CN104123558A - Multi-source distributed remote sensing discrimination method and system for geothermal resources - Google Patents

Abstract

The invention relates to a multisource distributed remote sensing discrimination method and a multisource distributed remote sensing discrimination system for geothermal resources, wherein the method comprises the following steps: a data acquisition step, which is used for acquiring multi-source remote sensing image data; the data processing step comprises the steps of obtaining temperature color coding image information by processing multispectral remote sensing image data through a temperature and emissivity separation algorithm, color coding and imaging; establishing a geological structure interpretation mark of geothermal resources for radar remote sensing image data and carrying out geological structure interpretation; establishing a remote sensing stratum lithology interpretation mark for the high-resolution remote sensing image data and carrying out remote sensing stratum lithology interpretation; and a data integration step, namely, overlapping, projection transformation and registration are carried out on the three paths of information obtained in the data processing step, the position of the geothermal resource is obtained through integration, and multi-source distributed remote sensing judgment of the geothermal resource is realized. The method realizes accurate judgment of geothermal resources by processing, interpreting and integrating multi-source remote sensing image data.

Description

The distributed remote sensing method of discrimination of multi-source and the system of geothermal energy resources

Technical field

The present invention relates to remote sensing technology and application, particularly a kind of distributed remote sensing method of discrimination of multi-source and system that is applicable to geothermal energy resources.

Background technology

Geothermal energy resources are a kind of novel energy and the resources that can regenerate and reuse, it is generally acknowledged that geothermal energy resources originate from Earth lava and radioelement decay.Ground water circulation, capillary action and fracture, magmation etc. can be heat energy from the underground earth's surfaces of taking to, on earth's surface and underground certain depth area, form thermal gradient, adopt the terrestrial materials thermal emissivity of remote sensing techniques detection and the parameter of temperature, utilize temperature and the emissivity separation algorithm of thermal infrared remote sensing, can fast detecting surface temperature, and remote sensing techniques can fast detecting surface temperature, be subject to the huge precision of surface condition less-restrictive and quantity of information higher, can be good at being applied among geothermal energy resources investigation.Remote sensing techniques is progressively applied in geothermal prospecting, utilizes remote sensing techniques on certain space scale, to find geothermal anomaly.Much underground heat is all relevant with tectonic structure, and tectonic structure is the important content of research underground heat.Utilizing remote sensing technology method geologize structure is one of important content of remote-sensing geology work.Active fault of certain scale, can cut wrong stratum, or controls deposition and magmatic exhalation thereof, or synchronizes turnover etc. along the landforms difference, wrench deformation that break to form various tectonic landforms and controlling both sides and water system.Therefore, their active state can be judged by information from objective pattern and hue information on satellite image.And radar has certain penetrability, work in recent years shows, Radar Technology has very important effect in tectonic structure decipher.Radar Technology is mainly used in geologic examination, the analysis of geological process, the research of the research of exterior planets, geology of mineral deposit, the aspects such as application of geologic hazard such as research, lithology and tectonic structure of geological movement in recent years.

The Remote Sensing Study of existing geological resource is used for the GEOLOGICAL INTERPRETATION of multi-spectral remote sensing image data and supposition mode that temperature decipher mutually combines is carried out, the main shortcoming of these technology is as follows: the rift structure that (1) utilizes remote sensing image data to carry out GEOLOGICAL INTERPRETATION is the surperficial rift structure that can see, for the thicker fracture of buried depth, macrotectonics, often cannot solution translate.And many structures relevant with geothermal energy resources often buried depth is larger, therefore, practical application effect is undesirable; (2) remote sensing techniques of utilizing is in the past come mainly to show with the form of image pixel, carries out image stack, fit exists certain difficulty with other data; (3) remote Sensing Interpretation in the past is often used single source data, exists the problem that remote sensing image data can not be verified mutually.

Summary of the invention

The present invention is directed to supposition mode that GEOLOGICAL INTERPRETATION and the temperature decipher of prior art by multi-spectral remote sensing image data mutually combine carries out the rift structure that the Remote Sensing Study of geothermal energy resources only can obtain earth's surface and causes the problem that effect is undesirable, remote sensing image data cannot be verified mutually and recognition accuracy is low, provide a kind of distributed remote sensing method of discrimination of multi-source of geothermal energy resources, by the accurate differentiation to the processing of multi-source Remote Sensing Images data, decipher and integration realization geothermal energy resources.The invention still further relates to a kind of distributed remote sensing judgement system of multi-source of geothermal energy resources.

Technical scheme of the present invention is as follows:

The distributed remote sensing method of discrimination of multi-source of geothermal energy resources, is characterized in that, described method comprises the steps:

Data acquisition step, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data;

Data processing step, comprise and multi-spectral remote sensing image data are obtained to the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; SAR image data are interfered with phase unwrapping and processed and set up the tectonic structure interpret tag of geothermal energy resources and carry out tectonic structure decipher; High-resolution remote sensing image data, by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object, and are set up remote sensing formation lithology interpret tag and carried out the decipher of remote sensing formation lithology;

Data integration step, temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology that data processing step is obtained superposes, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

Multi-spectral remote sensing image data are obtained the temperature value of Multi-spectral Remote Sensing Data inverting in data processing step by temperature and emissivity separation algorithm, then by multifractal method or Kriging method, temperature value is changed into after isotherm variable described isotherm variable is corresponding with coordinate and carries out coloud coding and become figure to process the temperature coloud coding image information that obtains.

In data processing step, be the feature of radar return to be set up to the geological fracture structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, the decipher of described geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.

The polynary color transformation technology of in data processing step, high-resolution remote sensing image data acquisition being used comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, the wave band number of the separated converter technique judgement of employing minimal noise high-resolution remote sensing image data to give prominence to the useful information in view data, adopts remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram with the noise in separated high-resolution remote sensing image data.

In data processing step, be according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, to set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology.

Described data integration step utilizes that the multi-source data of the vector quantization that GIS technology obtains data processing step superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure.

The distributed remote sensing judgement system of multi-source of geothermal energy resources, is characterized in that, comprises the data acquisition facility, data processing equipment and the data integration device that connect successively,

Data acquisition facility, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data;

Data processing equipment, comprise the first data processing equipment, the second data processing equipment and the 3rd data processing equipment that are all connected with data acquisition facility, described the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; Described the second data processing equipment is interfered by SAR image data and phase unwrapping is processed and sets up the tectonic structure interpret tag of geothermal energy resources and carries out tectonic structure decipher; Described the 3rd data processing equipment, and is set up remote sensing formation lithology interpret tag and is carried out the decipher of remote sensing formation lithology by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object high-resolution remote sensing image data;

Data integration device, be connected with first, second, and third data processing equipment respectively, for temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology are superposeed, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

Described the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data inverting by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, then by multifractal method or Kriging method, temperature value is changed into after isotherm variable described isotherm variable is corresponding with coordinate and carries out coloud coding and become figure to process the temperature coloud coding image information that obtains.

Described the second data processing equipment is the feature of radar return to be set up to the geological fracture structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, the decipher of described geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.

The polynary color transformation technology that described the 3rd data processing equipment is used high-resolution remote sensing image data acquisition comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, the wave band number of the separated converter technique judgement of employing minimal noise high-resolution remote sensing image data to give prominence to the useful information in view data, adopts remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram with the noise in separated high-resolution remote sensing image data;

And/or, described the 3rd data processing equipment is according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, to set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, and foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology.

Described data integration device utilizes that the multi-source data information of the vector quantization that GIS technology obtains data processing equipment superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure.

Technique effect of the present invention is as follows:

The present invention relates to a kind of distributed remote sensing method of discrimination of multi-source of geothermal energy resources, by data acquisition step, realize the multi-source Remote Sensing Images data acquisition of multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data, data processing step is carried out data processing for different remote sensing image datas, multi-spectral remote sensing image data are obtained to the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; SAR image data are interfered with phase unwrapping and processed and set up the tectonic structure interpret tag of geothermal energy resources and carry out tectonic structure decipher; High-resolution remote sensing image data, by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object, and are set up remote sensing formation lithology interpret tag and carried out the decipher of remote sensing formation lithology; Data integration step to temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology superpose, projective transformation and registration, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.The present invention is to obtaining the temperature value of multi-spectral remote sensing image data and carrying out coloud coding and become figure to process, realize the coloud coding of the vector quantization of IRMSS thermal band, avoided prior art to cause carrying out with other data the problem that fit has difficulties with the form performance IRMSS thermal band of image pixel; The present invention by high-resolution remote sensing image data by polynary color transformation and set up remote sensing formation lithology interpret tag, and to SAR image data processing tectonic structure interpret tag, and top layer and the degree of depth decipher of the geological fracture structure of geothermal energy resources have been realized, for the identification of the structure of the thicker geothermal energy resources of buried depth provides foundation, avoided prior art just for the surperficial rift structure that can see, to infer that mode decipher causes the undesirable problem of practical application effect.The invention solves the problem of the conformation identification difficulty being hidden under coverture, by geothermal energy resources being carried out to top layer and the degree of depth decipher of geological fracture, coordinate temperature coloud coding image information, the integrated processing of comprehensive stack of the information of carrying out, integrate the position of geothermal energy resources, fast and effeciently identify geothermal energy resources, the drawback that obtain and the data processing of multi-source Remote Sensing Images data avoided prior art only to use single source data to exist remote sensing image data mutually to verify, between multi-source Remote Sensing Images data, can realize mutual checking, improved the accuracy of the identification of geothermal energy resources, provide to reconnoitre with engineering and arrange foundation.

The invention still further relates to a kind of distributed remote sensing judgement system of multi-source of geothermal energy resources, comprise the data acquisition facility connecting successively, data processing equipment and data integration device, data acquisition facility can obtain multi-source Remote Sensing Images data, data processing equipment is by the first inner data processing equipment, the second data processing equipment and the 3rd data processing equipment carry out respectively different processing to multi-source Remote Sensing Images data, the coloud coding of decipher and temperature information with become figure, finally to several data, the integrated processing that superposes realizes the accurate differentiation of geothermal energy resources to data integration device.This system for be the tectonic structure decipher of the deep layer of geothermal energy resources, the identification of the coloud coding image information relevant with temperature on the decipher of remote sensing formation lithology and earth's surface, the information relevant with geothermal energy resources that multi-source Remote Sensing Images data are hidden discloses and overall treatment, realizing the multi-source remote sensing of geothermal energy resources differentiates, can effectively solve the many technical matters for the remote sensing exploration of geothermal energy resources, after system is processed, achievement is simple, recognition accuracy is high, meet in the use the operation of enterprise work, can arrange and reconnoitre the important technology data that provides for mineral rights delineation in early stage provides guidance and later stage engineering.

Accompanying drawing explanation

Fig. 1 is the process flow diagram of the distributed remote sensing method of discrimination of the multi-source of geothermal energy resources of the present invention.

Fig. 2 is the temperature color-coded graph in the data processing step of the inventive method, multi-spectral remote sensing image data processing being obtained.

Fig. 3 is the geological fracture structure decipher result figure in the data processing step of the inventive method, SAR image data processing being obtained.

Fig. 4 is the remote sensing formation lithology decipher result figure in the data processing step of the inventive method, high-resolution remote sensing image data processing being obtained.

Fig. 5 is that result figure is differentiated in the distributed remote sensing of the multi-source of geothermal energy resources.

Fig. 6 is geothermal energy resources prognostic chart.

Fig. 7 is the structural representation of the distributed remote sensing judgement system of the multi-source of geothermal energy resources of the present invention.

Embodiment

Below in conjunction with accompanying drawing, the present invention will be described.

The distributed remote sensing method of discrimination of multi-source that the present invention relates to a kind of geothermal energy resources, the flow process of the method as shown in Figure 1, comprises the steps:

Data acquisition step, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data.Wherein, multi-spectral remote sensing image data are as ASTER remote sensing image data, can select cloudless, less without snow, vegetation, day and night temperature to convert little data in winter; SAR image data, as PALSAR SAR image data, can be selected a pair of radar data, the data that horizontal base line and vertical parallax are less; High-resolution remote sensing image data are as high-resolution remote sensing image data such as GEOEYE, QUICKBIRD, WORLDVIEW, can select cloudless, without snow, vegetation cover few autumn or spring data.

Data processing step, comprise and multi-spectral remote sensing image data are obtained to the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; SAR image data are interfered with phase unwrapping and processed and set up the tectonic structure interpret tag of geothermal energy resources and carry out tectonic structure decipher; High-resolution remote sensing image data, by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object, and are set up remote sensing formation lithology interpret tag and carried out the decipher of remote sensing formation lithology.

Data integration step, temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology that data processing step is obtained superposes, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

The distributed remote sensing method of discrimination of multi-source of geothermal energy resources of the present invention for be that other method often can not solve areal coverage tectonic information, the geothermal energy resources that are hidden under thick coverture are identified difficult problem, adopting the remote sensing Distributed identification of multi-source is core methed, mainly that multi-source Remote Sensing Images data are retrained, the heat transfer structure relevant with geothermal energy resources and permeable structure are identified, and the Thermal Infrared Data in multi-spectral remote sensing image data is carried out to the coloud coding of vector quantization, the information relevant with geothermal energy resources that remotely-sensed data is hidden discloses and overall treatment, special announcement is hidden in the tectonic information under thick coverture, carrying out multi-source Remote Sensing Images data verifies mutually, the accuracy of identification is provided, it is a kind of state-of-the-art technology of differentiating for geothermal energy resources remote sensing, can identify effectively rapidly geothermal energy resources, provide to reconnoitre with engineering and arrange foundation.Below the concrete steps of the distributed remote sensing method of discrimination of the multi-source of geothermal energy resources of the present invention are elaborated.

In data acquisition step, obtain after multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data, it is according to San Ge branch, to complete respectively the processing of different pieces of information that data processing step can be understood as.

One, first branch carries out data processing to multi-spectral remote sensing image data, by temperature and emissivity separation algorithm, obtain the temperature value of Multi-spectral Remote Sensing Data, this temperature value is the temperature value of inverting preferably, by multifractal method or Kriging method, temperature value is changed into isotherm variable again, then isotherm variable is corresponding with coordinate and carry out coloud coding and become figure to process obtaining temperature coloud coding image information.Specific as follows:

1, by temperature and emissivity separation algorithm, obtain the temperature value of Multi-spectral Remote Sensing Data, be called for short temperature separated.The principle of temperature and emissivity separation algorithm is to utilize NEM normalization emissivity algorithm to estimate surface temperature value, calculate 10-14 five wave band greatest irradiation values, emissivity utilizes iterative algorithm to remove sky background radiation from descending sky radiation, the temperature range precision of final inverting is at ± 1.5K, and emissivity precision is ± 0.015.To the Thermal Infrared Data in Multi-spectral Remote Sensing Data, adopt following two formula to carry out temperature separated with emissivity:

$T=\frac{c_2}{\mathrm{\λ}\ln (1+\frac{{\mathrm{\ϵc}}_1}{{\mathrm{\λ}}^{5}R})}$

$\mathrm{\ϵ}=\frac{{\mathrm{R\λ}}^5(e^{\frac{c_2}{\mathrm{\λT}}}-1)}{c_1}$

Wherein: T is temperature, the wavelength that λ is Thermal Infrared Data, ε is emissivity, c ₁, c ₂for constant, c ₁=3.74818 * 10 ^-4w μ m ², c ₂=1.43878 * 10 ⁴k μ m; R is spectral radiance, can calculate by formula below:

$R={\mathrm{LMIN}}_{\mathrm{\λ}}+\left(\frac{{\mathrm{LMAX}}_{\mathrm{\λ}}-{\mathrm{LMIN}}_{\mathrm{\λ}}}{\mathrm{QCALMAX}}\right)\mathrm{QCAL}$

QCAL is the actual emanations of Thermal Infrared Data, LMIN _λspectral radiance value while being QCAL=0, LMAX _λbe the spectral radiance value at QCAL=QCALMAX, QCALMAX is the image radiation value of data.

What specify is, by the otherness of contrast inverting temperature and observed temperature, adopt linear regression method to inverting temperature and observed temperature trend analysis, from trend analysis and linear relationship, can draw, reconnoitring temperature that district utilizes thermal infrared inverting and be consistent in observed temperature general trend, and observed temperature and inverting temperature linearity correlativity very good, so the temperature value of Multi-spectral Remote Sensing Data inverting can meet actual computation needs.

2, by multifractal method and Kriging method, temperature value is changed into isotherm variable.Because said temperature value is the form with grating image or temperature pattern, exist, according to coordinate, grating image carried out to vector quantization, namely temperature pattern is transformed into isotherm variable:

1) list coordinate and the temperature value of each point on temperature pattern, form VectorLayer, be point vector

P(T) _i，j＝(x _i，j，y _i，j，T _i，j)

X _{i, j}for temperature pattern, i is capable, the coordinate figure of j row, T _{i, j}for image, i is capable, the accounting temperature value of j row.1<i<m, 1<j<n, m and n are temperature pattern ranks maximal values.

2) extreme difference calculates and according to extreme difference, vector point is calculated

1. by following formula, carry out extreme difference calculating:

$R\left(T\right)=\underset{1<i,j<m,n}{\max }{T}_{i,j}-\underset{1<i,j<m,n}{\min }{T}_{i,j}$

In formula, even if the temperature data of T for obtaining above, T _i,jfor i in temperature data T is capable, the actual temp value of j row, 1<i<m, 1<j<n, m and n are temperature pattern ranks maximal values.

2. judge the absolute value of extreme difference R (T) | R (T) |, if extreme difference differs larger employing multifractal method, extreme difference differs less employing Kriging method; Can carry out extreme difference judgement by specific numerical value ε, if | R (T) | > ε, adopt multifractal method, if | R (T) | < ε, adopts Kriging method.

A, multifractal method

Every a line of temperature pattern (or each row) is seen as to a spatial sequence (establishing the capable n row of m), obtain the T of each sequence _iindividual extreme difference and standard deviation, set up R (T _i)/S (T _i), T _idata pair, if loose point be distributed near straight line, the slope of this straight line is Hurst Exponent a _i, Fractal Dimension namely.

(a1) first calculate the dimension of each row (column), step is as follows:

The extreme difference of every a line (line number i):

$R\left(T_i\right)=\underset{1<j<n}{\max }{T}_j-\underset{1<j<n}{\min }{T}_j$

T _jbe the temperature value of capable j the data of i, n is maximum columns.

The standard deviation of every a line (line number i):

$S\left(T_i\right)=\sqrt{\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}(T_j-\frac{1}{n}\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{T}_j)}$

Set up the loose point of extreme difference and standard deviation relation,

$R\left(T_i\right)/S\left(T_i\right)\&Proportional;\left(\frac{\mathrm{\&pi;}}{2}\right)a_i$

A _ifor row minute dimension, T _jbe the temperature value of capable j the data of i, n is maximum columns.

In like manner can divide dimension b by calculated column _j.

(a2) set up a minute dimension matrix, element is

d _i，j＝(a _i，b _j) i＝1，2，...m；j＝1，2，...n

(a3) calculate the total dimension A of row

$R\left(T_A\right)/S\left(T_A\right)\&Proportional;{\left(\frac{\mathrm{\&pi;}}{2}\right)}^A$

Wherein

$R\left(T_A\right)=\underset{1<p,j<i,n}{\max }{T}_{p,j}-\underset{1<p,j<i,n}{\min }{T}_{p,j}$

$S\left(T_A\right)=\sqrt{\frac{1}{i\&times;n}\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\underset{p=1}{\overset{i}{\mathrm{\&Sigma;}}}(T_{p,j}-\frac{1}{i\&times;n}\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}\underset{p=1}{\overset{i}{\mathrm{\&Sigma;}}}{T}_{p,j})}$

I is line number.

In like manner can the total dimension B of calculated column

(a4) calculate minute dimensional vector distance of each unit

${\mathrm{\&Delta;d}}_{\mathrm{ij}}=\sqrt{{(A-a_i)}^2+{(B-b_i)}^2},i=\mathrm{1,2},...,n;j=\mathrm{1,2},...,m$

To every bit T _{i, j}distance calculate Δ d _ij, draw isotherm variable.

B, Krieger disposal route

Kriging method is, in limited area, regionalized variable is carried out to a kind of method without inclined to one side optimal estimation.

The temperature value image T drawing according to previous calculations, calculates certain 1 T _{i, j}near n temperature value is expressed as T _{i, j}(x _k), k=1 ..., n.

(b1) calculation expectation and covariance

Mathematical expectation vector m (x)

$m\left(x\right)=\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{T}_{i,j}\left(x_k\right)$

Calculate covariance c (x)

$c\left(x\right)=\frac{{\mathrm{\&Sigma;}}_{k=1}^n\left[(T_{i,j}\left(x_k\right)-m\left(x\right)){(T_{i,j}\left(x_k\right)-m\left(x\right))}^T\right]}{(n-1)}$

(T _{i, j}(x _k)-m (x)) ^tfor (T _{i, j}(x _k)-m (x)) transposed vector.

(b2) calculate unbiasedness

$m\left(x\right)\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{T}_{i,j}\left(x_k\right)$

Namely

$\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k=1$

λ _kfor to be evaluated.

(b3) calculate optimality

Meeting under unbiasedness condition variance

${\mathrm{\&sigma;}}^2=\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{(T_{i,j}\left(x_k\right)-\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k{T}_{i,j}\left(x_k\right))}^2$

Build Lagrange's equation

$F={\mathrm{\&sigma;}}^{2}2\mathrm{\&mu;}(\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k-1)$

μ and λ _kfor to be evaluated, respectively F is asked to μ and λ _kderivative and to make it be 0.Namely can obtain Kriging formula group.

(b4) calculate Kriging formula

$\left\{\begin{array}{c}\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_{k}c\left(x\right)-\mathrm{\&mu;}=c\left(x\right)\\ \underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k=1\end{array}\right.$

(b5) carry out interpolation

Calculating field Krieger interpolation method

$T_{i,j}\left(x\right)=\underset{k=1}{\overset{n}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_k{T}_{i,j}\left(x_k\right)$

Field T to each point _{i, j}(x) all carry out interpolation, draw isotherm variable.

3, isotherm variable is corresponding with coordinate and carry out coloud coding and become figure to process

According to Krieger conversion above or multifractal conversion, draw isotherm variable T _{i, j}or Δ d (x) _ijutilize T _{i, j}unified representation, i.e. T _{i, j}represent T _{i, j}or Δ d (x) _ij.On remote sensing images, according to calculating the temperature value of every in coordinate correspondence image, and temperature value is carried out to colored assignment by height:

1) list each point coordinate and accounting temperature value, form VectorLayer

(x ₁,y ₁,T ₁₁)，(x ₂,y ₂,T ₂₂)，...，(x _m,y _n,T _mn)

X ₁..., x _nthe X-axis coordinate figure of image, y ₁..., y _nfor the Y-axis coordinate figure of image, T ₁₁..., T _mnfor temperature value.

2) by the value of isotherm variable, coordinate is sorted out, be about to isotherm variable corresponding with coordinate, namely, when temperature isoline equals some values, extract the coordinate of all these temperature values.

If T _ij=T ₁, so,

(x _i1,y _j1,T ₁),(x _i2,y _j2,T ₁),...，(x _im,y _jn,T ₁)

X _i1..., x _imfor the X-axis coordinate figure of the image that extracts, y _i1..., y _jny-axis coordinate figure for the image that extracts.

The above-listed array representation of using

denotation coordination has specific temperature value relevant.

3) x _i1..., x _imand y _i1..., y _jncarry out line, and put on temperature value, namely coordinate (x _i1, y _i1) ..., (x _im, y _jn) with lines, connect.

4) according to above-mentioned steps, temperature interval is Δ T, to minimum temperature value MIN (T _{i, j}), MIN (T _{i, j})+Δ T, MIN (T _{i, j})+2 Δ T ..., until maximum temperature value MAX (T _{i, j}) carry out similar processing, can be to composing value of color between two temperature isoline that differ Δ T, thus realize coloud coding and become figure to process, obtain temperature coloud coding image information as shown in Figure 2.What in Fig. 2, show is gray-scale map, by temperature isoline, divide each region, for example, shown in label A, region is 24.7-25.0 ℃, shown in label B, region is 24.1-24.4 ℃, and shown in label C, region is 25.0-25.3 ℃, and shown in label D, region is 25.3-25.6 ℃, shown in label E, region is 25.9-26.2 ℃, and region shown in label F is 24.4-24.7 ℃ etc.

Two, second branch interferes and phase unwrapping processing SAR image data, and the feature of radar return is set up to the tectonic structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, the decipher of described geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.Wherein, the detailed step that interference and phase unwrapping are processed is as follows:

The mistiming that interferometer radar utilizes sensor to pass by for twice calculates, apart from ground distance R ₁and R ₂difference can utilize phase difference to measure, an image value is multiplied by the value of complex conjugate another image, thereby form to interfere.Can utilize GDEM or SRTM-DEM elevation information in processing procedure, to remove earth's surface elevation impact as phase place contribution, mainly contain two rail difference, three rail difference and four rail difference, the easy-to-use computing of general selection two rail difference, the multiple precision such as the permanent scatterer of disposal route also having (needing many scape data simultaneously to process) and short baseline (needing many scapes data simultaneously to process) can reach millimetre-sized disposal route.Satellite is when twice imaging, and sensor is respectively R to ground point distance ₁and R ₂, the poor information of two scape image phase (interferometric phase) is as follows:

$\mathrm{int}=S_1\&CenterDot;S_2^T$

$\mathrm{\&phi;}=\frac{4\mathrm{\&pi;}}{\mathrm{\&lambda;}}(R_2-R_1)$

S ₁and S ₂the satellite position that represents twice imaging, φ represents phase place, λ represents radar wavelength, R ₁and R ₂represent the oblique distance between satellite sensor and ground point.

In phase, both comprised Ground Deformation information φ during twice imaging of imaging region _def, comprised again terrain information φ _topo, the oval trend phase of reference that causes of earth curvature _flat, orbit error φ _orbit, atmospheric effect φ _atmos, space-time dephasing closes the noise information φ cause _noisedeng much information.

φ＝φ _def+φ _topo+φ _flat+φ _ortit+φ _atmos+φ _noise

If in interfering processing engineering, use outside dem data just can remove landform phase information φ _topo; By orbit parameter, can remove reference ellipsoid phase place trend φ _flat; If general baseline is shorter, orbit error φ _orbitless, can ignore, and noise information φ _noisecan process to suppress by filtering; Atmospheric effect φ _atmosthe measuring error causing shows as low-frequency information on space scale, can ignore.

Outside dem data can be isolated interferometric phase φ after adding processing and orbit parameter to participate in calculating _def', in order to obtain Ground Deformation, can obtain Ground Deformation phase by phase unwrapping _def.φ _defwith radar line of sight direction Ground Deformation Δ r (Δ r=R ₂-R ₁) be directly proportional.

${\mathrm{\&phi;}}_{\mathrm{def}}={\mathrm{\&phi;}}_{\mathrm{def}}^{\&prime;}+2\mathrm{k\&pi;}=\frac{4\mathrm{\&pi;}}{\mathrm{\&lambda;}}\mathrm{\&Delta;r},(k=0,\&PlusMinus;1,\&PlusMinus;2\&CenterDot;\&CenterDot;\&CenterDot;)$

The method of phase unwrapping is more, has branch to cut region growing method, minimum cost stream method, least square method, multi-grid method, Green Function Method etc.

SAR image data are being carried out after above-mentioned processing, according to SAR image data earth observation feature and fracture, the feature of radar return is being set up to the tectonic structure interpret tag of geothermal energy resources.Because conventional radar image can not well reflect fracture in heavy-cover area, ordinary radar image can not carry out in heavy-cover area Interpretation of Fracture Structures in other words, and interferometer radar has been avoided the problem of cladding thickness, from Ground Deformation feature, carry out the degree of depth decipher of remote-sensing geology.The present invention carries out the geological fracture structure decipher of the degree of depth according to image texture characteristic, both sides streak feature is different and have a foundation as fault recognition of linear feature, what particularly interference fringe had the feature that obviously staggers is exactly structural belt, geological fracture structure decipher result figure as shown in Figure 3.The decipher of geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture, is mainly that faulting stress feature is different: the direction of fracture is consistent with the direction of interference fringe, and fracture has a feature for property, is water guide fracture; Interference fringe direction and rift direction near normal, fracture has the feature of pressure property, is heat conduction rupture.

Three, San branch is by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object to high-resolution remote sensing image data, this polynary color transformation technological selection comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, adopt wave band number that the separated converter technique of minimal noise judges high-resolution remote sensing image data with the noise in separated high-resolution remote sensing image data to give prominence to the useful information in view data, adopt remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram, according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology.

1, polynary color transformation

The object of polynary color transformation is for the useful information in outstanding view data, expands the difference between different images feature, to improve the decipher of image and analysis ability.Polynary color transformation effect is relevant with the data characteristics of image itself.Mainly contain two aspects: the difference of Spectral Characteristic between (1) outstanding different atural object is mainly without geologic body, rock type and geologic anomaly for the ease of identification aspect GEOLOGICAL APPLICATION; (2) outstanding spatial shape, edge, lines and texture and structural characteristic etc., as tectonic structure, linear body and morphologic characteristics etc.Mainly by spatial alternation, carry out the separated converter technique of the reasonable minimal noise of preferred effect.

1) the separated conversion of minimal noise (Minimum Noise Fraction Rotation, MNF Rotation) technology is for judging the dimension (being wave band number) of view data inherence, noise in mask data, reduces with the computation requirement amount in aftertreatment.MNF is twice stacked principal component transform in essence.Conversion for the first time (noise covariance matrix based on estimating) is for separating of the noise with readjusting in data, and this step operation makes the noise data after conversion only have minimum variance and there is no the correlativity between wave band.The standard principal component transform to noise whitening data (Noise-whitened) for the second time.In order further to carry out wave spectrum processing, by checking that final eigenwert and associated picture carry out the inherent dimension of decision data.Data space can be divided into two parts: a part is relevant to larger eigenwert and corresponding characteristic image, remainder and approximately uniform eigenwert and the prevailing image correlation of noise.Suppose that each the observation signal z of remotely-sensed data obtaining can be expressed as: z=s+n

Wherein, n is noise (supposing uncorrelated with s), and s is the signal (noiseless) under ideal state.The covariance matrix of observation signal z is Σ _z, the covariance matrix of noise is Σ _n.Hypothesis matrix F is Σ _nalbefaction matrix:

$F^{\mathrm{\&Gamma;}}{\mathrm{\&Sigma;}}_{n}F=I,F^{\mathrm{\&Gamma;}}F={\mathrm{\&Delta;}}_n^{-1}$

In formula, Δ _nfor by Σ _nthe diagonal matrix that forms of eigenwert.In fact matrix E is by Σ _nproper vector form, meet E ^ΓΣ _ne=Δ _n.

Note Σ _w=F ^ΓΣ _zf, for adjusting the covariance matrix of noise (albefaction) observed data afterwards, carries out major component variation to this matrix, can obtain matrix G, makes

G ^ΓΣ _wG＝Δ _w，G ^ΓG＝I

In formula, Δ _wby Σ _wthe diagonal matrix that forms of eigenwert, G has corresponding proper vector to form.

NAPC (NOISE-ADJUSTEDPRINCIPALCOMPONENTS) converts total transformation matrix H=FG.

MNF operator is eigenvectors matrix.

2) image lithology strengthens processing

After the separated conversion of minimal noise, can also carry out image lithology and strengthen processing, mainly to utilize a series of technological means to improve the visual effect of image, define the difference of Spectral Characteristic between different atural object, improve the sharpness of image, image is changed into a kind of form that is more suitable for carrying out in people or computing machine analyzing and processing.

Remote sensing image data is after accurate normalized, and DN codomain is distributed in 0≤r _kin≤255 scopes.To any r in [0,255] interval _kvalue is carried out as down conversion:

When gray level is discrete value, the approximate probable value that replaces of available frequency, that is:

$p_r\left(r_k\right)=\frac{n_k}{N},(0\&le;r_k\&le;255;k=\mathrm{0,1,2},...,L-1)$

In formula, L is number of greyscale levels; p _r(r _k) be the probability of getting k level gray-scale value; n _kin image, to occur the number of times of k level gray scale; N is pixel count in image.

Conventionally being represented by formula with the discrete form of histogram cumulative distribution function for obtaining even histogrammic figure image intensifying:

$s_k=T\left(r_k\right)=\underset{i=0}{\overset{k}{\mathrm{\&Sigma;}}}\frac{n_j}{N}=\underset{i=0}{\overset{k}{\mathrm{\&Sigma;}}}{p}_r\left(r_j\right),(0\&le;r_k\&le;255;k=\mathrm{0,1,2},...,L-1)$

Its contravariant is changed to: r _k=T ^-1(s _k)

Main algorithm is as follows:

List the gray level of original image and the rear image of conversion: i, j=0,1 ..., L-1, wherein L is the number of gray level;

The number of pixels n of each gray level of statistics original image _i;

Calculate original image histogram: n is the total number of original image pixels;

Calculate accumulation histogram: $p_j=\underset{k=0}{\overset{j}{\mathrm{\&Sigma;}}}p\left(k\right);$

Utilize the gray-scale value after greyscale transformation function computational transformation, and round up: j=INT[(L-1) p _j+ 0.5];

Determine that greyscale transformation is related to i → j, accordingly gray-scale value f (m, the n)=i of original image is modified to g (m, n)=j;

The number of pixels n of each gray level after statistics conversion _j;

The histogram of image after computational transformation:

2, remote sensing formation lithology decipher

The decipher of remote sensing formation lithology comprises gives different image features different geological Significance, comprises the many factors such as stratum, rock mass lithologic character and lithofacies and fault tectonic and Volcanic Mechanism, and this need to infer unknown stratum geologic feature from known stratum geology.Remote-sensing geology decipher work be take compile mode as main, having geologic information and regional tectonics background is being carried out on the comprehensive basis of analyzing, using multi-spectrum remote sensing image figure, high-resolution remote sensing image figure as base map, with geologic map in district or ground thermal map, repair as a reference volume decipher.In decipher process, follow the principle of macroscopic view → microcosmic → macroscopic view, from known to unknown, from simple to complicated, from can decipher degree higher region to low area, incremental, decipher repeatedly, progressively in-depth.Decipher working routine is specially: the preliminary decipher → field reconnaissance of just build+remote-sensing geology of interpret tag+supplement improves that interpret tag → decipher in detail comprehensively → field checking+comprehensive analysiss → remote-sensing geology figure works out and decipher instructions is write.

1) interpret tag is set up

In decipher process first with reference to existing geologic information and map, by the contrast between known geologic body, structure etc. and remote sensing image, according to the characteristic feature analysis of the reflectance spectrum of master stratum, lithology in high-resolution remote sensing image data and formation, according to complicated geology degree difference, set up respectively the remote sensing formation lithology interpret tag of stratum, magmatite and the structure etc. of different times.From coarse to fine, to geologic body unit, along with the in-depth of decipher, progressively supplementary, substantial, perfect by image subarea, through the overall process of decipher.The direct looks that geologic body, geological phenomenon show to reflect on remote sensing image are direct interpret tag, and sentence by indirect factors such as topography and geomorphology, water system, vegetation the geologic content of translating, are indirect interpret tag.

2) remote Sensing Interpretation

Fully collecting and tentatively grasping and reconnoitre on the basis of district's geological condition and characteristics of remote sensing image, take Remote sensing photomap as main information source, in reference area, existing geologic information and map, take the mode that compiles combination to carry out decipher.First choose that tectonic structure is simple, lithostratigraphy exposure is more complete, image feature area clearly, carrying out the remote-sensing geology of system repaiies after volume decipher, according to by some principle to line to face, from the easier to the more advanced, progressively expand to the periphery the unknown area of identical geologic condition, same image feature so that the GEOLOGICAL INTERPRETATION of the whole district again.By geologic body image feature difference, the preliminary decipher of image combination rule, divide compilation unit, by attributive classification, generate remote Sensing Interpretation sketch, for field geology reconnaissance phase route, arrange foundation is provided.

Stratum: adopt lithostratigraphy method compilation, mapping unit as standard, is assigned to " group " with reference to former geologic map stratum more in choice.

Irruptive rock: adopt the compilation of age+lithology method for expressing, make full use of in decipher that it is planar, ring-type, ellipticity, lensing, the spatial shape such as irregular, color (tunes), landforms combination and draw a circle to approve and distinguish different rock type intrusive masss from the image feature such as the discordant relations of bedded rock around, shadow line structure mark.

Rift structure: decipher emphasis be take tomography, zone of fracture as main, has the image feature of important indicative significance suitably to represent in the drawings with reference to existing data for those reflection fault properties, occurrence, tektonite, associated structure, tectonic association and the raw sequential of one-tenth.Feature for the latent layer of those reflections, zone of fracture should be represented in detail.Mutual relationship of the feature Ji Yu neighboring region linear images such as the extension of linear image, bifurcated, compound, interspersed, meet etc. is carried out after decipher confirmation, by its geological property classification, name and divided rank.

Ring image: the annular information such as the planar reflection in earth's surface that the domal uplift that emphasis decipher aligned structure more than two encloses annular that limit forms, the little intrusive body of earth's surface exposure, Volcanic Mechanism, Hidden Granite Body form or other thermal source activity cause.

3) remote Sensing Interpretation figure establishment

Through detailed decipher and on-the-spot correction decipher, fully grasping and reconnoitring on the basis of district's geological condition, to setting up interpret tag before investigation, carry out complement and amendments, further determine compilation unit, utilize corresponding software, establishment remote Sensing Interpretation figure.

Drawing content comprises: geographic element, compilation unit, attribute, boundary line, code name and mutual relationship, and the content such as legend, the map title, engineer's scale.Geographic element is worked out with reference to topomap, comprises contemporary glaciation, water system, mountain system title and main place name etc., wherein reconnoitres existing water system district in, traffic and closes condition and with reference to remote sensing image, repair volume and form; In compilation, stratigraphic unit should be unified with reference to former geologic map, and stratigraphic unit is assigned to " group " more.Drawing adopts Gauss Kru&4&ger projection, Xi'an coordinate system in 1980,6 degree minute band.For keeping the consistent of drawing parameter, all maps are all used the integrated system storehouse of legend standard.For the ease of revising, drawing graphic layer structure is divided into some figure layers by different content, mainly comprises that geology wants sketch map layer, geographic map layer, the interior ornamenting figure layer of figure etc.Graphic, legend used, symbol, colour code etc. in compilation, with reference to the GB6390-86 < < of Minitry of Geology and Mineral Resources geologic map with colour standard and with chromogen the related standards of > > etc. carry out.The result of remote sensing formation lithology decipher as shown in Figure 4.In figure, solid line represents Remote Sensing Structural Interpretation, and dotted line represents remote sensing supposition structure; For example, the alluviation of region representation Quaternary system shown in label X rubble, gravel, the blanket sand of region representation Quaternary system shown in label Y, rubble, the glacial drift of region representation Quaternary system shown in label Z boulder, mud, the sandy soil of region representation Quaternary system shown in label O, mud, the limestone of region representation lime shown in label P, the gravel of region representation Quaternary system shown in label Q, sand, region representation monzonitic granite shown in label W.

After completing the data processing step of above-mentioned one, two, three branches, start data integration step.Data integration step utilizes that the multi-source data information of the vector quantization that GIS technology obtains data processing step superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure.

This step is mainly to utilize GIS platform, according to coordinate a series of map superpose, projective transformation and registration.Various signs are comprehensively analyzed, and preferred target area.Various information is carried out preferably over the ground, outstanding crucial effectively information.

1) GIS can superpose integrated to the various information relevant with looking for ore deposit according to the concrete coordinate of terrestrial object information.When application GIS carries out multi-source information stack, first need the projective parameter of various information to carry out remarks accurately, make earth model, projection pattern and reel number etc. all consistent, avoid occurring location dislocation equal error.Then need every kind of information all to do a layer, as utilize MAPGIS to process, need to carry out to some map the restructuring in " point ", " line ", " district "." point " refers to word, code name information; " line " refers to tomography and various geological boundaries etc.; " district " refers to geologic body etc.Finally, utilize GIS platform various information to looking for the favourable sign in ore deposit all summarize and analyze, from various information analyses, extract relevant information, optimize to analyze, preferably target area.

2) informix

By GIS platform, the temperature coloud coding image hum pattern layer of remote sensing vector quantization, tectonic structure decipher figure layer and remote sensing formation lithology decipher figure layer are carried out to projective transformation and coordinate registration, by intersecting the overall treatments such as analysis, discriminatory analysis or weighted stacking analytic operation, research abnormal morphology, intensity of anomaly, the abnormal space regularity of distribution and meaning thereof, differentiate preferred significant point.The distributed remote sensing of multi-source of geothermal energy resources of the present invention is differentiated result as shown in Figure 5, and in figure, the white institute's region that encloses is that geothermal energy resources are differentiated district.

3) extremely choose

Preferably, can on GIS platform, comprehensive various information further come preferably extremely, then in conjunction with Field Geology Investigations and GPS location technology, on the comprehensive basis of analyzing of multi-source information, carry out field and investigate on the spot.

The distributed remote sensing method of discrimination of multi-source of geothermal energy resources of the present invention can further carry out analysis decision processing according to the content of the several respects such as the coloud coding image of GEOLOGICAL INTERPRETATION, temperature and Interpretation of Fracture Structures.For example, 1) utilize remote sensing images analysis remote sensing morphologic characteristics, determine the geomorphic units such as river, lake, mountain region, forest land, farmland; 2) utilize GEOLOGICAL INTERPRETATION graphical analysis rock signature; 3) utilize interferometer radar to analyze structure, analyze the distribution of compressional structure, extensional structure, the permeable structure in district is carried out to interpretation; 4) utilize the temperature anomaly of temperature pattern to compressional structure, heat transfer structure in district is carried out to interpretation; 5), according to the position of heat transfer structure and permeable structure, determine prediction target area.After the distributed remote sensing method of discrimination of multi-source of geothermal energy resources of the present invention, the remote sensing images that comprise information of forecasting that can draw, geothermal energy resources prognostic chart as shown in Figure 6, utilize RGB to synthesize a width false color image, the predictably heat conduction rupture of hot-zone and water guide fracture, the image of working it out is like this indication predicting information directly, is more applicable to reconnoitring the decision-making of arranging with engineering.

The invention still further relates to a kind of distributed remote sensing judgement system of multi-source of geothermal energy resources.The remote sensing exploration that the present invention is geothermal energy resources provides a kind of brand-new technical solution, by the Treatment Analysis of multi-source Remote Sensing Images data is determined to the heat conduction relevant with geothermal energy resources and the position of permeable structure with decipher, by multi-spectral remote sensing image data are carried out to thermal infrared remote sensing processing and vector quantization, and to the several data integrated processing that superposes, provide a kind of multi-source for geothermal energy resources remote sensing exploration distributed remote sensing judgement system.Special announcement is hidden in the tectonic information under thick coverture.The overall treatment of system of the present invention based in multi-source Remote Sensing Images data and integrated, can effectively solve the many technical matters for geothermal energy resources remote sensing exploration, after system is processed, achievement is simple, meet in the use the operation of surveying part, can arrange the important technology data that provides for reconnoitring with engineering of later stage.

The distributed remote sensing method of discrimination of multi-source of the geothermal energy resources that the distributed remote sensing judgement system of multi-source of geothermal energy resources of the present invention is above-mentioned with the present invention is corresponding, and also can be understood as is the system that realizes the distributed remote sensing method of discrimination of multi-source of geothermal energy resources of the present invention.The structure of system of the present invention as shown in Figure 7, comprises the data acquisition facility, data processing equipment and the data integration device that connect successively.Wherein, data acquisition facility, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data.Data processing equipment, comprise the first data processing equipment, the second data processing equipment and the 3rd data processing equipment that are all connected with data acquisition facility, described the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; Described the second data processing equipment is interfered by SAR image data and phase unwrapping is processed and sets up the tectonic structure interpret tag of geothermal energy resources and carries out tectonic structure decipher; Described the 3rd data processing equipment, and is set up remote sensing formation lithology interpret tag and is carried out the decipher of remote sensing formation lithology by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object high-resolution remote sensing image data.Data integration device, be connected with first, second, and third data processing equipment respectively, for temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology are superposeed, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

Preferably, the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data inverting by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, by multifractal method or Kriging method, temperature value is changed into isotherm variable again, then by multifractal method or Kriging method, temperature value is changed into after isotherm variable described isotherm variable is corresponding with coordinate and carries out coloud coding and become figure to process obtaining temperature coloud coding image information, temperature color-coded graph as shown in Figure 2.

Preferably, the second data processing equipment is the feature of radar return to be set up to the geological fracture structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, this geological fracture structure decipher result is as shown in Figure 3.Wherein, the decipher of geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.

Preferably, the polynary color transformation technology that the 3rd data processing equipment is used high-resolution remote sensing image data acquisition comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, the wave band number of the separated converter technique judgement of employing minimal noise high-resolution remote sensing image data to give prominence to the useful information in view data, adopts remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram with the noise in separated high-resolution remote sensing image data.The 3rd data processing equipment is according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, to set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology, and remote sensing formation lithology decipher result as shown in Figure 4.

Preferably, data integration device utilizes that the multi-source data information of the vector quantization that GIS technology obtains data processing equipment superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.The distributed remote sensing of multi-source of geothermal energy resources of the present invention is differentiated result as shown in Figure 5.

The distributed remote sensing method of discrimination of multi-source of geothermal energy resources of the present invention and the advantage of system:

1) utilize separated by temperature and emissivity of thermal infrared remote sensing, and utilize on this basis multiple analysis or Kriging method and coloud coding to generate temperature isogram (being temperature color-coded graph), reflected the trend of heat transfer structure.Lithology is fractured into the high value of geothermal anomaly, and the heat transfer structure reflecting is that East and West direction is moved towards feature, and interpretation can be verified mutually with interferometer radar decipher result is consistent.

2) by interferometer radar and radar image, can decipher reconnoitre the structure in district, utilize interferometer radar can analyze the character of structure, draw pressure property and extensional structure, permeable structure and heat transfer structure are carried out to preliminary interpretation.

3) can be combined with indoor high-resolution remote sensing image data by field, the identification of remote sensing has been carried out in realization to reconnoitring the morphologic characteristics in district, particularly high-definition remote sensing is very clear to the identification of landforms, to morphologic characteristicss such as mountain region, low mountains and hills, river, farmland, road, wetland, city, soot, forest land, water bodys, can identify.

4) utilize multiple remote sensing image data to investigate in conjunction with actual field, on the basis of interferometer radar, the decipher of radar image structure, in conjunction with the temperature isogram of Thermal Infrared Data, can carry out remote-sensing geology decipher to stratum and lithology.

5) by multi-source Remote Sensing Images data message, and the position of the heat conduction drawing and permeable structure, and the position of hydrothermal exchange generation geothermal energy resources, for geothermal prospecting provides foundation, remote sensing prediction district is proposed.

The present invention is suitable for engineering field geothermal energy resources remote sensing exploration and target area prediction, engineering is arranged and is carried out addressing, identification etc.; Also can apply the analysis of reconnoitring district's structure, the interpretation of tectonic property; Morphologic analysis, GEOLOGICAL INTERPRETATION; The inspection that the Quaternary period, constructed areal coverage, geophysics is arranged; The production application of geothermal energy resources field and research.

It should be pointed out that the above embodiment can make the invention of those skilled in the art's comprehend, but do not limit the present invention in any way creation.Therefore; although this instructions has been described in detail the invention with reference to drawings and Examples; but; those skilled in the art are to be understood that; still can modify or be equal to replacement the invention; in a word, all do not depart from technical scheme and the improvement thereof of the spirit and scope of the invention, and it all should be encompassed in the middle of the protection domain of the invention patent.

Claims (11)

1. the distributed remote sensing method of discrimination of the multi-source of geothermal energy resources, is characterized in that, described method comprises the steps:

Data acquisition step, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data;

Data processing step, comprise and multi-spectral remote sensing image data are obtained to the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; SAR image data are interfered with phase unwrapping and processed and set up the tectonic structure interpret tag of geothermal energy resources and carry out tectonic structure decipher; High-resolution remote sensing image data, by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object, and are set up remote sensing formation lithology interpret tag and carried out the decipher of remote sensing formation lithology;

Data integration step, temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology that data processing step is obtained superposes, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

2. method according to claim 1, it is characterized in that, multi-spectral remote sensing image data are obtained the temperature value of Multi-spectral Remote Sensing Data inverting in data processing step by temperature and emissivity separation algorithm, then by multifractal method or Kriging method, temperature value is changed into after isotherm variable described isotherm variable is corresponding with coordinate and carries out coloud coding and become figure to process the temperature coloud coding image information that obtains.

3. method according to claim 1, it is characterized in that, in data processing step, be the feature of radar return to be set up to the geological fracture structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, the decipher of described geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.

4. method according to claim 1, it is characterized in that, the polynary color transformation technology of in data processing step, high-resolution remote sensing image data acquisition being used comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, the wave band number of the separated converter technique judgement of employing minimal noise high-resolution remote sensing image data to give prominence to the useful information in view data, adopts remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram with the noise in separated high-resolution remote sensing image data.

5. method according to claim 4, it is characterized in that, in data processing step, be according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, to set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology.

6. according to the method one of claim 1 to 5 Suo Shu, it is characterized in that, described data integration step utilizes that the multi-source data of the vector quantization that GIS technology obtains data processing step superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure.

7. the distributed remote sensing judgement system of the multi-source of geothermal energy resources, is characterized in that, comprises the data acquisition facility, data processing equipment and the data integration device that connect successively,

Data acquisition facility, for carrying out multi-source Remote Sensing Images data acquisition, described multi-source Remote Sensing Images data comprise multi-spectral remote sensing image data, SAR image data and high-resolution remote sensing image data;

Data processing equipment, comprise the first data processing equipment, the second data processing equipment and the 3rd data processing equipment that are all connected with data acquisition facility, described the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, then carry out coloud coding and become figure to process the temperature coloud coding image information that obtains after temperature value is changed into isotherm variable; Described the second data processing equipment is interfered by SAR image data and phase unwrapping is processed and sets up the tectonic structure interpret tag of geothermal energy resources and carries out tectonic structure decipher; Described the 3rd data processing equipment, and is set up remote sensing formation lithology interpret tag and is carried out the decipher of remote sensing formation lithology by the difference of Spectral Characteristic between the useful information in the outstanding view data of polynary color transformation technology and clear and definite different atural object high-resolution remote sensing image data;

Data integration device, be connected with first, second, and third data processing equipment respectively, for temperature coloud coding image information, tectonic structure decipher and the decipher of remote sensing formation lithology are superposeed, projective transformation and registration, integrate the position of geothermal energy resources, realize the distributed remote sensing of multi-source of geothermal energy resources and differentiate.

8. system according to claim 7, it is characterized in that, described the first data processing equipment obtains the temperature value of Multi-spectral Remote Sensing Data inverting by temperature and emissivity separation algorithm to multi-spectral remote sensing image data, then by multifractal method or Kriging method, temperature value is changed into after isotherm variable described isotherm variable is corresponding with coordinate and carries out coloud coding and become figure to process the temperature coloud coding image information that obtains.

9. system according to claim 7, it is characterized in that, described the second data processing equipment is the feature of radar return to be set up to the geological fracture structure interpret tag of geothermal energy resources according to SAR image data earth observation feature and fracture, and according to image texture characteristic, carry out the geological fracture structure decipher of the degree of depth, the decipher of described geological fracture structure comprises the decipher to water guide fracture and heat conduction rupture.

10. system according to claim 7, it is characterized in that, the polynary color transformation technology that described the 3rd data processing equipment is used high-resolution remote sensing image data acquisition comprises the separated converter technique of minimal noise and the remote sensing images lithology enhancing technology of adopting, adopt wave band number that the separated converter technique of minimal noise judges high-resolution remote sensing image data with the noise in separated high-resolution remote sensing image data to give prominence to the useful information in view data, adopt remote sensing images lithology enhancing technology by the difference of Spectral Characteristic between the clear and definite different atural object of mode of accumulation histogram,

And/or, described the 3rd data processing equipment is according to the characteristic feature analysis of the reflectance spectrum of the stratum in high-resolution remote sensing image data, lithology and formation, to set up respectively the remote sensing formation lithology interpret tag of stratum, magma layer and the structure of different times, and foundation is put to line to face and the attributive classification of passing stratum, irruptive rock, rift structure and ring image in principle of peripheral expansion carries out the decipher of remote sensing formation lithology.

11. according to the system one of claim 7 to 10 Suo Shu, it is characterized in that, described data integration device utilizes that the multi-source data information of the vector quantization that GIS technology obtains data processing equipment superposes, projective transformation and registration, and by intersecting analytic approach or techniques of discriminant analysis or the overall treatment of weighted stacking analytic approach, the heat conduction of integrated extraction geothermal energy resources and the position of permeable structure.