83 results about "Wetland vegetation" patented technology

The invention relates to a mangrove forest vegetation carbon sink monitoring and metering method based on an unmanned aerial vehicle and an AI technology, and the method comprises the steps: constructing a mangrove forest recognition model of a U-Net improved model based on a PyTorch deep learning framework through the unmanned aerial vehicle AI technology, achieving the intelligent recognition and discrimination of various mangrove forest vegetations, and the area and number of regions thereof, and achieving the accuracy of 90% or above; through regular aerial photography monitoring of an unmanned aerial vehicle, in combination with growth parameters measured on site and variable parameters derived from aerial photography data of the unmanned aerial vehicle, an optimal fitting model of mangrove forest height crown breadth, overground biomass and unit leaf area based on aerial survey of the unmanned aerial vehicle is constructed, and the carbon reserve and carbon sequestration amount of mangrove forest region vegetation are accurately calculated. And comprehensively evaluating the mangrove forest carbon sequestration capability in the monitoring area. According to the application, intelligent, digital and comprehensive monitoring and evaluation of the mangrove forest wetland vegetation carbon sequestration capability are realized.

The invention provides a wetland vegetation intelligent monitoring method and system based on multi-dimensional data fusion, and the method comprises the following steps: collecting a water area unmanned plane image of a wetland water area through a monitoring unmanned plane, and obtaining a water area remote sensing image of the wetland water area through a remote sensing satellite; the water area unmanned aerial vehicle image and the water area remote sensing image are fused into a water area fusion image, the submerged vegetation distribution condition is recognized, and a submerged vegetation monitoring route is planned; the underwater monitoring robot is controlled to continuously detect a wetland water area, and a submerged vegetation standard image and a submerged vegetation multispectral image are collected at the same time; performing image enhancement on the submerged vegetation standard image through a submerged vegetation identification model, and identifying and marking target submerged vegetation from the submerged vegetation enhanced image; selecting a target multispectral region containing target submerged vegetation from the submerged vegetation multispectral image; and vegetation feature data of the target submerged vegetation are calculated based on the target multispectral region. According to the invention, related data of submerged vegetation can be continuously and accurately monitored.

The invention provides a coastal salt marsh vegetation and sediment deposition comprehensive carbon sink assessment method and system. The system comprises a vegetation dynamic module, a water power module, a carbon dynamic module and a vegetation dynamic-water power-carbon dynamic coupling module. Output results are divided into vegetation-water and sediment-landform space-time dynamic and ecological system carbon exchange space-time dynamic, and the results are used for landform development and carbon sink dynamic evaluation of the salt marsh-light beach system. On the basis of development of a grid type process model, a vegetation dynamic model, a hydrodynamic model and a carbon dynamic model are coupled together, a biogeochemical coupling model integrating interaction among biological, hydrological and geomorphic processes is constructed, and a biogeochemical process of coastal salt marsh vegetation dynamic and sediment carbon sink is parameterized; and an effective evaluation technology can be provided for community development and carbon sink dynamics of coastal wetland vegetation.

The invention discloses a coastal wetland vegetation degradation dynamic monitoring method based on multi-modal transfer learning, and belongs to the technical field of ecological environment monitoring, and the method comprises the steps: data acquisition: collecting coastal wetland region data through a plurality of sensors, feature extraction and fusion: preprocessing multi-source data, extracting space, time series and physical parameter features, and carrying out feature fusion; and fusing the data features of different modalities. According to the method, all-around and high-precision perception of the coastal wetland ecological environment is realized, the spatial-temporal resolution of data acquisition is improved, the response capability to complex environmental factors is enhanced, the generalization capability and prediction precision of the model are effectively improved, key environmental factors such as soil salinity can be incorporated into an evaluation system, and the evaluation accuracy is improved. The scientificity and pertinence of ecological risk identification are further improved, the efficiency and response speed of coastal wetland ecological management are improved, and powerful support is provided for formulating scientific and reasonable ecological protection and restoration measures.

The invention relates to a large-scale comprehensive treatment method for spartina alterniflora, which has the advantages that firstly, conventional multi-time cutting is replaced by deep digging of spartina alterniflora, so that the manufacturing cost is saved, and the construction period is shortened; secondly, the conventional repeated plowing and outward transportation are replaced by adopting a burying and compacting mode, so that the manufacturing cost is saved, and the construction period is shortened; thirdly, a new soil backfilling technology is adopted, new soil hydraulic reclamation is completed by laying a hydraulic reclamation pipeline, oxygen is further blocked, and meanwhile, salt marsh vegetation planting conditions are achieved; and fourthly, the original ecology is restored through salt marsh vegetation replacement. The method is economical, efficient and simple in procedure, the vegetation habitat of the wetland is restored, the ecological function of the wetland is improved, and the original ecology can be restored while the spartina alterniflora is managed.

A method of creating a wetland in a hot, arid, location includes identifying or establishing a channel of flowing water at the arid location, and installing therein a mat containing seeds, and / or seedlings, and a super absorbent polymer (SAP). Water from the channel is applied to hydrate the SAP, and both edible and dam-constructing vegetation is allowed to grow and mature from the seeds and / or seedlings. Beavers are then introduced into the arid location, which eat the edible vegetation and use the dam-constructing vegetation to construct at least one dam across the channel of flowing water, thereby forming a wetland that further encourages both the vegetation and the beavers to propagate. A perforated, transparent or translucent cover sheet can be placed on or suspended above the mat. A water barrier can be placed below the mat. The wetland vegetation cools and humidifies the environment by transpiration of water.

A method of creating a wetland in a remote arid location includes identifying or establishing a channel of flowing water at the arid location, and installing therein a mat containing seeds, and / or seedlings, and a super absorbent polymer (SAP). Water is applied to the SAP, such that both edible and dam-constructing vegetation grows and matures from the mat. Beavers are then dropped into the arid location by parachute in containers that open upon landing. The beavers eat the edible vegetation and use the dam-constructing vegetation to construct at least one dam across the channel of flowing water, thereby forming a wetland that further encourages both the vegetation and the beavers to propagate. A perforated, transparent or translucent cover sheet can be placed on or suspended above the mat. A water barrier can be placed below the mat. The wetland vegetation cools and humidifies the environment by transpiration of water.

A method of creating a wetland in a hot, arid, location includes identifying or establishing a channel of flowing water at the arid location, and installing therein a mat containing seeds, and / or seedlings, and a super absorbent polymer (SAP). Water from the channel is applied to hydrate the SAP, and both edible and dam-constructing vegetation is allowed to grow and mature from the seeds and / or seedlings. Beavers are then introduced into the arid location, which eat the edible vegetation and use the dam-constructing vegetation to construct at least one dam across the channel of flowing water, thereby forming a wetland that further encourages both the vegetation and the beavers to propagate. A perforated, transparent or translucent cover sheet can be placed on or suspended above the mat. A water barrier can be placed below the mat. The wetland vegetation cools and humidifies the environment by transpiration of water.

A method of creating a wetland in a remote arid location includes identifying or establishing a channel of flowing water at the arid location, and installing therein a mat containing seeds, and / or seedlings, and a super absorbent polymer (SAP). Water is applied to the SAP, such that both edible and dam-constructing vegetation grows and matures from the mat. Beavers are then dropped into the arid location by parachute in containers that open upon landing. The beavers eat the edible vegetation and use the dam-constructing vegetation to construct at least one dam across the channel of flowing water, thereby forming a wetland that further encourages both the vegetation and the beavers to propagate. A perforated, transparent or translucent cover sheet can be placed on or suspended above the mat. A water barrier can be placed below the mat. The wetland vegetation cools and humidifies the environment by transpiration of water.

The invention discloses an emergent vegetation management method for increasing a biological carbon sequestration function, and belongs to the technical field of ecological system management and restoration, and the method comprises the following steps: in the stable growth period of emergent vegetation, discharging part of wetland moisture, and carrying out first mowing on overground parts of plants above the water surface; after the emergent vegetation further grows, the water level is restored to the end of the growth season, finally water is drained, secondary mowing is carried out, and all the emergent vegetation on the ground is harvested. According to the method, the overground biomass is increased through the plant photosynthetic carbon sequestration function by adjusting the appropriate harvesting time and mode of the wetland emergent vegetation, and therefore the biological carbon sequestration amount is increased. Compared with a traditional method for harvesting wetland vegetation at a time, the method has the advantages that the plant growth rate is remarkably increased, the overground biomass of the plants and the accumulation of organic carbon in surface soil are promoted, and the improvement of the wetland carbon sequestration function is facilitated.

The invention discloses a tidal wetland space-time evolution monitoring method based on Landsat, and the method comprises the following steps: S1, obtaining multi-temporal Landsat remote sensing image data of a target region, and carrying out the consistency preprocessing; s2, on the basis of the preprocessed multi-temporal Landsat remote sensing image data, constructing a spectral index time sequence including NDWI, NDVI, PSRI and NIRv; s3, generating a key period image based on the spectral index time sequence; s4, performing initial classification of tidal flat and wetland vegetation based on the image in the key period to obtain an initial classification map year by year; s5, based on the spectral index time sequence, performing segmentation by using a LandTrendr algorithm, and performing time sequence consistency optimization on the initial classification graph according to an obtained segmentation result to obtain an optimized classification result; and S6, performing post-processing on the optimization classification result to generate a tidal wetland year-by-year dynamic classification data set. According to the method, the high-quality data set capable of accurately reflecting year-by-year dynamic evolution of the tidal wetland can be generated.

The invention discloses a greenhouse gas emission reduction evaluation method for a coastal salt marsh wetland vegetation restoration project, and belongs to methodology in the fields of forestry and other carbon sink types. According to the salt marsh vegetation restoration project meeting the conditions, a greenhouse gas voluntary emission reduction project can be designed and approved according to the file requirements; and accounting and checking the emission reduction amount of the greenhouse gas voluntary emission reduction project. According to the method, the greenhouse gas emission reduction effect of the coastal salt marsh wetland vegetation restoration project can be scientifically and systematically evaluated, and powerful support is provided for project design and approval.

The invention discloses a wetland extraction method based on a neural network. The wetland extraction method comprises the following steps: step 1, acquiring data; the acquisition time interval of the optical remote sensing image data and the acquisition time interval of the radar remote sensing image data have an overlapping part, the overlapping duration is between 30 days and 90 days, and the overlapping duration is comprehensively determined according to the wetland vegetation growth cycle and the hydrological change cycle; the multi-source feature information of the wetland in the key period is reflected by the data; preprocessing operation is carried out on collected original remote sensing image data, and the error rate of radiation correction is strictly controlled within + / -3%. Compared with a traditional artificial remote sensing image interpretation wetland extraction mode, the neural network-based wetland extraction method has the advantages that the processing efficiency is greatly improved, large-scale multi-source remote sensing image data can be quickly processed, and the time and labor cost required by wetland information extraction is reduced.

The embodiment of the invention discloses a method for inverting satellite image wetland biomass based on unmanned aerial vehicle data, and relates to the technical field of remote sensing information processing, and the method comprises the steps: obtaining a satellite image of a target research region, and carrying out the preprocessing of the satellite image, calculating broadband vegetation index distribution of the satellite image based on the preprocessed satellite image, inputting the broadband vegetation index distribution into the trained wetland biomass inversion model, and performing inversion based on the broadband vegetation index of each pixel in the satellite image to obtain the wet biomass of the corresponding pixel; and outputting a wet biomass distribution diagram of the target research area. According to the method, the multi-variable-based wetland biomass inversion model is established by combining the high-resolution satellite data, so that the precision of directly inverting the vegetation biomass through the satellite image is improved, the precision of the data obtained by monitoring the wetland vegetation biomass can be improved, and data support can be provided for wetland vegetation parameter inversion, environment monitoring and carbon sink research.

The invention provides a wetland vegetation terrain inversion method and system based on unmanned aerial vehicle data and machine learning fusion, and the method comprises the steps: obtaining an unmanned aerial vehicle multispectral image and laser radar point cloud data of a target wetland area, and generating a vegetation coverage area multidimensional data set through combining with RTK actual measurement ground elevation sampling points; the feature parameters and the terrain correlation parameters are stored in a vegetation feature set and a terrain correlation parameter set; forming a training sample set by the vegetation characteristic parameters, the terrain correlation parameters and RTK actual measurement ground elevation, constructing a terrain inversion model, and calculating a mapping relation between the vegetation characteristic parameters and the terrain correlation parameters and the ground elevation; calculating the feature correlation degree between the vegetation feature parameters and the terrain correlation parameters in the training sample set and the ground elevation, and the cross-modal coupling degree between the parameters; calculating a terrain inversion confidence coefficient according to the feature correlation degree, the cross-modal coupling degree and the parameter weight; and generating a ground elevation inversion result. According to the invention, the precision and reliability of terrain inversion of the vegetation-covered area can be improved.

The invention relates to the related field of ecological environment protection, in particular to a high-phreatic-water-level secondary wetland landscape construction method, which constructs a wetland system with complete ecological functions by reasonably selecting wetland vegetation and introducing a proper amount of aquatic animals and microorganisms. The system has the functions of water purification, nutrition circulation, biodiversity maintenance and the like. Landscape design is combined with the natural form of the wetland, facilities such as a footpath, a viewing platform and an ecological plank road are arranged, and the ornamental value and the ecological education function of the wetland are improved. According to the method, the ecological stability and sustainability of the wetland are enhanced, a place for entertainment and ecological tourism is provided for the public, the balance of ecological protection and humanistic utilization is realized, and the method has remarkable environmental benefits, economic benefits and social benefits.

The invention discloses a vegetation community classification map generation method and a related device, and relates to the technical field of electronic information. Comprising the following steps: acquiring a plurality of radar images and / or a plurality of spectral images of a target wetland as a plurality of images of the target wetland; extracting a feature map from each image of the target wetland to obtain a plurality of feature images; screening out a preset number of images with the maximum importance value from the plurality of feature images as a plurality of target feature images; and generating a vegetation community classification map of the target wetland according to the plurality of target feature images. The radar image is less influenced by weather, so that the structural characteristics of vegetation can be effectively reflected; the spectral image has higher spatial resolution and higher time resolution, and can accurately capture the color and texture details of the vegetation; therefore, the plurality of images of the target wetland obtained in the application can well reflect the characteristics of the vegetation community; by adopting the method provided by the invention, a relatively accurate wetland vegetation community classification image can be obtained.

The invention provides an arid region salt marsh grassland wetland water supplement regulation and control method and a related device, and the method comprises the steps: determining the ecological water demand and deficiency corresponding to a target region according to the wetland vegetation evapotranspiration, precipitation and underground water-soil water exchange flux of the target region in a target time period, the target area is any area in the salt marsh grassland wetland in the arid area; determining a water quantity adaptive gap corresponding to the target area according to the earth surface water supplementing quantity and the ecological water demand deficit quantity of the target area in the target time period; and performing water supplementing regulation and control on the target area according to the water quantity adaptive gap. According to the accurate evaluation result of the water volume adaptation gap, a refined drip irrigation technology is adopted to carry out ecological water supplementation on the salt marsh grassland wetland, the requirements of plants for water in all stages of the whole life cycle are ensured, and the stability and adaptability of a wetland ecological system are improved; and multi-target collaborative development of hydrological communication, biodiversity improvement, habitat optimization and the like of the wetland ecosystem is realized.

The invention relates to a wetland vegetation extraction method and system based on spatial-temporal feature fusion, and belongs to the field of wetland remote sensing intelligent interpretation. The problems that an existing wetland vegetation classification method does not make full use of remote sensing data time sequence features, and the wetland vegetation extraction precision is insufficient are solved. According to the technical scheme, a single optical multi-temporal remote sensing image is used as input, frequency domain decomposition and convolution long and short time memory network modeling long-term phenology and short-term fluctuation are carried out through a time-frequency enhancement time sequence branch, and spectral grouping of a spectral space branch and cavity convolution multi-scale feature extraction are combined; and a cross-domain cross attention fusion module is utilized to realize time sequence spectral space three-dimensional feature deep fusion, and finally a wetland vegetation community classification map is output. On the premise of not depending on multi-source data, the time-frequency enhanced double-branch space-time model is innovatively provided, the multi-temporal remote sensing data time sequence feature self-adaptive extraction capacity can be effectively improved, the classification stability and robustness are improved, and finally the remote sensing monitoring precision of a wetland ecosystem is improved.

The invention relates to the technical field of ecological environment protection and restoration, and provides a karst area lakeside wetland vegetation pollution reduction and carbon sequestration method, and a vegetation combination comprises Acorus calamus (Acorus calamus), Nymphaea tetragona (Nymphaea tetragona (Nymphaea tetragona) and Myriophyllum sphaeroides (Myriophyllum sphaeroides). According to the vegetation combination, special environmental conditions of the karst area are fully considered, the carbon sink capacity of the lakeside wetland of the karst area can be effectively improved, water pollution is reduced, and the dual effects of pollution reduction and carbon sequestration are achieved; and the planting success rate of the aquatic plants in the karst lakeside wetland can be increased, the pollution reduction and carbon sequestration capabilities of the aquatic plants are enhanced, the restoration and stability of the ecological system of the karst lakeside wetland are promoted, and technical support is provided for the karst aquatic ecological system to cope with climate change, water pollution control and carbon sequestration and sink increase.

The invention discloses a wetland vegetation phenology monitoring method based on cooperation of ground observation and satellite remote sensing. The method comprises the following steps: arranging sample points in the field to obtain wetland vegetation ground observation phenology data; preprocessing the high / low resolution remote sensing data and generating dense EVI time sequence data by adopting a multi-source remote sensing image space-time fusion algorithm; carrying out smooth denoising on the time sequence EVI data based on an SG filtering algorithm; performing inversion based on a dynamic threshold method to obtain wetland vegetation satellite remote sensing phenological data; the relationship between ground observation phenological data and satellite remote sensing phenological inversion data is analyzed based on a linear regression method, a collaborative inversion model is constructed, and the wetland vegetation phenological inversion precision is improved. According to the method, the problem of scale errors caused by different observation scales of ground observation and remote sensing inversion data modeling is solved through cooperation of ground observation and remote sensing inversion data modeling, the wetland vegetation phenology inversion precision and robustness are remarkably improved, large-scale wetland vegetation phenology remote sensing inversion is achieved, and theoretical and technical supports are provided for health assessment of a wetland ecosystem.

The present application discloses a wetland vegetation carbon sequestration potential prediction method and system under the influence of future climate change, belongs to the technical field of wetland vegetation carbon sequestration potential prediction, and comprises the following steps: obtaining the net primary productivity of vegetation, the vegetation coverage, the monthly temperature, the precipitation and the atmospheric carbon dioxide concentration in the historical period and the future period; calculating the annual average net primary productivity of vegetation, the coverage and the multi-year average vegetation coverage; calculating the annual average temperature, the precipitation and the carbon dioxide concentration; extracting the wetland vegetation pixel distribution as the research area range; calculating the ratio of the annual average net primary productivity to the vegetation coverage to obtain the wetland vegetation carbon sequestration potential value in the historical period; adopting the multiple stepwise regression analysis method to build a per-pixel wetland vegetation carbon sequestration potential estimation model; and utilizing the annual temperature, the precipitation and the carbon dioxide concentration in the future period to realize the accurate prediction of the wetland vegetation carbon sequestration potential in the research area range in the future period.

The invention discloses a wetland vegetation automatic classification method based on time sequence remote sensing data segmentation. Comprising the following steps: step 1, performing Savitzky-Golay filtering preprocessing on NDVI data of a time sequence, and reconstructing NDVI data of a dense time sequence; step 2, based on a vegetation habitat similarity principle, using an X-means algorithm to segment NDVI dense time sequence data; and step 3, based on sample plot survey data and literature data, determining a mapping relation between the classification of the segmented plaques and the classification of the actual vegetation clusters, and realizing classification and precision evaluation of the vegetation clusters. According to the method, automatic classification on the vegetation cluster level can be achieved, the precision of vegetation classification based on medium-resolution optical data is improved, the defect that priori knowledge is insufficient in wetland vegetation remote sensing classification is overcome, and a new technical means is provided for large-scale vegetation mapping.

The invention discloses a method for estimating the photosynthetic efficiency of wetland vegetation under the influence of climate change, relates to the technical field of agricultural remote sensing, and aims to solve the problems that the photosynthetic efficiency of the wetland vegetation is inaccurately estimated and the future cannot be predicted in the conventional method. The method comprises the steps of 1, obtaining and preprocessing a data set; 2, collecting the month-by-month data into a growth season data set; 3, calculating to obtain a multi-year average LAI value in the research time period; 4, obtaining wetland vegetation distribution as a research area range; 5, obtaining a pixel-by-pixel growth season SIF value, a pixel-by-pixel growth season LAI value, a pixel-by-pixel growth season historical meteorological element value and a pixel-by-pixel growth season future meteorological element value in the research area range; 6, calculating the photosynthetic efficiency value of the wetland vegetation pixel by pixel in the range of the research area; 7, constructing a pixel-by-pixel wetland vegetation photosynthetic efficiency estimation model under the influence of climate change; and 8, predicting the photosynthetic efficiency of the future wetland vegetation in the range of the research area. According to the method, the future wetland vegetation photosynthetic efficiency can be quickly and accurately estimated and predicted on the regional scale.

The invention is suitable for the technical field of ecological environment monitoring, and provides an in-situ test device and method for analyzing the growth relationship between underground water and wetland vegetation, and the device comprises a probe which is located below a wetland vegetation root system layer and is used for collecting surface water-underground water exchange data; the automatic water level gauge is located in the center of the research area or the quadrat and used for monitoring the water level variation of the research area or the quadrat; the control terminal is located on the research area or the quadrat edge and comprises a power supply module, a data storage module, an unmanned aerial vehicle take-off recovery maintenance device and a device storage part, and the control terminal is fixed to the fixed base through a plug pin; the probe and the automatic water level gauge are connected with the control terminal through the data transmission line; and the unmanned aerial vehicle carries a hyperspectral imager and adopts a vertical take-off and landing fixed wing. According to the invention, the hydrological process of a research area or a quadrat and wetland vegetation growth state data can be continuously monitored in a long-sequence manner, so that the supporting effect of underground water on the growth of wetland vegetation is explored.

The invention relates to a multi-factor-driven coastal salt marsh wetland blue carbon potential evaluation method, which comprises the following steps: acquiring coastal salt marsh wetland area data, and preprocessing; evaluating the dynamic change trend of the coastal salt marsh wetland by using a PLUS model; predicting the appropriate distribution probability of different salt marsh wetland vegetation by using a Maxent model, and obtaining the spatial distribution result of different salt marsh wetland vegetation in the future; evaluating the blue carbon potential of the coastal salt marsh wetland by using an InVEST model to obtain the blue carbon potential of each vegetation of the coastal salt marsh wetland; and carrying out weighted stacking on the blue carbon potential of different salt marsh wetland vegetation of the coastal salt marsh wetland. The method has the beneficial effects that efficient and accurate evaluation of the blue carbon potential of the coastal salt marsh wetland is realized through multi-model collaboration and data driving.

A method for improving the germination of *Carex lumbricoides* seeds based on nano-zinc oxide initiation belongs to the field of wetland ecological engineering technology. The invention includes the following steps: First, nano-zinc oxide particles with a particle size of 30±10 nm are dispersed in deionized water by ultrasonic oscillation to prepare a suspension of 12.5-200 mg / L; second, collected *Carex lumbricoides* seeds are float-screened, and plump seeds that sink to the bottom are selected and subjected to surface sterilization; subsequently, the sterilized seeds are immersed in the nano-zinc oxide suspension and initiated by agitation under light-proof conditions for 6 or 24 hours, followed by air drying to restore the initial moisture content; finally, the initiated seeds are placed in an artificial climate incubator for germination culture under specific variable temperature and light conditions. This invention utilizes the biocompatibility of nano-zinc oxide and effectively solves the problems of long germination cycles and low germination rates of *Carex lumbricoides* seeds by precisely controlling the initiation concentration and time. This invention has the advantages of simple operation, low cost, and environmental friendliness, and can significantly improve the germination rate and germination percentage, providing high-quality seedlings for the restoration of degraded wetland vegetation.

The invention provides a method, a device and equipment for predicting influence of marsh vegetation change on surface temperature, and belongs to the technical field of ecological remote sensing and climate effect evaluation. The method comprises the following steps: firstly, determining vegetation pixel distribution as a research area range in an unchanged marsh wetland distribution range; a year-by-year and multi-year average growth season data set is constructed through a maximum value synthesis and arithmetic mean method; in the grid units, the pixels are divided into a high value group and a low value group according to the multi-year average growth season leaf area indexes, the difference value between the multi-year average growth season leaf area indexes of all the pixels in the high value group and the low value group and the average surface temperature value is calculated, and then the surface temperature change degree caused by the marsh wetland vegetation coverage change is quantified; and finally, realizing accurate prediction of future surface temperature influence in combination with a vegetation change trend on a pixel scale.

The application relates to a drought area salt water lake shore wetland stress-resistant vegetation configuration repair method, and belongs to the technical field of wetland ecological repair, and specifically relates to a drought area salt water lake shore wetland stress-resistant vegetation configuration repair method. The method solves the problem that the existing lake shore wetland vegetation repair technology cannot adapt to the extreme compound stress habitat of the inland closed salt water lake in the drought area, that is, no external fresh water supply, high mineralized water body, heavy saline soil and strong wind erosion, and overcomes the technical bottlenecks in the application of traditional technology in the region, such as low vegetation survival rate, poor community structure stability, insufficient directional conservation of local halophytes, secondary degradation after repair and the like. The method comprises the following steps: dividing the drought area salt water lake shore wetland into four functional repair regions according to four stress factors as quantitative partition basis; configuring stress-resistant vegetation for the four functional repair regions; and performing auxiliary repair measures for the four functional repair regions.

The application discloses a Landsat-based tidal wetland spatio-temporal evolution monitoring method, which comprises the following steps: S1, acquiring multi-temporal Landsat remote sensing image data of a target region and performing consistency preprocessing; S2, constructing a spectral index time sequence comprising NDWI, NDVI, PSRI and NIRv based on the preprocessed multi-temporal Landsat remote sensing image data; S3, generating key period images based on the spectral index time sequence; S4, performing initial classification of tidal flats and wetland vegetation based on the key period images to obtain initial classification maps year by year; S5, performing segmentation by using a LandTrendr algorithm based on the spectral index time sequence, and performing time sequence consistency optimization on the initial classification maps according to the obtained segmentation results to obtain optimized classification results; and S6, performing post-processing on the optimized classification results to generate a tidal wetland year-by-year dynamic classification data set. The application can generate a high-quality data set accurately reflecting the year-by-year dynamic evolution of a tidal wetland.