21 results about "Grassland ecosystem" patented technology

The invention belongs to the field of remote sensing technology application, mainly aims at three typical grassland ecological system types of desert, grassland and meadow in an arid region, and discloses a grassland ecological health four-dimensional quantitative evaluation method based on multi-source remote sensing data. Comprising the following steps: S1, data fusion and long-time-sequence base construction: aiming at three typical grassland ecosystems of desert, grassland and meadow in an arid region, integrating long-time-sequence multi-source remote sensing images and auxiliary environment observation data, and reconstructing a model through a space-time fusion algorithm and missing data; and constructing a long-time-sequence multi-dimensional raster data set which is consistent in spatial resolution and covers non-biological background conditions. According to the system, accurate evaluation of long-time-sequence comprehensive conditions of different typical grassland types in the arid region is realized, the input information dimension and quality of the evaluation model are remarkably improved, and the ecological health problem is innovatively and accurately diagnosed from the deficiency of system bases, functional vitality, structural tissues or stress resistance recovery capability on the spatio-temporal scale.

The invention relates to the technical field of risk assessment, in particular to a grassland ecosystem comprehensive drought risk assessment system based on multi-source data. The risk feature highlighting characterization value is calculated by determining the feature highlighting factors of the different risk areas of the grassland, so that the feature highlighting sorting sequence of the risk areas of the grassland is rapidly determined, the precision of grassland comprehensive drought risk assessment is improved, and meanwhile, the risk assessment accuracy is improved. According to the grassland actual data uploaded by the user side and the drought risk index information corresponding to the grassland ecological system, the maximum feature highlighting characterization value of each risk area of the grassland can be accurately obtained, and the accuracy of comprehensive drought risk assessment of the grassland ecological area is improved.

This invention discloses a method for assessing the impact of photovoltaic (PV) installations on grassland ecosystems based on multi-source remote sensing data. The method includes the following steps: constructing a multi-source remote sensing dataset of the PV installation area and surrounding grasslands; acquiring time series data of multi-dimensional ecological indicators such as vegetation, water, and energy; establishing multi-ring buffer zones based on the PV boundary, and extracting the variation characteristics of each ecological indicator within and outside the PV area and at different distances; and quantitatively assessing the intensity and spatial decay characteristics of the impact of PV installations on the grassland ecosystem through spatial difference analysis and comprehensive ecological impact indicators. This method enables long-term dynamic monitoring of the ecological effects of PV construction without ground-based observation, and has the advantages of high automation, strong scalability, and wide application range, providing scientific support for the ecological assessment and management of grassland renewable energy development.

The invention discloses an unmanned aerial vehicle multispectral monitoring method for grassland fragmentation dynamic analysis, and relates to the technical field of grassland ecosystem monitoring, and the unmanned aerial vehicle multispectral monitoring method for grassland fragmentation dynamic analysis comprises the steps: collecting standardized space-time sequence data through an unmanned aerial vehicle multispectral system; processing the data to generate a land cover distribution map and a three-dimensional model; quantifying landscape pattern and soil erosion indexes in a two-dimensional space and a three-dimensional space based on the model; the quantitative indexes are coupled with the ecological process model, and influences on species exchange, soil conservation and carbon storage functions are evaluated; and finally, trend analysis and visual expression are carried out. According to the method, the technical problems of low efficiency, insufficient satellite remote sensing resolution, difficulty in three-dimensional monitoring and incapability of quantitatively associating pattern change with ecological function influence of a traditional method are solved, so that efficient, accurate and three-dimensional quantification of grassland fragmentation dynamics is realized, and the ecological consequence of the grassland fragmentation dynamics is scientifically evaluated.

The invention belongs to the technical field of ecological restoration of alpine grassland, and particularly relates to an ecological planting method for shrub grassland in a super plateau semi-arid region. The method comprises the following steps: delimiting a sample plot in a to-be-restored super plateau semi-arid region degraded grassland area, and applying a bio-organic fertilizer and biochar for soil improvement and activation; ditching and soil preparation; after a water-retaining agent absorbs water and is prepared into gel, uniformly applying the gel into the sowing furrows and uniformly mixing the gel with furrow soil; and performing multi-species matching and sowing. According to the ecological planting method, a low-disturbance degraded shrub grassland remediation technology is adopted, a liquid mulching film is directly sprayed on the surface of soil on the basis of soil improvement, the effects of preventing wind, maintaining soil moisture and increasing ground temperature are achieved, the soil moisture condition and the moisture utilization rate can be obviously improved, soil remediation and vegetation planting are both considered, and the ecological planting effect is achieved. The multifunctionality of the ecological system of the shrub grassland is improved.

The invention relates to the technical field of image processing, in particular to a soil carbon reserve estimation method and model of a grassland ecosystem, and solves the technical problems of low precision and reliability of soil carbon reserve estimation of the grassland ecosystem by an existing estimation method. The method comprises the following steps: acquiring remote sensing spectral image time sequence data of the grassland ecosystem and humidity time sequence data of a plurality of monitoring points of the grassland ecosystem; determining a growth interval of each monitoring point according to the remote sensing spectral image time sequence data and the humidity time sequence data; screening vigorous monitoring points and ideal monitoring points from the plurality of monitoring points based on the growth interval and the humidity time sequence data; the normalized difference vegetation index is determined based on remote sensing spectral image time sequence data; determining the vegetation coverage rate of each monitoring point according to the vigorous monitoring points, the ideal monitoring points and the remote sensing spectrum image time sequence data; and determining the soil carbon reserve of the grassland ecosystem based on the determined vegetation coverage rate of each current monitoring point.

The application relates to an evaluation method for greenhouse gas emission of a grazing grassland, comprising the following steps: S1: collecting air above the grassland by a static chamber method and measuring the concentration of various greenhouse gases in the collected air and the change rate thereof; S2: calculating the annual greenhouse gas emission of the whole grassland ecosystem; S3: estimating direct or indirect energy consumption in the grassland production process, including direct emission generated by using fossil energy such as diesel, gasoline and coal and indirect emission caused by power consumption such as pumping irrigation, drainage and machine ploughing; S4: calculating the whole-year equivalent of the whole grassland production process; S5: obtaining the whole-year economic output of the whole grassland; S6: calculating the greenhouse gas emission intensity of the grassland according to the whole-year equivalent of the whole grassland and the whole-year economic output of the whole grassland. Since the above technical scheme is adopted, the evaluation method for greenhouse gas emission of the grazing grassland can improve the accuracy of the calculation result, and further improve the accuracy of the obtained greenhouse gas emission intensity.

The present application belongs to the technical field of grassland ecosystem management, and particularly relates to a grassland fence device facilitating the passing of wild animals, comprising a first protective net and a second protective net; the first protective net is composed of positioning supports one longitudinally sleeved by support seats and blocking ropes arranged between adjacent two positioning supports one; the second protective net is composed of positioning supports two longitudinally sleeved by support seats and electronic cables arranged between adjacent two positioning supports two; a connecting rod for mounting the blocking ropes and the electronic cables is arranged between the positioning supports one and the positioning supports two; when the monitoring assembly monitors that there is a wild animal within the set range of the first protective net, the lifting assembly is started to drive the connecting rod to move upwards along the positioning supports one and the positioning supports two, so that a passing area is formed below the first protective net and the second protective net. The grassland fence device can effectively promote the free passing of wild animals, while the basic function of the fence is taken into account, and the strong electric shock feeling caused by accidental touch during the passing of the animals can be avoided.

The invention belongs to the technical field of microorganisms, and particularly relates to a peoriae paenibacillus ZM1, a fungicide and application, the peoriae paenibacillus ZM1 is preserved in China General Microbiological Culture Collection Center (CGMCC) on May 26, 2025, and the preservation number is CGMCC No.34680. The invention further discloses a preparation method of the peoriae paenibacillus ZM1, the fungicide and application of the peoriae paenibacillus ZM1 and the fungicide. The invention provides a new way for screening excellent strain resources for research and development of microbial fertilizers, restoring degraded desert steppe soil environment and restoring biological functions of a degraded grassland ecosystem. The strain has the functions of fixing nitrogen, dissolving phosphorus, dissolving potassium, producing indoleacetic acid and producing siderophores, can significantly improve the content of alkali-hydrolyzable nitrogen, rapidly available phosphorus and rapidly available potassium in the desert steppe soil of Inner Mongolia, and can significantly promote plant growth.

This invention relates to the field of image processing technology, and more particularly to a method and system for evaluating grassland ecosystem function based on multi-source data. The method includes the following steps: acquiring remote sensing image data and aerial images of the target area, and performing image geometric registration; extracting vegetation spatial distribution indicators of the target area based on the spectral characteristics of ground features obtained from the geometric registration results; retrieving land surface temperature indicators, and combining the land surface temperature indicator retrieving results with acquired meteorological observation data to construct a land surface energy balance curve; identifying functional trends in each season based on the land surface energy balance curve; dividing functional feature domains according to the spatial clustering results of functional trends in each season, and determining the distribution of functional feature domains in each temporal phase; and evaluating the grassland ecosystem function score based on the distribution of functional feature domains in each temporal phase. Compared with traditional evaluation methods based on single-source data, this invention achieves a more accurate, quantitative, and dynamic evaluation of ecological function.

The present application discloses a kind of grassland ecological system monitoring method, system based on remote sensing data, electronic equipment and storage medium, method includes: using satellite sensor to collect the original remote sensing image covering grassland area, and the original remote sensing image is preprocessed, obtain multispectral image dataset;Spectral features in multispectral image dataset are extracted and each band reflectivity and vegetation index are calculated, to determine the spectral feature distribution map of grassland vegetation;Spectral feature distribution map is identified using convolutional neural network, and vegetation structure feature is obtained;Function characteristic parameters are extracted and analyzed from vegetation structure feature, and quantitative characterization result is obtained;Based on spectral feature distribution map, vegetation structure feature and quantitative characterization result, using time series analysis method obtains the spatio-temporal variation trend of grassland vegetation state;Through clustering analysis method, spatio-temporal variation trend is compared with preset ecological health threshold value, to judge the health state partition of grassland ecological system, and obtain health condition classification map.

The invention relates to the technical field of image processing, in particular to a grassland ecosystem function evaluation method and system based on multi-source data. The method comprises the following steps: acquiring remote sensing image data and an aerial image of a target area, and executing image geometric registration; extracting vegetation spatial distribution indexes of the target area according to the ground feature spectral features of the geometric registration result; inverting a surface temperature index, and combining an inversion result of the surface temperature index with the acquired meteorological observation data to construct a surface energy balance curve; identifying the function trend of each season based on the surface energy balance curve; dividing functional feature domains according to the spatial clustering result of the functional trend of each season, and determining the distribution condition of the functional feature domains of each time phase; and evaluating a grassland ecosystem function score according to the distribution condition of each time phase function feature domain. Compared with a traditional evaluation method based on single-source data, more accurate quantitative and dynamic ecological function evaluation is realized.

The invention discloses a method for measuring the optimal application amount of a degraded warm desert steppe sheep manure organic fertilizer, and relates to the technical field of damaged steppe ecosystem remediation, the method comprises the following steps: in a warm desert steppe area, selecting a degraded grassland with the vegetation coverage lower than 30%, the net primary productivity on the ground lower than 10g / g and the dominant plant of silver gray hedge; uniformly spreading the fermented and decomposed sheep manure organic fertilizer on the ground surface of an experiment area independently set for the corresponding sheep manure organic fertilizer addition amount value in the middle stage of the plant growth season, and not turning over; at the last stage of the plant growth season, the overground net primary productivity of the plants in each experiment area is measured; carrying out modeling analysis by using a threshold regression function in a'chngpt 'program package; and determining a numerical value corresponding to an inflection point which is identified by the model and has a significant change of the dependent variable along with the increase trend of the independent variable as an optimal additive amount threshold value. According to the method, the repairing object can be accurately judged, and the optimal adding amount threshold value of the sheep manure organic fertilizer can be quantitatively determined.

The invention relates to the technical field of sustainable grassland management, in particular to a grassland ecosystem carbon footprint evaluation and management optimization method and system.The method comprises the steps that historical data of a grassland ecosystem are extracted from a time-space database, a carbon source factor set and a carbon sink factor set are obtained, a dynamic carbon source set is obtained based on the carbon source factor set and a carbon source database, and the dynamic carbon source set is obtained; and a carbon source matrix is constructed in the carbon source calculation unit according to a preset initial decision set, the carbon source quantity is calculated by using the carbon source matrix and the dynamic carbon source set, if the decision state is an unequal state, the difference value between the carbon source quantity and the carbon sink quantity is calculated to obtain a carbon balance value, and the decision is adjusted in the optimization management unit according to the decision weight set to obtain an optimal decision set. According to the invention, management optimization of the grassland ecosystem can be realized.

The invention discloses a grassland ecosystem drought vulnerability dynamic evaluation method based on multi-source remote sensing data and multi-dimensional indexes, and the method comprises the steps: fusing the multi-source remote sensing data, and constructing a grassland total primary productivity data set and a leaf area index data set; identifying drought events and extracting drought features based on the grassland total primary productivity data set and the leaf area index data set, and quantifying an accumulative effect and a hysteresis effect of a grassland ecosystem on drought; constructing a multi-dimensional vulnerability index system comprising a resistance index, a resilience index and a sensitivity index, and dynamically evaluating the drought vulnerability of the grassland ecosystem to obtain an evaluation result; rGB three channels are mapped based on an evaluation result, a grassland drought vulnerability spatial distribution diagram is generated through three-channel numerical value combination, and vulnerability grading classification and preferential restoration area identification are achieved. According to the method, multi-source data is fused, the bottleneck of discontinuous spatio-temporal data is broken through, and high-precision spatialization evaluation of grassland drought response is realized.

The invention discloses a soil pretreatment method for promoting planting of reseeding species. The invention relates to a soil pretreatment method for promoting planting of reseeding species, which comprises the following steps: 1) taking a moderately and severely degraded grassland as a reseeding area, and performing reseeding strip planning; (2) carrying out rotary tillage operation on the planned reseeding strips; and (3) performing drilling operation on the strips subjected to rotary tillage in the step (2) so as to realize planting of reseeding species. Strip type local rotary tillage is adopted, only a reseeding area is improved, compared with traditional rotary tillage (overall disturbance), the water and soil loss risk is reduced, and the structure stability of a grassland ecological system is maintained; the rotary tillage depth is 6-8 cm, the rotary tillage depth is precisely matched with the thickness of a soil hardened layer, physical obstacles of reseeding species planting are eliminated, and ecological risks caused by deep soil disturbance are avoided; through cooperative adaptation of rotary tillage and seeding operation links, a loose, breathable and moisture-sufficient environment is created for plant growth, and the reseeding effect is remarkable.

The invention discloses an ecological effect evaluation method and system for landscapes, forests, lakes, grass and sand, and relates to the field of ecological effect evaluation. The method comprises the steps of obtaining ecological index data of an engineering area and a non-engineering area before and after ecological engineering implementation and ecological background covariable data before ecological engineering implementation; according to the ecological background covariable data of the engineering area and the non-engineering area before the ecological engineering is implemented, adopting a tendency score matching method to obtain a space unit set after the engineering area and the non-engineering area are matched; according to the ecological index data of the engineering area and the non-engineering area before and after the implementation of the ecological engineering and the matched space unit set, adopting a double difference method to obtain an average processing effect value of the ecological engineering of the engineering area in each space unit; and associating and fusing the average processing effect value of the ecological engineering in the engineering area in each space unit with the geographic information system space unit to generate an ecological effect evaluation chart. According to the invention, accurate evaluation of the ecological effect can be realized.

The present application relates to a kind of thyme biomass prediction method based on multispectral data and machine learning, comprising: obtaining the multispectral image data of research area and pre-processing;Carry out single plant scale segmentation, and obtain the target extraction result of single plant scale;Calculate vegetation index;Using machine learning model, vegetation index is modeled, obtain biomass prediction model and training, carry out the automatic prediction of thyme biomass, obtain two prediction targets of dry weight and fresh weight.The present application utilizes unmanned aerial vehicle low-altitude multispectral image data to combine multiple machine learning models, establishes high-precision biomass prediction model, and real-time and accurately obtains the spatial distribution characteristics of large-area thyme biomass, provides basis for grassland ecosystem management and resource assessment;It improves the prediction accuracy, overcomes the limitation of single model through the prediction of 11 kinds of machine learning models, enhances the stability and reliability of prediction result.

The invention relates to the field of ecological meteorological monitoring and drought identification, and discloses an extreme drought event identification method based on multi-dimensional indexes such as a rainfall anomaly percentage (PA) and a space coverage rate. According to the method, whether an extreme drought year is formed or not is judged by acquiring multi-year meteorological data, calculating an annual rainfall anomaly percentage, combining spatial distribution characteristics of drought grades (light drought, medium drought, heavy drought and extra drought) and integrating multi-dimensional indexes such as an annual average PA value, area proportions of regions of heavy drought and above, the number of drought stations and the like. Compared with a traditional single index recognition mode, the method can achieve dual recognition of short-term sudden drought and continuous drought of the region, and has high time sequence sensitivity and spatial resolution. The method is suitable for large-scale ecological system drought monitoring, regional drought risk assessment and climate response research, is especially suitable for extreme drought analysis and spatial-temporal change tracking of a grassland ecological system, and has good scientific research expansibility and popularization and application value.

The invention relates to a typical grassland miscanthus sinensis population dynamic regulation and control method based on precipitation, belongs to the technical field of livestock breeding, and aims to solve the problem that the trampling intensity is not matched with the growth requirement of miscanthus sinensis due to the fact that traditional grazing management cannot respond to the dynamic change of the environment in time and a quantitative regulation and control basis is lacked. According to the technical scheme, the method is characterized in that environmental index data such as soil volume moisture content, precipitation and effective accumulated temperature in a target grassland area are obtained in the grazing season and matched with a pre-established grazing decision query table to obtain an optimal trampling intensity interval, and grazing is executed with the interval median as the initial trampling intensity; and repeating the step of acquiring and matching the environmental indexes according to a preset period in the grazing season, and calibrating and updating the trampling intensity. The method can accurately adapt to environmental changes, dynamically regulate and control the miscanthus longicoides population in the typical grassland, maintain stable growth of the miscanthus longicoides population and balance of a grassland ecosystem, and is suitable for a grazing management scene of the typical grassland.