51 results about "Ecological resources" patented technology

The invention provides a method for establishing an ecological resource intelligent credible data element model. The method comprises the following steps: acquiring natural ecological basic data; obtaining natural ecology derivative data, wherein the natural ecology derivative data comprises ecological tourism description metadata and leisure health care description metadata; performing controlled feature mining on the natural ecology basic data and the natural ecology derivative data to generate ecological basic data elements and ecological derivative data elements; performing key feature extraction on the ecological basic data elements and the ecological derivative data elements to obtain basic ecological key features and derivative ecological key features; and obtaining green financial data elements, and establishing association relationships between the green financial data elements and the basic ecological key features and between the green financial data elements and the derivative ecological key features to generate an ecological resource credible data element model. According to the technical scheme, the problem that effective association between green financial data elements and ecological resource data is lacked is at least solved.

The invention relates to the technical field of carbon emission monitoring, in particular to a cold region city carbon emission dynamic monitoring control method based on big data, and the method comprises the steps: obtaining regional point source carbon emission data, city space distribution data, meteorological data and ecological resource data of different monitoring regions of a cold region city; evaluating the spatial aggregation of the carbon emission intensity of the monitoring area; evaluating a carbon emission intensity high-value accumulation area; evaluating the carbon emission diffusivity of the carbon emission intensity high-value accumulation area; the carbon absorption capacity of the carbon emission intensity high-value accumulation area is evaluated; and according to the carbon emission substance diffusion capability and the carbon absorption capability, evaluating the regional carbon budget and expenditure balance capability of the carbon emission intensity high-value accumulation region and optimizing the regional carbon budget and expenditure. According to the method, the influence of urban spatial distribution and ecological resource distribution on carbon emission substance diffusion and carbon absorption capability is quantified, so that accurate evaluation and effective control on the carbon emission of the urban in the cold region are realized.

The invention provides an urban and rural planning surveying and mapping result generation method and system, and the method comprises the steps: obtaining ecological resource monitoring data, multiband spectrum remote sensing data and current urban and rural road network data of a target region, the spectral data comprises surface reflectance time sequence characteristics. Multi-modal environment sensing data is generated through dynamic coupling processing of vegetation distribution and reflectivity change, and then the multi-modal environment sensing data and road network density gradient information are subjected to adversarial learning matching to obtain surveying and mapping intermediate data. And based on a preset density constraint and an ecological bearing threshold value, cooperatively analyzing the intermediate data, and extracting topological constraint information fusing the road permeation path and the ecological boundary conflict. And generating an urban and rural planning surveying and mapping result through iterative spatial superposition processing. The collaborative optimization effect of ecological protection and construction development in urban and rural planning is improved.

The invention discloses a fish habitat real-time monitoring system based on Internet of Things. Comprising a data acquisition module used for acquiring fish habitat data, a communication networking module used for transmitting the acquired data, an analysis early warning module used for analyzing the data, a comprehensive management module used for assisting device operation and a propaganda education module used for propagandizing habitat education. Water quality parameters, hydrological parameters, fish activity data and human activity data of a fish habitat are collected, analysis data are generated in an analysis and early warning module, an ecological health index of the fish habitat is calculated, an early warning signal is generated, ecological risks of a fish living environment are predicted, and an ecological health index thermodynamic diagram is generated in a comprehensive management module. And real-time monitoring is completed under cooperation of multiple modules. The fish ecological resource environment is subjected to multi-source collection and analysis through the multi-source sensing technology, the correlation between fish habitat data and fish population distribution is deeply excavated, information of the habitat is accurately grasped, the monitoring accuracy is high, and the risk pre-judgment capability is high.

The present invention relates to the technical field of river and lake sediment treatment, and discloses a spiral propulsion type underwater elution robot for river and lake sediment, including a spiral propulsion power system for precise steering and movement in underwater soft foundation silt. The spiral propeller has the advantages of strong terrain adaptability, large traveling driving force, precise direction control, etc.; the sediment elution robot can achieve the suction separation of fine particulate matter and the in-situ covering of large inorganic sediment particles on the bottom of rivers and lakes through gravity separation in the sediment elution chamber and regulation of the water outlet flow rate, improving the sufficiency of sediment particle coverage at the mud-water interface. Using the underwater elution robot to carry out river and lake sediment treatment has the advantages of less sludge generation, high pollutant separation rate, low treatment cost, etc. After dehydration, the eluted silt can be used for the ecological resource utilization of sediment. The present invention is applicable to the in-situ treatment of sediment in urban rivers, lakes and reservoirs and the restoration of submerged plant habitats.

The invention discloses a vegetation coverage index algorithm and system based on an unmanned aerial vehicle. The algorithm comprises the following steps: S1, data acquisition and multi-source data preprocessing; s2, dynamic environment correction and multi-source data fusion; s3, red edge enhanced vegetation index calculation and terrain correction; s4, vegetation coverage intelligent prediction and precision verification; and S5, result visualization and decision support: generating a vegetation coverage spatial distribution map and a statistical report, and supporting a resource management decision. By integrating the unmanned aerial vehicle, the multispectral imaging sensor, the dynamic environment correction model and the data fusion algorithm, efficient and high-precision technical support is provided for precision agriculture, ecological resource management and disaster monitoring.

The present application provides a method and system for generating urban and rural planning surveying and mapping results, wherein the method includes: obtaining ecological resource monitoring data, multi-band spectral remote sensing data and current urban and rural road network data of the target area, wherein the ecological data includes vegetation coverage type and water body boundary information, and the spectral data includes surface reflectivity time series characteristics. Multimodal environmental perception data is generated by dynamically coupling vegetation distribution and reflectivity changes, and then adversarial learning matching is performed with road network density gradient information to obtain surveying and mapping intermediate data. Based on the preset density constraints and ecological carrying capacity thresholds, the intermediate data is collaboratively analyzed to extract topological constraint information that integrates the conflict between road infiltration paths and ecological boundaries. Urban and rural planning surveying and mapping results are generated through iterative spatial overlay processing. The present application improves the collaborative optimization effect of ecological protection and construction and development in urban and rural planning.

The invention belongs to the technical field of ecological system management, and particularly relates to a multi-system collaborative ecological niche segmentation system which comprises an environment sensing system, a data analysis and decision making system, a resource distribution system, a biological regulation and control system and a feedback regulation system. The environment sensing system is used for monitoring ecological environment parameters in real time; the data analysis and decision-making system receives and analyzes data of the environment sensing system and makes an ecological niche segmentation decision; and the resource allocation system allocates the ecological resources according to the decision. The system is reasonable in design, achieves the precise management of organisms and resources in an ecological system through the integration of the environment perception system, the data analysis and decision-making system, the resource distribution system, the biological regulation and control system and the feedback regulation system, promotes different species to reasonably occupy ecological niche, improves the resource utilization efficiency, maintains the ecological balance, and improves the economic benefit. And an innovative solution is provided for ecological protection and sustainable development.

The invention discloses an eel fry fishing gear and a using method thereof, the fishing gear is a double-pile winged single-bag expanding net, the mesh size of a net bag is innovatively limited to be 2.5 mm, and key structure parameters such as the perimeter, the height and the width of a net opening and the length of a netting are optimized. The method comprises four standardized operation steps of piling, net hanging, net hauling and net changing, and special permission and resource monitoring management are fused. According to the method, efficient and selective fishing of eel fry is achieved, the fishing efficiency is remarkably improved, meanwhile, the fishing rate of non-target economic fish larvae is effectively reduced, damage to ecological resources is relieved, and reliable technical support is provided for scientific management and industrial sustainable development of eel fry resources.

The invention provides a grassland community volume estimation method and device, and is applied to the technical field of ecological resource investigation. The method comprises the following steps: acquiring laser radar point cloud data, point cloud scanning angle data and ground quadrat canopy height measurement information of a grassland community; determining canopy height model raster data according to the laser radar point cloud data, determining a grassland community average canopy estimation height according to the canopy height model raster data, and determining an average canopy measurement height according to the ground quadrat canopy height measurement value; performing linear fitting on a difference value between the average canopy estimation height of the grassland community and the average canopy measurement height and the point cloud scanning angle data to obtain an association relationship between the grassland height loss amount and the point cloud scanning angle; and correcting the canopy height model raster data based on the association relationship, and calculating the grassland community volume based on the corrected canopy height model raster data.

The invention relates to a resource utilization ecological evaluation method and system, a storage and a medium, and belongs to the technical field of resource utilization evaluation.Ecological resource data information demanded in a target area is obtained, and the ecological resource data information in the target area is estimated and evaluated based on the ecological resource data information demanded in the target area; according to the method, the ecological bearing capacity estimation result is obtained, resource utilization analysis is carried out according to the ecological bearing capacity estimation result, a resource utilization analysis result is obtained, and finally ecological resource utilization of the target area is dynamically adjusted according to the resource utilization analysis result. According to the method, the ecological bearing capacity condition of the ecological resource data information in the target area is analyzed according to the ecological resource data information required in the target area, so that whether the current ecological system can be self-sufficient or not is evaluated, and resource development is reasonably arranged under the condition that the ecological system is not damaged; and the green idea of an ecological system is considered.

The invention discloses an unmanned aerial vehicle remote sensing image processing method for ecological resource monitoring, and belongs to the technical field of unmanned aerial vehicle remote sensing, and the method comprises the steps: S10, carrying out the image collection of an ecological resource region, obtaining the region area of the ecological resource region before the image collection, and carrying out the image collection based on the region area; acquiring position positioning information of the unmanned aerial vehicle in the image acquisition process; step S20, preprocessing the collected image, wherein the preprocessing comprises image denoising, image enhancement and image splicing; wherein in the image splicing process, splicing is carried out by taking at least two images collected by the unmanned aerial vehicle as a splicing unit, and the two images are the images collected when the unmanned aerial vehicle flies in the same direction. The reliability of ecological resource monitoring is improved, the adaptability to the complex ecological environment and the sensitivity to ecological resource changes are high, and the requirement of modern society for ecological resource monitoring is met.

The invention discloses an urban ecological evaluation method based on dynamic evolution and spatial correlation, and belongs to the technical field of urban ecological performance. The method comprises the following steps: establishing an urban ecological performance index system through a Markov chain and a kernel density estimation method, and dynamically evaluating the urban ecological performance; weighting the urban ecological performance index system through an entropy method; analyzing spatial correlation of urban ecological performance by adopting a global Moran index and Datonian coefficient decomposition method; and combining convergence and a convergence model to evaluate the long-term development trajectory of urban ecological performance. The space-time evolution rule and the space correlation characteristics of the urban ecological performance are disclosed from time and space dimensions, so that the dynamic change state of the city and different cities are linked, the comprehensive performance of the city in the aspects of ecological resource utilization, environmental protection and carbon emission control is comprehensively reflected, the defects of an existing evaluation system are overcome, and the evaluation system is suitable for the urban ecological environment. And the accuracy, comprehensiveness and scientificity of evaluation are improved.

This invention discloses a zoning method and system for realizing the value of natural resource ecological products, belonging to the technical field of natural resource ecological product value realization. The method first uses a zoning model to iteratively rank the ecological function priorities at the landscape scale of the study area, generating a nested landscape sequence. The model output is analyzed to identify potentially important ecological spaces and high- and low-priority areas. Then, the STARS algorithm is used to determine the grading thresholds for important ecological spaces through mutation testing and to classify them. Next, the SOFM algorithm is used to cluster the supply and demand variables of ecological products to identify clusters of supply and demand relationship characteristics. Finally, based on the identification results of these clusters, functionally similar and spatially adjacent clusters are merged, and the identification results of important ecological spaces are superimposed to obtain the ecological product value realization zoning, and zoning realization strategies and paths are proposed. This method realizes the optimal allocation and protection of ecological resources, the precise formulation of management strategies, and the coordinated green development of the region.

The application provides an ecological resource intelligent credible data element model establishment method, including: obtaining natural ecological basic data; obtaining natural ecological derived data, the natural ecological derived data including ecological tourism description metadata and leisure and health care description metadata; respectively performing controlled feature mining on the natural ecological basic data and the natural ecological derived data to generate ecological basic data elements and ecological derived data elements; respectively performing key feature extraction on the ecological basic data elements and the ecological derived data elements to obtain basic ecological key features and derived ecological key features; obtaining green finance data elements, and establishing an association relationship between the green finance data elements and the basic ecological key features and the derived ecological key features to generate an ecological resource credible data element model. The technical scheme in the application at least solves the problem that green finance data elements and ecological resource data lack effective association.

The application discloses a kind of vegetation cover index algorithm and system based on unmanned plane, wherein algorithm includes the following steps: S1, data acquisition and multi-source data preprocessing;S2, dynamic environment correction and multi-source data fusion;S3, red edge enhanced vegetation index calculation and terrain correction;S4, vegetation coverage intelligent prediction and precision verification;S5, result visualization and decision support: generate vegetation coverage spatial distribution map and statistical report, support resource management decision.The application provides efficient, high-precision technical support for precision agriculture, ecological resource management and disaster monitoring by integrating unmanned plane, multispectral imaging sensor, dynamic environment correction model and data fusion algorithm.

The invention discloses a forest ecological product value accounting method based on a remote sensing and geographic information system, relates to the technical field of ecological resource digital management, and aims to solve the technical problems that a traditional accounting method is low in efficiency and insufficient in data precision, and dynamic monitoring and multi-dimensional value comprehensive evaluation are difficult to realize. Comprising the following steps: S1, constructing a space-air-ground acquisition network through a satellite, an unmanned aerial vehicle and a ground sensor, and carrying out intelligent cleaning, registration and standardization preprocessing on multi-modal data; and S2, inverting forest three-dimensional structure parameters by using multi-temporal remote sensing data, and constructing a digital twin model to dynamically simulate the whole-cycle growth process. According to the invention, a space-air-ground integrated monitoring network is constructed, high-frequency and high-precision data is collected in combination with a spatio-temporal data fusion algorithm, individual tree parameters are inversed cooperatively through LiDAR point cloud and hyperspectrum, errors are eliminated through spectral angle mapping, the accounting precision is improved to a sub-meter level, and the problem of spatio-temporal heterogeneity is solved.

The application discloses a kind of based on carbon source-sink and biological process's preferential protection area demarcation method, comprising: obtaining the multi-source remote sensing data of research area, generates the ecological resistance surface of research area;Based on circuit theory extraction ecological corridor and ecological node, construct the static ecological network of source-corridor-node structure;For the spatio-temporal heterogeneity characteristics of ecological source, the supply and demand of carbon fixation service of ecological source are calculated;Carbon fixation service as important ecological resources, according to the characteristics of biological migration from low resource habitat to high resource habitat, compare the supply and demand ratio of carbon fixation service between ecological source, to determine the trend of ecological corridor, calculate the flow radius of ecological source carbon sink supply area, according to flow radius determine the biological flow relationship between ecological source, divide ecological source into carbon source protection area and carbon sink protection area.

The application discloses an ecological economic value evaluation method based on data analysis, and relates to the technical field of value evaluation. When the method is in operation, multi-dimensional data related to an ecological system is collected, ecological resource utilization efficiency data, environmental protection contribution and environmental loss data are obtained, the collected multi-dimensional parameters are preprocessed, and resource utilization benefit coefficient R util , environmental protection contribution coefficient P env , environmental loss coefficient E loss and ecological economic value evaluation index S tjj are calculated. The ecological economic value evaluation index S tjj is compared with a preset first threshold value V and a preset second threshold value B, future development direction and potential risks are evaluated, an ecological economic value evaluation report is automatically generated, and the report content includes: detailed analysis of each coefficient, trend analysis result, ecological economic value evaluation index S tjj and comparison result with the preset threshold value. The report adopts a form combining charts, data and words, and directly displays the evaluation result.

The invention provides an intelligent model construction method for evaluating the ecological value of lake water and application thereof, and relates to the technical field of digital evaluation of ecological resources. The intelligent model construction method based on lake water ecological value evaluation comprises the steps that multi-source ecological data are collected through a multi-platform cooperative sensing system, and the multi-platform cooperative sensing system comprises the steps that a satellite remote sensing system obtains spectral data not less than 10 wave bands, and the spatial resolution is not greater than 10 meters; the unmanned aerial vehicle platform carries a multispectral imager to collect image data of a 200-2500 nanometer wave band; the buoy Internet of Things network distributed on the lake surface collects time sequence data of total phosphorus, total nitrogen, permanganate index and pH value. Through multi-dimensional cooperation of the space-based satellite, the aerial unmanned aerial vehicle and the internet-of-things buoy, wide-coverage, high-precision and real-time collection of water area ecological elements is achieved, the temporal-spatial resolution reaches the industry breakthrough level, the timeliness of treatment measures and the resource release precision are greatly improved, and a standardized implementation normal form is provided for long-acting ecological protection.

The invention discloses a man-made forest and natural forest deep learning classification method based on a satellite-borne laser radar waveform. The method comprises the following steps: step 1, obtaining an L1B geographic positioning waveform of a satellite-borne full-waveform laser radar GEDI of a forest area; 2, carrying out preprocessing operation on the obtained data to obtain waveform information of high-quality GEDI light spots in an area; step 3, performing dimension raising on the waveform, and encoding the one-dimensional waveform into a two-dimensional matrix format as subsequent input; step 4, constructing a convolutional neural network model, firstly extracting local features of the image through a convolutional layer, reinforcing features of important channels through an SE module, then reducing spatial dimensions of an output feature map through a global average pooling layer, then performing global modeling on the features by using an MHA mechanism, and finally outputting a classification result through a full connection layer; and 5, evaluating the classification precision of the artificial forest and the natural forest. According to the method, two forest types can be distinguished, so that a scientific basis is provided for forest management and ecological resource monitoring.

The invention relates to the technical field of marine ecological environment monitoring, in particular to a sky-land-sea integrated marine environment monitoring network construction method. Comprising the following steps: comprehensively acquiring multi-dimensional marine environment elements through a multi-level collaborative sensing network consisting of satellite remote sensing, a low-altitude unmanned aerial vehicle, a marine buoy and a shore-based automatic monitoring station; constructing a unified data access and processing platform, integrating and fusing multi-source monitoring data of the sky, the air, the ground and the sea, and performing standardization processing; a flexible data query service is provided through a GraphQL interface, multi-dimensional retrieval according to a space-time range and a parameter type is supported, a multi-modal artificial intelligence analysis model is integrated, and intelligent recognition, generation and prediction capabilities are provided; by means of the mode, comprehensive, multi-element and high-frequency monitoring on the ecological environment of the watershed, the estuary and the bay is achieved, and the change situation of the marine ecological environment and the distribution, number and quality situation of ecological resources can be known.

The application discloses a kind of based on water temperature regulation and control's supplementary fish-passing facility lure fish system and method, lure fish system includes water source acquisition unit, water delivery unit, water temperature regulation and control unit and temperature effect field monitoring unit;A kind of based on water temperature regulation and control's supplementary fish-passing facility lure fish method includes the following steps: S1, reconnaissance and design;S2, pipeline layout;S3, system commissioning;S4, mode debugging;S5, operation and maintenance.The application systematically proposes the inherent unit cooling water of hydropower station as ecological regulation medium, without additional consumption of a large amount of energy to manufacture lure fish signal, realizes the cyclic efficient utilization of in-plant resources.Using existing water source and plant infrastructure, the purchase and installation of expensive special equipment are avoided.The application converts the unit cooling outflow, originally discharged as "waste heat", into a controllable "ecological resource", realizes the dynamic integration of "fish driving" and "fish luring" dual functions.

The application discloses a kind of ecological resource utilization efficiency measurement method based on combination of planting and breeding, and the technical scheme directly obtains remote sensing image, without other complex operations, can be aimed at remote sensing image and the situation of plants and animals on planting and breeding area is identified, and the consumption and production of plants and animals on planting and breeding area are calculated respectively;Combined with the proportion of different types of plants and animals on the soil area, considering the influence of animals on the green plants in the area for consumption and reducing consumption, and the distance between each soil area is too far, animals do not cross regional activities and cause animals to produce manure as fertilizer for the green plants in the area and bring the influence on plant consumption, animal consumption, animal production, plant production and plant consumption can be accurately calculated, so as to obtain the ecological resource utilization efficiency of combination of planting and breeding in super large area captive breeding area, and provide strong data support for subsequent improvement of ecological resource utilization efficiency.

The present invention relates to the technical field of ecological product value analysis. A method and system for ecological product value analysis based on deep learning includes: determining a cultural scenic area, obtaining a group of popular scenic spot areas, sequentially extracting a popular scenic spot area from the group of popular scenic spot areas, and performing the following operations on each of the extracted popular scenic spot areas: obtaining the biodiversity value, calculating the air purification value of the popular scenic spot area, obtaining the air purification value threshold, performing a green vegetation optimization operation on the popular scenic spot area to obtain an optimized area scenic spot, obtaining the optimization cost value of the optimized area scenic spot, summarizing the optimal value scenic spots, obtaining the optimal value scenic spot group corresponding to the group of popular scenic spot areas, and completing the ecological product value analysis based on deep learning based on the optimization cost value and the optimal value scenic spot group. The present invention can improve the accurate evaluation of ecological product value and the scientific management of ecological resources.

This invention provides a SED ecological descaling system for thin-gauge steel plates, designing a steel plate descaling technology field. High-pressure water and abrasive are mixed inside the descaling nozzle to form a high-pressure abrasive jet, which then impacts the steel strip surface. Relying on the impact grinding of the abrasive and the water wedge effect of the high-pressure water, the oxide scale and rust on the steel plate surface are removed. The continuous arrangement of four descaling units allows for full-width descaling coverage of the steel plate as it is conveyed, and the system is finished by a rinsing unit to improve the overall descaling effect. The wastewater and waste sand generated during descaling can be recycled and reused through a sand sorting and recovery system, a water circulation system, and a sand circulation system. This achieves graded recovery and recycling of the abrasive, and sedimentation, filtration, and reuse of the wastewater, significantly improving the abrasive recovery rate and wastewater reuse rate, realizing an ecological resource recycling descaling effect.

The application relates to the field of ecological resource development evaluation, and in particular to an ecological resource asset development and operation evaluation method and system based on deep learning. The method comprises the following steps: acquiring operation and environment perception data sets of mulberry base fish ponds, based on which, modern influence behavior analysis and cyclic conduction precursor signal capture are performed to generate a risk disturbance quantification information set; based on this, through deep time sequence causal inference, the correlation modeling of operation behavior and cyclic chain resilience attenuation is performed to generate a cyclic resilience attenuation trajectory information set capable of quantifying delay influence and identifying implicit inflection points; based on this, the cyclic chain resilience dynamic evaluation and implicit inflection point early warning of the mulberry base fish pond are performed to generate and output a mulberry base fish pond operation health degree evaluation report. In the ecological resource asset development and operation evaluation process, the application can prospectively identify the implicit inflection point of ecological deterioration, greatly improving the accuracy, forward-looking nature and sustainability of ecological asset operation.

The invention relates to the field of ecological resource monitoring, in particular to a forest change driving factor recognition method and system based on machine learning, and the method comprises the steps: collecting target forest ecological data, inputting the forest ecological data subjected to structured processing into a pre-constructed linear fusion model to obtain a response variable, and then, carrying out the recognition of the forest change driving factor. And inputting the response variables and the target forest ecological data subjected to the structured processing into a pre-constructed nonlinear decision model to obtain a Grain value of each influence variable, finally sorting the influence variables according to the Grain values, and performing recognition according to a sorting sequence result to obtain a key driving factor. Compared with the prior art, the method solves the technical problem that an existing forest change driving mechanism is low in recognition accuracy and applicability.

The invention relates to the technical field of river and lake sediment treatment, and discloses a spiral propulsion type river and lake bottom muddy water lower elution robot which comprises a spiral propulsion power system used for accurately steering and moving underwater soft foundation sludge. The spiral propeller has the advantages of being high in terrain adaptability, large in advancing pushing force, accurate in direction control and the like. The sediment elution robot can realize suction separation of fine particles and in-situ coverage of large inorganic sediment particles on the bottoms of rivers and lakes through gravity separation of a sediment elution cabin and regulation and control of water outlet flow, and the coverage sufficiency of sediment particles on a mud-water interface is improved. The underwater elution robot has the advantages of being small in sludge output, high in pollutant separation rate, low in treatment cost and the like when used for river and lake bottom mud treatment, eluted sludge can be used for bottom mud ecological resource utilization after being dewatered, and the underwater elution robot is suitable for bottom mud in-situ treatment and submerged plant habitat recovery of urban river channels, lakes and reservoirs.