-objective optimization of natural protected area resources according to claim 1, wherein the multi-source remote sensing data includes at least two variables, and after obtaining the multi-source remote sensing data, the method comprises: selecting related variables with correlation with above-ground biomass and plant crude proteins from the at least two variables based on a pearson related analysis algorithm; selecting significant variables with significance association with the above-ground biomass and the plant crude protein from the related variables based on a Boruta feature selection algorithm to obtain a feature subset; randomly selecting sampling points in a target natural protection area, and acquiring the above-ground biomass and plant crude protein data of the sampling points to obtain sample data; And generating a data set based on the feature subset and the sample data, and pre-training the deep neural network model by using the data set to obtain a prediction model.
3. The method for multi-objective optimization of natural protected area resources according to claim 1, wherein obtaining the above-ground biomass data and the plant crude protein data of the objective natural protected area according to the multi-source remote sensing data and the pre-trained predictive model comprises: Preprocessing the multisource remote sensing data, wherein the preprocessing comprises missing value processing, feature standardization and space alignment; carrying out uniform resampling and coordinate conversion on raster data with spatial heterogeneity in the multi-source remote sensing data, and unifying the raster data into target resolution; And reading a plurality of single-band raster data block by block, and generating an overground biomass predicted value and a plant crude protein predicted value block by utilizing the pre-trained predicted model.
4. A natural protected area resource multi-objective optimization method as recited in claim 1, wherein the decision objective comprises an animal husbandry productivity optimization objective comprising increasing a yield rate: Wherein, the In order to achieve the out-of-line rate, For the annual sales of livestock i, The number of the last year columns of the livestock j.
5. The method of claim 1, wherein the decision goal comprises an economic benefit optimization goal comprising maximizing a pasture yield value: Wherein, the For the value of the pasture industry production, For the average annual output of meat, wool, and down of each sheep, For the annual output value of each goat, For the annual output value of each yak, For the number of sheep to be considered, For the number of goats, Is the number of the yaks, To outsource an average price of 1kg of hay, In order to purchase the quantity of hay, For various areas where artificial grasslands are planted, Is the cost of planting 1 hm 2 .
6. The method of claim 1, wherein the decision targets comprise grassland quality targets for optimizing the aboveground biomass of natural grasslands and artificial grasslands to achieve balance and stabilization of the ecosystem: Wherein, the For the quality of the environment, u is the total available area of the natural grassland, d is the average value of the biomass on the ground in the protected area, For various areas where artificial grasslands are planted, The yield per mu of each artificial grass land is obtained.
7. A natural protection zone resource multi-objective optimization device, comprising: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring biological data and multisource remote sensing data of a target natural protection area, and the biological data comprises grassland data, livestock data and wild animal data; the data prediction module is used for acquiring the above-ground biomass data and the plant crude protein data of the target natural protection area according to the multi-source remote sensing data and the pre-trained prediction model; the decision information acquisition module is used for acquiring a decision target and constraint conditions of a target natural protection area, wherein the decision target The method comprises a grassland ecological environment optimization target, wherein the constraint conditions comprise pasture production constraint and grass and livestock balance constraint; The grassland ecological optimization objective includes minimizing grassland resource pressure: ), Wherein, the For the purpose of grassland resource pressure, For the number of the last year columns of each livestock, Feeding food to the aboveground organisms of each livestock; For the number of the respective wild animals, For daily feed intake of each wild animal, For grazing days for k-type natural grasslands, when k=1, the grazing days for the corresponding warm-season natural grasslands are 153 days, and when k=2, the grazing days for the corresponding cold-season natural grasslands are 212 days; The pasture production constraint is used for constraining the slaughtering rate of the corresponding herd to be kept within a set range: , wherein, And Is the upper and lower limits of the out-rate; the grass-animal balance constraints include natural grass utilization constraints and artificial grass natural constraints, The natural grassland utilization constraint is used to constrain the forage demand of livestock to match the forage output of the grassland resource for each season: , , Wherein, the Is the number of the annual stock columns of various domestic animals, Is the number of various wild animals, and the number of the wild animals is the number of the wild animals, Daily feed intake for various domestic and wild animals in the kth natural grassland; For grazing days for k-type natural grasslands, when k=1, the grazing days for the corresponding warm-season natural grasslands are 153 days, and when k=2, the grazing days for the corresponding cold-season natural grasslands are 212 days; the available grassland area for k types of natural grasslands, k=1 being a warm season pasture and k=2 being a cold season pasture; is the aboveground biomass of k-type natural grasslands, For various areas where artificial grasslands are planted, For the single production of each artificial grass land, Is the area of the peripheral support region; The natural constraint of the artificial grassland is the constraint of artificial grass planting land: , Wherein, the To purchase the quantity of hay; the area of the grass planting land is artificially planted; the dry grass yield of artificial grass planting land, The daily hay amount of the livestock is fed, Days for cold season supplementary feeding; The planning information acquisition module is used for constructing a grass-livestock balance model based on nutrition according to the biological data of the target natural protection area, the aboveground biomass data, the plant crude protein data, the decision target and the constraint condition based on a second generation non-dominant ordering genetic algorithm to acquire optimal planning information of the target natural protection area, wherein the optimal planning information comprises a herd structure, the number of wild animals and artificial grassland planting information, and comprises the following steps: constructing an optimal dynamic balance of nutrient supply and body requirements: , , Wherein, the For daily crude protein demand in various domestic and wild animals in natural grasslands of the k-th type, Crude protein amount of pasture available for natural pasture; for daily acidic wash fiber demand in a variety of domestic and wild animals in a type k natural grass, The amount of pasture acid wash fiber available for a natural pasture; Based on the available grassland amount and the actual demand of livestock and wild animals, the spatial distribution of the unbalanced grassland area and the supplementary feeding amount required for achieving the forage supply and demand balance are calculated: , , Wherein, the Unbalanced aboveground biomass for grasslands in warm seasons or cold seasons, Daily actual demand for aboveground biomass in warm or cold seasons for domestic animals and wild animals, The theoretical availability of biomass on land for warm or cold season grasslands, The unbalanced crude protein amount of grassland warm season or cold season grasses and animals, Daily actual demand for warm or cold season crude proteins for domestic animals and wild animals, The crude protein provided for warm or cold season grassland biomass theoretically may be provided in amounts.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the natural protection resource multi-objective optimization method according to any one of claims 1-6.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable by the processor; the processor, when executing the computer program, implements the steps of the natural protection zone resource multi-objective optimization method according to any one of claims 1-6.

Description

Multi-objective optimization method, device, storage medium and equipment for natural protection area resources Technical Field The invention relates to the field of land utilization planning, in particular to a multi-objective optimization method, device, storage medium and equipment for resources in a natural protection area. Background The natural protection area plays a vital role in protecting the alpine ecosystem and maintaining the national ecological safety. Problems such as lack of nutrition of wild herbivores and domestic animals, biodiversity of grasslands, deterioration of versatility, and reduction of income of herd exist in natural protection areas due to the influence of climate change and human activities. In the past, the research on the resource utilization of the natural protection area mainly focuses on the supply of grassland and pasture yield and the demand of livestock on pasture yield, and the focus is single, so that the accurate configuration and sustainable utilization of the resource of the natural protection area are difficult to realize. Disclosure of Invention The embodiment of the application provides a multi-target optimization method, a device, a storage medium and equipment for natural protection area resources, which can provide data support for planning of resources such as a flock structure, the number of wild animals, artificial grassland planting and the like of a target natural protection area and promote sustainable development of the natural protection area. In a first aspect, an embodiment of the present application provides a method for multi-objective optimization of resources in a natural protection area, including: Acquiring biological data and multisource remote sensing data of a target natural protection area, wherein the biological data comprises grassland data, livestock data and wild animal data; Acquiring the above-ground biomass data and the plant crude protein data of a target natural protection area according to the multi-source remote sensing data and a pre-trained prediction model; Obtaining decision targets and constraint conditions of a target natural protection area, wherein the number of the decision targets is at least two, and the decision targets and the constraint conditions are related to at least one data of above-ground biomass data, crude protein data, grassland data and animal data; based on a second generation non-dominant ranking genetic algorithm, optimal planning information of the target natural protection area is obtained according to the biological data of the target natural protection area, the aboveground biomass data, the plant crude protein data, the decision target and the constraint condition, wherein the optimal planning information comprises a herd structure, the number of wild animals and artificial grassland planting information. In a second aspect, an embodiment of the present application provides a multi-objective optimization apparatus for natural protection area resources, including: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring biological data and multisource remote sensing data of a target natural protection area, and the biological data comprises grassland data, livestock data and wild animal data; the data prediction module is used for acquiring the above-ground biomass data and the plant crude protein data of the target natural protection area according to the multi-source remote sensing data and the pre-trained prediction model; The system comprises a decision information acquisition module, a control module and a control module, wherein the decision information acquisition module is used for acquiring decision targets and constraint conditions of a target natural protection area, wherein the number of the decision targets is at least two, and the decision targets and the constraint conditions are related to at least one data of above-ground biomass data, crude protein data, grassland data and animal data; The planning information acquisition module is used for acquiring optimal planning information of the target natural protection area according to the biological data of the target natural protection area, the aboveground biomass data, the plant crude protein data, the decision target and the constraint condition based on a second generation non-dominant ordering genetic algorithm, wherein the optimal planning information comprises a herd structure, the number of wild animals and artificial grassland planting information. In a third aspect, an embodiment of the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of a natural protected area resource multi-objective optimization method as defined in any one of the preceding claims. In a fourth aspect, embodiments of the present application