70 results about "Cover-abundance" patented technology

The invention relates to a construction method and application of a remote sensing comprehensive ecological model RSIEI for evaluating a ground surface thermal environment differentiation effect of amining development dense area. The construction method comprises the following steps: inverting the surface temperature of a research area by using a radiation conduction equation method; representingthe earth surface vegetation biomass by using the photosynthetic vegetation coverage parameter and the non-photosynthetic vegetation coverage parameter; characterizing the soil moisture content by using the soil humidity index parameters; representing the bare soil and building density by using bare soil and building index parameters; and integrating the four basic ecological parameters based ona principal component analysis method to construct RSIEI. The application comprises the step of quantitatively analyzing the contribution of four ecological parameters to the ground surface thermal environment differentiation effect of the mining industry development dense region by means of a statistical method. The method is suitable for evaluating the thermal environment differentiation effectof mining development dense cities, and evaluating the surface thermal environment differentiation effect of small-scale mining development dense villages and towns with administrative boundaries as boundaries is also feasible.

The invention discloses a feature analysis method for regional vegetation restoration, and the method comprises the steps: determining a research region, and collecting annual rainfall data and annualNDVI remote sensing data of a meteorological station; performing statistical analysis on the annual vegetation coverage time sequence raster data according to the collected annual NDVI remote sensingdata; wherein the grid data, the grid data of which the vegetation coverage continuously increases, of the region, the grid data of which the vegetation coverage remarkably changes suddenly and the region with time stability are obtained through calculation, and the correlation grid data of the vegetation coverage with different remarkable levels and rainfall is the regional vegetation recovery comprehensive evaluation index. According to the characteristic analysis method for regional vegetation restoration, the vegetation restoration condition of a research region can be evaluated rapidly and simply by means of less data, and a scientific basis is provided for regional ecological construction decision.

The invention belongs to the technical field of the earth surface evapotranspiration remote sensing estimation, and relates to an evapotranspiration remote sensing inversion method and the applicationbased on the two-dimensional space of the reflectivity-vegetation coverage. The method comprises the steps of: obtaining the relevant data of a target area at the pre-set time scale; determining theprinciple and the definition of the evapotranspiration remote sensing inversion method based on the two-dimensional space of the reflectivity-vegetation coverage, and a variation law of the evapotranspiration ratio in the two-dimensional space of the reflectivity-vegetation coverage; according to the long-term sequence remote sensing short-wave infrared reflectance data and the vegetation coveragedata, determining dry and wet edges of the two-dimensional space of the reflectivity-vegetation coverage, and constructing the two-dimensional space of the reflectivity-vegetation coverage; determining a parameter [Phi] related to the evapotranspiration ratio according to an extended P-T equation and a change of evapotranspiration ratio in the two-dimensional space of the constructed reflectivity-vegetation coverage; and calculating the evapotranspiration of the pre-set time scale based on the determined parameter [Phi]. The evapotranspiration remote sensing inversion method and the application based on the two-dimensional space of the reflectivity-vegetation coverage are of great significance to accurately use the remote sensing to obtain the surface evapotranspiration.

The invention discloses a method and device of estimating and verifying a sequence assembly result of three-generation sequencing. The method comprises the steps of comparing a two-generation sequencewith a three-generation assembly result; extending and selecting a low cover degree area, and obtaining the extended sequence; comparing a three-generation sequence with the extended sequence; counting basic group coverage depth; marking the assembly result. The method and device can screen out the area with not too high quality from the three-generation assembly result, and mark the area. In thefollowing species research, a prompt function is provided if the area with not too high quality needs to be used, and a rapid screening method is provided for the following improvement; meanwhile, the accuracy and quality of the three-generation assembly result can be proved, and the accuracy of the assembly result can be improved.

The invention provides a method and device for estimating the ecological underground water level of an arid plain area. The method comprises the steps: constructing typical quadrat division on the arid plain area to be studied, and obtaining environmental factors; constructing a land surface vegetation coverage remote sensing quantitative inversion model according to the satellite remote sensing image data and the environmental elements in the historical period of the arid plain area to be studied; extracting satellite remote sensing image data of a target point in the arid plain area to be studied in each historical period, and performing vegetation coverage inversion by utilizing the constructed land surface vegetation coverage remote sensing quantitative inversion model to obtain vegetation coverage of the target point in the historical period; and collecting the underground water burial depth of the target point in the corresponding historical period, establishing a relationship between the vegetation coverage of the target point and the underground water burial depth according to the underground water burial depth in the same historical period and the vegetation coverage obtained by inversion, and determining the ecological underground water level of the target point according to the established relationship. The estimation precision of the ecological underground water level in the arid plain area can be improved.

The invention relates to a method for treating black and odorous contaminated water of rivers by adopting a modularized treatment device. The method comprises the following steps: (1) providing the modularized treatment device; (2) placing the modularized treatment device obtained in the step (1) in a target water area; and controlling parameters as follows: the planting density range of aquatic plants is 15 plants / m<2> to 35 plants / m<2>, and the specific surface area of a filler is 250m<2> / kg to 380m<2> / kg; the loaded amount of a microbial agent is 0.1kg / m<2> to 0.9kg / m<2>; and the water coverage area of the modularized treatment device is 15% to 35% the area of the target water area; and (3) placing the treatment device in the target water area for 10 to 15 days so as to enable the microbial agent to be successfully attached to and colonized into the filler; and then, keeping the treatment device in the target water area for 90 to 120 days, so as to complete treatment on the target water area. According to the method, the microbial agent is used for removing organic contaminants, the aquatic plants are used for absorbing nutrients from the water, and thus, the efficiency of greatly removing water contaminants is achieved; and meanwhile, the device employed in the method has the characteristics that the structure is simple, the mounting is convenient, the cost is low, the size can be changed according to field conditions through re-assembling of the device, the maintenance and management are simple, and reuse is achieved.

The invention discloses a vegetation phenological period extraction method based on effective pixels of a digital camera image, and belongs to the technical field of vegetation parameter remote sensing inversion methods. For a phenological camera or a common digital camera, a green vegetation index of a pixel scale is calculated by using a day-by-day multi-temporal observation image; based on the change amplitude of a green vegetation index in a year, an amplitude threshold value is screened, ground feature identification is carried out on an image region of interest, vegetation leaf pixels and non-leaf pixels such as soil and branches are rapidly identified, and when a mean value of the vegetation green index of the day-by-day image region of interest is obtained, the non-leaf pixels are removed. The signal-to-noise ratio of the vegetation greenness index mean value is increased, and the key phenological period of the vegetation growth cycle is extracted by using the vegetation index mean value time series data after noise reduction. According to the method, the influence of surface landscape change on vegetation phenology extraction of the region of interest can be effectively reduced, and the method has higher applicability to deciduous vegetation with medium and low coverage.

The invention provides a vegetation recovery method for extremely acidified mine soil, and belongs to the technical field of vegetation recovery. The method follows a primary succession rule; plant configuration is performed in a layered and staged manner; in the first stage, primary succession started in a primary bare area is simulated, acid-resistant and heavy-metal-resistant plants are taken as main plants, and multiple plants such as trees, shrubs and grasses are subjected to group configuration; and in the second stage, tolerant plants are transited to natural succession through the compensation effect of biodiversity, and a near-natural plant community independent of the tolerant plants is constructed. According to the method, a stable three-dimensional vegetation ecological systemcan be established on the extremely acidified mine soil in a short time, soil acidification and re-acidification are effectively controlled, and the long-term stability of the vegetation system is achieved. The method is easy to operate, rapid in vegetation reconstruction, high in coverage degree, not prone to degradation, good in acidification control effect and suitable for large-area application and popularization.

The invention discloses a non-growing season vegetation coverage remote sensing estimation method which comprises the following steps: acquiring remote sensing data of a research area in a non-growingseason, and acquiring the reflectivity of all pixels in the research area in a short-wave infrared band based on the remote sensing data; respectively selecting a plurality of vegetation pure pixelsand bare soil pure pixels based on the remote sensing data of the research area in the non-growing season, respectively calculating the average reflectivity of the vegetation pure pixels and the baresoil pure pixels in the short-wave infrared band, and calculating the vegetation indexes of the vegetation pure pixels and the bare soil pure pixels of the research area in the non-growing season based on the average reflectivity; and calculating the vegetation indexes of all the pixels in the research area in the non-growing season, and calculating the vegetation coverage of all the pixels in theresearch area in the non-growing season based on the vegetation indexes of the vegetation pure pixels and the vegetation indexes of the bare soil pure pixels. According to the method, the vegetationcoverage of all the pixels in a research area in non-growing seasons can be quickly and accurately calculated, and the method is not limited by time and space scales.

The invention discloses a component temperature-based earth surface temperature angle normalization method. The method comprises the following steps of describing component temperatures of vegetationand soil by utilizing a temperature daily change model; constructing a mixed pixel surface temperature model by combining a directional surface temperature product and a directional preparation indexproduct; solving the mixed pixel surface temperature model by utilizing a Bayesian optimization algorithm, obtaining an optimal neighborhood size based on an akaike information criterion, and obtaining component temperatures of vegetation and soil; and obtaining vegetation coverage in the reference direction by using a bidirectional reflection distribution function, and substituting the componenttemperature and the vegetation coverage into the mixed pixel surface temperature model to obtain surface temperature in the reference direction, thereby completing angle normalization. The temperatureis started from the physical mechanism of the surface temperature, the previous research based on illumination and shadow component difference is converted into the research based on vegetation and soil component difference, and high-precision angle normalization is carried out on the surface temperature based on the component temperature.

The invention provides a plant drought monitoring method, a monitoring module and a monitoring device, and belongs to the technical field of crop meteorological automatic observation. The plant drought monitoring method comprises the following steps of: collecting plant images; processing the collected plant images, and preliminarily acquiring the drought condition of plants by combining the established image feature library; when preliminarily judging that the plants has a drought condition, acquiring a connected domain area change condition corresponding to the plants in the plant images ina first set time period, and acquiring a plant coverage change condition in a second set time period; and when the connected domain area is not increased in the first set time period and the plant coverage is not increased in the second set time period, judging that the plant has a drought condition. Compared with an existing plant drought monitoring method, the plant drought monitoring method hasthe advantages that the judgment on whether the connected domain area and the plant coverage corresponding to the plants in the plant images in the set time period are increased or not is added, andthe possibility of misjudgment on the plant drought condition is reduced, so that the accuracy of a detection result is improved.

The invention discloses a mining area long-time-sequence surface soil water content remote sensing data production method and system, and the method comprises the steps: firstly collecting original historical data of a target mining area, carrying out the screening, cutting and elimination processing, obtaining surface soil water content data, collecting the data, and respectively calculating a normalized vegetation index NDVI, a vegetation coverage FVC and a leaf equivalent water thickness EWT; and then determining a downscaling expansion multiple strategy according to the target resolution, and finally performing model training and downscaling expansion according to the downscaling expansion multiple strategy to finally obtain a surface soil water content data product similar to the target spatial resolution. A long-time-sequence, high-spatial-resolution and high-time-resolution earth surface soil water content data product which has consistency and adapts to a mining area scene can be obtained, long-time-sequence monitoring of the earth surface soil water content of the mining area can be achieved, and data support is provided for mining of an ecological environment evolution mechanism of the mining area, quantification of an activity influence range of the mining area and the like.

The invention belongs to the field of ecological treatment, and particularly discloses a plant community configuration model and a slope protection vegetation planting method by utilizing native shrubs and grasses in an arid area. On the basis of mastering natural conditions of the arid area, substrate conditions of road slope and local ecological characteristics, and correctly identifying key factors restricting planting of plants on the slope, a configuration model is established through matching planting of different species, and substrate environment is manually regulated and controlled bycombining the slope protection vegetation planting method, so that the planting of local plants on the slope of the arid area is promoted, a stable vegetation structure is constructed, coverage of grass vegetation on the slope is improved, and soil and water loss is slowed down. The model and the method can solve problems of serious environmental factors in arid areas, difficult vegetation restoration, and hidden ecological safety hazards caused by introduction of a large number of foreign species on a side slope.

The invention discloses a method for calculating high and cold withered grass coverage based on a withered grass vegetation index. The withered grass reflectivity of a corresponding wave band of an MODIS is calculated by utilizing actually measured withered grass hyperspectral data and a wave band response function of the MODIS; then calculating dispersion data of the subglazed reflection spectrum by using a range analysis method to obtain a sensitive wave band of subglazed spectrum reflectivity. and in combination with the wavelength range of the MODIS sensitive wave band, selecting a corresponding MODIS wave band to construct a withered grass vegetation index DGVI, and further correcting the withered grass vegetation index on the basis of the withered grass vegetation index DGVI. An inversion model of the withered grass coverage is constructed on the basis of the corrected vegetation index, and compared with inversion models constructed by the vegetation indexes such as NDVI and RVI, it is proved that the coverage estimation value error of the withered grass inversion model constructed by the DGVI is obviously smaller than that of other models.

The invention provides a construction method of a regional scale evapotranspiration model synchronously considering dynamic changes of a vegetation canopy and a root system. The construction method comprises the following steps: S1, calculating net radiation, net radiation components and influence factors through regional scale data required by a PT-JPL model; s2, estimating the plant effective root depth Zr of the Chinese regional scale based on a Guswa model; and S3, coupling the effective root depth Zr of the plant into the PT-JPL three-source evapotranspiration model to construct a regional scale evapotranspiration model synchronously considering the dynamic change of the vegetation canopy and the root depth. According to the model, the vegetation dynamic change and the plant effective root depth are jointly incorporated into evapotranspiration calculation and analysis, the transverse change (vegetation coverage) of the vegetation dynamic state is considered, meanwhile, the longitudinal change (root depth) of the vegetation change is considered, the multi-scale analysis function is achieved, the requirements for ground data and aerodynamics are low, and the method is easy to implement. And the improvement of the evapotranspiration of the regional scale and the evapotranspiration component estimation accuracy is promoted.

The invention provides a method for ecological restoration of artificial vegetations on a high and steep rock slope. The high and steep rock slope has the gradient of 45 degrees or above, plants growin an ecological bag filled with soil in a mode of anchoring the high-molecular polymer environment-friendly material ecological bag in the ecological restoration of the artificial vegetations, the plants are effectively fixed, and a technology of slope protection and environment restoration is achieved; and nutrient elements needed by plant growth are prepared in the ecological bag, plant seeds are directly mixed in formula soil or seedlings at an opening of the ecological bag are directly planted, the plants grow robustly, plant diversity is promoted, vegetation coverage is increased, vegetation communities are balanced, the habitat of the high and steep rock slope is well fused with the surrounding natural ecological environment, and the purpose of rapidly restoring the high and steep rock slope is achieved.

The invention discloses a vegetation coverage early warning method. The method specifically comprises the following steps of preprocessing the remote sensing data, calculating to obtain the vegetationcoverage according to a preset algorithm, and projecting to form a grid map; calculating a vegetation coverage mean value of a preset period year in the grid map, and drawing a mean value grid map inthe preset period year; and calculating the vegetation coverage standard deviation of the grid data in the mean grid map, and drawing and outputting a difference grid map according to the mean valueand the standard deviation of the grid data. The beneficial effects of the invention are that the early warning or normal use is distinguished and marked with different colors or shadows in the difference grid map, and then is drawn in the corresponding grid data, so that the early warning or normal conditions of the vegetation coverage of a to-be-detected area can be directly revealed, and the area needing ecological restoration is further accurately recognized; based on a geographic information system, the seamless link when the correlation analysis is carried out with other meteorological index data, such as rainfall, accumulated temperature, etc., is realized.

The invention discloses a quantitative evaluation method for a s spatial-temporal differentiation effect of earth surface thermal environment based on a pixel trisection model. The vegetation coverageof a mining development dense area is estimated by using a pixel trisection model; an NDVI-DFI feature space is constructed to extract an end member feature value; and a mixed pixel on a medium-resolution remote sensing image is decomposed into three parts, namely photosynthetic / non-photosynthetic vegetation and bare soil. The estimation conforms to actual situations, the capability of obtainingvegetation information through remote sensing is enhanced, the spatial-temporal differentiation characteristic relation of photosynthetic / non-photosynthetic vegetation and bare soil to the regional earth surface thermal environment is evaluated quantitatively, and a quantitative reference basis is provided for revealing an influence mechanism of photosynthetic / non-photosynthetic vegetation and bare soil to the spatial-temporal heterogeneity of the earth surface thermal environment in a mining development dense region.

The invention provides a soil water content inversion method of a comprehensive drought model. The soil water content inversion method comprises the following steps: A, selecting cloudless MODIS datain a to-be-studied area range as a data source, and preprocessing the data source; B, calculating a broadband albedo, a normalized vegetation index and vegetation coverage (Fv) according to the surface reflectance in the MOD09 data, and calculating the day and night temperature difference of the area to be researched according to the surface temperature in the MOD11; C, calculating an apparent thermal inertia and vegetation water supply index model according to the result of the step B, assigning a vegetation coverage degree as a coefficient to a vegetation water supply index, assigning (1-Fv)as a coefficient to the apparent thermal inertia, and weighting the two products to obtain a comprehensive drought model; and D, performing regression simulation on the calculation result of the comprehensive drought model and the actually measured soil water content data to obtain a relational expression between the comprehensive drought model and the soil water content for inverting the soil water content of the research area.

The invention provides a soil nitrogen estimation method based on vegetation coverage for soil nitrogen, which comprises the following steps: firstly, collecting remote sensing data, preprocessing the data, then calculating a normalized vegetation index, and then calculating the vegetation coverage of an image by the normalized vegetation index; distributing points in a to-be-monitored area to collect soil data, and measuring field vegetation coverage in real time; next, carrying out regression analysis of actually measured soil nitrogen data and actually measured vegetation coverage, and establishing a mapping relation; calculating a regression equation between the image vegetation coverage and the actually measured vegetation coverage; and finally, simultaneously establishing the two equations to obtain an inversion model between the image vegetation coverage and the soil nitrogen. Inversion from images to soil nitrogen is achieved, large-scale rapid monitoring of the soil nitrogen is completed, stable and continuous soil monitoring data are obtained, and the method is used for guiding scientific management of soil nutrients and controlling the cost of soil nutrient management.

The invention discloses a method for northern low hilly area river bank side zone ecological construction, and relates to a method for ecologically constructing a river bank side zone. The method solves the problems of high cost, unreasonable tree species selection and limited ecological functions of an existing ecological restoration method for the low hilly area river bank side zone. The methodcomprises the steps that 1, the river bank side zone is trimmed; 2, arbors are planted on a bank of the river bank side zone, shrub plants are planted at the bottom of a bank slope, and herbaceous plants are planted on the slope surface of the bank slope; and 3, vegetation on the river bank side zone is watered or reseeded for maintenance. According to the method, the northern low hilly area riverbank side zone ecological construction is realized, so that the shear strength of the surface layer of soil of the bank side zone within a range of 0-1 m is improved by 50%, the vegetation coverage of the bank side zone reaches 95% or above, the water and soil conservation capacity in the bank side zone is obviously improved, the effect is good, the method is scientific and reasonable, the biodiversity is increased, and a good ecological function is achieved.

The invention discloses a vegetation temperature and bare land temperature estimation method based on satellite remote sensing data. The vegetation temperature and bare land temperature estimation method comprises the following steps: step 1, preparing satellite remote sensing data and ground meteorological observation data; 2, calculating the vegetation coverage according to the data in the step 1; 3, calculating the bare land albedo, the bare land emissivity and the vegetation emissivity according to the data in the step 1; and 4, calculating the bare land temperature and the vegetation temperature. The method is based on the earth surface energy balance principle, does not depend on other pixel information, uses satellite remote sensing data, including but not limited to the earth surface temperature, the earth surface emissivity, the vegetation index, the vegetation type and ground meteorological observation data, of a target pixel as input, calculates the vegetation temperature and bare land temperature of the target pixel, has spatial independence, and is high in precision, and improves the estimation precision.

The invention discloses a plant proportioning method for ecological restoration of a coal mine area based on remote sensing images, and relates to the technical field of ecological restoration. The method comprises the following operation steps: 1, dividing auxiliary data of different site conditions into different types by adopting a remote sensing image technology; and 2, comparing the auxiliary data of different site conditions with plant species composition under different vegetation coverage change trends, and determining key plant types required for vegetation restoration and reconstruction in each site condition and vegetation coverage change trend region. The method is suitable for ecological restoration, by improving the vegetation proportion, optimizing the phytoremediation proportion for different site conditions and conducting vegetation distribution, the mine ecological restoration sustainability and efficiency are improved, good ecological benefits are generated, reasonable vegetation proportion matching is achieved, the symbiosis is good, the ecological sustainability is excellent, and good popularization value is achieved.

The invention provides a forest fire behavior potential prediction method based on multi-source data fusion, and belongs to the field of forest fire early warning. The forest fire behavior potential prediction method comprises the following steps: identifying combustible types according to airborne hyperspectral remote sensing data, estimating vegetation coverage, and inverting vegetation canopy moisture content; inverting a vegetation vertical structure according to the laser radar point cloud data; obtaining a subcompartment factor according to the forest resource planning survey data; obtaining surface combustible information according to the sample plot survey data; and establishing a combustible attribute data table by using the combustible type, the vegetation coverage, the vertical structure, the subcompartment factor and the ground surface combustible information and taking a subcompartment as a unit, generating three potential indexes and a spatial distribution diagram of a ground surface fire behavior, a crown fire behavior and an effective combustible, and carrying out forest fire behavior potential prediction. According to the method, the forest fire behavior potential is predicted by taking a subcompartment as a unit on the forest farm scale, so that the forest fire behavior potential is predicted more accurately and timely, and prevention and timely fighting of forest fire disasters are realized.

The invention discloses a river basin water and soil conservation measure configuration method adaptive to river sediment transport, which comprises the following steps: determining the regional suitability grade of a terrace according to positive and negative terrains and the soil distribution range and thickness; determining the regional suitability grade of the forest land according to the climate subareas and the soil characteristics; determining different vegetation coverage scenes based on vegetation coverage change characteristics; according to the obtained data, determining multiple water and soil conservation slope measure combination modes , and calculating the slope soil erosion amount Ts under each combination mode; giving the river sediment transport amount, and determining the number of reference silt dam systems in each combination mode according to the calculation result of the slope soil erosion amount; and comparing the treatment scene with the existing water and soil conservation measure configuration of the watershed, and determining a watershed water and soil conservation measure configuration scheme. The method is scientific in process and high in operability, and the relationship between drainage basin treatment and river sediment transport can be fully coordinated according to the determined drainage basin water and soil conservation measure configuration scheme.

The invention discloses a grassland ecology dynamic monitoring and analysis system, relates to the technical field of data analysis, and automatically obtains monitoring data and satellite remote sensing data of a grassland ecology automatic monitoring station, and simulates to obtain the vegetation coverage and overground biomass of grassland. And judging whether the vegetation is in a reviving period, a withered and yellow period or a growing period based on image recognition and a dynamic threshold value, and performing change value analysis and driving cause analysis on the plant coverage and the biomass by combining meteorological data to obtain the change dynamic state of the grassland ecological environment. According to the grassland original ecology dynamic monitoring and analysis system provided by the invention, based on monitoring data and satellite remote sensing data of a grassland automatic monitoring station, grassland coverage, overground biomass, theoretical livestock capacity, meteorological conditions and phenological conditions such as a reviving period, a withered and yellow period and a growing period are dynamically monitored and analyzed by utilizing a machine learning and quantitative inversion technology; and providing a grassland ecology dynamic monitoring analysis report.

The invention discloses a calculation method for a discontinuous forest combustible load, and relates to the technical field of remote sensing inversion. Aiming at the problems of lack of a vegetation radiation transmission mechanism, strong dependence on data, poor universality and the like of an existing empirical method-based forest combustible load estimation method, and the problems of serious high-value underestimation and the like caused by insufficient consideration of vegetation coverage in a discontinuous forest coverage area of an existing semi-empirical model-based overground biomass estimation method, the invention provides a forest combustible load estimation method based on a semi-empirical model. According to the method, the established semi-empirical model is adopted, optical data are introduced into the semi-empirical model and applied to estimation of forest combustible loads, vegetation coverage information of a discontinuous forest coverage area is fully represented, the simulation capacity of the model for ground surface back scattering signals is improved, and therefore the problem of high-value underestimation is relieved; the forest combustible load estimation precision and universality based on the semi-empirical model are improved, and a new method is provided for large-range forest combustible load spatial distribution estimation.

The invention discloses an airborne downscaling method for constructing vegetation coverage through multi-source data fusion. The airborne downscaling method comprises the following steps: s1, acquiring high-score 1 data in an NDVI product; s2, supervising and classifying down-sampled high-score No.1 data, and dividing the down-sampled high-score No.1 data into a vegetation region and a non-vegetation region; s3, filling the vegetation area with NDVI values while the non-vegetation area is not filled with data; s4, training the high-score No.1 image sample by adopting deep learning to obtain data for accurately identifying the NDVI model; s5, based on an NDVI model, carrying out NDVI image extraction on the downsampled Gaofen-1 data, and correcting a numerical value in the downscaled NDVI image data. The method plays an important role in monitoring vegetation coverage change, crop growth condition, ground feature type identification, crop yield estimation, biomass estimation, surface evapotranspiration, soil humidity monitoring, climate change and the like in the NDVI image data with high temporal-spatial resolution.

The invention discloses a multi-type urban green land classification method, solves the problems of low efficiency and low accuracy of obtaining urban green land space information in the prior art, and belongs to the technical field of urban green land change monitoring. The method comprises the following steps: acquiring vegetation phenology of a research area; acquiring remote sensing images ofa pre-growing season, a growing season and a non-growing season of the research area; calculating vegetation coverage by utilizing the growth season image, and performing segmenting to obtain a vegetation range; calculating the vegetation coverage by using the non-growing season image, and performing segmenting to obtain an evergreen forest range; calculating and obtaining a grayscale image by using the pre-growing season image, and performing segmenting to obtain a grassland range; performing spatial masking on the vegetation range by utilizing the evergreen forest range and the grassland range to obtain a deciduous forest range; acquiring a night light image, and performing segmenting to obtain a city range; and masking the evergreen forest range, the grassland range and the deciduous forest range by using the urban range to obtain various types of urban greenbelts including evergreen forests, deciduous forests and grassland. According to the invention, the efficiency and accuracy ofobtaining the urban green space information can be improved.

The invention provides a chlorophyll content remote sensing inversion method and device, electronic equipment, a medium and a product. The method comprises the following steps: acquiring spectral information of a to-be-detected sample; calculating a chlorophyll content sensitive red-edge trigonometric vegetation index RETVI of the to-be-detected sample according to the reflectivity at the multiple wave bands in the spectral information of the to-be-detected sample; according to the RETVI of the to-be-detected sample and the linear relation between the RETVI and the chlorophyll content, the chlorophyll content of the to-be-detected sample is obtained through inversion. The method has the best performance in adaptability tests of multiple scenes of different spectral data types, different vegetation types, different crop growth periods, different vegetation coverage degrees and the like. Meanwhile, the method not only provides a reliable and powerful tool for wide-range remote sensing application, but also provides a brand-new thought for construction of a new index.