5660 results about "Ecology" patented technology

The invention discloses a forestry ecological environment real-time monitoring and management method based on big data, and belongs to the technical field of forestry ecological environment management, and the method comprises the following steps: S1, multi-source heterogeneous data collection and sensor network deployment; s2, multi-modal data fusion and intelligent transmission: developing an adaptive communication protocol dynamic switching module, and automatically switching to a satellite communication link in a 4G / 5G network blind area; s3, mass data storage and distributed calculation: constructing a hybrid cloud storage architecture, and storing real-time monitoring data into a Redis cache queue; s4, intelligently extracting ecological environment indexes; s5, dynamically evaluating the ecological bearing capacity; s6, performing multi-level early warning and emergency response; s7, making a precise forestry management decision; and S8, carrying out system self-optimization and closed-loop management. According to the method, the air-space-ground integrated monitoring network is constructed, so that the comprehensiveness and the real-time performance of forestry ecological environment perception are remarkably improved; multi-source data of the unmanned aerial vehicle, the satellite remote sensing and the ground sensor are complementary.

The invention relates to the technical field of slope protection, in particular to a slope stability assessment method and system applied to mine ecological restoration, and the method comprises the steps: collecting basic geological data and dynamic monitoring data of a slope in an assessment region based on a set data collection frequency; performing space-time division according to a preset time window and a space grid to obtain a plurality of space-time window units, and calculating to obtain a multi-dimensional stability evaluation index according to the basic geological data and the dynamic monitoring data corresponding to each space-time window unit; based on the multi-dimensional stability evaluation indexes corresponding to different space-time window units, constructing a space-time serialized slope stability characteristic matrix; inputting the dynamic stability data into a preset multi-dimensional stability evaluation model to obtain a dynamic stability index; correcting the dynamic stability index by considering the obtained real-time environmental load interference data to obtain a corrected stability index; and a preset slope stability threshold value is utilized to perform early warning judgment.

The invention discloses a percolate intelligent remote monitoring and control system and method, and relates to the technical field of percolate monitoring. The percolate intelligent remote monitoring and control method comprises the following steps: S1, acquiring percolate working condition response data, and preprocessing the percolate working condition response data; s2, analyzing joint mutation characteristics of the three-dimensional core mutation parameters, identifying mutation event candidate points, aggregating to form mutation sections, and constructing a mutation section data set; s3, constructing an intervention judgment data set based on the abrupt change section data set, evaluating the intervention triggering strength of the abrupt change section, and judging whether to implement an intervention strategy or not based on an evaluation result; and S4, calling mutation event candidate points in which mutation sections are not formed, calculating trend characteristic parameters of various working conditions, evaluating working condition evolution risks and judging risk levels of abnormal candidate sections. The problem that the blocking risk cannot be recognized in time when the inlet water is mixed with the suspended fibers is solved.

The invention discloses a river water surface two-dimensional flow field reconstruction method based on effective tracer detection and tracking, and the method comprises the steps: carrying out the distortion correction of an original video image sequence, and setting an ROI region according to the water level detection river water surface range; the method comprises the following steps: collecting a multi-scene floating object data set, screening floating objects with high relative brightness and clear outlines in different scenes, and training a YOLO model to detect the floating objects on the surface of a river; using an OCSORT matching tracking method to track adjacent frames of targets to obtain a trajectory, and filtering according to the length, angle and variance of the trajectory to obtain a stable trajectory; according to the method, object information obtained through target detection is utilized, according to the area, the area change rate and the length-width ratio of a floating object on an image, the following performance and stability of the floating object are evaluated, a track fusion weight is calculated, and the influence of unreliable floating objects is reduced; and gridding the river surface area after orthographic correction, and for a grid with a plurality of tracks, calculating the average flow velocity of the grid according to the confidence coefficient of each track to obtain a gridding two-dimensional flow velocity vector field. The method can accurately identify the floating object which meets the requirements of visibility, following performance and stability on the river surface as an effective water flow tracer, and is suitable for measuring the flow velocity of the river surface in complex scenes such as night, storm, flare, shadow and the like.

The invention relates to the technical field of pattern recognition, in particular to an ecological restoration nursery stock quality detection system based on pattern recognition, which comprises an image acquisition module for controlling camera equipment to acquire nursery stock images under target time and illumination conditions to obtain an original image set; and performing format unification and cleaning on the original image set, removing image noise and irrelevant information, and generating a cleaned image set. According to the method, the image pickup equipment is controlled to obtain the original nursery stock image under the target time and illumination condition, the consistency and stability of image data are improved, after unified format and information cleaning are carried out on the original image, image noise and invalid information are eliminated, and the nursery stock feature extraction precision is improved. Based on multi-dimensional feature extraction of colors, textures and shapes and comparative analysis of known quality standards, accurate judgment of seedling growth quality is realized, and scientificity and reliability of seedling screening are improved.

The invention provides a carbon neutralization evaluation method for an ecological park, and the method comprises the steps: obtaining the basic data of various carbon assets in the ecological park, and the basic data comprises the natural ecological system carbon sink capability and human activity carbon emission intensity data; according to the carbon asset basic data, a time sequence analysis method is adopted to carry out modeling on the change trend of the carbon sink capacity and the carbon emission intensity, and a change trend model is obtained; modeling the spatial distribution of the carbon reserves and the carbon flux by utilizing a geographic information system technology and combining a change trend model to obtain a spatial distribution model; key variables are extracted from the spatial distribution model, and the effects of different factors on the carbon assets are quantified by adopting a multiple regression analysis method; acquiring carbon asset monitoring data, evaluating data quality, and if an abnormal value exists, performing correction by adopting a data cleaning algorithm; and according to the corrected carbon asset data, adopting a random forest model to predict the carbon sink capacity and the carbon emission intensity, and generating a dynamic evaluation result.

The invention discloses a method for denitrifying wastewater by using a low-temperature-resistant heterotrophic nitrification and aerobic denitrification bacterium, and relates to a method for denitrifying wastewater by using a biological bacterium, the bacterium is Pseudomonas putida, is named as Pseudomonas umsongensis BK17, belongs to Pseudomonas, and is preserved in the China Center for Type Culture Collection (CCTCC), the preservation number is CCTCC M 20242924, and the preservation date is December 27, 2024. The strain is a heterotrophic nitrification-aerobic denitrification bacterium, can efficiently remove inorganic nitrogen pollution in a water body, still has good denitrification performance under low-temperature stress, and is high in low-temperature tolerance. The strain can efficiently treat nitrogen-containing wastewater under the condition of 10 DEG C, and the removal efficiency can reach 99% or above. The method has great potential in the application of inorganic nitrogen pollution treatment of domestic sewage and other water bodies in cold regions in China.

The invention provides a sheep body size measuring method and device based on three-dimensional reconstruction and point cloud segmentation, a medium and a program product, and relates to the technical field of computer vision. The method comprises the following steps: acquiring a sheep image of a to-be-detected sheep, and preprocessing the sheep image to obtain a multi-view sheep target point cloud; performing point cloud registration processing on the multi-view sheep target point cloud to obtain a sheep three-dimensional model; performing point cloud segmentation processing based on the body size measurement key points and the sheep three-dimensional model to obtain key point region point clouds; based on the key point region point cloud, determining a region point cloud projection space, performing attitude normalization on the interval point cloud, and determining an attitude normalized key point region point cloud; and calculating the body size data of the to-be-measured sheep based on the point cloud of the key point region subjected to attitude normalization. According to the embodiment of the invention, through three-dimensional reconstruction of the body surface point cloud of the sheep, non-contact measurement of the body size data of the sheep is realized, and the measurement efficiency and accuracy are improved.

The invention discloses an ecological restoration effect evaluation method and system based on satellite remote sensing, and the method comprises the steps: collecting the satellite remote sensing data and field soil data of a preset region, and taking the remote sensing data of the preset region within a specified time as to-be-analyzed data; calculating a time sequence deviation and a contrast ratio based on the satellite remote sensing data to obtain a grading region; performing deviation correction on the satellite remote sensing data according to the field soil data in the grading region, and inputting the corrected satellite remote sensing data into a space-time ecological development prediction model to obtain ecological development prediction data; performing restoration uncertainty analysis according to the ecological development prediction data and the field soil data to obtain an ecological restoration effect confidence coefficient, and performing elastic capability analysis according to the ecological restoration effect confidence coefficient and the satellite remote sensing data to obtain an ecological elastic index; and constructing a time-varying ecological restoration effect evaluation model according to the ecological elasticity index, and outputting an evaluation result based on the to-be-analyzed data.

The invention discloses a tuna pond culture strategy optimization method and system based on meteorological influence analysis, and the method comprises the steps: collecting regional meteorological data and pond culture monitoring data, and constructing a multi-modal pond ecological feature vector; establishing a weather-water body dynamic coupling model by using a space-time diagram neural network, and generating water body situation response prediction information; a breeding regulation and control strategy is made based on the prediction information, and strategy self-adaptive optimization is achieved through real-time monitoring data; evaluating the anti-disaster capability of the tuna after the meteorological influence is finished, screening high-quality germplasm resources by combining genetic analysis, and generating an anti-disaster breeding scheme. According to the method, full-chain optimization from meteorological early warning to culture regulation and control to genetic breeding is achieved, and the climate toughness and economic benefits of tuna pond culture are comprehensively improved.

The invention relates to the technical field of germ detection, in particular to a method and a device for detecting response of corn to setosphaeria turcica infection. The method comprises the following steps: acquiring initial spectral reflectivity of corn leaves and environmental parameters of an environment where the corn leaves are located; the environment parameters comprise temperature, humidity and illumination; according to the growth characteristics of the corn leaves in different growth stages, extracting the initial spectral reflectance to obtain a key spectral reflectance; extracting the spatial-spectral characteristics of the key spectral reflectivity, and extracting the time sequence correlation characteristics of the environmental parameters and the key spectral reflectivity; generating a disease sensitive feature vector according to the space-spectrum feature and the time sequence correlation feature; according to the disease sensitive feature vector, determining the infection detection result of the corn leaves responding to the setosphaeria turcica.

The invention relates to acid-resistant sulfate reducing bacteria and application thereof, and belongs to the technical field of microorganisms. The acid-resistant sulfate reducing bacterium disclosed by the invention is Desulfovibrio desulfuricans QY411, and is preserved in the Guangdong Microbial Culture Collection Center on March 14, 2024, and the preservation number of the acid-resistant sulfate reducing bacterium is GDMCC No: 64412. The acid-resistant sulfate reducing bacterium provided by the invention can survive in an environment with the pH value of 4, and can be applied to ecological reconstruction of acid tailings and waste dump soil, the pH values of mining wasteland soil and surface water after ecological reconstruction are remarkably increased, the concentration of SO4 < 2-> in the soil is remarkably reduced, the acidification process in the mining wasteland soil is effectively inhibited, and the acid-resistant sulfate reducing bacterium has the advantages of being safe and reliable. Therefore, the acidification process in the mining wasteland is effectively controlled. Meanwhile, soil heavy metal pollution is reduced, and vegetation growth is recovered.

The invention relates to the technical field of crop disease and insect pest monitoring, and particularly provides a crop disease and insect pest intelligent monitoring system based on image recognition and machine learning, and the system comprises a reference model generation subsystem which obtains a continuous state flow in a crop growth period through a multispectral imaging array; performing micro-variation field comparison on the real-time image of the continuous state flow and the ideal form reference vector, and outputting a biological stress difference chart; the mutual exclusion association engine subsystem purifies a pathological response map, inputs the pathological response map into a pathological characteristic dissociation network, and outputs an environmental immune type disease mark set; and the disease source trajectory deduction subsystem diffuses a power chain through organisms on the basis of the initial infection focus coordinates in combination with a real-time wind direction vector field and a plant density topological graph. According to the method, the problem of high false positive rate in a complex farmland scene is solved through a dual denoising mechanism of growth rhythm decoupling and environmental interference stripping; and finally, monitoring dimension jump from single-point identification to group prevention and control is realized.

The invention discloses a ship attitude prediction method and system based on FT-Mama architecture. The method comprises the following steps: collecting training data of multiple modes; performing feature extraction on the training data of various modes to obtain time domain features and Fourier transform frequency domain features corresponding to the training data of various modes; according to the time domain feature and the Fourier transform frequency domain feature, training a preset FT-Mama multi-modal fusion model to obtain a ship attitude prediction model; obtaining to-be-processed multi-modal ship data, inputting the to-be-processed multi-modal ship data into the ship attitude prediction model, and outputting a ship attitude prediction result; wherein the training data comprises ship attitude data, sea condition data and meteorological data. The method can effectively improve the ship attitude prediction precision under the complex sea condition, reduces the prediction delay, provides reliable look-ahead information for boarding compensation control, and can be widely applied to the technical field of ship control.

The invention discloses a cultivated land state monitoring method based on cultivated land boundary identification, and relates to the technical field of image analysis, and the technical scheme comprises the steps: carrying out the preprocessing of a periodically obtained cultivated land real-time image, and carrying out the screening to obtain a gray-scale map corresponding to a set optimal spectral band; based on the grey-scale map and the spatial distribution characteristics and the time sequence difference characteristics of the seedlings, calculating the comprehensive probability that each local peak pixel point represents the existence of the seedlings in the grey-scale map of the current period; based on the comprehensive probability, judging whether each local peak pixel point represents a seedling or not; dividing a cultivated land boundary based on a judgment result, and distinguishing a cultivated area and a non-cultivated area; according to the method, the existence probability of the seedlings is judged by utilizing the spatial distribution characteristics and the time sequence difference characteristics of the seedlings, the accuracy of cultivated land boundary identification can be improved, and the cultivated land state is periodically updated and monitored in real time.

The invention discloses a Yellow River delta tidal creek intelligent segmentation method based on deep learning, and mainly relates to the technical field of ocean monitoring, and the method comprises the steps: obtaining a remote sensing image of a target region, carrying out the preprocessing of the remote sensing image, and constructing a tidal creek data set; constructing a tidal creek segmentation and extraction model, training the tidal creek segmentation and extraction model based on the tidal creek data set, and extracting tidal creek features through a model decoder; adding a multi-scale module based on a coordinate attention mechanism in the tidal creek segmentation extraction model, and performing sampling, feature fusion and average pooling processing on the extracted tidal creek features through the multi-scale module to obtain weighted tidal creek features; introducing a loss function to train and optimize the model, outputting a tidal creek semantic segmentation result through a model encoder, verifying the constructed tidal creek segmentation extraction model based on a tidal creek training set, and calculating the model accuracy.

The invention relates to the technical field of microorganism culture, and discloses a microorganism culture tank device which comprises a culture tank, a concave observation area is arranged in the center of the top of the culture tank, a central culture area surrounding the observation area is arranged in the culture tank, an oil path temperature control area wraps the culture tank, and a double-helix heat conduction oil path is integrated in the oil path temperature control area. Through the cooperation of the uniform distributor and the distributed simulated liquid conveying unit, the gas-liquid proportion and fluid distribution can be accurately regulated and controlled, the physical and chemical conditions in the deep sea or extreme environment are simulated, the constant-temperature precision of + / -0.005 DEG C is realized through the double-helix heat conduction oil way, the low-temperature environment is stably maintained, and the real thermodynamic conditions of deep-sea sediments are simulated; the device meets the sensitive requirements of different microorganisms on temperature, and has the characteristics of high practicability and capability of simulating a dynamic fluid environment of deep sea.

The invention provides a construction method of an ecological credit evaluation model. The construction method comprises the steps of collecting green financial activity data of an evaluation subject; analyzing the green financial activity data to obtain a subject portrait feature library of the evaluation subject, the subject portrait feature library comprising basic information of the evaluation subject, behavior pattern features and preference features of the evaluation subject in the green financial field; distributing a multi-dimensional identity label set for the evaluation subject; constructing an evaluation subject portrait based on the subject portrait feature library of the evaluation subject and the multi-dimensional identity identification set; based on the constructed causal inference model, according to the evaluation subject portrait, mining internal factor characteristics and external factor characteristics of green financial behaviors and ecological credit influencing the evaluation subject; and training the pre-trained neural network model according to the internal factor characteristics and the external factor characteristics until the training is finished, thereby obtaining an ecological credit evaluation model, and remarkably improving scientificity, accuracy and practicability of an ecological credit evaluation result.

The invention relates to the technical field of rock slope ecological protection, in particular to a rock slope ecological protection anchoring system which comprises a slope body, a planting frame, a greening vegetation layer, a protective net and an ecological restoration assembly. The ecological restoration assembly conveys and irrigates stored rainwater through a water storage tank, a water conveying pump, a water conveying pipe, permeation pipes and a first blocking pipe structure, meanwhile, the first blocking pipe is a hose, when water flows through the first blocking pipe, the first blocking pipe can expand and bulge, the first blocking pipe and the permeation pipes form a cross-shaped closure structure, and a stable supporting structure is formed; soil in the greening vegetation layer can be effectively intercepted, water and soil loss is prevented, collaborative optimization of ecological restoration and structural reinforcement is achieved, and long-term reliability and ecological benefits of the system are guaranteed.

The present invention relates to the technical field of water conservancy construction. Disclosed is an ecological restoration revetment structure, which is applied to a slope surface. The ecological restoration revetment structure comprises: a laying net which is laid from the top to the bottom of a slope, wherein a plurality of planting holes are provided in the surface of the laying net; and a plurality of frame blocks, all of which are detachably connected to the surface of the laying net, wherein each frame block has a limiting hole, and the limiting hole in each frame block corresponds to a set number of planting holes. By means of the cooperation of the laying net, inserting portions and blocking portions, the present invention can perform slope reinforcement and water flow blocking operations on a slope surface, thereby reducing the influence of water flow scouring on the slope surface. Specifically, the laying net is directly laid from the top to the bottom of a slope, and the frame blocks are then mounted on the laying net. When the frame blocks are mounted, the inserting portions are guided to be inserted into the slope, and the blocking portions then block and converge water spreading from the edges of the ends of the frame blocks away from the bottom of the slope, and guide the water to the surface of the laying net on two sides of each frame block. Figure accompanying the abstract

The invention discloses a YOLOv8 improvement-based lightweight detection method for wheat diseases and insect pests in northwest weather, and relates to the technical field of artificial intelligence and machine vision monitoring. The method comprises the following steps: acquiring an original RGB image in a wheat filling period in a northwest dry land area environment; performing screening and Mosaic-8 data enhancement on the collected original image data set, and establishing a wheat disease and insect pest image data set; constructing an improved wheat lesion detection lightweight model based on YOLOv8, and optimizing a network structure; inputting the established wheat disease and insect pest image data set into the improved network model for training; testing the application of the improved network model in a wheat disease and insect pest image test data set, and continuously updating learning parameters of the improved YOLOv8 network model; the updated and trained YOLOv8 network model is used for monitoring a dry land area where wheat is planted in the Gansu province in real time, and the complexity and accuracy of the model are evaluated; and finally, real-time feedback of a model detection result is realized, and wheat plant diseases are dynamically updated to improve model precision.

The invention relates to the field of river ecological water flow regulation and control, in particular to an intelligent water flow regulation and control system based on a river ecological environment, and the system comprises a data processing module which comprises a data collection unit for collecting sensor data at a river downstream gate; the decision-making module is connected with the data processing module and comprises a data analysis unit which is used for analyzing the standardized data by utilizing a machine learning model so as to output an analysis result; the storage module is respectively connected with the data processing module and the decision making module and is used for respectively storing the sensor data, the standardized data and the analysis result; and the control module is respectively connected with the data processing module, the decision module and the storage module and is used for determining the refresh rate of the sensor data according to the fluctuation amplitude of the water flow at the downstream gate. According to the invention, the accuracy of intelligent regulation and control of the water flow is improved.

The present invention relates to the technical field of tree transplantation, and discloses a tree transplantation device for garden construction based on green environmental protection, including a tree root shoveling mechanism. Above the tree root shoveling mechanism, there is a water spraying structure. Above the water spraying structure, there is a tree trunk clamping mechanism. Behind the tree root shoveling mechanism, there is a driving mechanism. The rear side of the driving mechanism is fixedly connected with a welding panel. One end of the tree trunk clamping mechanism close to the driving mechanism is fixedly connected with an L-shaped fixing rod. The tree root shoveling mechanism includes a circular plate. The outer side surface of the circular plate is fixedly connected with a first gear. Inside the circular plate near the first gear, there is a sliding bar slidably connected. The upper and lower surfaces of the sliding bar are both fixedly connected with cylinders. The front side surface of the sliding bar is fixedly connected with a small gear. The present invention has the characteristics of stabilizing trees, automatically watering, and improving the survival rate of transplanted trees.

The invention discloses a bionic gastrodia elata cultivation method based on modular mushroom sticks and an ecological prevention and control system, and belongs to the technical field of ecological cultivation of traditional Chinese medicinal materials. The cultivation method specifically comprises the following steps: (1) adopting modular mushroom sticks; (2) adopting a pest and disease damage prevention and control method; (3) adopting an ecological cooperation and environment adaptation cyclic utilization method; (4) an intelligent and automatic production method is adopted; (5) adopting a bionic cultivation process; and (6) adopting a gastrodia elata-morchella esculenta rotation method. According to the method, the wood cost is reduced by 80%, the disease occurrence rate is smaller than or equal to 3.5%, the insect attack rate is smaller than or equal to 4%, the chemical pesticide use amount is reduced by 90%, the yield of gastrodia elata per mu reaches 450 kg, the yield is increased by 20%, the yield of fresh mushrooms per mu is 310 kg through rotation of morchella esculenta, the comprehensive income is increased by 6000 yuan / mu, and the method is suitable for large-scale planting of resource-saving gastrodia elata in plains and under-forest planting scenes at the altitude of 800-1200 m.

The utility model discloses a sea grass seedling rope transplanting device and relates to the technical field of marine ecological restoration. The sea grass seedling rope transplanting device mainly comprises a supporting walking structure, a seedling rope guiding frame structure and a seedling rope transplanting structure, wherein the seedling rope transplanting structure comprises a coulter assembly, a soil covering structure, a compaction wheel and the like; the device is tightly attached to the surface of a seabed to walk and operate under the action of self weight, artificial sea grass seedling or adult plant transplanting bundle units which are connected in series and bound by taking a rope belt as a medium are sequentially conveyed into C-shaped grooves formed by the coulter assembly under the action of the guide structure, and the transplanting operation is completed after the artificial sea grass seedling or adult plant transplanting bundle units are buried by the soil covering structure and compacted by the compaction wheel, so that construction can be assisted by manpower, and the transplanting efficiency is improved. The equipment is simple in structure, convenient to construct and operate on the sea, high in sea condition adaptability, free of loss of transplanting units, standard and normative in transplanting depth, and capable of greatly reducing the operation intensity, improving the operation efficiency and improving the transplanting seedling rate.

The present invention relates to an SV molecular marker related to the vegetative branch number trait of Gossypium hirsutum L. and the use thereof. Provided are an SV molecular marker related to the vegetative branch number trait of Gossypium hirsutum L., primers shown as SEQ ID NO. 1-SEQ ID NO. 3 obtained on the basis of said SV molecular marker, and a detection kit. Therefore, the present invention can accurately predict and screen the vegetative branch number trait of Gossypium hirsutum L., and provides a scientific basis for cultivating Gossypium hirsutum L. having different vegetative branch types.

The invention relates to the technical field of river bank protection, in particular to a river bank slope protection for cofferdam construction and a construction method thereof. S2, construction of a near-water area structure; s3, construction of a far water area structure; s4, ecological enhancement; triple optimization of river bank protection is achieved through dynamic water level monitoring and modular design, a double-layer reinforced concrete and elastic sealant structure is adopted in a near-water area, the compressive strength is improved by 20%, the crack width is smaller than or equal to 0.2 mm, and material waste is reduced by 15% in cooperation with dynamic width adjustment (+ / -2 m); the mold bag concrete slope protection is combined with an atomization spraying system, the anti-scouring capacity reaches 5 m / (m.s), the vegetation coverage rate is larger than or equal to 80% within 3 months, and the water and soil loss rate is reduced by 70%; the modular honeycomb structure inflation assembly efficiency is improved by 40%, the transportation cost is reduced by 50%, the distributed sensors achieve structure displacement / pressure three-level early warning, the operation and maintenance cost is reduced by 70%, the overall service life is prolonged by more than 5 years, and an ecological-engineering collaborative protection system is formed.

The present invention belongs to the technical field of saline-alkali land improvement, and specifically relates to a method for improving saline-alkali land based on an efficient cultivation mode of alfalfa, oats and okra, comprising the following steps: S1. Plant alfalfa on the saline-alkali land, and let the alfalfa overwinter after being mowed; S2. Interplant oats and alfalfa in rows, and harvest the oats after they mature; S3. After harvesting the oats, plant okra in the planting area of the oats. The okra and alfalfa are interplanted in rows. After the okra matures, pick the okra, then cut the above-ground part of the okra and spread it flat between the planting rows; S4. During the planting period of oats and okra, mow the alfalfa multiple times, and let the alfalfa overwinter after the last mowing. By means of the efficient cultivation mode of interplanting alfalfa and oats, interplanting alfalfa and okra, and rotating oats and okra, the present invention improves the yield and quality of alfalfa and enhances the improvement effect of alfalfa on saline-alkali land.

The invention relates to the technical field of remote sensing, in particular to a method, device and equipment for identifying algal blooms in rivers around lakes and reservoirs and a storage medium. The method comprises the following steps: acquiring sentinel No.2 remote sensing image data at historical moments in a preset area, and performing radiometric calibration, atmospheric correction and super-resolution reconstruction; extracting an algal bloom sample and a non-algal bloom sample; performing feature conversion on the samples to obtain a sample feature data set; performing model training by using an XGBoost method based on the sample feature data set to obtain a water bloom recognition model; and inputting a feature data set obtained by converting the reflectivity image data of the to-be-monitored area into the water bloom recognition model to obtain a water bloom recognition result. According to the method, water bloom monitoring is carried out by adopting sentinel No.2 remote sensing image data, so that the problem that a conventional water color satellite cannot be used for monitoring due to the narrow width of a river channel around a lake and a reservoir in the related technology is solved; and the method does not need to set a water bloom identification threshold value in advance and extract a water body, so that the automation degree of water bloom identification is improved.

The utility model discloses an anti-scouring device for a river bridge pier, which relates to the technical field of bridge engineering and comprises a bottom support hoop, a first arc-shaped protective cover, a first mounting plate and a second arc-shaped protective cover, and one end of the top of the bottom support hoop is fixedly connected with the first arc-shaped protective cover. First mounting plates are fixedly connected to the two ends of the top and the two ends of the bottom of the first arc-shaped protection cover correspondingly, a second arc-shaped protection cover is slidably connected to the other end of the top of the bottom supporting hoop, and second mounting plates are fixedly connected to the two ends of the top and the two ends of the bottom of the second arc-shaped protection cover correspondingly. According to the bottom supporting hoop, the first arc-shaped protection cover, the first mounting plate and the second arc-shaped protection cover, the bridge pier is protected on the basis of buffering water flow, and therefore the problem that an existing river channel bridge pier anti-scouring device cannot buffer the water flow, and the anti-scouring effect is poor is solved.