CN101949916B - Remote sensing quantitative inversion method for soil moisture supply amount - Google Patents
Remote sensing quantitative inversion method for soil moisture supply amount Download PDFInfo
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Abstract
The invention discloses a remote sensing quantitative inversion method for soil moisture supply amount. The method comprises the integration of dynamic simulation of crop growth, remote sensing quantitative inversion, soil moisture balance and kinetic equation so as to obtain the soil moisture supply amount from a certain time interval to the entire growth period of a crop growth period. The characteristics of dynamic simulation technology and remote sensing quantitative inversion technology for crop moisture stress information are integrated, so that real-time and dynamic monitoring of the soil moisture supply amount in the crop growth period is realized. The largest advantage of the method is that the monitoring of the soil moisture supply amount is dynamic in the aspect of time and continuous in the aspect of space.
Description
Technical field
The present invention relates to a kind of remote sensing quantitative inversion method of crop whole growing soil moisture quantity delivered, carry out the dynamic monitoring of the information of coercing with the closely-related crop water of agricultural production by plant growth dynamic Simulation Techniques and remote sensing quantitative inversion technology.
Background technology
Soil moisture and plant growth are closely related, traditional soil moisture and the monitoring method of crop water are to adopt the soil moisture content of the method measurement different levels of ground field observation, coerce information by calculating the soil moisture quantity delivered and the crop water that obtain a certain period again.The plant growth dynamic Simulation Techniques is according to meteorological condition, edaphic condition, plant growth characteristic and arable farming and control measures simulation crop yield, liquid manure balance and plant growth and the Physiology and biochemistry parameter between the puberty and the model of structural parameters.Crop growth model can be used for simulating a certain period of plant growth to soil water balance and the crop water of whole growing and coerces information, utilizes this technology to carry out draught monitor as texas,U.S.Data on above-mentioned two kinds of methods all are based on a little obtain the information of coercing of crop water, and are spatially representative relatively poor, and it is bigger and ageing relatively poor etc. to waste time and energy, pay wages.
Soil moisture and crop water are coerced the remote sensing quantitative inversion technology of information.Utilize remote sensing earth observation data can acquisition face on a large scale soil moisture and crop water coerce information, be one of present remote sensing technology main application fields in agricultural.Cover situation according to the face of land, this inversion technique can be divided into two classes simply: a class covers soil thermal inertia method suitable under the less situation and microwave remote sensing method etc. on the face of land, effect when these class methods have vegetation to cover on the face of land is relatively poor, and is the monitoring result of water stress information in a certain short period; Another kind of is the monitoring method that is applicable under the coverage condition of the face of land, these class methods crop water that generally to be the remotely-sensed data of utilizing visible light, near infrared and thermal infrared wave band carry out a certain period of plant growth by inverting surface temperature and vegetation index etc. is coerced the remote sensing monitoring of information, as with ten days or month be the cycle, also can't directly apply at present the monitoring of crop whole growth phase water stress information, and can't directly contact with the foundation of soil moisture quantity delivered.
Summary of the invention
(1) technical matters that will solve
The technical problem to be solved in the present invention is: overcoming on traditional point of application observation and simulated soil moisture and crop water, to coerce the space representativeness of information poor, even be difficult to be suitable for and the difficulty of businessization operation the real-time and dynamic monitoring of realization crop water stress information in whole growing in certain areas.
(2) technical scheme
In order to solve the problems of the technologies described above, the invention provides a kind of remote sensing quantitative inversion method of soil moisture quantity delivered, it may further comprise the steps:
Dynamic similation: according to the observation data on the observation station of crop ground and plant growth characteristic operation crop growth model, the moisture of simulation plant growth parameter and each layer of soil profile;
Quantitative inversion: based on broadband reflectivity, vegetation index and surface temperature, utilize the plant growth parameter of empirical model and a certain period of semiempirical model inverting; Simultaneously, based on vegetation index and surface temperature, utilize the quantitative crop water that obtains a certain period of drought monitoring method of condition vegetation humidity index to coerce information;
Integrated: as to set up plant growth parameter and crop water according to soil moisture kinetic model and water balance and coerce relational model between the information, by the soil moisture quantity delivered in the integrated acquisition crop growth period.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, in the described dynamic similation step, described observation data comprises: weather data, soil attribute data, crop water and fertilizer management data; Described plant growth characterisitic parameter comprises: crop vernalization characterisitic parameter, photoperiod characterisitic parameter, pustulation period characterisitic parameter, kernal number characterisitic parameter, potential grouting rate parameter, the heavy parameter of potential single stem fringe of florescence and leafing interval characteristics parameter; The plant growth parameter of simulation comprises: the crop of crop leaf area index, biomass and crop.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, described quantitative inversion comprises:
Vegetation index calculates: according to the calibration coefficient of satellite borne sensor, the near-infrared band after application atmospheric correction and the geometry correction and the remotely-sensed data of red spectral band are calculated normalized differential vegetation index;
The inverting of surface temperature: according to the calibration coefficient of satellite borne sensor, the remotely-sensed data inverting surface temperature of the thermal infrared wave band after application atmospheric correction and the geometry correction;
Crop water is coerced the inverting of information: according to the definition of condition vegetation humidity index, use that normalized differential vegetation index and surface temperature are carried out satellite when passing by or the calculating of the quantification draught monitor of synthetic period of maximal value; Determine that according to the phenology feature of the variation characteristic of time series condition vegetation humidity index and crop the crop water in plant growth stage coerces information;
The inverting of plant growth parameter: based on the plant growth parameter of seasonal effect in time series normalized differential vegetation index, ground observation and the plant growth parameter of crop growth model simulation, application experience and semiempirical model carry out the inverting of plant growth parameter.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, in the inverting of described surface temperature, to single-range sensor application normalized differential vegetation index approximate treatment emissivity, inverting surface temperature then; To two wave bands and multiband sensor, use split window algorithm inverting surface temperature.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, the inversion method of described plant growth parameter is linear regression method, perhaps logarithmic relationship model, perhaps exponential relationship model.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, described integrated comprising:
Plant growth parameter(s) and crop water according to described dynamic similation are coerced information, and plant growth is divided into some stages, and with the plant growth parameter(s) in described some stages over time rule express with linear or nonlinear mathematical formulae;
Use described linearity or nonlinear mathematical formulae is set up the soil moisture kinetic model;
Move the soil moisture kinetic model on the whole, obtain soil profile moisture rule over time on the whole;
According to the soil moisture quantity delivered in the Changing Pattern calculating crop growth period of soil profile moisture.
In the remote sensing quantitative inversion method of above-mentioned soil moisture quantity delivered, described plant growth parameter comprises the crop of crop leaf area index, biomass and crop.
(3) beneficial effect
The dynamic Simulation Techniques that the present invention coerces crop water information combines with remote sensing quantitative inversion technology, utilize the weather data of ground observation, the soil data, plant growth characteristic and arable farming and control measures are dynamically simulated the crop leaf area index, biomass, output, liquid manure balance and crop water are coerced parameters such as information, utilize piggyback satellite remotely-sensed data inverting leaf area index, biomass, output and crop water such as coerce at information, by soil water balance and kinetics equation foundation contact between the two, realize the remote sensing comprehensive and quantitative inverting of soil moisture quantity delivered in the crop growth period, monitor a certain period crop water and coerce the method for information and dynamically be generalized to the crop whole growing using remote sensing technology, reach crop water and coerce information in real time and the purpose of dynamic monitoring, and the monitoring of the soil moisture quantity delivered that this method realizes is dynamic in time, spatially is continuous.
Description of drawings
Fig. 1 is the workflow sketch of the remote sensing quantitative inversion method of soil moisture quantity delivered of the present invention;
Fig. 2 is the inversion result synoptic diagram of the remote sensing quantitative inversion method embodiment of soil moisture quantity delivered of the present invention.
Embodiment
Below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.Following examples are used for explanation the present invention, but are not used for limiting the scope of the invention.
The needs of the inventive method is integrated plant growth dynamic Simulation Techniques and remote sensing quantitative inversion technology and development thereof, studied the inversion method of crop whole growth phase soil moisture quantity delivered, and the appliance computer program has realized follow-up data processing software module, formed one and overlapped the comparatively remote sensing quantitative inversion system of the soil moisture quantity delivered of system, this system can be used for the inverting from a certain period to whole growth phase soil moisture quantity delivered during the plant growth, improved crop water and coerced the technology content of remote-sensing inversion of information and the timeliness of monitoring thereof.
As shown in Figure 1, the remote sensing quantitative inversion method of soil moisture quantity delivered of the present invention comprises following flow process:
(1) dynamic similation
Crop growth model is comparatively extensive in the application of present stage, is according to meteorological condition, edaphic condition and arable farming and control measures simulation crop yield, liquid manure balance and plant growth and the Physiology and biochemistry parameter between the puberty and the model of structural parameters.Crop growth model generally is that time step is dynamically described plant growth, growth and output forming process and to the response of environment with the sky, the basic physiological ecological process of crop can be described quantitatively, " crop-soil-weather " is done as a whole the description, can describe the factors such as light, temperature, water, fertilizer and field cultivation and control measures comparatively exactly to the influence of plant growth and growth.
The inventive method is utilized the consistent of parameters such as crop phenology feature, leaf area index, biomass and output that crop growth model not only will make simulation and ground observation, and the soil water balance information that makes simulation and ground observation is consistent.
In the methods of the invention, dynamic similation is that Simulation result generally can only represent the plant growth information on the point according to the observation data on the point and plant growth characteristic operation crop growth model.Observation data on the point comprises: (1) weather data: comprise a day the highest and lowest temperature, daily precipitation amount, day sunshine time etc.; (2) soil attribute data: comprise soil nutrient and moisture information and the soil physical and chemical property etc. measured before the soil profile sowing; (3) crop management measure: comprise the data such as crop water and fertilizer management that obtain by ground investigation.The plant growth characterisitic parameter comprises: according to the data that obtain in (1), (2), (3), using for many years, weather data obtains the plant growth characterisitic parameter item by item by the operation crop growth model, comprise the heavy parameter of the potential single stem fringe of vernalization characterisitic parameter, photoperiod characterisitic parameter, pustulation period characterisitic parameter, kernal number characterisitic parameter, potential grouting rate parameter, florescence and leafing interval characteristics parameter, crop phenology feature, output in recent years and the harvest date of using actual observation judge whether obtain the plant growth characterisitic parameter correct.The output data of dynamic similation comprise: soil moisture and crop water data and soil moisture and crop water equilibrium criterion, Soil Nitrogen nutrition and crop nitrogen nutrition data and Soil Nitrogen nutrition and crop nitrogen nutrition equilibrium criterion, and plant growth parameter, wherein plant growth parameter comprises leaf area index (Leaf Area Index, LAI), biomass, the number of blade and the output of each ingredient, crop growth rate and withered rate etc.
(2) quantitative inversion
Utilize the remote sensing quantitative inversion technology of satellite remote sensing date inverting broadband reflectivity, vegetation index and surface temperature etc. comparatively ripe; Inverting crop phenology feature, leaf area index, biomass and the isoparametric technology of output are also among constantly improving, and the inverting time scale of these parameters mostly is day or a certain period.
One of remote sensing quantitative inversion technology that the inventive method adopts is based on broadband reflectivity, vegetation index and surface temperature etc., utilize empirical model and a certain period of semiempirical model inverting, as one day, leaf area index and biomass, and the crop of crop etc.; Another quantitative inversion technology is based on vegetation index and surface temperature, utilizes the drought monitoring method of condition vegetation humidity index to obtain a certain period quantitatively, as ten days, crop water coerce information.The draught monitor result of binding time sequence condition vegetation humidity index, and combine with phenology feature and dynamic similation result, can provide crop main breeding time, especially be in the high crop water that covers breeding time and coerce information.
The quantitative inversion of the inventive method mainly comprises following process:
(a) calculating of vegetation index: according to the calibration coefficient of satellite borne sensor, near-infrared band after application atmospheric correction and the geometry correction and the remotely-sensed data of red spectral band calculating normalized differential vegetation index (Normalized Differential Vegetation Index, NDVI).
For the high remotely-sensed data of temporal resolution, also to use the maximal value generated data product that the maximal value synthetic technology generates NDVI.
Perhaps, (the NDVI data product as Moderate Imaging Spectroradiomete (Moderate-resolution Imaging Spectroradiometer, MODIS)) directly carries out the calculating of vegetation index can also to use existing relevant remote sensor.
With the rule that the plant growth time series changes, determine the phenology feature of crop, as the breeding time of NDVI maximal value correspondence according to NDVI.
(b) inverting of surface temperature: according to the calibration coefficient of satellite borne sensor, the remotely-sensed data inverting surface temperature of the thermal infrared wave band after application atmospheric correction and the geometry correction (Land Surface Temperature, LST); Single-range sensor application NDVI is calculated emissivity approx, and then carry out temperature retrieval; To two wave bands and multiband sensor, mainly use split window algorithm inverting LST; For the high remotely-sensed data of temporal resolution, also to use the maximal value generated data product that the maximal value synthetic technology generates LST.
Perhaps, the LST data product that can also use relevant remote sensor directly carries out the inverting of surface temperature.
(c) crop water is coerced the inverting of information: according to the definition of condition vegetation humidity index, use that normalized differential vegetation index and surface temperature are carried out satellite when passing by or the calculating of the quantification draught monitor of synthetic period of maximal value; Determine that according to the phenology feature of the variation characteristic of time series condition vegetation humidity index and crop the crop water in plant growth stage coerces information.
Determine that the crop water of the main growth phase of crop is coerced information and to the influence of crop production according to the phenology feature of the variation characteristic of time series condition vegetation humidity index and crop.
(d) inverting of plant growth parameter: based on the plant growth parameter of seasonal effect in time series NDVI data, ground observation and the plant growth parameter of crop growth model simulation, application experience and semiempirical model carry out the inverting of plant growth parameter, the preferred linear regression method of inversion method or logarithmic relationship model, or exponential relationship model.
Perhaps, the data products such as plant growth parameter that can also use relevant remote sensor directly carry out the inverting of plant growth parameter.
(3) integrated
Exist the relation that interdepends with mutual restriction between soil moisture content and the plant growth parameter, observation data on the research of traditional soil moisture content mainly is based on a little, relation between research soil moisture and the plant growth parameter, the soil moisture kinetic model is usually with the input of plant growth parameter as model, not only can explain the relation between crop LAI and biomass etc. and the soil moisture, but also consider that illumination and temperature are to the influence of plant growth parameter
The inventive method is based on soil water balance and kinetics equation, plant growth parameter dynamic similation and remote-sensing inversion and water stress information are linked together nearly, by operation soil moisture kinetics equation on the face, realize the quantitative inversion of soil moisture quantity delivered on a large scale.
Among the inventive method dynamic similation and the quantitative inversion gained result, the plant growth parameter is the output of model.Concerning the plant growth parameter of crop growth model dynamic similation, can obtain with the sky is dynamic similation result on the point of step-length, and concerning the plant growth parameter of remote sensing quantitative inversion, what obtain usually is inversion result on the face of satellite when passing by.When operation soil moisture kinetic model, at first according to parameter and soil moisture dynamic variation rules such as the leaf area index of crop growth model simulation, biomasss, plant growth is divided into some stages, and the leaf area index in these stages and biomass etc. in time (my god) Changing Pattern can express with linear or nonlinear mathematical formulae; Pass by constantly according to satellite then or crop LAI that the synthetic period of maximal value obtains and biomass etc., utilize these mathematical expression formula stage by stage that the correlated variables in the soil moisture kinetic model is substituted or assimilate, set up soil moisture kinetics equation stage by stage; Obtain constantly in remotely-sensed data, based on parameters such as vegetation index inverting leaf area index and biomasss, and the crop water that reference conditions vegetation humidity index reflects coerces information, with these parameter substitution soil moisture kinetics equations, moves the soil moisture kinetics equation on the whole; The operation of soil moisture kinetic model on the face can obtain soil profile moisture rule over time on the whole, calculates in the crop growth period a certain period to the soil moisture quantity delivered of whole growing according to the Changing Pattern of soil profile moisture at last.
The remote sensing quantitative inversion method of soil moisture quantity delivered of the present invention, the dynamic Simulation Techniques of crop water being coerced information combines with remote sensing quantitative inversion technology, utilize the weather data of ground observation, the soil data, plant growth characteristic and arable farming and control measures are dynamically simulated the crop leaf area index, biomass, output, liquid manure balance and crop water are coerced parameters such as information, utilize piggyback satellite remotely-sensed data inverting leaf area index, biomass, output and crop water such as coerce at information, by soil water balance and kinetics equation foundation contact between the two, realize the remote sensing comprehensive and quantitative inverting of crop growth period soil moisture quantity delivered, monitor a certain period crop water and coerce the method for information and dynamically be generalized to the crop whole growing using remote sensing technology, reach crop water and coerce information in real time and the purpose of dynamic monitoring.
The above only is preferred implementation of the present invention; should be pointed out that for those skilled in the art, under the prerequisite that does not break away from the technology of the present invention principle; can also make some improvement and replacement, these improvement and replacement also should be considered as protection scope of the present invention.
Claims (4)
1. the remote sensing quantitative inversion method of a soil moisture quantity delivered is characterized in that, may further comprise the steps:
Dynamic similation: according to the observation data on the observation station of crop ground and plant growth characterisitic parameter operation crop growth model, the moisture of simulation plant growth parameter and each layer of soil profile;
Quantitative inversion: based on broadband reflectivity, vegetation index and surface temperature, utilize the plant growth parameter of empirical model and a certain period of semiempirical model inverting; Simultaneously, based on vegetation index and surface temperature, utilize the quantitative crop water that obtains a certain period of drought monitoring method of condition vegetation humidity index to coerce information;
Integrated: as to set up plant growth parameter and crop water according to soil moisture kinetic model and water balance and coerce relational model between the information, by the soil moisture quantity delivered in the integrated acquisition crop growth period; In the described dynamic similation step, described observation data comprises: weather data, soil attribute data, crop water and fertilizer management data; Described plant growth characterisitic parameter comprises: crop vernalization characterisitic parameter, photoperiod characterisitic parameter, pustulation period characterisitic parameter, kernal number characterisitic parameter, potential grouting rate parameter, the heavy parameter of potential single stem fringe of florescence and leafing interval characteristics parameter; The plant growth parameter of simulation comprises: the crop of crop leaf area index, biomass and crop;
Described quantitative inversion comprises:
Vegetation index calculates: according to the calibration coefficient of satellite borne sensor, the near-infrared band after application atmospheric correction and the geometry correction and the remotely-sensed data of red spectral band are calculated normalized differential vegetation index;
The inverting of surface temperature: according to the calibration coefficient of satellite borne sensor, the remotely-sensed data inverting surface temperature of the thermal infrared wave band after application atmospheric correction and the geometry correction;
Crop water is coerced the inverting of information: according to the definition of condition vegetation humidity index, use that normalized differential vegetation index and surface temperature are carried out satellite when passing by or the calculating of the quantification draught monitor of synthetic period of maximal value; Determine that according to the phenology feature of the variation characteristic of time series condition vegetation humidity index and crop the crop water in plant growth stage coerces information;
The inverting of plant growth parameter: based on the plant growth parameter of seasonal effect in time series normalized differential vegetation index, ground observation and the plant growth parameter of crop growth model simulation, application experience and semiempirical model carry out the inverting of plant growth parameter.
2. the remote sensing quantitative inversion method of soil moisture quantity delivered as claimed in claim 1 is characterized in that, in the inverting of described surface temperature, to single-range sensor application normalized differential vegetation index approximate treatment emissivity, inverting surface temperature then; To two wave bands and multiband sensor, use split window algorithm inverting surface temperature.
3. the remote sensing quantitative inversion method of soil moisture quantity delivered as claimed in claim 1 is characterized in that, the inversion method of described plant growth parameter is linear regression method, perhaps logarithmic relationship model, perhaps exponential relationship model.
4. the remote sensing quantitative inversion method of soil moisture quantity delivered as claimed in claim 1 is characterized in that, described integrated comprising:
Plant growth parameter and crop water according to described simulation are coerced information, and plant growth is divided into some stages, and with the plant growth parameter in described some stages over time rule express with linear or nonlinear mathematical formulae;
Use described linearity or nonlinear mathematical formulae is set up the soil moisture kinetic model;
Move the soil moisture kinetic model on the whole, obtain soil profile moisture rule over time on the whole;
According to the soil moisture quantity delivered in the Changing Pattern calculating crop growth period of soil profile moisture.
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| CN103149220B (en) * | 2013-01-30 | 2016-03-16 | 中国科学院对地观测与数字地球科学中心 | A kind of inversion method of unifrequency microwave radiometer soil moisture |
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