5 results about "Moisture index" patented technology

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the establishment of a reflection response function and the extraction of geometric sensitivity parameters and stable historical reference states to quantitatively characterize vegetation moisture changes.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 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.

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.

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.