19 results about "Moisture index" patented technology

The invention provides a tobacco shred wet mass online detection method based on hyperspectral imaging and time-space fusion, which comprises the following steps: acquiring a hyperspectral data cube of a tobacco shred flow, extracting a tobacco shred area and generating a mask; calculating a standardized moisture index of each pixel point in the mask according to the spectral response values of the moisture absorption wave band and the reference wave band to obtain a standardized moisture index image; based on a set index threshold value, converting the standardized moisture index image into a binary image, and performing morphological cleaning; carrying out wet group identification and marking on the cleaned binarized image to obtain an external rectangular frame of the binarized image; overlapping or adjacent external rectangular frames are combined, the combined external rectangular frames are screened based on the minimum area threshold value, the external rectangular frames which do not meet the area condition are removed, and the final tobacco shred wet mass external rectangular frames are obtained; according to the invention, misjudgment caused by shielding is significantly reduced; the high-speed and real-time online detection requirements of a cigarette production line can be completely met.

The invention discloses a GIS-based arid and semi-arid region farmland irrigation priority dynamic evaluation and zoning method, system, device and medium, and belongs to the technical field of farmland irrigation priority evaluation and zoning, and the method comprises the steps: collecting various types of remote sensing satellite data of a to-be-irrigated region; performing pretreatment; identifying the boundary and range of the to-be-irrigated area, and extracting a remote sensing image of the to-be-irrigated area; based on the remote sensing image of the to-be-irrigated area and the basic geographic information, parameter calculation is carried out, and normalization processing is carried out; performing superposition calculation on each normalized parameter according to a set weight to obtain an irrigation priority index; partitioning the to-be-irrigated area based on the irrigation priority index to generate an irrigation priority map; and judging whether agricultural irrigation management requirements are met or not according to preset conditions. According to the method, temperature vegetation drought indexes, normalized moisture indexes, water resource accessibility and crop economic value parameters are coupled; the irrigation priority index weight can be automatically adjusted according to a season strategy.

This invention discloses a remote sensing identification and stand age estimation method for multi-mode rubber plantations. Utilizing multi-source remote sensing data and advanced image processing and analysis methods, it accurately monitors and estimates the distribution and stand age of rubber plantations with different modes, such as large-scale and small-scale farming. First, through data preparation and integration, combined with unsupervised image segmentation and classification optimization using Gaussian mixture models, a high-precision rubber plantation distribution map is generated. Second, based on time-series vegetation-moisture index (e.g., NDWI) data, phenological features are extracted to identify the planting year of rubber trees and estimate stand age, ultimately generating a rubber stand age distribution map, providing scientific support for plantation management and ecological assessment.

The invention discloses a remote sensing moisture index construction method combining surface temperature and short wave infrared information. The method comprises the following steps: step 1, collecting satellite remote sensing data in a research area; step 2, meteorological radiation data collection and spatial interpolation of a research area; 3, performing remote sensing inversion on the surface biophysical parameters; step 4, calculating surface net radiation and soil heat flux; step 5, constructing a remote sensing moisture index combined with the surface temperature and the short wave infrared information; and step 6, performing space-time reconstruction on the remote sensing moisture index. The remote sensing moisture index combining the surface temperature and the short-wave infrared information is constructed, the key defect that a traditional moisture index based on the surface temperature information is greatly influenced by albedo is overcome, and the supersaturation effect of the moisture index based on the short-wave infrared information in a high vegetation coverage area is optimized; satellite thermal infrared and short wave infrared observation information can be fully utilized, and large-range, data-area-free, complex and non-uniform underlying surface moisture index calculation is achieved.

This invention discloses a method for dynamic monitoring and inversion of vegetation moisture based on the GNSS reflection geometric response index, belonging to the field of GNSS remote sensing inversion and surface ecological parameter monitoring technology. This invention solves the problems of existing GNSS-R vegetation moisture indices, such as reliance on empirical normalization, sensitivity to observation geometry, and difficulty in long-term stable comparative analysis. This invention utilizes direct sunlight and surface reflection signals observed by a ground-based GNSS receiver during continuous observation. Based on the response characteristics of the reflection signals to changes in satellite geometry, a vegetation reflection geometric response index is established to characterize the changing features of vegetation moisture status. This invention uses the establishment of a reflection response function and the extraction of geometric sensitivity parameters and stable historical reference states to quantitatively characterize vegetation moisture changes. This reduces the impact of noise interference or abnormal observations, eliminates the need for inversion using external remote sensing products or ground-based measured data, and is suitable for long-term continuous vegetation moisture monitoring in various climatic zones and vegetation types.

The embodiment of the invention provides a camellia oleifera grafting quality assessment method and system, and relates to the technical field of camellia oleifera grafting quality assessment, and the method comprises the steps: collecting a hyperspectral spectrum of a graft union region under a preset wave band, and obtaining the hyperspectral spectrum of the graft union region; obtaining a moisture index of the graft union area according to the hyperspectral spectrum of the graft union area; preset temperature stimulation is applied to the graft union area, and a physiological response infrared image sequence of the graft union area after temperature stimulation is obtained; calculating the temperature recovery rate of the graft union area according to the infrared image sequence; evaluating the temperature distribution uniformity according to the infrared image sequence; and judging the healing quality of the graft union according to the moisture index, the temperature recovery rate or the temperature distribution uniformity. The survival rate and the subsequent growth quality of the camellia oleifera grafted seedlings can be improved.

The invention provides a use control method and system for a concrete spraying maintenance device, and the method comprises the steps: obtaining a spraying request, and controlling a spraying device located at the top of a slope in a dam slope according to the spraying request to carry out the spraying of a top grid unit of the dam slope; wherein the slope of the dam is uniformly divided into a plurality of grid units in advance, and each grid unit is provided with a corresponding spraying device; a multispectral image of the dam slope is obtained, the moisture index of each cell in the multispectral image is calculated, and the position of a moist frontal surface in the dam slope moisture infiltration process is monitored in real time based on the moisture indexes; and dynamically adjusting a spraying strategy of the slope of the dam according to the position of the wet frontal surface, and controlling a spraying device of a specified grid unit to execute corresponding spraying operation according to the adjusted spraying strategy. According to the mode of dynamically adjusting the spraying strategy, the water resource utilization rate can be increased, the good maintenance effect of the concrete structure is guaranteed, and meanwhile water resource waste can be reduced.

The moisture control method for air flow drying process comprises the following steps: comparing the reference moisture of the product with the real-time moisture of the material to obtain a first error, wherein the reference moisture is the moisture index of the product; obtaining a temperature fine-tuning value according to the first error; predicting a compensation temperature according to the real-time detected inlet air temperature and outlet air temperature and the real-time moisture of the material, wherein the compensation temperature is the theoretical outlet air temperature predicted in advance based on the real-time working condition; superimposing the temperature fine-tuning value and the compensation temperature to obtain a reference temperature; adjusting the rotating speed of the feeding mechanism for feeding to adjust the real-time moisture according to the reference temperature; and repeating the above five steps. The control method can overcome the time lag existing in the air flow drying process and improve the precision of moisture control. A control system for executing the control method is also provided.

The invention discloses a soil water content determination method, prediction model and system based on multispectral data and machine learning inversion. The method comprises the following steps: firstly, constructing a standard sample set containing a plurality of soil types and a plurality of water content gradients; then, collecting a multispectral image of the sample and extracting spectral reflectivity; calculating a plurality of vegetation indexes including a normalized vegetation index NDVI, a soil conditioning vegetation index SAVI, a normalized moisture index NDWI, a ratio vegetation index RVI and a normalized red edge index NDRE based on the reflectivity; and finally, taking the multiple vegetation indexes as input characteristics, taking the actually measured water content as an output target, and adopting a random forest algorithm to train to obtain a soil water content prediction model which can be simultaneously suitable for the multiple soil types. Through multi-feature fusion and ensemble learning, the generalization ability of the model among different soil types is effectively improved, and the problem that a single model is difficult to be universally applied to various soils is solved.

This invention relates to the field of data analysis technology, specifically a corn canopy moisture sensing system and method based on a drone sensor network. The method includes: obtaining a specific reflectance image of the corn canopy; calculating an adaptive moisture index and outputting a corn canopy moisture content heatmap; calculating the barrier effect coefficient and corn transpiration source term, marking water vapor channel blockage hotspots on a three-dimensional cornfield structural model, delineating the locations of outer barrier zones and internal retention zones, estimating corn growth potential, and distinguishing between high-potential and risk zones; performing thinning priority scoring, formulating a dynamic thinning strategy based on the thinning priority score, and outputting the thinning coordinates of the cornfield. This invention solves the problem in the prior art where the simplified water vapor flux model ignores the three-dimensional barrier effect, leading to inaccurate analysis of water retention zones.

The present application relates to pesticide residue hyperspectral screening method of crop, utilize preset pesticide action mechanism coding table to the pesticide type to be measured is carried out identification, according to the identification result judges whether pesticide produces enzyme class response or structural change in crop surface layer or tissue layer;When determining that there is structural change, start hyperspectral feature extraction process;In the extracted hyperspectral image, analyze local spectral disturbance mode, and determine the asymmetric disturbance region according to the distribution of disturbance signal in the key physiological wave band of vegetation;Metabolic abnormality positioning is carried out on the asymmetric disturbance region by using nonlinear brightness parameter, water index parameter and pigment abnormality parameter;The present application realizes the structured modeling of pesticide type, action site and physiological response by constructing pesticide action mechanism coding table, which opens the data correlation channel between pesticide chemical characteristics and crop tissue response from the source.

The utility model belongs to the technical field of coal quality analyzers, and discloses a three-part coal quality industrial analyzer, which comprises a volatile component part, an ash component part and a water component part, the volatile component part comprises a volatile component heating furnace, a volatile component rotary table body, a volatile component sample feeding mechanism and a volatile component crucible, the volatile component rotary table body is horizontally arranged below the volatile component heating furnace, and the volatile component sample feeding mechanism is located below the volatile component rotary table body; the ash content part comprises an ash content heating furnace body, an ash content rotary table and an ash content crucible, and the ash content rotary table is horizontally arranged below the ash content heating furnace body; the volatile component part, the ash component part and the moisture component part are respectively used for testing volatile component, ash and moisture indexes of the coal sample. The coal quality index parallel test is realized by adopting the three-part independent design, the analysis efficiency and precision are improved, and the coal quality index parallel test device is particularly suitable for rapid detection of large-batch coal samples.

The application discloses a kind of remote sensing moisture index construction methods of joint ground surface temperature and short-wave infrared information, the method includes the following steps: step 1, research area satellite remote sensing data collection;Step 2, research area meteorological radiation data collection and spatial interpolation;Step 3, remote sensing inversion of ground surface biophysical parameter;Step 4, ground surface net radiation and soil heat flux calculation;Step 5, remote sensing moisture index construction of joint ground surface temperature and short-wave infrared information;Step 6, remote sensing moisture index space-time reconstruction.The application constructs a kind of remote sensing moisture index of joint ground surface temperature and short-wave infrared information, improves the key deficiency that traditional moisture index based on ground surface temperature information is greatly influenced by albedo, optimizes the oversaturation effect of moisture index based on short-wave infrared information in high vegetation cover area, can make full use of satellite thermal infrared and short-wave infrared observation information, realizes the moisture index calculation of large range, no data area, complex non-uniform underlying surface.

The invention relates to a hyperspectral screening method for pesticide residues of crops, which comprises the following steps of: identifying the type of a pesticide to be detected by utilizing a preset pesticide action mechanism coding table, and judging whether the pesticide generates enzyme reaction or structural change in an epidermal layer or a tissue layer of the crops according to an identification result; when it is judged that the structural change exists, a hyperspectral feature extraction process is started; analyzing a local spectrum disturbance mode in the extracted hyperspectral image, and determining an asymmetric disturbance area according to the distribution condition of disturbance signals in a vegetation key physiological wave band; performing metabolic abnormality positioning on the asymmetric disturbance region by using a nonlinear brightness parameter, a moisture index parameter and a pigment abnormality parameter; structured modeling of pesticide types, action parts and physiological reactions is realized by constructing a pesticide action mechanism coding table, and a data association channel between pesticide chemical characteristics and crop tissue responses is opened from the source.

The invention discloses a wheat waterlogging risk assessment method based on a remote sensing daily waterlogging index, and relates to the technical field of agricultural information, and the method comprises the steps: collecting multi-source agricultural geographic data, and carrying out the preprocessing; performing inversion derivation on the radar image data, and acquiring vegetation moisture index and surface temperature data from the optical image data; analyzing the synergistic effect of the soil moisture content data, the vegetation moisture index and the surface temperature data through a weighted fusion mechanism, and outputting the waterlogging accumulated intensity in the growth period; inputting the spatial node coordinates and the elevation fall into a pre-trained hydrological analysis model to analyze a hydrological diffusion path, and outputting a conduction network topology; and superposing the accumulated intensity of waterlogging in the growth period to the conduction network topology, generating a waterlogging risk conduction thermodynamic diagram, and evaluating the waterlogging risk of wheat. According to the invention, through cooperation of multi-source remote sensing data fusion and conduction network topology construction, accurate association of waterlogging risk dynamic representation and a spatial conduction mechanism is realized.

The application discloses a regional 30-meter resolution evapotranspiration estimation method cooperating with multi-satellite shortwave infrared observation, comprising the following steps: 1, obtaining meteorological radiation data of a research region and spatializing the data to form evapotranspiration model driving data; 2, obtaining satellite remote sensing data of the research region; 3, 1.24-micron shortwave infrared band reconstruction; 4, shortwave infrared moisture index calculation and remote sensing vegetation index time series reconstruction; 5, evapotranspiration estimation model construction; 6, construction of a relative evaporation ratio parameter model based on remote sensing shortwave infrared; 7, model parameter calibration; 8, verification and evaluation of regional evapotranspiration; the method of the application supports the demand of application fields such as regional water resource management, agricultural water use efficiency evaluation, regional drought monitoring and agricultural water saving, provides a train of thought for estimation of regional evapotranspiration, and the estimated evapotranspiration data product can provide key support for regional water and drought disaster monitoring and agricultural water management.

The invention discloses a regional 30-meter resolution evapotranspiration estimation method cooperating with multi-satellite short-wave infrared observation. The method comprises the steps of 1, obtaining meteorological radiation data of a research region and spatializing the meteorological radiation data to form evapotranspiration model driving data; 2, acquiring satellite remote sensing data of a research area; 3, reconstructing a 1.24 micron short wave infrared band; 4, short wave infrared moisture index calculation and remote sensing vegetation index time sequence reconstruction; 5, constructing an evapotranspiration estimation model; 6, constructing a relative evaporation ratio parameter model based on remote sensing short wave infrared; 7, calibrating model parameters; 8, verifying and evaluating regional evapotranspiration; according to the method, the requirements of the application fields in the aspects of arid region water resource management, agricultural water efficiency evaluation, regional drought monitoring, agricultural water saving and the like are met, a thought is provided for estimation of regional evapotranspiration, and an estimated evapotranspiration data product can provide key support for the aspects of regional flood and drought disaster monitoring, agricultural water management and the like.

The invention relates to an outlet moisture control method, device and equipment for a loosening and moisture regaining process. The method comprises the following steps: obtaining respective index parameters of each candidate association index and water outlet parameters of an outlet moisture index; determining respective correlation coefficients of each candidate correlation index and the outlet moisture index based on the respective index parameter and the water outlet parameter of each candidate correlation index, and determining at least one target correlation index from each candidate correlation index according to each correlation coefficient; determining an outlet moisture prediction parameter of the loosening and moisture regaining process based on the respective index parameter of the at least one target association index and the water adding flow setting parameter; according to the difference between the outlet moisture prediction parameter and the outlet moisture setting parameter, the water adding flow setting parameter is updated, and the updated water adding flow setting parameter is obtained; and on the basis of the updated water adding flow setting parameters, the loosening and moisture regaining process is controlled, and the water adding flow can be dynamically regulated and controlled, so that the reliability of moisture control is improved.

This application relates to the field of landscape maintenance technology, specifically to an intelligent adjustment system for landscape maintenance spraying; it addresses the technical problem that existing landscape spraying systems struggle to balance aesthetic appeal with ground drying requirements under complex operating conditions. The system includes: a data acquisition unit that collects pipeline pressure data from the pump station outlet and environmental meteorological data from the spraying area; a risk calculation unit that calculates particle size risk factors and accumulation risk factors based on the pipeline pressure data and environmental meteorological data, and synthesizes these factors into a ground moisture index; and a control unit that, when the ground moisture index reaches a first threshold, increases the pump's operating frequency to increase pipeline pressure and reduces the solenoid valve's duty cycle to decrease spray flow.