13 results about "Urban forest" patented technology

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 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.

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.

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 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 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.

The invention relates to the technical field of ecological environment remote sensing monitoring and evaluation, and discloses an urban forest SO2 purification benefit remote sensing inversion method based on a coupling model, and the method comprises the steps: firstly generating a normalized digital surface model and a leaf area index based on multi-source data; secondly, urban canopy three-dimensional aerodynamic resistance modeling is executed, and the friction speed and the microenvironment ventilation coefficient are solved; further constructing a particulate matter stomatal co-stress model, calculating an actual blade dust accumulation load and calculating corrected canopy stomatal resistance; meanwhile, a sulfur dioxide effective exposure concentration field is reconstructed based on the source-sink neighbor degree; and finally, synthesizing the dry settling velocity by integrating the aerodynamic resistance, the quasi-laminar flow boundary layer resistance and the corrected canopy pore resistance, and inverting the purification flux and the total amount. By coupling microenvironment ventilation, particulate matter physical blockage and non-uniform concentration field characteristics, the physical authenticity and accuracy of forest ecological benefit evaluation in a complex urban environment are improved.