32 results about "Urban forest" patented technology

The invention discloses a multi-source collaborative checking system and method for the real quantity of natural resource assets, and relates to the technical field of natural resource management. The system comprises a data acquisition module used for acquiring multi-source data and real-time data and preprocessing the multi-source data and the real-time data; the knowledge graph processing module is used for constructing a forest resource knowledge graph according to the multi-source data and the real-time data; and the check analysis module is used for constructing an intelligent check model based on the knowledge graph constructed by the knowledge graph processing module. By automatically collecting and preprocessing multi-source data, constructing and dynamically maintaining a knowledge graph, and intelligently checking and analyzing and visually presenting a result based on the graph, efficient data integration, accurate and intelligent checking, trend prediction and active early warning are realized, and a scientific decision basis is provided for urban forest resource management.

The invention relates to a high-precision single tree segmentation method based on multi-source point cloud data, and the method comprises the steps: building a high-density point cloud data set through the cooperative collection of an unmanned plane and a knapsack laser radar, carrying out the data preprocessing through the multi-site ICP registration and CSF filtering, carrying out the semantic segmentation based on an Enhanced Tree Instance Net network, and carrying out the segmentation of a single tree. Through feature contribution analysis and dynamic scene adaptive optimization segmentation data, semantic and geometric features are fused to realize individual tree instance segmentation, a physical constraint neural network is introduced to realize multi-parameter collaborative inversion of tree height, diameter at breast height, crown breadth, tree age and the like, it is ensured that the parameters conform to tree growth rules, precision evaluation and calibration are performed through a multi-level index system, and tree growth accuracy is improved. And finally realizing visual expression of a segmentation result and forest stand parameters. According to the method, the individual tree segmentation precision and the growth rule rationality are remarkably improved, and the method is suitable for urban forest carbon sink accurate measurement and intelligent forestry management.

The invention is suitable for the technical field of forest assessment methods, and provides an urban forest community carbon reserve assessment method and system based on multi-source data, and the method comprises the steps: obtaining research region information; the method comprises the following steps of: obtaining a geometrical relationship between an orientation in a panoramic image and a point cloud center direction after equipment installation, generating individual tree data units according to a relationship model, and binding the individual tree data units with unique numbers; extracting contour features of image areas corresponding to the individual tree data units, identifying whether the contour features have contradictions, performing secondary stripping on abnormal contours to obtain final individual tree data units, and performing species classification according to the final individual tree data units; a structure weighting factor is constructed by combining the area of the sample plot, a corresponding grade is judged according to the total carbon storage value of the whole sample plot, a theoretical carbon storage upper limit is calculated, the relative deviation rate of the current carbon storage is calculated according to the theoretical carbon storage upper limit and the total carbon storage value of the sample plot, and the method has the advantages that structure expression is refined, model matching is flexible, and the distinguishable grade of an evaluation result can be improved.

The invention provides a regional carbon sink monitoring method and device based on an urban forest, and belongs to the technical field of carbon sink monitoring, and the method comprises the steps: obtaining the vegetation spectrum information and ground image data of the urban forest collected by a space-based satellite monitoring end, generating a vegetation map of the urban forest based on the vegetation spectrum information and the ground image data, and dividing a carbon sink monitoring area based on a vegetation map of the urban forest. And performing multi-source data monitoring on the carbon sink monitoring area, and determining biomass information of the carbon sink monitoring area based on the monitored multi-source data. And determining target carbon sink data of the carbon sink monitoring area based on the biomass information. According to the regional carbon sink monitoring method and device based on the urban forest provided by the invention, the problems that the monitoring data acquired by the existing carbon sink monitoring means for the urban forest is not comprehensive enough and the accuracy of the carbon sink data is low can be solved.

The present application discloses a GNSS positioning solution method and device based on factor graph optimization, which belongs to the field of satellite navigation technology, including: obtaining GNSS measurement values ​​and performing preliminary processing on the measurement values; constructing a robustness model for state estimation based on the factor graph in combination with the switching factor according to the maximum a posteriori probability estimation theory; then determining the state quantity to be solved according to the measurement value, and establishing a motion model of the receiver; establishing a cost function based on the measurement principle and motion model corresponding to the measurement value; finally, establishing an objective function in combination with the robustness model and the cost function, and according to the objective function, solving the state quantity to be solved by the sliding window idea to obtain the positioning result of the receiver. The GNSS positioning solution method and device provided by the present application effectively improve the accuracy of single-point positioning and carrier phase differential positioning in satellite positioning application scenarios under poor satellite reception conditions, and can be applied to application scenarios with poor satellite reception such as cities and forests.

This application discloses a method for systematically monitoring and evaluating the structural and functional diversity of urban forest stands. It identifies the plant type by analyzing the ratio of leaf to leaf root length among different plants, combined with pigment information of plants of the same type. The ratio of leaf to leaf root length is a prominent feature of plant leaves, and identifying this feature through binarized images is fast and accurate. However, identifying plant types solely based on the ratio of leaf to leaf root length or plant pigment information can lead to low accuracy because some plants have similar ratios, and different plants may have similar pigment information. This application combines these two features, using the ratio of leaf to leaf root length and plant pigment information to comprehensively determine the plant type, thus greatly improving the comprehensiveness of the features and increasing the accuracy of identification.

The invention relates to an urban forest resource monitoring system and method based on multi-source remote sensing fusion, and the system constructs a sound-vibration cooperative control and edge intelligent processing dual-core system architecture, collects the remote sensing data of an urban complex operation environment in a high-quality manner, achieves the total-factor centimeter-level perception and robust obstacle avoidance of the urban forest complex environment, and achieves the real-time monitoring of the urban forest complex environment. And the operation safety and the data integrity are ensured. On the basis of interpretable AI and multi-modal fusion knowledge acquisition, scale pushing from a single tree to a forest stand is implemented, high-precision intelligent analysis of forest stand scale parameters is completed, and automatic and quantitative inversion of forest stand scale key parameters is realized at an airborne edge end. According to the system, key stand structure factors such as stand density, canopy density, average height and variation coefficient are automatically calculated by aggregating individual tree detection results, single-machine intelligence and group cooperation are realized, and large-scale and high-efficiency urban forest resource checking and dynamic monitoring can be realized.

According to the urban forest space fine particulate matter concentration assessment method and system disclosed by the invention, the mobile monitoring equipment is arranged in different areas of an urban forest, so that fine particulate matter concentration data of each area can be obtained in real time; meanwhile, a more comprehensive and detailed data set can be formed by combining data of a fixed-point monitoring station, so that the distribution condition of the fine particulate matter concentration in the urban forest space can be reflected more accurately; by setting the fine particulate matter concentration warning threshold value, the management end is reminded to take corresponding measures in time, and the ecological safety of urban forests and the health of citizens are effectively guaranteed.

The invention relates to an urban forest cooling function baseline construction and attenuation recovery evaluation method and system. The method comprises the following steps: acquiring day-by-day meteorological data of a research area to identify starting and ending dates of an extreme high temperature event; acquiring urban forest coverage distribution information in the research area and near-surface air temperature data or surface temperature data in a first date range, and calculating urban forest cooling efficiency data of each date in the first date range; calculating statistical characteristics of the urban forest cooling efficiency data of all dates of the beforehand reference period; determining the maximum attenuation value and date of the cooling efficiency during the extreme high-temperature event; and calculating the statistical characteristics of the urban forest cooling efficiency data of each sliding window by using the sliding windows, and calculating the recovery time and rate of urban forest cooling efficiency attenuation according to the baseline and a preset discrimination condition. It is ensured that attenuation is caused by the extreme high-temperature event, and the attenuation degree and the recovery process of the cooling function under the influence of the extreme high-temperature event are quantified.

The invention discloses a prediction method for simulating overground biomass different-speed growth of an urban forest, which integrates airborne laser radar of an unmanned aerial vehicle and airborne multispectral data of the unmanned aerial vehicle and comprises the following steps: extracting six types of structural parameters including canopy height, coverage and openness, heterogeneity, stand density, three-dimensional volume and physiological characteristics of the urban forest; a structural diversity parameter set for predicting the above-ground biomass of the urban forest is formed, a power law model for estimating the above-ground biomass is constructed on the basis of the different-speed growth relation of the structural diversity of the urban forest, and then all combinations of optimal parameters are tested through a nonlinear least square method and a forward step-by-step selection method. And determining an optimal model for estimating the above-ground biomass of the urban forest and realizing above-ground biomass prediction. The method is used for solving the problem of overfitting when a traditional linear model and a machine learning model are used for estimating the above-ground biomass of the urban forest, and solving the problem of predicting the above-ground biomass of the urban forest with continuous space.

This invention discloses a method and temperature monitoring system for assessing the intensity and stability of cooling in urban forests. The method includes: collecting basic forest data in various local climate types; calibrating the spatial distribution of temperature data across multiple time periods based on parameter calibration data and temperature monitoring data; calculating the intensity and stability of the cooling effect of urban forests based on urban forest attribute data and calibrated temperature monitoring data; standardizing the intensity and stability of the cooling effect of urban forests; analyzing the driving mechanisms that cause the intensity and stability of the forest cooling effect; and constructing a spatial distribution map of urban vulnerable forest patches. Based on the spatial distribution map of urban vulnerable forest patches, optimization schemes for urban forests in different local climate zones are formulated. This invention proposes differentiated tree species configuration, structural optimization, and spatial transformation schemes for different local climate zones and synergistic types, achieving synergistic maximization of cooling benefits with limited resources.

The utility model belongs to the field of bionic hives, particularly relates to a bionic habitat building hive for an urban forest park, and aims to solve the problems that faeces, food residues and the like of nestlings exist in the existing hive, bacteria and parasites are easy to breed, health of the nestlings is not facilitated, the hive is generally integrated, the interior of the hive is inconvenient to clean, and the hive is inconvenient to clean. According to the technical scheme, the nest box comprises a box body, a nest opening allowing the birds to enter conveniently is formed in the front side of the box body, two supporting columns are fixedly connected to the top of the box body, and a shielding plate is fixedly connected to the tops of the two supporting columns; the rear side of the box body is fixedly connected with the mounting plate facilitating mounting of the box body, and the mounting plate is provided with the mounting holes facilitating mounting, so that the interior of the box body can be conveniently and quickly cleaned, the whole nest box does not need to be disassembled, time and energy are saved, and subsequent use of the nest box by birds is facilitated.

The urban forest garden residence comprises a building, each floor is provided with a core tube, the living rooms and a hanging garden, restaurants are arranged in a stacked mode in the vertical direction, the living rooms on the odd-numbered floors are horizontally communicated with the restaurants, the living rooms on the even-numbered floors are vertically communicated with the restaurants, and the living rooms on the odd-numbered floors are horizontally communicated with the restaurants. The living rooms on the odd-numbered floors and the living rooms on the even-numbered floors are vertically staggered in an L shape on the whole on the horizontal projection, each living room is provided with a plurality of outer wall surfaces, the dining room is of a natural floor height, one outer wall surface is provided with a door and window, the living room is of two natural floor heights, and the two outer wall surfaces are provided with three doors and windows. The doors and windows can achieve lighting and ventilation, the living room is good in lighting and ventilation, at least one door and window of the living room faces the south, no structural beam is arranged in the middle of the living room, the hanging garden is provided with three continuous open faces, one open face faces the south, and the living room and the hanging garden are good in sunshine.

The invention relates to the technical field of forestry remote sensing, in particular to a single-plant crown segmentation method based on a remote sensing image. Tree RGB images are collected through remote sensing images, three data sets of man-made forests, urban forests and natural forests are created, and data are preprocessed at the same time, including the steps of data enhancement, noise removal, image distortion correction, image size and color space unification and the like; a deep neural network TCSRCNN is used for training; and deploying the optimal model in an actual application scene, and performing automatic segmentation of the single-tree crown on a new remote sensing image. According to the method, the irregular edges of the crowns can be accurately segmented, and the problems of adhesion between single-tree crowns, insufficient generalization ability of the algorithm and the like are effectively solved. Accurate data support is provided for forest resource monitoring, and powerful technical support is provided for the fields of ecological environment assessment, forestry planning and management and the like.

The invention provides an urban evergreen forest and fallen leaf forest extraction method, which comprises the following steps of: obtaining image blocks in two seasons of late winter and early summer, and forming a data set I by all the image blocks in the two seasons; each image block comprises an urban forest land parcel and a non-urban forest land parcel; creating a label value of a non-urban forest land parcel; based on the trained random forest model, acquiring respective pseudo label data of the evergreen forest and the deciduous forest corresponding to the data set I; the label values of the non-urban forest land parcels and the label values corresponding to the pseudo label data of the evergreen forest and the deciduous forest form a data set III; training a deep learning model based on the data set I and the data set III; and based on the trained deep learning model, obtaining a probability graph of the urban evergreen forest and the deciduous forest. According to the method, the drawing precision of urban evergreen forest and deciduous forest distribution is improved.

The present invention is applicable to the technical field of forest assessment methods, and provides an urban forest community carbon storage assessment method and system based on multi-source data to obtain research area information; after the equipment is installed, the geometric relationship between the position in the panoramic image and the center direction of the point cloud is obtained, a single tree data unit is generated according to the relationship model, and the single tree data unit is bound to a unique number; the contour features of the image area corresponding to the single tree data unit are extracted, and whether there are contradictions in the contour features, the abnormal contours are secondary peeled off to obtain the final single tree data unit, and species classification is performed based on the final single tree data unit; a structural weighting factor is constructed in combination with the area of ​​the sample plot, the corresponding level is determined according to the total carbon storage value of the entire sample plot, the theoretical carbon storage upper limit is calculated, and the relative deviation rate of the current carbon storage is calculated according to the theoretical carbon storage upper limit and the total carbon storage value of the sample plot. The method has the advantages of refined structural expression, flexible model matching, and the ability to judge and improve the assessment results.

The present application belongs to the field of pollution reduction and carbon reduction evaluation, and in particular to an evaluation method for the synergistic effect of urban forest pollution reduction and carbon reduction; Based on the data calculated by dividing each region, the chart drawn is more intuitive to reflect the synergistic effect of pollution reduction and carbon reduction in each region, providing data support for the evaluation group to evaluate the overall synergistic effect of pollution reduction and carbon reduction of urban forest, so that in the case that the evaluation group is limited in manpower and material resources and cannot fully monitor and obtain data of the entire urban forest, the synergistic effect of pollution reduction and carbon reduction of the urban forest coverage area can be efficiently evaluated, and data support is also provided for subsequent urban planning schemes such as green area planning of each region, energy saving and emission reduction plan of factory, traffic arrangement, etc.

The invention discloses a forest carbon sink parameter time sequence product generation method, system and device and a storage medium, and is applied to the cross technical field of vegetation remote sensing and carbon cycle monitoring, and the method comprises the steps: obtaining multi-source data of a target region, and generating a vegetation index based on remote sensing data in the multi-source data; based on the vegetation index, constructing a nonlinear model for different forest types, and performing inversion to obtain a corresponding net primary productivity initial time sequence; performing type-oriented differential purification treatment on the initial time sequence of the net primary productivity; feature difference identification is carried out based on the purified time sequence, and the nonlinear model is optimized according to an identification result; generating a net primary productivity time sequence product through the optimized model; according to the method, the problems of mechanism mismatching and information loss when a traditional single model processes heterogeneous forest types are solved, and a high-credibility time sequence parameter product basis is provided for urban forest carbon sink accurate monitoring, operation and management policy making and carbon trading market support.

The invention relates to an urban vehicle-mounted point cloud forest tree classification method based on RoPE operator local feature aggregation, and belongs to the technical field of photogrammetry and remote sensing. According to the method, the ROPE operator technology is adopted, the relative coordinates and the original features of all points in the neighborhood are coded to establish the weight relation, a model is helped to distinguish the fine features of the trunk, the coding operator is utilized to carry out secondary local feature dynamic aggregation, the local structure and context information of the forest are captured, and the problem that the classification precision of the trunk and the shielding forest is low is solved; meanwhile, a U-shaped encoder-decoder network architecture and a jump connection strategy are introduced, forest features are fused among different levels, and multi-scale forest information is obtained. Compared with other methods, the method can solve the problem that tree classification errors of tree trunks and shelters often occur in urban tree classification, and realizes accurate segmentation of complete tree information in a complex urban scene.

The invention relates to an urban forest garden residence with a living room with three lighting directions, the residence is provided with the living room, a rest area, an activity area and a hanging garden, and the rest area, the activity area and the hanging garden are arranged around the living room; compared with the prior art, the living rooms on the odd-numbered floors and the living rooms on the even-numbered floors are each provided with a lighting wall face in three directions, the lighting wall faces are each provided with a lighting door and window, and the lighting doors and windows are arranged on the lighting wall faces in the three directions, so that the living rooms on the odd-numbered floors and the living rooms on the even-numbered floors are not prone to falling off. The living rooms on the odd-numbered floors and the living rooms on the even-numbered floors are provided with lighting doors and windows in three directions, the hanging garden and the outer end rest area do not interfere with each other, the hanging garden and the sleeve type of the upper floor do not interfere with each other, the hanging gardens do not interfere with each other, and safety and privacy are high. The living rooms of the first cover type, the second cover type, the third cover type and the fourth cover type are good in sunshine and lighting.

1. The name of this design product: Urban Forest Garden Building (End Hall). 2. Purpose of this design product: used as a building. 3. The design key point of this appearance design product lies in the shape. 4. The picture or photo that best illustrates the design points: Stereoscopic diagram 4. 5. The bottom view of this design product is a part that is difficult to see or cannot be seen when in use, so the bottom view is omitted.

The invention provides an urban forest extraction method. The method comprises the following steps: step 1, preprocessing data; step 2, finding a city boundary in the data image, then selecting a forest sample plot in the city boundary, segmenting the data into image blocks with the same size, and forming a data set I by all the image blocks; each image block comprises an urban forest land parcel and a non-urban forest land parcel; step 3, creating a label image corresponding to each image block through visual interpretation, wherein the label image comprises a polygonal region of the urban forest land parcel and a polygonal region of a non-urban forest land parcel; all label images form a data set II; 4, establishing an artificial intelligence model; 5, training an artificial intelligence model based on the data set I and the data set II; step 6, obtaining an urban forest plot probability graph; and step 7, obtaining the area occupied by the urban forest land parcel. According to the invention, the precision of urban forest extraction is improved.

The invention provides a screening method for improving the multifunctionality of urban forest tree species based on functional traits, and the method comprises the following steps: determining representative tree species of urban forests, measuring the functional traits of plants of each tree species, measuring the ecological functions of each tree species, standardizing the measured data, calculating and quantifying the multifunctionality of each tree species, optimizing, screening and predicting the optimal character combination of the tree variety multifunctionality, and determining the character combination threshold value for improving the tree variety multifunctionality. The method provided by the invention can effectively evaluate and improve the ecological function of the urban forest tree species based on the plant functional traits, and is of great significance to urban forestry scientific research and practical guidance under the background of climate change.

The invention relates to an urban forest garden residence with two hanging gardens, the sleeve type of the urban forest garden residence comprises an activity area, a home-entry rest area, an outer-end rest area and the hanging gardens, and the home-entry rest area, the outer-end rest area and the hanging gardens are arranged around the activity area. Compared with the prior art, the outer end rest area and the activity area are symmetrically arranged in an inverted-T shape and form two parallel L-shaped notches, the activity area is provided with outer wall faces in four directions, and the sleeve type of the odd-numbered floors and the sleeve type of the even-numbered floors are each provided with two hanging gardens in different directions. The moving areas of the odd-numbered floors and the moving areas of the even-numbered floors are each provided with two lighting doors and windows in different directions, the hanging gardens and the outer end rest areas do not interfere with each other, the hanging gardens and the sleeve type of the upper floor do not interfere with each other, the hanging gardens do not interfere with each other, and safety and privacy are high.

1. Name of the Design Product: Urban Forest Garden Building (Cross-shaped). 2. Use of the Design Product: Used as a building. 3. Design Key Points of the Design Product: Lies in the shape. 4. Picture or Photograph that Best Illustrates the Design Key Points: Perspective View 3. 5. The bottom view of the Design Product is a part that is not easily seen or not seen during use, so the bottom view is omitted.

The application provides a kind of urban forest carbon sink measurement method and system based on remote sensing image and machine learning, comprising: collecting remote sensing image of forest to be estimated in urban area;The collected remote sensing image is preprocessed to form multi-band remote sensing image data;Based on the multi-band remote sensing image data, the vegetation index under different bands is constructed, the correlation and importance of the vegetation index under different bands are analyzed, and the vegetation index under the optimal band is obtained;Based on the vegetation index under the optimal band, a leaf chlorophyll content estimation model of urban forest is constructed by combining a machine learning method;Obtain the vegetation stand factor and meteorological factor in each sample area;Based on the estimated leaf chlorophyll content, vegetation stand factor and meteorological factor, an urban forest carbon sink measurement model is constructed by combining a machine learning model.The application realizes small-scale urban forest carbon sink measurement with high precision, high intelligence and strong applicability based on remote sensing image and machine learning model.

The invention provides an intelligent identification method and system for tree species of an urban forest, and relates to the technical field of image processing, and the method comprises the steps: carrying out the preprocessing of original hyperspectral image data and original inclined image data; performing characteristic wave band extraction on the target hyperspectral image data through a minimum noise separation algorithm to obtain characteristic wave band extraction data; performing vegetation extraction on the target hyperspectral image data according to the characteristic wave band extraction data to obtain a vegetation mask; according to an urban forest canopy height model, through a multi-scale segmentation algorithm, single tree segmentation is carried out on tree species in the target oblique photography image data; a tree species intelligent identification model based on a double-flow HybrdSN network is constructed; using the training data set to train the tree species intelligent identification model; and inputting the to-be-identified hyperspectral image data and the to-be-identified oblique photography image data into the trained tree species intelligent identification model for intelligent identification, and outputting an identification result of the tree species of the urban forest.

A current situation evaluation and prediction method for urban forest vegetation carbon reserves comprises the steps of obtaining global built-up area data, administrative division data of a target city, remote sensing image data of land coverage over the years, actually measured meteorological data over the years and monthly average prediction data of future meteorology, performing preprocessing, extracting a built-up area range of the target city, and performing prediction on the built-up area range of the target city; generating a forest vegetation coverage distribution map, and calculating total newly-added forest vegetation data Sum (m, j) in a built-up area range; based on the actually measured meteorological data over the years, calculating the biomass Bt of a newly added forest vegetation coverage range in a built-up area range; and constructing a carbon sequestration process model, calculating the total newly-added forest vegetation carbon density Cdensity (m, j) in the built-up area range, and obtaining the current situation and prediction data of the total newly-added forest vegetation carbon reserve Cstore (m, a) in the built-up area range. According to the method, the current situation evaluation and prediction are performed on the carbon reserve of the target city by integrating the processes of land cover change and growth mechanism over the years, and the dynamic evaluation and prediction of the carbon reserve of the newly-added urban forest are realized.

The invention discloses a device and a method for collecting and determining volatile organic compounds in atmosphere, and relates to the technical field of atmosphere component determination, the technical key point is that the method comprises the following steps: connecting a micro-extraction head adapter pipe with an atmosphere sampler, setting sampling flow and time, dynamically exposing adsorption fibers to capture VOCs, and determining the volatile organic compounds in the atmosphere. Desorbing for 5 minutes at the temperature of 250 DEG C through a gas chromatograph-mass spectrometer, and completing detection by combining helium carrier gas and a DB-1MS capillary column; the device comprises a micro-extraction head adapter tube, an atmosphere sampling instrument and a GC-MS, the adapter tube is made of an inert polymer material, an adapter opening can fix micro-extraction head suites of different specifications, and rapid replacement is supported. By optimizing dynamic sampling control and GC-MS detection conditions, the method solves the problem of unstable sampling in the open environment of the traditional SPME technology, has the advantages of high sensitivity, low cost, convenience in operation and the like, and is suitable for efficiently monitoring VOCs in open environments such as cities, forests, industrial areas and the like.