41 results about "Plant Distributions" patented technology

The present invention discloses a method for monitoring and early warning of wild plant distribution status based on image recognition, relating to the technical field of monitoring and early warning of wild plant distribution status. This method promotes the scientific assessment of ecological protection status of each sub-area by calculating coverage indexes Fgl and population complexity indexes When one of the coverage indexes or the population complexity indexes of a sub-area does not reach a preset threshold, an unqualified mark is marked accordingly. By calculating environmental pressure indexes HJyl, a first early warning instruction is automatically sent when one of the environmental pressure indexes HJyl exceeds a preset first pressure threshold, indicating that the environmental pollution status is unqualified.

The invention belongs to the technical field of remote sensing, and discloses a wolfberry planting distribution high-precision remote sensing monitoring method based on multi-temporal fusion and spectral feature optimization. According to the method, a multi-temporal and multi-spectral satellite image is used as a data source, and preprocessing and multi-temporal image fusion are firstly carried out; the method comprises the following core steps: establishing a time sequence characteristic curve according to a unique phenological period (such as bare soil characteristics in a dormancy period and high vegetation coverage in a rapid growth period) of wolfberry; in a spectral domain, screening out a characteristic spectrum dimension combination with the highest discrimination degree between the wolfberry and other crops through a characteristic wave band optimization algorithm (such as vegetation index difference degree and red edge characteristics); and in combination with an object-oriented classification or deep learning classification model, constructing a space-time coupling classifier, and performing high-precision extraction and distribution mapping on the Chinese wolfberry planting region. The method can effectively solve the problem of confusion classification of Chinese wolfberry and similar ground features (such as other shrubs and orchards), and realizes rapid and accurate monitoring of Chinese wolfberry planting area and spatial distribution.

The invention provides an early warning method and system for greenhouse vegetable diseases and insect pests, and relates to the technical field of agricultural informationization. Environmental parameters and vegetable images are collected, a plant distribution network is established, and the propagation influence degree is calculated; analyzing an environmental suitability index of a pest propagation mechanism based on the environmental parameters; extracting disease features by using multi-source image fusion to determine an initial focus; calculating the propagation probability by combining the propagation influence degree and the environmental suitability degree, and constructing a dynamic propagation path prediction map; determining a prevention and control priority and generating partition early warning information; finally, relevant parameters are optimized according to the actual prevention and control effect, and accurate and timely disease and pest early warning is achieved.

The invention belongs to the technical field of crop growth monitoring and agricultural economy, and particularly relates to a crop production risk assessment method and system based on MODIS time series data and machine learning, and the method comprises the following steps: S1, obtaining MODIS time series data, crop planting distribution data, county-level crop per unit yield statistical data and an administrative division base map, s2, performing mask processing on the MODIS time series data and the crop planting distribution data to obtain an 8-day time series data set corresponding to crops, S3, calculating a per unit yield fluctuation rate, adopting a non-parametric weighted local linear regression method to eliminate a crop per unit yield trend to obtain per unit yield fluctuation data, and then calculating per unit yield fluctuation rates of county-divided crops, S4, constructing a model, and S5, constructing a model. The method includes the steps of S1, establishing a machine learning regression model based on the GPP data set and the LST data set in the step S2 and the unit yield fluctuation rate data in the step S3, S5, crop production risk assessment, and generating a grid-level crop unit yield loss result by utilizing the optimal model in the step S4 and combining an MODIS time sequence grid data set.

The application discloses a kind of quick assessment system and method of the influence of flood disaster on wetland ecosystem, and the system includes, animal image acquisition module, for obtaining animal image data;Animal behavior analysis module, for identifying animal behavior based on animal image data, to obtain animal behavior distribution map and animal behavior timetable;Plant remote sensing module, for obtaining wetland plant distribution map based on wetland remote sensing data;Flood data acquisition module, for obtaining water environment parameters when flood disaster occurs;Influence index evaluation module, for evaluating model to determine ecosystem influence index.The application integrates animal image acquisition and analysis, plant remote sensing identification, real-time acquisition of water environment parameters and other multi-source data, and constructs a unified influence index evaluation model, can quickly generate the comprehensive influence index of wetland animals and plants after flood disaster occurs, so that the assessment of disaster influence is timely and effective.

Embodiments of the present application provide a crop planting distribution plot identification method, device and equipment, wherein the method comprises: acquiring SAR time series data, high-resolution remote sensing image data and time series optical data corresponding to a measured area; determining a suspected crop planting area in the measured area based on the SAR time series data and in combination with the phenological characteristics of different crop planting sub-regions corresponding to the measured area; determining an agricultural planting plot from the measured area based on the high-resolution remote sensing image data; performing superimposition processing on a distribution map of the suspected crop planting area and a distribution map of the agricultural planting plot to obtain a suspected crop planting plot distribution map; and determining a crop planting distribution plot distribution map based on the suspected crop planting plot distribution map and the time series optical data.

This invention discloses a method and apparatus for fine extraction of aquatic vegetation and landscape connectivity assessment in rivers and lakes based on high-resolution remote sensing, belonging to the field of environmental remote sensing monitoring and water ecology assessment technology. It includes: acquiring and preprocessing high-resolution satellite imagery to obtain a standardized remote sensing image dataset; extracting water body masks and aquatic vegetation coverage areas through hierarchical threshold segmentation; constructing a dual-threshold discrimination rule based on the normalized vegetation index and soil-regulated vegetation index to finely divide the distribution areas of floating and submerged plants; constructing a binary raster map of vegetation distribution based on the distribution areas; combining a preset connectivity distance threshold; calculating the landscape connectivity index of vegetation patches based on graph theory; determining the ratio of equivalent connected area to effective connected area; and completing a comprehensive assessment of the ecological effectiveness of the aquatic vegetation community. This invention is mainly used for remote sensing monitoring of aquatic vegetation in urban rivers and lakes and for assessing the effectiveness of water ecology restoration, effectively mitigating spectral interference from complex water body sediment backgrounds.

The application is suitable for the field of agricultural monitoring technology, and particularly relates to a corn whole life cycle monitoring method and system based on air-ground cooperation, which comprises the following steps: outputting inferred stalk diameter and top plane coordinates through a UAV; obtaining measured stalk diameter and base plane coordinates through a ground robot; constructing a first plant distribution matrix and a second plant distribution matrix; matching the first plant distribution matrix with the second plant distribution matrix; and according to the matching result, associating the top monitoring data collected by the UAV with the side monitoring data collected by the ground robot to the same corn plant. Through the matching based on the relative position relationship between the plant stalk diameter and the group, the application overcomes the data misplacement problem caused by the positioning drift of the UAV and the ground robot, does not need to rely on expensive high-precision positioning equipment, provides a reliable data basis for planting decisions such as variable rate fertilization and precision pesticide spraying, and improves the accuracy of corn precision management.

The application discloses a natural solution-based ecological restoration method for salinized land in a semi-arid area, which comprises the following steps: S1, demarcating a plurality of ecological restoration areas; S2, planting plants; in each ecological restoration area, high-level plants are planted in a circle at the edge of the ecological restoration area, and medium-level plants and low-level plants are sequentially planted in circles towards the inside of the ecological restoration area; and S3, setting the ecological restoration area; the application can form an ecological restoration area with multi-level plant distribution, which is helpful to restore and improve biodiversity; through the setting of the first groove, the sand barrier and the spacing therebetween, the seeds of plants at various levels can be deposited in the first groove or nearby along with the wind in subsequent years to achieve the purpose of sowing and growth, multi-level plants along the first groove are formed, the ecological restoration effect is strengthened, subsequent sowing by using wind power is facilitated, and manual dense planting is not needed.

The invention relates to the field of agricultural robots, and discloses an autonomous navigation picking and sorting method and system for a blueberry picking and sorting robot, and the method comprises the steps: obtaining the plant distribution and space structure through an environment sensing module, generating a density self-adaptive path and a resource pre-distribution strategy through a global task planner, and carrying out the self-navigation picking and sorting of a blueberry picking and sorting robot; the picking module and the sorting module cooperatively work according to a strategy, the material caching and buffering module dynamically adjusts the rates of the two ends according to a load threshold value, and multi-mode feedback data drives a double-closed-loop PID algorithm to achieve millisecond rate synchronization. The system integrates a laser radar, stereoscopic vision and a near-infrared sensor, is equipped with a flexible clamping mechanical arm, a multi-stage screen sorting mechanism and a conical container cache module, and supports abnormal self-correction and multi-machine cooperative load redistribution. Through a dynamic coupling control framework, the working efficiency is improved, the fruit damage rate is reduced, and the system is guaranteed to continuously and stably run for more than 8 hours.

A method for classifying disturbing plants using drone orthophotos is disclosed, and the method for classifying disturbing plants using drone orthophotos may include: (a) forming a drone orthophoto in which a target area is shown during a preset period; and (b) determining a candidate object of a disturbing plant from the drone orthophoto as the disturbing plant.

The invention discloses a crop harvesting progress monitoring method and system, electronic equipment and a storage medium, and relates to the technical field of crop harvesting progress monitoring, and the method comprises the steps: obtaining a target region satellite image and the same-period agricultural machine track data; processing the crop planting distribution data to generate a mask pattern, and processing an image; carrying out cloud detection; generating a clustering result graph based on the cloud and the crop mask; agricultural machine track points are mapped to a clustering graph, the harvesting state is judged, and a classification result graph layer is generated; and counting the harvested and total planting areas based on the image layer and the crop mask, and calculating the progress percentage. The method introduces the same-period agricultural machine trajectory data to participate in determination, reduces the dependence on an artificial sample and a supervision model, and improves the generalization ability. In combination with multi-source data processing, timeliness is enhanced, day-by-day updating and automatic monitoring are supported, and a reliable basis is provided for agricultural management.

The invention discloses a model for exploring the influence of an environment on plant distribution and application. The plant refers to gentiana dahurica fisch. Based on geographical distribution of gentiana dahurica fisch and ecological factors influencing growth of gentiana dahurica fisch, which are determined by literatures and field investigation, an ecological suitable area of gentiana dahurica fisch is modeled by adopting an enhanced regression tree (BRT). And establishing a relationship between the content of each active component in the Inner Mongolia plant and an ecological factor by adopting a linear regression method. The invention discloses a model for exploring the influence of the environment on the distribution of gentiana dahurica fisch, and discusses the influence of the environment on the growth of gentiana dahurica fisch and the content of active ingredients. The model provides guidance for coordinated development of medicinal plant science.

The invention relates to the technical field of smart agriculture, and provides an unmanned aerial vehicle hyperspectral technology-based pecan tree species classification method, which comprises the following steps of: obtaining a hyperspectral image, and performing image cutting on the hyperspectral image to obtain a plurality of block images with specified sizes; analyzing a single hickory tree variety accurately, performing first feature extraction on the block image to obtain first feature information corresponding to the block image, and performing second feature extraction on the spatial feature to obtain second feature information corresponding to the spatial feature; feature information corresponding to the target is accurately collected through two times of feature extraction of different dimensions, the block images are classified based on the first feature information and the second feature information, classification information corresponding to the block images is obtained, and the classification information comprises pecan tree species information; based on the block images and the classification information, the pecan tree species classification image is obtained, an accurate pecan tree species classification result can be obtained, planting distribution of pecan tree species in the forest land is analyzed, and sustainable development of the forest land is promoted.

The utility model discloses a soybean planting hand -operated formula gyro wheel seed sowing machine belongs to soybean planting technical field, and its technical scheme main points include the main shaft, the middle part on the surface of main shaft is connected with the moving wheel through bearing rotation, the both ends of main shaft all are provided with seeding assembly, the back of seeding assembly is provided with the earthing component, through setting seeding assembly, seeding assembly adopts the design of the cooperation seed groove of carousel, can ensure every time seed falling is single or preset quantity, effectively avoids the phenomenon of missing sowing, and the phenomenon of sowing again, and precision control sowing interval and density make soybean plant distribution even, improve the uniformity of emergence rate and crop growth, through setting earthing component, earthing component can realize the flexible adjustment of earthing plate height, can accurate matching soybean seed's best earthing depth requirement, ensure that seed obtains suitable covering thickness, significantly promotes seed emergence rate and seedling survival rate.

The invention discloses a soil heavy metal pollution detection method and system based on a remote sensing image, and relates to the technical field of heavy metal pollution detection.The method comprises the steps that spectral data of current soil are obtained through the remote sensing image technology, and soil information and plant information during historical detection are obtained from a database; analyzing the relation between the soil detection spectrum data and the actual spectrum data and plant distribution and the relation between the content of each heavy metal and the effective content of each heavy metal, obtaining the effective content of each heavy metal in the current soil, and obtaining the threshold value of the effective content of each heavy metal in the soil from the database; meanwhile, the heavy metal content threshold values of various plants under different soil parameter characteristics and purposes are analyzed, whether the current soil is polluted by heavy metal or not is judged, early warning is conducted when the soil is polluted by heavy metal, and the effectiveness of soil heavy metal pollution monitoring is guaranteed; and the accuracy of heavy metal content monitoring and soil heavy metal pollution analysis is ensured.

The invention provides a near-natural plant community construction method of an engineering slope. The method comprises the steps that the annual precipitation of an area where a to-be-planted land is located and different types of slope parameters are obtained, and the effective precipitation of each type of slope is calculated; taking the effective precipitation of each type of slope as a condition, establishing a region library according to a moisture condition region similar to the to-be-built planting land, and screening and determining at least one typical region; investigating and analyzing plant distribution communities of various types of slopes in the typical area, and determining colonization species and associated species of the plant distribution communities according to importance and availability of each species; and respectively calculating slope surface wettability indexes of the to-be-planted land and various types of slopes in the typical area, and evaluating the suitability of the colonies and the associated species to the to-be-planted land according to the slope surface wettability indexes so as to construct a near-natural plant community of the engineering slope. According to the scheme, reasonable construction of the slope natural plant community of the to-be-built planting land can be realized.

This invention relates to an automated monitoring method for the dynamic changes of plant diversity in mountainous forest areas, comprising: constructing a three-dimensional model of the target mountainous area and deploying a sensor network; collecting microclimate data and soil characteristic data to determine a spatial distribution matrix; acquiring historical plant distribution data of the target mountainous area, mapping it to the spatial distribution matrix to construct a comprehensive distribution map of environmental factors, and determining a correlation model between plant distribution and environmental factors; acquiring real-time satellite remote sensing image data of the target mountainous area, using the correlation model to analyze the characteristics of changes in plant cover and plant diversity distribution, and locating several key plant distribution areas; identifying plant species and counting their numbers in the key plant distribution areas, updating the comprehensive distribution map of environmental factors, and completing the automated monitoring of the dynamic changes of plant diversity in the target mountainous area. This invention integrates multi-source environmental data to achieve automated analysis of plant diversity distribution.

The present application relates to the water ecological restoration technical field, specifically to a kind of detection device and application method for assisting submersed plant recovery, including working system, for water navigation, carry information acquisition system, sampling system, store and transport collected water quality, sediment sample;Information acquisition system is used to obtain point coordinate information, water depth, flow rate, transparency and shoot underwater submersed plant and sediment image;Sampling system is used to simultaneously carry out water quality, sediment sample collection;Information receiving and processing terminal is used to receive the information of information acquisition system, and process underwater image, analysis obtains submersed plant species, coverage, biomass level grade and sediment category and pollution degree grade information, then comprehensive discriminant analysis is carried out.The present application can simultaneously obtain the hydrology of water body, sediment characteristics and submersed plant distribution characteristics, and simultaneously monitor water quality and other indicators of sediment, and assist system to identify submersed plant suitable recovery area, avoid the risk of blindly carrying out large-scale submersed plant restoration investment.

The utility model discloses an irrigation device for landscaping construction, which comprises a base, a water tank and a frame are mounted at the upper end of the base, a mounting frame is slidably connected in the frame, a water spray pipe is rotatably connected in the mounting frame, one end of the water spray pipe is communicated with the water tank through a connecting pipe, and an electric telescopic rod is rotatably connected in the mounting frame. And the inserting rods penetrate through the telescopic ends of the side plates and extend to the other side plate, and a driving assembly for driving the mounting frame to slide is mounted in the frame. The servo motor drives the threaded rod to adjust the height of the water spraying pipe, the electric telescopic rod adjusts the angle of the water spraying pipe, irrigation requirements of complex terrains such as slopes and flower beds can be flexibly met, and the height and the angle of the water spraying pipe can be accurately adjusted according to the terrains and plant distribution. The problems that a traditional irrigation device accumulates water at a high position and is dry at a low position are solved, uniform distribution and efficient utilization of water resources are achieved, and the irrigation effect is remarkably improved.

The invention discloses a forest health environment evaluation and analysis system, and belongs to the field of environment evaluation and analysis systems. Comprising an animal buzzing data acquisition module, a plant distribution data acquisition module, a facility service acquisition module, an environment quality acquisition module, a data receiving module, a data analysis module, a preset data import module, an evaluation module and an early warning notification module. The animal chirp data acquisition module is used for acquiring chirp data of animals in a target forest and sending the acquired animal chirp data to the data receiving module; the plant distribution data acquisition module is used for acquiring distribution data of plants in a target forest; the facility service acquisition module is used for acquiring the operation state of facilities in a target forest and the online scores of catering accommodation stores within three kilometers of the target forest. According to the method and the device, the chirp of the animal can be put into evaluation and analysis, so that an evaluation and analysis result is more accurate and comprehensive.

The utility model relates to a drip irrigation device for agricultural planting and cultivation, which comprises a plurality of water collecting mechanisms, adjacent water collecting mechanisms are connected through a connecting pipe, one of the water collecting mechanisms is connected with a water pump through a connecting pipe, the water collecting mechanism comprises a box body, a water collecting tank is arranged on the top side of the box body, and a water inlet is arranged at the bottom of the water collecting tank; according to actual plant distribution and planting density, a plurality of water collecting mechanisms and a plurality of drip irrigation branch pipes are arranged to be combined and matched for use, drip irrigation is guaranteed, meanwhile, water resources are saved, a box body of each water collecting mechanism is divided into a water storage cavity and a drip irrigation cavity, rainwater can be conveniently collected and stored through the water storage cavities, and during irrigation, the rainwater can be conveniently collected and stored through the drip irrigation cavities. Communication between the water storage cavity and the drip irrigation cavity is achieved through the electromagnetic valve, water resources are fully utilized, and the solar panel is used for charging for the device to use.

The utility model discloses a water-saving type spray pipe structure, which relates to the technical field of spray pipes, and comprises spray pipes, outer pipes, annular air bag sealing bodies and metal hoses, the adjacent spray pipes are connected through the metal hoses, various types of spray heads are linearly arranged and circumferentially distributed on the spray pipes along the pipe body direction, the rotatable outer pipes are arranged outside the spray pipes, and water spray ports are arranged on the outer pipes. The outer pipe is rotated to adjust the water injection nozzle to align to the nozzles in different directions so as to change the water injection direction, meanwhile, the annular air bag sealing body is arranged between the outer pipe and the spray pipe and cooperates with the suction assembly to inflate or exhaust air, a non-target nozzle can be blocked, water injection accuracy is guaranteed, water resource waste is avoided, in addition, the spray pipes are connected through the metal hose, the position can be flexibly adjusted, and use is convenient. The structure is remarkable in water-saving effect, wide in application prospect in the field of irrigation and the like, capable of effectively reducing waste of water resources and improving sprinkling irrigation efficiency, easy and convenient to operate and suitable for various complex terrains and plant layouts.

The present application relates to the technical field of ecological restoration, and discloses a submerged plant distribution scheme determination method and device, computer equipment and a medium. The method is based on environmental information of a target water area and environmental parameters of different types of submerged plants in the target water area to solve a submerged plant distribution probability model, obtain a first distribution probability of each type of submerged plant, and determine a distribution scheme of different types of submerged plants in the target water area based on the first distribution probability corresponding to each type of submerged plant. The method provided by the present application considers the adaptability of different types of submerged plants to the environment of the target water area when determining the distribution scheme of the submerged plants in the target water area. Based on the obtained distribution scheme, the submerged plants can be planted in the target water area, which can make the distribution of the submerged plants more adaptive to the environment of the target water area, effectively reduce the dramatic succession of the submerged plant community in the ecological restoration project, and make the water ecological restoration more natural and long-acting.

The invention is suitable for the technical field of agricultural monitoring, and particularly relates to a corn full life cycle monitoring method and system based on air-ground cooperation, and the method comprises the steps: deducing the diameter of a stalk and the plane coordinates of the top through the output of an unmanned aerial vehicle; the actually-measured stalk diameter and the base plane coordinates of the stalk diameter are obtained through the ground robot; constructing a first plant distribution matrix and a second plant distribution matrix; matching the first plant distribution matrix with the second plant distribution matrix; and according to a matching result, associating the top monitoring data acquired by the unmanned aerial vehicle and the side monitoring data acquired by the ground robot to the same corn plant. According to the method, the problem of data dislocation caused by positioning drifting of the unmanned aerial vehicle and the ground robot is solved based on matching of the relative position relation of the plant stalk diameter and the group, expensive high-precision positioning equipment does not need to be relied on, a reliable data basis is provided for planting decisions such as variable fertilization and precise pesticide spraying, and the method is suitable for large-scale popularization and application. And the accuracy of accurate corn management is improved.

The application relates to the field of agricultural robots and discloses a blueberry picking and sorting robot autonomous navigation picking and sorting method and system, wherein the plant distribution and spatial structure are acquired through an environment perception module, a density self-adaptive path and a resource pre-allocation strategy are generated by a global task planner, a picking and sorting module cooperates according to the strategy, a material buffer module dynamically adjusts the two end rates according to a load threshold, and a multi-mode feedback data driven double closed loop PID algorithm realizes millisecond level rate synchronization. The system integrates a laser radar, a stereo vision and a near infrared sensor, is equipped with a flexible clamping mechanical arm, a multi-stage screen sorting mechanism and a conical container buffer module, supports abnormal self-correction and multi-machine cooperative load redistribution. Through a dynamic coupling control architecture, the application improves the working efficiency, reduces the fruit damage rate and guarantees the continuous stable operation of the system for more than 8 hours.

The utility model relates to a movable garden maintenance drip irrigation frame which comprises at least one supporting frame and two transverse plates. The two transverse plates are both transversely installed in the supporting frame, and four walking wheels are rotationally connected to the bottom of the supporting frame. A pipeline assembly is mounted below the transverse plate and is used for carrying out drip irrigation treatment on plants; a locking assembly is arranged on the transverse plate and used for locking and fixing a pipeline assembly and the transverse plate. According to the movable garden maintenance drip irrigation frame, the walking wheels are installed at the bottom of the supporting frame, so that the drip irrigation frame can easily move in a garden, the drip irrigation position can be conveniently adjusted in time according to garden layout changes and plant growth requirements, and a water guide pipe is connected with water guide pipes of other drip irrigation frames through threaded sleeves and external threads; a plurality of drip irrigation frames can be flexibly combined according to the actual irrigation area and the plant distribution condition, the irrigation range is expanded, the applicability of the drip irrigation system is improved, and the irrigation requirements of different garden scenes are met.

The invention relates to a collaborative recognition method and device for soybeans and peanuts in seasons, and belongs to the technical field of agricultural remote sensing. According to the method, through ingenious design of a three-dimensional coupling coordination degree and a crop canopy coverage index, a large-scale soybean and peanut sample generation module is constructed, a leguminous crop collaborative identification technology process is established, and a multi-year leguminous crop after-season distribution result is obtained. A soybean and peanut distribution reasoning model based on space-time perception is designed, multi-year stable training samples and feature intervals of soybeans and peanuts are obtained in combination with multi-year post-season distribution results of leguminous crops, and a historical knowledge constrained soybean and peanut intra-season collaborative recognition method is constructed. The method has interpretability and large-scale cross-domain migration capability, and a technical method and device are provided for obtaining large-scale and high-precision soybean and peanut planting distribution information in a high-time-efficiency manner.

The invention discloses a waxberry yield analysis method and device based on remote sensing data and a medium, and relates to the technical field of remote sensing and image processing, and the method comprises the steps: obtaining multi-source data, preprocessing the multi-source data, segmenting the preprocessed multi-source data, and determining a plurality of tree samples according to the segmented multi-source data; sending the plurality of tree samples to a preset deep learning model, performing model training through the deep learning model to obtain an identification model, and performing tree identification through the identification model to determine a planting distribution vector pattern spot; performing matrix calculation according to the planting distribution vector pattern spots to determine precision data, and determining planting area distribution data according to the precision data; the net primary productivity of the waxberries is determined, and the yield of the waxberries is determined according to the net primary productivity and the planting area distribution data. The multi-source data processing flow is complete, deep learning and accurate recognition are combined, and the waxberry yield can be scientifically determined.