CN103760113A - Hyperspectral remote sensing cane sugar analysis device - Google Patents
Hyperspectral remote sensing cane sugar analysis device Download PDFInfo
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- CN103760113A CN103760113A CN201410039694.XA CN201410039694A CN103760113A CN 103760113 A CN103760113 A CN 103760113A CN 201410039694 A CN201410039694 A CN 201410039694A CN 103760113 A CN103760113 A CN 103760113A
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Abstract
The invention discloses a hyperspectral remote sensing cane sugar analysis device which is composed of a satellite information receiving module, a communication module, a storage module, an embedded system and a display module, wherein the satellite information receiving module is respectively connected with the storage module and the communication module; the communication module and the embedded system are both connected with the storage module; the storage module and the embedded system are both connected with the display module; the satellite information receiving module is provided with a wireless communication antenna and a wired communication interface. The device disclosed by the invention has the advantages of simple structure, convenience in use, safety, reliability and low use cost, and is the equipment designed on the basis of the hyperspectral remote sensing technology, and the device is specially used for analysis of cane sugar.
Description
Technical field
The present invention relates to a kind of sugarcane sugar analytical equipment, be specifically related to a kind of high-spectrum remote-sensing sugarcane sugar analytical equipment.
Background technology
High-spectrum remote-sensing be visible ray at electromagnetic wave spectrum, near infrared, in infrared and thermal infrared wavelength band, obtain the technology of the continuous image data of much very narrow spectrum, can collect up to a hundred very narrow spectral band information.High-spectrum remote-sensing is the Disciplinary Frontiers of current remote sensing technology, and it utilizes a lot of very narrow electromagnetic wave bands to obtain relevant data from interested object, has comprised the triple information of abundant space, radiation and spectrum.This technology is widely used in the fields such as geologic examination, vegetation study, disaster monitoring.
The prediction of sugarcane sugar is before sucrose squeezes season production, and the sugarcane Sucrose in new squeezing season is predicted.On producing, before annual squeezing season starts, the preliminary work of producing in season all will be squeezed in sugar refinery, comprises and arranges to cut fortune, production, preparation auxiliary material etc.Sugar industry task and every economic and technical norms also will be assigned by higher authority.Above-mentioned work all will be dependent on the prediction of the Dui Zhe of Nong Wu department district sugarcane sugar.Therefore this is a key link in sugar industry, and optimization harvesting and the sugar industry of sugarcane are had to material impact.
Existing research shows, climatic factor (rainfall amount, degree of exposure, temperature), sugar cane breed and the factors such as phase, soil quality of planting are larger on the impact of sugarcane sugar.Set up accordingly multiple sugar forecast model, as the meteorological sugar forecast model based on squeezing season, conic model, Logistic piecewise model etc.Mostly existing model is to study for some or two influence factors, has larger limitation during prediction.And Data Source is only several sugar refinery in a certain region, or even some sugar refinery, and basic data does not have ubiquity.The large area data acquisition of high-spectrum remote-sensing, weatherproof, does not need manual intervention, is very suitable for the collection of agricultural data, and sugarcane sugar forecasting techniques based on high-spectrum remote-sensing is at home or blank.So, on market, be badly in need of a kind of simple in structure, safe and reliable, use cost is low based on high-spectrum remote-sensing and be specifically applied to the equipment of sugarcane sugar analysis.
Summary of the invention
The object of the invention is to for the deficiencies in the prior art, provide a kind of simple in structure, esy to use, safe and reliable, use cost is low, and the device that is specifically designed to sugarcane sugar analysis designing based on high spectrum resolution remote sensing technique.
To achieve these goals, the present invention has adopted following technical scheme:
A high-spectrum remote-sensing sugarcane sugar analytical equipment, mainly consists of satellite information receiver module, communication module, memory module, embedded system and display module; Described satellite information receiver module is connected with memory module, communication module respectively; Described communication module, embedded system are connected with memory module respectively; Described memory module, embedded system are connected with display module respectively; Wherein, described memory module is provided with sensor information storehouse, climatic information storehouse, sugar history library, sugarcane information bank and sugar forecast model storehouse; In sugar forecast model storehouse, store the sugar forecast model being built by embedded system, comprise basic sugar analysis submodel, weather sugar analysis submodel, soil sugar analysis submodel and environment sugar analysis submodel; Described embedded system is provided with sugar predicting unit, cuts fortune predicting unit, model construction unit and model modification unit;
Described satellite information receiver module from remote sensing satellite ground receiving station, He Zhe district, weather station agricultural sector obtains corresponding historical information data, being transferred to memory module stores, model construction unit in embedded system reads in memory module corresponding historical information data, builds to be transferred to memory module after corresponding sugar forecast model and to store, before squeezing starts in season, in the time of need to predicting sugar, satellite information receiver module obtains corresponding up-to-date information data from remote sensing satellite ground receiving station and weather station, being transferred to memory module stores, sugar predicting unit in embedded system is obtained up-to-date information data and sugar forecast model from memory module, and will in the corresponding sugar forecast model of up-to-date information data substitution, carry out analyzing and processing, obtain corresponding predicted value, again each predicted value is multiplied each other with each self-corresponding factor of influence respectively, gained product is sued for peace, obtain final sugar predicted value, cutting in embedded system transported predicting unit according to sugar predicted value, and in conjunction with historical sugar data and growth period data carry out inverting, the best that obtains obtaining maximum sugar is cut the fortune time, generates and specifically cuts fortune scheme, as sugar refinery, arranges this squeezing season to cut the reference frame of fortune work.
As of the present invention, further illustrate, described communication module comprises for sending the Beidou satellite navigation communication chip of communication short message and for the SIM card of Mobile data radio communication.
As of the present invention, further illustrate, described satellite information receiver module is provided with wireless communication antenna and wire communication interface.
As of the present invention, further illustrate, described memory module comprises for moving embedded system and depositing the built-in RAM (random access memory) card of a small amount of real time data and for the external RAM (random access memory) card of long-term storage mass data.
As of the present invention, further illustrate, described embedded system adopts the microprocessor of compatible mobile phone operating system; What described display module adopted is touch display screen.Display module is for carrying out alternately with user, and running status, Various types of data that can display device and predict the outcome etc. also can receive the instruction that user inputs by touch-screen.
As of the present invention, further illustrate, described historical information data comprise the historical sugar data that each sugar refinery in the historical high-spectrum remote sensing data of magnanimity that obtains Zhe district from remote sensing satellite ground receiving station, climatic information that on-site weather station, Cong Zhe district obtains, sugarcane essential information He Youzhe district that You Zhe district agricultural sector provides provides; Described up-to-date information data comprise that from remote sensing satellite ground receiving station, obtaining up-to-date on-site weather station, high-spectrum remote sensing data He Congzhe district obtains up-to-date climatic information.
Above-mentioned high-spectrum remote sensing data comprises photosynthesis amount, radiant quantity, vegetation index, soil moisture content, the content of organic matter and content of mineral substances; Described climatic information comprises day and night temperature, rainfall amount and illuminance; Described sugarcane essential information comprises sugar cane breed, plants the phase, perennial root time, growth cycle, planting density and growing way index.
As of the present invention, further illustrate, the input message of described basic sugar analysis submodel comprises sugar cane breed, plants the phase, perennial root time, growth cycle, planting density and growing way; The input message of described weather sugar analysis submodel comprises day and night temperature, rainfall amount and illuminance; The input message of described soil sugar analysis submodel comprises soil moisture content, the content of organic matter and content of mineral substances; The input message of described environment sugar analysis submodel comprises photosynthesis amount and radiant quantity.
As of the present invention, further illustrate, the modeling method adopting during model construction cell formation sugar forecast model in embedded system comprises difference equation method, data fitting method, linear programming technique and probabilistic method.
As of the present invention, further illustrate, described factor of influence is by drawing the characteristic curve diagram of sugarcane Back ground Information, weather, soil and environmental data and sugar historical data, and usings the average gradient of every characteristic curve as the factor of influence of this feature.
Embedded system in the present invention is the management platform of whole device, be responsible for from memory module, extracting basic data and setting up sugar analysis model, regularly carry out model modification, and mainly according to up-to-date real time data, by sugar analysis model, carry out sugar prediction and cut fortune prediction.
Basis sugar analysis submodel is set up as follows: through a large amount of historical data analysis results, show, sugarcane sugar height not only to kind, to plant the intrinsic informations such as phase, perennial root time relevant, affected by the growing way in planting density and each growth period.Therefore the foundation of basic sugar analysis submodel will be started with from above-mentioned several features, finds with the linear relationship of sugar and sets up mathematical function.First from sugarcane information bank, obtain sugarcane kind, plant phase and perennial root time information, by kind information, can obtain the growth cycle duration.The growth cycle of sugarcane is divided into 6 periods (sugarcane stem, bud differentiation, booting, ear, bloom and solid), different kinds for each period growth time used be different.Can calculate that at present this kind sugarcane is residing and be which growth period in conjunction with the phase of planting (spring planting, summer plantinge, fall planting and winter plant).Then set up time sequence spacing, by sensor information, carry out the Sugarcane growth in each growth period and analyze, obtain the superiority-inferiority index of growing way in each in growth period.Then utilize Analysis of Remote Sensing Information normalized differential vegetation index NDVI quantitative estimation cane planting density out, obtain the poor of the NDVI value of picture dot and the NDVI value of naked graph region, and the NDVI value of pure vegetation picture dot and the NDVI value of naked graph region is poor, both ratio is planting density.Using kind, plant phase, planting density, growing way exponential sum perennial root year piece of data as the input of model, sugar historical data is as the output of model, use the modes such as linear programming, neural metwork training to set up objective function, basis of formation sugar analysis submodel, and deposit in the model bank of memory module.
Weather sugar analysis submodel is set up as follows: in a large amount of historical climate data, choose the typical climatic factors such as weather conditions, rainfall amount, wind speed, temperature, humidity, day and night temperature, illuminance, in conjunction with sugar historical data, set up timing variations curve map, find that the climatic factor that sugar is had the greatest impact is day and night temperature, rainfall amount and illuminance; Therefore for the input parameter as weather sugar analysis model.From climatic information storehouse, obtain the historical data of a large amount of day and night temperatures, rainfall amount, illuminance, input as model, sugar historical data is as the output of model, through iteration repeatedly, calculation, move closer to objective function, according to each parameter value of the assimilation number modified objective function of historical data (being the coefficient of modified objective function), set up weather sugar analysis model, and deposit in the model bank of memory module.
Soil sugar analysis submodel is set up as follows: test and show, soil quality and composition can affect the sugar height of sugarcane.In order to find out the relation of soil characteristic and sugar, must first soil characteristic data be extracted from high-spectrum remote-sensing information.Need the soil characteristic extracting to have soil moisture content, soil organic matter content and soil mineral content.First in high-spectrum remote-sensing information, select to have the spectral band of lowest mean square root error, in conjunction with relative reflectance method, single order differential method, difference method, soil moisture content is estimated.Then carry out the estimation of soil organic matter content, utilize spectrum differential technology to carry out mathematical simulation to part reflectance spectrum numerical value, determine curve of spectrum flex point.The soil sample content of organic matter of having measured in advance and spectral reflectance data are carried out to correlation analysis, calculate related coefficient.Utilize reflectivity logarithm differential equation of first order to set up regression equation, adopt Stepwise Regression Method, set up soil organism predictive equation.Carry out afterwards the estimation of soil mineral content, with spectral reflectivity (reflectivity reciprocal, reflectivity logarithm, First derivative reflectance etc.) as independent variable, soil sample content of mineral substances, as dependent variable, uses multiple linear regression, BP neural net method to set up mathematical model.Finally, the input using soil moisture content, the content of organic matter and content of mineral substances as model, sugar historical data is as the output of model, constantly carry out inverting iteration, obtain the relation of soil data and sugar, set up soil sugar analysis submodel, and deposit in the model bank of memory module.
It is as follows that environment sugar analysis submodel is set up: the intensity of photosynthesis of sugarcane and effect just have considerable influence effect to sugar, so as the object of environment sugar analysis.Sugarcane top area index (LAI) and absorbed photosynthtic active radiation (APAR) historical data are compared, set up functional relation; Because the photosynthesis characteristics of sugarcane top, respiratory characteristic, space configuration all equate, just leaf area index is variant, so can show according to the size of leaf area index the changing condition of population photosynthesis curve; With normalized differential vegetation index (NDVI), map with leaf area index, absorbed photosynthtic active radiation respectively, find out relevance between any two.Input using the photosynthesis amount estimating and radiant quantity as model, sugar historical data is as the output of model, and constantly the parameter of adjustment aim function, is finally inversed by environment sugar analysis submodel, and deposits in the model bank of memory module.
After above-mentioned model is set up, by drawing respectively the relationship characteristic curve of each influence factor (the basic factor such as kind, climatic factor, edphic factor, environmental factor) and sugar historical data and analyzing, determine the impact size of each influence factor on sugar, formulate corresponding factor of influence, again the product of the predicted value of each submodel and factor of influence is sued for peace, obtain final sugar predicted value.According to sugar predicted value and this kind historical data, compare, analyze and will reach the required growth time of predicted value, be combined with current time and can obtain optimum and cut the fortune time.
In the present invention, satellite information receiver module mainly receives two category informations, and a class is from remote sensing satellite ground receiving station, to obtain high-spectrum remote-sensing raw video data, and another kind of is from weather station, to obtain magnanimity historical climate information.Original remotely-sensed data will first be carried out spectral analysis, be mainly to the target in hyperspectral remotely sensed image monitoring of classifying, adopt spectral space analytic approach, feature space analysis method, Decomposition of Mixed Pixels method, layering and zoning Images Classification method, multi temporal analysis method and multi-source data combined techniques etc. that the characteristic in image is extracted.By being carried out to various algebraic operations, original wave band can access various spectral informations and vegetation index, mainly comprise AVI(anomaly vegetation index), NDVI (normalization difference vegetation index), RVI (ratio vegetation index), the vertical vegetation index of PVI(), DVI(difference vegetation index), the green degree vegetation index of GVI(), SAVI(soil regulates vegetation index), DVIEVI (difference environmental vegetation index), VCI(condition vegetation index), TCI(condition humidity index), NDTI(normalization humidity index), VTCI(condition vegetation humidity index) and GVMI(overall situation vegetation humidity index) etc.Data and the result analyzed out deposit in sensor information storehouse.Historical climate information comprises rainfall amount, day and night temperature and the illuminance etc. of every day, deposits in climatic information storehouse.
Communication module of the present invention is carried out two-way communication by two kinds of modes and remote information administrative center system or mobile terminal (as mobile phone).The raw data that satellite information receiver module collects and the sugar after embedded system analysis predict the outcome and cut fortune and predict the outcome and can be sent to tele-control system or mobile terminal by it, simultaneously also can receiving remote control system or the command information that sends over of mobile terminal, as the sugar in requirement forecast somewhere or Renewal model etc.
Compared with prior art, the advantage that the present invention possesses:
1. high-spectrum remote-sensing sugarcane sugar analytical equipment of the present invention is simple in structure, esy to use, safe and reliable, use cost is low; The equipment that is specifically designed to sugarcane sugar analysis designing based on high spectrum resolution remote sensing technique.Satellite information receiver module is mainly used in receiving high-spectrum remote sensing data and weather information data; Embedded system can, to data analysis, draw the predicted value of sugar; Communication module can allow this device and telemanagement center or other mobile terminal mutual data transmissions; Display module is for carrying out alternately with user, and running status, Various types of data that can display device and predicting the outcome etc. also can receive the instruction that user inputs by touch-screen.
2. use high-spectrum remote-sensing to carry out the collection of sugarcane production environmental data, area coverage is wide, unmanned, and data accuracy is high.
3. adopt basic sugar analysis submodel, weather sugar analysis submodel, soil sugar analysis submodel and environment sugar analysis submodel, fully taken into account and affect each influence factor that sugar changes, improved accuracy and the science of prediction.
4. can predict the outcome to provide according to sugar and cut fortune scheme proposals, for the production decision in sugar refinery provides reference frame.
Accompanying drawing explanation
Fig. 1 is structural framing schematic diagram of the present invention.
Embodiment
Below in conjunction with accompanying drawing and most preferred embodiment, the present invention is further described, but protection scope of the present invention is not limited to following examples.
Embodiment:
As shown in the figure, a kind of high-spectrum remote-sensing sugarcane sugar analytical equipment, mainly consists of satellite information receiver module, communication module, memory module, embedded system and display module; Described satellite information receiver module is connected with memory module, communication module respectively; Described communication module, embedded system are connected with memory module respectively; Described memory module, embedded system are connected with display module respectively; Wherein, described memory module is provided with sensor information storehouse, climatic information storehouse, sugar history library, sugarcane information bank and sugar forecast model storehouse; In sugar forecast model storehouse, store the sugar forecast model being built by embedded system, comprise basic sugar analysis submodel, weather sugar analysis submodel, soil sugar analysis submodel and environment sugar analysis submodel; Described embedded system is provided with sugar predicting unit, cuts fortune predicting unit, model construction unit and model modification unit;
Described satellite information receiver module from remote sensing satellite ground receiving station, He Zhe district, weather station agricultural sector obtains corresponding historical information data, being transferred to memory module stores, model construction unit in embedded system reads in memory module corresponding historical information data, builds to be transferred to memory module after corresponding sugar forecast model and to store, before squeezing starts in season, in the time of need to predicting sugar, satellite information receiver module obtains corresponding up-to-date information data from remote sensing satellite ground receiving station and weather station, being transferred to memory module stores, sugar predicting unit in embedded system is obtained up-to-date information data and sugar forecast model from memory module, and will in the corresponding sugar forecast model of up-to-date information data substitution, carry out analyzing and processing, obtain corresponding predicted value, again each predicted value is multiplied each other with each self-corresponding factor of influence respectively, gained product is sued for peace, obtain final sugar predicted value, cutting in embedded system transported predicting unit according to sugar predicted value, and in conjunction with historical sugar data and growth period data carry out inverting, the best that obtains obtaining maximum sugar is cut the fortune time, generates and specifically cuts fortune scheme, as sugar refinery, arranges this squeezing season to cut the reference frame of fortune work.
Above-mentioned communication module comprises for sending the Beidou satellite navigation communication chip of communication short message and for the SIM card of Mobile data radio communication; Satellite information receiver module is provided with wireless communication antenna and wire communication interface; Memory module comprises for moving embedded system and depositing the built-in RAM (random access memory) card of a small amount of real time data and for the external RAM (random access memory) card of long-term storage mass data; Embedded system adopts the microprocessor of compatible mobile phone operating system; What display module adopted is touch display screen.
This apparatus structure is simple, esy to use, safe and reliable, use cost is low; Adopt basic sugar analysis submodel, weather sugar analysis submodel, soil sugar analysis submodel and environment sugar analysis submodel, fully taken into account and affect each influence factor that sugar changes, improved accuracy and the science of prediction; Can predict the outcome to provide according to sugar and cut fortune scheme proposals, for the production decision in sugar refinery provides reference frame.
Claims (10)
1. a high-spectrum remote-sensing sugarcane sugar analytical equipment, mainly consists of satellite information receiver module, communication module, memory module, embedded system and display module; Described satellite information receiver module is connected with memory module, communication module respectively; Described communication module, embedded system are connected with memory module respectively; Described memory module, embedded system are connected with display module respectively; It is characterized in that: described memory module is provided with sensor information storehouse, climatic information storehouse, sugar history library, sugarcane information bank and sugar forecast model storehouse; In sugar forecast model storehouse, store the sugar forecast model being built by embedded system, comprise basic sugar analysis submodel, weather sugar analysis submodel, soil sugar analysis submodel and environment sugar analysis submodel; Described embedded system is provided with sugar predicting unit, cuts fortune predicting unit, model construction unit and model modification unit;
Described satellite information receiver module from remote sensing satellite ground receiving station, He Zhe district, weather station agricultural sector obtains corresponding historical information data, being transferred to memory module stores, model construction unit in embedded system reads in memory module corresponding historical information data, builds to be transferred to memory module after corresponding sugar forecast model and to store, before squeezing starts in season, in the time of need to predicting sugar, satellite information receiver module obtains corresponding up-to-date information data from remote sensing satellite ground receiving station and weather station, being transferred to memory module stores, sugar predicting unit in embedded system is obtained up-to-date information data and sugar forecast model from memory module, and will in the corresponding sugar forecast model of up-to-date information data substitution, carry out analyzing and processing, obtain corresponding predicted value, again each predicted value is multiplied each other with each self-corresponding factor of influence respectively, gained product is sued for peace, obtain final sugar predicted value, cutting in embedded system transported predicting unit according to sugar predicted value, and in conjunction with historical sugar data and growth period data carry out inverting, the best that obtains obtaining maximum sugar is cut the fortune time, generates and specifically cuts fortune scheme, as sugar refinery, arranges this squeezing season to cut the reference frame of fortune work.
2. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 1, is characterized in that: described communication module comprises for sending the Beidou satellite navigation communication chip of communication short message and for the SIM card of Mobile data radio communication.
3. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 1 and 2, is characterized in that: described satellite information receiver module is provided with wireless communication antenna and wire communication interface.
4. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 3, is characterized in that: described memory module comprises for moving embedded system and depositing the built-in RAM (random access memory) card of a small amount of real time data and for the external RAM (random access memory) card of long-term storage mass data.
5. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 3, is characterized in that: described embedded system adopts the microprocessor of compatible mobile phone operating system; What described display module adopted is touch display screen.
6. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 1, is characterized in that: described historical information data comprise the historical sugar data that each sugar refinery in the historical high-spectrum remote sensing data of magnanimity that obtains Zhe district from remote sensing satellite ground receiving station, climatic information that on-site weather station, Cong Zhe district obtains, sugarcane essential information He Youzhe district that You Zhe district agricultural sector provides provides; Described up-to-date information data comprise that from remote sensing satellite ground receiving station, obtaining up-to-date on-site weather station, high-spectrum remote sensing data He Congzhe district obtains up-to-date climatic information.
7. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 6, is characterized in that: described high-spectrum remote sensing data comprises photosynthesis amount, radiant quantity, vegetation index, soil moisture content, the content of organic matter and content of mineral substances; Described climatic information comprises day and night temperature, rainfall amount and illuminance; Described sugarcane essential information comprises sugar cane breed, plants the phase, perennial root time, growth cycle, planting density and growing way index.
8. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 7, is characterized in that: the input message of described basic sugar analysis submodel comprises sugar cane breed, plants the phase, perennial root time, growth cycle, planting density and growing way; The input message of described weather sugar analysis submodel comprises day and night temperature, rainfall amount and illuminance; The input message of described soil sugar analysis submodel comprises soil moisture content, the content of organic matter and content of mineral substances; The input message of described environment sugar analysis submodel comprises photosynthesis amount and radiant quantity.
9. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 1, is characterized in that: the modeling method adopting during model construction cell formation sugar forecast model in described embedded system comprises difference equation method, data fitting method, linear programming technique and probabilistic method.
10. high-spectrum remote-sensing sugarcane sugar analytical equipment according to claim 1, it is characterized in that: described factor of influence is by drawing the characteristic curve diagram of sugarcane Back ground Information, weather, soil and environmental data and sugar historical data, and using the average gradient of every characteristic curve as the factor of influence of this feature.
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