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14 results about "Grassland degradation" patented technology

Grassland degradation, also called vegetation or steppe degradation is a biotic disturbance in which grass struggles to grow or can no longer exist on a piece of land due to causes such as overgrazing, burrowing of small mammals, and climate change. Since the 1970s, it has been noticed to affects plains and plateaus of alpine meadows or grasslands, most notably being in the Philippines and in the Tibetan and Inner Mongolian region of China where 2460 km² of grassland is degraded each year. Across the globe it is estimated that 23% of the land is degraded. It takes years and sometimes even decades, depending on what is happening to that piece of land, for a grassland to become degraded. The process is slow and gradual but at the same time so is restoring degraded grassland. Initially only patches of grass appear to die and appear brown in nature; but the degradation process, if not addressed, can spread to decimate many acres of land, which in the most severe cases is merely bare, black soil bereft of any usefulness. As a result, the frequency of landslides and dust storms increases; the degraded land’s less fertile ground cannot yield any produce nor can animals graze in these fields any longer; a dramatic decrease in plant diversity in this ecosystem; and more carbon and nitrogen are released into the atmosphere. These results can have serious effects on humans such as displacing herders from their community; a decrease in vegetables, fruit, and meat that are regularly acquired from these fields; and a catalyzing effect on global warming.

Vehicle-mounted unmanned aerial vehicle take-off and landing platform in grassland scene

PendingCN121608920AFreight handlingUncrewed vehicleGrassland degradation
The invention relates to a vehicle-mounted unmanned aerial vehicle take-off and landing platform in a grassland scene, the vehicle-mounted unmanned aerial vehicle take-off and landing platform is composed of an intelligent box body and an integrated connection platform, the intelligent box body integrates various sensors, monitors environment information inside and outside the box, provides conditional decisions for take-off and landing and charging operation of an unmanned aerial vehicle as a basis, and is provided with a high-speed data interface and a single-drive opening and closing mechanism; flight data of the unmanned aerial vehicle can be downloaded quickly, and energy loss of opening and closing actions is reduced; an integrated connection platform is nested in the box body, meanwhile, reset charging and autonomous feeding functions are integrated, and the endurance and material supply capacity of the unmanned aerial vehicle is improved; the platform can be carried on the upper portion of a movable chassis, near-low-altitude remote sensing image collection of the unmanned aerial vehicle is carried out on the rugged grassland terrain, and good scientific basis and technical support are provided for producers to monitor grassland degradation conditions and carry out ecological protection operation such as grass seed reseeding. And powerful technical support is provided for sustainable development of the grassland and promotion of intellectualization of related industries.
Owner:CHINA AGRI UNIV

Grassland degradation ecological risk assessment method based on multi-agent model

This invention relates to the field of ecological environment assessment and spatial simulation technology, and discloses a method for grassland degradation ecological risk assessment based on a multi-agent model. The method includes a spatial risk assessment module that acquires multi-source basic data and divides it into discrete grid cells, calculating a landscape ecological risk index to generate spatial distribution results; a driving mechanism identification module that extracts driving factors to construct an improved regression tree model and outputs nonlinear response rules; and a multi-agent dynamic simulation module that constructs grassland environmental entities based on grid cells, injects risk indices and response rules, generates herder behavior entities, and inputs management policy parameters. Iterative calculations are performed using these two types of entities to simulate the dynamic process of herder relocation and resource consumption. After the iteration reaches the target year, the grid landscape attributes are reclassified according to the remaining grass cover, and the data is re-input into the assessment module for aggregation calculations, outputting a spatial distribution map to complete the evolution assessment. This invention can intuitively test the intervention effect of management policies on grassland degradation.
Owner:GANSU AGRI UNIV

Ecological restoration method for moderately degenerated Coilin grassland

The invention discloses a method for ecologically restoring moderately degenerated Coilsein grassland. The method comprises the following steps: S1, investigating the degeneration condition of the Coilsein grassland; s2, investigating plant community characteristics and biomass; s3, determining the quality of the forage grass in the plant community; s4, collecting a soil sample; s5, reseeding, wherein the ratio of the agropyron crocea to the astragalus adsurgens is (2.5-3.5): 1; according to the method, appropriate grass seeds and fertilizer bags are screened out according to the plant community conditions of the moderately-degenerated Coerquin grassland, reseeding and fertilization are carried out, and finally the moderately-degenerated Coerquin grassland monoennial plants, biennial plants, perennial gramineae, hybrid grass and perennial leguminous plants all grow, so that the yield of the Coerquin grassland is increased, the yield of the Coerquin grassland is increased, and the yield of the Coerquin grassland is increased. The pH value of the soil tends to be neutral, the total nitrogen content of the soil is increased through fertilization, and moderately degenerated Coilin grassland vegetation is recovered.
Owner:MENGCAO ECOLOGICAL ENVIRONMENT (GRP) CO LTD

Method for improving production performance of grazing Tan sheep by using ground-source feed

PendingCN121942631Aresolve the disconnectRealize coupling utilizationAnimal husbandryStipaGrassland degradation
The invention discloses a method for improving production performance of grazing Tan sheep by utilizing ground-source feed, and relates to the technical field of improvement of productivity of the grazing Tan sheep and reasonable utilization of natural grassland, and the method comprises the following steps: selecting grassland with community vegetation coverage of more than or equal to 60%, plant overground net primary productivity of more than or equal to 100g / m < 2 >, and taking stipa brachycarpa or desertleweed as dominant species as grazing grassland; setting a continuous grazing group, a continuous grazing and supplementary feeding corn granule group and a continuous grazing and supplementary feeding caragana microphylla granule group, and respectively measuring body weight gain dynamic data, grazing behavior data and body size index data of the Tan sheep in each treatment group; and respectively monitoring the grassland plant overground net primary productivity and species richness of each treatment group by adopting a quadrat determination method, and determining whether the plant overground net primary productivity of each treatment group is lower than a desert grassland degradation warning threshold value or not. Ground-source feed utilization, grazing parameter optimization and grass and livestock cooperative monitoring are combined, and grassland ecological safety can be ensured while the production performance of the grazing Tan sheep can be improved.
Owner:NINGXIA UNIVERSITY

A degraded grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes

The application discloses a degraded grassland ecological restoration method and system based on ecological water demand inside and outside rivers and lakes, and comprises the following steps: conducting field investigation, analyzing the main characteristics of the degraded grassland to divide the degradation grade area, wherein the main characteristics include but are not limited to vegetation coverage, species diversity index and soil bulk density; carrying out ecological unit grid division based on terrain self-adaption; constructing a multi-objective function and constraint condition of the degraded grassland ecological restoration based on the ecological water demand inside and outside rivers and lakes according to water resource allocation, grassland restoration, grazing management and economic benefits; on the basis of the ecological water demand inside and outside rivers and lakes and in combination with the specific grassland degradation grade of the degraded area, the multi-objective function and the constraint condition are used to carry out restoration priority ranking, dynamic adjustment strategy and water resource dynamic adjustment, so that an optimal degraded grassland ecological restoration scheme is obtained; the application is a comprehensive ecological restoration scheme combining water resource utilization, ecological water demand, grazing management and economic benefits, and is helpful to promoting sustainable restoration of the grassland.
Owner:INNER MONGOLIA AGRICULTURAL UNIVERSITY

A method for ecological restoration of caragana planting based on remote sensing and intelligent monitoring

The present application relates to the technical field of ecological restoration, and more particularly to a caragana laying ecological restoration method based on remote sensing and intelligent monitoring. The method comprises the following steps: obtaining multispectral remote sensing images and ground survey data of the target grassland, and extracting vegetation coverage, soil erosion intensity and surface roughness; evaluating the degradation degree of the target grassland according to the vegetation coverage, soil erosion intensity and surface roughness, and determining the grassland degradation zoning map; determining the caragana laying parameters based on the grassland degradation zoning map; leveling and cleaning the target grassland; laying caragana on the pretreated target grassland surface according to the caragana laying parameters, and collecting monitoring images of the laying area in the target grassland by using a UAV at a preset period. The present application can accurately identify the degradation level and spatial difference of the grassland, thereby providing scientific and reasonable parameter settings for caragana laying, significantly improving the pertinence and effectiveness of the restoration measures, and optimizing the resource utilization efficiency.
Owner:INST OF WATER RESOURCES FOR PASTERAL AREA MINIST OF WATER RESOURCES P R C

A method of monitoring grassland degradation in fusion with animal activity

The application discloses a kind of grassland degradation monitoring methods of fusing animal activity, it is related to grassland ecological degradation monitoring technical field, in target area deployment multi-source sensor and animal activity tracking equipment, continuously collect vegetation, soil and in-situ monitoring data of animal activity;Preliminary cleaning and fusion are carried out to in-situ monitoring data by end side equipment, and after compression, it is uploaded to cloud end;In cloud end, integrate multi-time remote sensing image data, generate regional remote sensing-monitoring space-time data set.The application is through end cloud cooperation architecture, in target area deployment multi-source sensor and animal activity tracking equipment, continuously collect vegetation, soil and animal activity data, and combine multi-time remote sensing image, generate regional remote sensing-monitoring space-time data set, effectively solve the problem of discontinuous time-space data in traditional monitoring method, can capture the dynamic process of grassland degradation, provide continuous and consistent monitoring result on space-time, provide data basis for accurate evaluation of grassland degradation degree.
Owner:BAICHENG ANIMAL HUSBANDRY SCI RES INST

Grassland degradation grade diagnosis and restoration system based on AI image recognition

PendingCN121582874ACharacter and pattern recognitionProcess engineeringGrassland degradation
The invention relates to the technical field of grassland degradation restoration, and discloses a grassland degradation grade diagnosis and restoration system based on AI image recognition, and the system comprises an acquisition module which is configured to acquire image data of a to-be-monitored grassland, analyze the image data, and determine a degradation evaluation value of the to-be-monitored grassland based on an analysis result; the judgment module is configured to collect a preset ecological index of the to-be-monitored grassland and judge whether to adjust the degradation evaluation value or not according to the preset ecological index; the adjusting module is configured to determine an adjusting coefficient of the degradation evaluation value based on the rhizome density and obtain a degradation evaluation final value; the grade diagnosis module is configured to determine the degradation grade of the to-be-monitored grassland according to the degradation evaluation final value; and the restoration module is configured to determine a restoration strategy of the to-be-monitored grassland according to the degradation level. By combining the AI image recognition technology, the system can efficiently and accurately diagnose and repair the grassland degradation problem.
Owner:SHENYANG INST OF APPL ECOLOGY CHINESE ACAD OF SCI

A Method and System for Diagnostic of Secondary Degradation of Alpine Grasslands Based on Multi-Source Data

PendingCN122336561APerimetriesEngineering
This invention relates to the field of UAV image processing technology, specifically to a method and system for diagnosing secondary degradation of alpine grasslands based on multi-source data. Existing technologies suffer from the following drawbacks: low image processing accuracy, large data processing errors, and a lack of spatiotemporal comparability. To address these shortcomings, this invention first acquires images using the hypotenuse target method and calculates the modulation transfer function characteristic parameters to construct a multi-scale Gaussian space. An adaptive threshold algorithm is used to determine and fix thresholds, achieving binarization of the multi-scale images. Connected components meeting certain conditions are extracted from the binary images at each scale, and their directional robust perimeters are calculated, forming a perimeter sequence. Based on the perimeter sequence, a logarithmic scale-perimeter curve is established, and the second derivative is calculated to determine the collapse scale and standard scale, calculating the geometric features of the connected components. Combining degradation judgment thresholds and proportional constraints, crack-type early degradation patches satisfying the condition with the maximum negative second-order curvature are identified, achieving automatic identification of secondary grassland degradation.
Owner:NORTHWEST INST OF PLATEAU BIOLOGY CHINESE ACAD OF SCI

A grassland degradation monitoring method based on remote sensing monitoring

The application discloses a grassland degradation monitoring method based on remote sensing monitoring, comprising: acquiring multi-source remote sensing data; preprocessing the multi-source remote sensing data to obtain preprocessed remote sensing data; extracting multi-dimensional feature parameters based on the preprocessed remote sensing data to obtain a multi-dimensional feature parameter set; performing time sequence analysis on vegetation dynamic characteristics, soil dynamic characteristics and human disturbance characteristics by combining multi-time observation data through the multi-dimensional feature parameter set to construct a dynamic characteristic time sequence data set; performing deep fusion on spatial features and time sequence changes in the time sequence by using a convolutional neural network model according to the dynamic characteristic time sequence data set to generate a spatio-temporal fusion feature set; obtaining a degradation grade division result map according to the spatio-temporal fusion feature set; integrating multi-source remote sensing data based on the degradation grade division result map to obtain a refined grassland degradation evaluation result, and monitoring grassland degradation according to the evaluation result.
Owner:INSTITUTE OF GRASSLAND RESEARCH OF CAAS

A high-cold and arid environment-adapted potassium-dissolving growth-promoting bacterial strain and application thereof

PendingCN122344533ABiotechnologyArid
This application relates to the field of agricultural microbiology, and in particular to a potassium-solubilizing and growth-promoting bacterial strain adapted to high-altitude and arid environments and its application. The strain was isolated from sandy soil in a recovery phase following degradation in the Ruoergai Grassland in a high-altitude and cold region. It was identified as a *Comamonas* strain by 16S rDNA gene sequencing and phylogenetic analysis. After 7 days of shaking culture in potassium-solubilizing liquid medium at 30°C and 180 r / min, the effective potassium content in the fermentation broth was 14.41 mg / L. The strain can grow in LB medium at 12°C, remains viable after freezing, and can also grow in LB solid medium containing 800 mM mannitol at 30°C. The strain is classified as *Comamonas sp ZSK1*, with accession number CCTCC NO: M 20252437, deposited on November 3, 2025, at the China Center for Type Culture Collection. The strain described in this application solves the technical problem of existing potassium-solubilizing bacteria being functionally inactive and having low colonization rates due to limited or insufficient stress resistance.
Owner:CHENGDU UNIVERSITY OF TECHNOLOGY

Grassland degradation evaluation method and system based on multi-source remote sensing data

The invention relates to a grassland degradation evaluation method and system based on multi-source remote sensing data, and relates to the technical field of ecological monitoring. The method comprises the following steps: collecting and fusing satellite-air-ground multi-source monitoring data; inverting the vegetation coverage and the above-ground biomass based on the fusion data; analyzing the time sequence change trend and significance of the two; comprehensively judging the grassland degradation grade according to a judgment rule taking biomass as a main part and covering degree as an auxiliary part. The system comprises a data acquisition and transmission module, a data fusion treatment module and a degradation identification and evaluation module, and is used for realizing the method. According to the method, the problem of missing of a single monitoring scale is solved through multi-source collaboration, a scientific evaluation model is established, full-process automation from data to evaluation is realized, and an efficient and reliable technical scheme is provided for grassland ecological supervision.
Owner:BEIJING SHANHAICHUSHI INFORMATION TECH CO LTD

A method for rapidly improving the productivity of degraded grassland

PendingCN122074348Aincrease production capacitybreak the knotHops/wine cultivationFertilising methodsTemperate climateSemi-arid climate
This invention discloses a method for rapidly improving the productivity of degraded grassland, relating to the field of grassland ecological restoration technology, and is mainly applicable to degraded Leymus chinensis meadow steppes in temperate continental semi-arid climates. The method involves a combined root-cutting and fertilization operation on the target degraded grassland, followed by enclosure and management to complete the restoration. During the regreening period of the degraded grassland, 1-2 rows and oblique root cuts are performed at 6-10 day intervals. Fertilization involves applying 45-60 kg / mu of granular or mixed organic fertilizer. Granular or mixed organic fertilizer is applied 3-5 days after root cutting, and enclosure and management are implemented for 2-2.5 years with a complete ban on grazing. This invention is simple to operate, effectively promotes the natural recovery of Leymus chinensis communities, rapidly improves the productivity of degraded grasslands, meets the restoration needs of degraded Leymus chinensis meadow steppes in temperate continental semi-arid climates, and is easily scalable and applicable.
Owner:INST OF AGRI RESOURCES & REGIONAL PLANNING CHINESE ACADEMY OF AGRI SCI

Grassland degradation ecological risk assessment method based on multi-agent model

The invention relates to the technical field of ecological environment assessment and space simulation, and discloses a grassland degradation ecological risk assessment method based on a multi-agent model, and the method comprises the steps: obtaining multi-source basic data through a space risk assessment module, dividing the data into discrete grid units, calculating a landscape ecological risk index, and generating a space distribution result; the driving mechanism identification module extracts driving factors to construct a lifting regression tree model, and outputs a nonlinear response rule; the multi-agent dynamic simulation module constructs a grassland environment entity based on a grid unit, injects a risk index and a response rule, generates a pasture behavior entity, inputs a management policy parameter, executes iterative operation by using the two entities, and simulates a pasture addressing transfer and resource consumption dynamic process; after iteration reaches the target year, grid landscape attributes are re-classified according to the residual grass quantity, the grid landscape attributes are re-input into the evaluation module for aggregation operation, and a spatial distribution map is output to complete evolution evaluation. The method can visually test the intervention effect of the management and control policy on the grassland degradation.
Owner:GANSU AGRI UNIV