CN109272227B - Green mine site selection method based on remote sensing data and geographic information system - Google Patents
Green mine site selection method based on remote sensing data and geographic information system Download PDFInfo
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Abstract
The invention discloses a green mine site selection method based on remote sensing data and a geographic information system, which comprises the following steps: acquiring remote sensing image data of a region to be researched and preprocessing the remote sensing image data; extracting factor information of the preprocessed remote sensing image data; quantitatively processing the extracted factor information; calculating the weight coefficient of the quantified factor information, and constructing a mine site selection linear model; wherein the factor information is selected from fracture structure, mining area location, vegetation coverage, drilling and exploring grooves, villages, river channels, roads, slopes and height differences. The invention provides a green mine site selection method based on remote sensing data and a geographic information system by utilizing a remote sensing information extraction technology and combining strong space analysis functions of space superposition, buffer area analysis and the like of a GIS (geographic information system) to provide help for green mine site selection, so that the remote sensing data plays an important role in green mine construction.
Description
Technical field
The present invention relates to geological exploration technical fields.Remotely-sensed data and geography information system are based on more particularly, to one kind
The Green Mine site selecting method of system.
Background technique
Mineral resources are the important material bases that the mankind depend on for existence, build and develop.The large-scale development and benefit of mineral products
With the development for greatly having pushed human economy and society, it is a series of also to bring environmental pollution, terrestrial reference depression, mine shake etc.
Negative effect, mineral exploration and exploitation and environment maintenance problem are the significant problems of world today's facing, reasonable, orderly, safety
Exploitation mineral resources are to maintain the guarantee of economic growth and biometric safeguard state environment.
Although abundant for some areas Kuang Ji resource reserve, since mine collection zone position is special, there is High aititude, severe cold
And the features such as arid, ecological environment is extremely fragile, and what unreasonable exploitation of mineral resources easily caused around ecological environment can not
It is inverse to destroy, in order to realize social sustainable development, need to need to carry out before mine development the Green Mine Site Selection in mine.
Remote sensing technology has the advantages such as investigative range is big, contain much information, timeliness is strong, can with extract real-time topography and geomorphology,
The information such as vegetation, water body, Human dried bloodstains, geologic Environment Problem；Geographic information system technology is a kind of to related geographical point
The technological system that cloth data are acquired, store, managing, operation, analyzing, be shown and described can extract remotely-sensed data
Information carries out the processing such as spatial analysis, can provide the two combination to scientific basis for addressing.Currently with remote sensing skill
Art carries out siting analysis and is mainly used for tunnel, refuse landfill, dam, farm, airport, market and ATM machine etc., and for green
Color mine siting analysis is substantially at space state.
Accordingly, it is desirable to provide a kind of new mine site selecting method using remote sensing investigation data, the green in the mine Lai Shixian
It develops and utilizes.
Summary of the invention
It is an object of the present invention to provide it is a kind of it is more acurrate, more directly, feasibility it is high based on remotely-sensed data and ground
Manage the Green Mine site selecting method of information system.
It is another object of the present invention to provide a kind of more imperial mining areas based on remotely-sensed data and GIS-Geographic Information System are green
Color mine site selecting method.
In order to achieve the above objectives, the present invention adopts the following technical solutions:
The present invention provides a kind of Green Mine site selecting method based on remotely-sensed data and GIS-Geographic Information System, including it is following
Step:
It obtains the remote sensing image data in area to be studied and is pre-processed；
Extract the factor information of pretreated remote sensing image data；
The factor information that quantification processing is extracted；
The weight coefficient of factor information after calculating quantification constructs mine addressing linear model；
Wherein, the factor information is selected from rift structure, mining area position, vegetation coverage, drilling and exploratory trench, village, river
Road, road, the gradient and height difference.
Green Mine site selecting method of the present invention further comprises: constructing mine site selection model according to mine addressing linear model
Result figure provides the Green Mine addressing position in area to be studied.
Further, the pretreatment is selected from radiation calibration, atmospheric correction, visual fusion, image mosaic, image cutting, shadow
One or more processing in image intensifying.
Further, the mathematical model for calculating weight coefficient is selected from analytic hierarchy process (AHP) (Analytic Hierarchy
Process, AHP), Logistic Regression model, evidence-right-weight " method, artificial nerve network model, Newmark model
Middle one kind；It preferably, is analytic hierarchy process (AHP).
Further, the mine site selection model is y=a1×C1+a2×C2...+am× Cm, wherein C1 be and fracture distance
Quantification value, C2 are with mining area apart from quantification value, and C3 is vegetation coverage quantification value, and C4 is drilling exploratory trench density quantification
Value, C5 are with village apart from quantification value, and C6 is with river apart from quantification value, and C7 is to be with road distance quantification value, C8
Gradient quantification value, C9 are height difference quantification value；a1、a2…a9For the weight coefficient of corresponding C1, C2 ... C9.
Further, the mine site selection model is y=(0.1017~0.1350) × C1+ (0.1980~0.2863) × C2
+ (0.1980~0.2863) × C3+ (0.1017~0.1241) × C4+ (0.0282~0.0355) × C5+ (0.1017~
0.1241) × C6+ (0.1017~0.1241) × C7+ (0.0550~0.0639) × C8+ (0.0550~0.0639) × C9.
The present invention also provides a kind of more imperial mining area Green Mine addressing sides based on remotely-sensed data and GIS-Geographic Information System
Method, comprising the following steps:
It obtains the remote sensing image data in area to be studied and is pre-processed；
Extract the factor information of pretreated remote sensing image data；
The factor information that quantification processing is extracted；
The weight coefficient of factor information after calculating quantification；And
Mine addressing is carried out using such as drag:
Y=0.1887 × with fracture apart from quantification value+0.0659 × and mining area apart from quantification+0.0941 × vegetation of value
Coverage quantification value+0.1236 × drilling exploratory trench density quantification value+0.1018 × and village are apart from quantification value+0.0711
× and river apart from quantification value+0.044 × with road distance quantification value+0.1554 × gradient quantification value+0.1554 ×
Height difference quantification value.
The present invention is more, and imperial mining area mine site selecting method further comprises: further, being constructed according to mine addressing linear model
Mine site selection model result figure provides the Green Mine addressing scheme in area to be studied.
Beneficial effects of the present invention are as follows:
According to the method for the present invention, using remote sensing information extractive technique, in conjunction with space overlapping, the buffer zone analysis etc. of GIS
Powerful spatial analysis functions, the present invention consider rift structure, mining area position, vegetation coverage, drilling and exploratory trench, village,
On the basis of river, road, the gradient and height difference factor information, emphasis considers mining area position and vegetation coverage, provides multiple
Preferred embodiment provides help for mine addressing, thus provides a kind of Green Mine based on remotely-sensed data and GIS-Geographic Information System
Site selecting method makes remotely-sensed data play a significant role in Green Mine construction.Method according to the invention it is possible to at-once monitor
Mine environment information and Developing status, and the factor element that can be extracted using remote sensing technology combination remote sensing image carries out mine
Green addressing and planning.
Detailed description of the invention
Specific embodiments of the present invention will be described in further detail with reference to the accompanying drawing.
Fig. 1 shows the Green Mine site selecting method flow chart based on remotely-sensed data and GIS-Geographic Information System.
Fig. 2 shows mine addressing hierarchy Models.
Fig. 3 shows rift structure information extraction figure；Wherein, dot represents mineral deposit position, and line segment represents fracture.
Fig. 4 shows the Tibet mining area Duo Long location map；Wherein, dot represents mineral deposit position, and the position irised out represents village
The village.
Fig. 5 shows the area Duo Longkuangji vegetation coverage classification figure；Wherein, dot represents mineral deposit position, the depth generation of gray scale
The size of table vegetation coverage.
Fig. 6 shows exploratory trench, drilling factor information extraction figure；Wherein, triangle represents drilling, and vertical bar represents exploratory trench.
Fig. 7 shows village factor information extraction figure；Wherein, dot represents mineral deposit position, and the position irised out represents village.
Fig. 8 shows river factor information extraction figure；Wherein, lines represent river.
Fig. 9 shows road factor information extraction figure；Wherein, lines represent road.
Figure 10 shows grade information extraction figure；Wherein, the depth of gray scale represents the size of the gradient.
Figure 11 shows height difference information extraction figure；Wherein, the depth of gray scale represents the size of height difference.
Figure 12 shows breaking factor and quantifies assignment graph.
Figure 13 shows mining area location factor and quantifies assignment graph.
Figure 14 shows Vegetation factors and quantifies assignment graph.
Figure 15 shows the drilling exploratory trench factor and quantifies assignment graph.
Figure 16 shows the village factor and quantifies assignment graph.
Figure 17 shows the river factor and quantifies assignment graph.
Figure 18 shows path divisor and quantifies assignment graph.
Figure 19 shows slope factor and quantifies assignment graph.
Figure 20 shows the height difference factor and quantifies assignment graph.
Wherein, in Figure 12-20, the depth of gray scale represents the size of quantitative assignment.
Figure 21 shows the area Duo Longkuangji mountain green color sorting location result figure.
Figure 22 shows the area Duo Longkuangji remote sensing image three-dimensional rendering figure.
Figure 23 shows the area Duo Longkuangji mine Site Selection result three-dimensional rendering figure.
Specific embodiment
In order to illustrate more clearly of the present invention, the present invention is done further below with reference to preferred embodiments and drawings
It is bright.Similar component is indicated in attached drawing with identical appended drawing reference.It will be appreciated by those skilled in the art that institute is specific below
The content of description is illustrative and be not restrictive, and should not be limited the scope of the invention with this.
According to the preferred embodiment of the present invention, a kind of Green Mine based on remotely-sensed data and GIS-Geographic Information System is provided
Site selecting method, as shown in Figure 1, comprising the following steps:
It obtains the remote sensing image data in area to be studied and is pre-processed；
Extract the factor information of pretreated remote sensing image data；
The factor information that quantification processing is extracted；
The weight coefficient of factor information after calculating quantification constructs mine addressing linear model；
Wherein, the factor information is selected from rift structure, mining area position, vegetation coverage, drilling and exploratory trench, village, river
Road, road, the gradient and height difference.
It is special for the site selecting method in mine, especially mine collection zone position, such as belong to a part of nature reserve area, height
How the region of height above sea level height, ecological environment frailty, select remote sensing to influence the factor information of data, how to determine each factor letter
The influence coefficient of breath, it is most important for mountain green color sorting location.
The presence of rift structure will cause to dive to the security and stability of mine slope and the leakproof of Tailings Dam to environment
It is threatening, is easily causing the region of the generation of the events such as geological disaster and underground water pollution；
The specific location distribution in mining area is of great significance to the determination of stope place range position in the site selection model of mine,
In addition it is also closely connected with stope industrial sites and waste-rock yard place election；
Grassland grassland is not only rare animal and plant growth habitat and herdsman herds base, also has self-restraint water and soil, prevents
Wind fixes the sand, prevent erosion and ecological balances effect, the mine place elections such as desertification sprawling should avoid as far as possible high vegetation from covering
Cover region and the meadow transplanting and repair for carrying out mine place, guarantee environmental type addressing；
Drilling, exploratory trench are primary human's engineering activities that mining area occurs, and by drilling, the estimation analysis of exploratory trench dot density
It was found that drilling, the distribution of exploratory trench and mining area position are closely related, deposit mining can substantially be determined by dot density estimation analysis
Region area；
Mine development can more or less offend local resident's faith and herdsman's interests is caused to lose, in mine during addressing
It needs to consider village factor, respects the life activity space of local resident as far as possible, to avoid the contradiction that may occur；
Distance of the mine development Site Selection apart from river can cause different degrees of influence to river water, and due to river
Corrosion function also can bring unstable factor to mine exploitation and construction；It is generally believed that apart from closer, the then mine development of river distance
It is larger with influencing each other for river, it is on the contrary then smaller；
The convenience of traffic route all has great influence to the mineral products transport after mine exploitation and construction and deposit mining,
Convenient and fast communications and transportation can greatly save manpower, financial resources, material resources；
Ramp slope and height difference size are closely related with the stability of geologic body, the higher gradient and biggish height difference energy
The appearance for directly breeding disaster body easily causes disaster when ramp slope is more than 20 degree.
By being analyzed above it is found that selecting above-mentioned rift structure, mining area position, vegetation coverage, drilling and exploratory trench, village
The village, river, road, the gradient and the height difference factor, have great importance for Green Mine addressing.Above-mentioned 9 are selected in the present invention
Factor information of a factor information as remote sensing image data, for constructing mine addressing linear model.
To complete the remote sensing geology environmental survey of the area Kuang Ji and green siting analysis work, it is necessary first to which collection research area is for example
The basic datas data such as political geography, geology, meteorology, DEM, Worldview2, GF-1, GF-2, Landsat8, and to acquisition
Remote sensing image data is pre-processed, such as carries out radiation calibration, atmospheric correction, visual fusion, shadow based on ENVI software platform
As inlaying, image cutting, the pretreatment works such as Imaging enhanced.
Then, basic political geography and geologic information is combined to carry out the area Duo Longkuangji ecology using remote sensing image after pretreatment
Geological environment information extraction simultaneously carries out quantification processing.
Then, such as analytic hierarchy process (AHP), Logistic Regression model, evidence-right-weight " method, artificial neural network are utilized
A kind of weight coefficient calculating each factor information in network model, Newmark model.
For example, being included the following steps: using the weight coefficient that analytic hierarchy process (AHP) calculates factor information
1) hierarchy Model is established；
2) Judgement Matricies；
3) weighted value of each factor is calculated.
Firstly, establish the hierarchy Model of mine Site Selection, mainly include destination layer (will solve the problems, such as),
Because of sublayer (each condition for influencing target) and solution layer.Wherein, destination layer of the present invention is the address area for selecting mine place, because
Sublayer (C) and fracture distance, with mining area distance, vegetation coverage, drilling exploratory trench density, with village distance, with river distance, and
Road distance, the gradient, height difference etc., solution layer are the final available region as mine place, specific mine addressing
Hierarchy Model is as shown in Figure 2.
Secondly, determining that each factor for the importance of mine addressing, constructs the judgement square between each factor by being compared to each other
Battle array.To carry out quantification comparison to each factor relative importance, scaling law is judged using matrix, is used in the present invention as described above
9 factors, using 1~9 scaling law, if factor i and factor j, the value range of i, j are 1~9, the ratio between importance be Cij.
If factor i is compared with factor j, importance having the same, then Cij=1；If factor i, compared with factor j, the former is slightly than the latter
It is important, then Cij=3；If factor i, compared with factor j, the former is more obvious than the latter important, then Cij=5；If factor i and factor j phase
Than comparing, the former is more of crucial importance than the latter, then Cij=7；If factor i is compared compared with factor j, the former is stronger than the latter important,
Then Cij=9.Other situations between above-mentioned adjacent judgement median (2,4,6,8), and the importance of factor j and factor i it
Than Cji=1/Cij, i.e. the inverse of the ratio between factor i and factor j importance.Because 9 factors of sublayer are respectively as follows: and are broken distance
C1, and mining area distance C2, vegetation coverage C3, drill exploratory trench density C4, and village distance C5, and river distance C6, with road
Distance C7, gradient C8, height difference C9.
According to the actual situation, the present invention selects " at a distance from mining area " and " vegetation coverage " is Main Factors, important
Property marking when assign its value range.Important ratio two-by-two is carried out for mine Site Selection region relatively to give a mark, and constructs importance square
Battle array, the results are shown in Table 1.
Each Importance of Factors matrix of table 1
Then, each factor (C) is calculated to the weight system of destination layer using each Importance of Factors matrix development of judgment matrix A
Number, as linear combination relationship it is found that feature vector corresponding to maximum eigenvalue to matrix A is normalized as each factor
Corresponding weight coefficient, calculation process are as follows:
1) the product Li of the every row element of judgment matrix A is calculated:
2) the m th Root a of Li is calculatedi:M=9,
3) standardization processing is carried out to vector:
Then TA=(a1,a2,…,am)TAs required feature vector.
4) judgment matrix Maximum characteristic root λ is calculatedmax:
In formula, (TA)iIndicate i-th of element of feature vector TA.
The weight coefficient result such as table 2 of judgment matrix is acquired, maximum eigenvalue is as follows:
λmax=9.1453
The weight coefficient range of each factor of table 2
Finally, constructing mine site selection model according to the weight coefficient of the factor information of quantification and each factor information, obtaining
Following mine addressing location formulas:
Y=(0.1017~0.1350) × and fracture distance+(0.1980~0.2863) × and mining area distance+(0.1980
~0.2863) × vegetation coverage+(0.1017~0.1241) × drilling exploratory trench density+(0.0282~0.0355) × and village
Distance+(0.1017~0.1241) × with river distance+(0.1017~0.1241) × with road distance+(0.0550~
0.0639) × gradient+(0.0550~0.0639) × height difference.
Multiple addressing schemes can be provided based on the above-mentioned mine site selection model of the present invention, are treated according to actual needs for people
It studies area and carries out mine addressing.
Mine site selecting method of the present invention preferably further includes: to construct mine site selection model according to mine addressing linear model
Result figure provides the mine addressing position in area to be studied.
It will illustrate that the present invention is based on remotely-sensed datas and geography information system using Tibet Duo Longkuang Ji Qu as embodiment below
The Green Mine site selecting method of system.
Method in following embodiments is unless otherwise instructed the conventional method of this field.
The Tibet mineral deposit Duo Long environmental remote sensing Geological Survey Projects are distant using domestic high score No. two (GF-2) and Landsat8 etc.
Satellite image data are felt after pretreatment, to Tibet Duo Longkuang collection area rift structure, mining area position, vegetation coverage, drilling
It is extracted with information such as exploratory trench, village, river, road, the gradient and height differences.
1, it obtains the remote sensing image data of Tibet Duo Longkuang Ji Qu and is pre-processed
The remote sensing shadow of Tibet Duo Longkuang Ji Qu is obtained using remote sensing satellites such as domestic high score No. two (GF-2) and Landsat8
As data.
Pretreatment cuts including radiation calibration, atmospheric correction, visual fusion, image mosaic, image, is a kind of in Imaging enhanced
Or a variety of processing.For simplicity, repeats no more herein.In the present embodiment, Fig. 3-23 is to ENVI software after pretreatment
Area (four angular coordinates are as follows: 83 ° 23 ' 33 " E, 33 ° of 00 ' 23 " N to be studied on platform；84 ° 00 ' 15 " E, 33 ° of 00 ' 23 " N；83°
13 ' 27 " E, 32 ° of 41 ' 23 " N；83 ° 50 ' 15 " E, 32 ° 41 ' 23 " N) schematic diagram carry out the knot of factor information extraction and quantitative assignment
Fruit.
2, the factor information of pretreated remote sensing image data is extracted；
Remote sensing image data is after pretreatment, to Tibet Duo Longkuang collection area rift structure, mining area position, vegetative coverage
Degree, drilling are extracted with factor informations such as exploratory trench, village, river, road, the gradient, height differences.
(1) rift structure factor information is extracted
The area Duo Longkuangji rift structure information is extracted, shows that rift structure is developed very much in the area Duo Longkuangji, always
Body has three groups: mainly in Dong-west to, east northeast-Nan Xi and northwest (NW)-east southeast to spread.Wherein approximately EW rift structure extend compared with
It is long, it is that regional fault, east northeast-Nan Xi and northwest (NW)-east southeast are smaller to being broken, is secondary fragmentation.By superposition mining area point with
Fracture information discovery mining area is distributed in Fault crossing more, illustrates the formation relationship in the area Duo Longkuangji rift structure information and mineral deposit
Closely, as shown in Figure 3.
(2) mining area location factor information extraction
It carries out being registrated analysis with Tibet Duo Longkuang collection area schematic diagram (as shown in Figure 4) by No. two remote sensing images of high score, obtain
Specific distributing position of each mineral deposit in the area Duo Longkuangji on remote sensing image, from southwest to northeastward be respectively that wooden hilllock of bunker,
If by, wave dragon, it is mostly not miscellaneous, flourish that, take, the mineral deposits such as Tie Gelong, Se Na and Ga Er are diligent.
(3) vegetation coverage factor information is extracted
The area Duo Longkuangji vegetation coverage information is extracted, grassland vegetation coverage is divided into 4 grades: non-Grass cover
Area, low Grass cover area, the middle meadow area of coverage, the praire land area of coverage obtain the area Duo Longkuangji vegetation coverage spatial framework figure,
Specific distribution is as shown in Figure 5.Wherein, non-meadow vegetation-covered area accounting 23%, area is about 46km2, low grassland vegetation covering
Area's accounting 35%, area about 70km2；Middle meadow vegetation-covered area accounting 34%, area about 68km2；Praire land vegetation accounting 8%,
Area about 16km2。
(4) drilling, exploratory trench factor information are extracted
The drilling of the area Duo Longkuangji, exploratory trench information are extracted, by extraction and statistical result it is found that being bored in the area Duo Longkuangji
Hole be 64 holes, exploratory trench number 178, drilling and exploratory trench dense distribution and be in it is parallel be arranged side by side, be mainly distributed on more Long Kuangji
In the middle part of the area and west and south, it is specific as shown in Figure 6.It is 1.62 × 10 through statistics exploratory trench area5m2, average area 911.76m2, visit
The area the slot gross area Zhan Duolong Kuang Ji gross area 0.008%.
(5) village factor information is extracted
The area Duo Longkuangji is extracted according to mark village information is extracted, it is as a result as shown in fig. 7, mostly imperial as shown in Figure 7
Three natural villages, the respectively village Ben Song, the village Sa Malong and the village Zha Duo Na are co-existed in the area Kuang Ji；Residenter house and cattle and sheep in area
Circle etc. is at totally 468, and about 51.85 ten thousand square metres of the gross area.Three, the area Duo Longkuangji village be located at the Rhone Ben Songhe, Sa Ma and
Proper autumn Watershed, meets the characteristics of mankind select water and dwell, and since natural conditions limit, local resident cannot be engaged in planting industry, more
It depends on animal husbandry for one's livelihood.
(6) river factor information is extracted
The area Duo Longkuangji river factor information is extracted, by extraction and statistical result it is found that the area Duo Longkuangji inland river
Road has a very wide distribution, extends far, and mainstream and tributary sum are 174 altogether, and main river overall length is 703.02km；The area Duo Longkuangji
Interior Main Lakes are that granny rag is wrong, are located at workspace northeast, area of lake is about 15.24km2, specific as shown in Figure 8.
(7) road factor information is extracted
The area Duo Longkuangji extracts whole district's road factor information according to mark is extracted, as a result as shown in figure 9, by scheming
Known to 9 principal traffic route (P.T.R.) 72 in the area Duo Longkuangji, it is always about 564.31km, road is mainly in that north-south extends.
(8) gradient and height difference factor information are extracted
The area the Duo Longkuangji gradient and height difference information are extracted.The gradient and height difference in the area Duo Longkuangji are at 30m points
It is extracted on the basis of resolution dem data.As shown in Figure 10, the area the Duo Longkuangji most area gradient is lower, most area
The gradient is lower than 15 degree, and region of the gradient greater than 30 degree is distributed mainly in the middle part of the area Duo Longkuangji, i.e. deposit distribution compact district.By
Height above sea level in the area Yu Duolong Kuang Ji, hypsography is relatively large, and height difference is more than that 20 meters of region is larger, is distributed mainly on Duo Longkuang
Collect area middle part, east and the west and south, as shown in figure 11.
3, quantification handle it is extracted after factor information；
Factor information carries out quantitative, normalized, could complete the Green Mine addressing of Tibet Duo Longkuang collection area and build
Mould.
(1) rift structure factor quantification
Development has a plurality of Dong-west to, east northeast-Nan Xi to the joint of fracture and some associations and breaks in the area Duo Longkuangji
The little structures such as layer.It is now based on ArcGis platform, distance is broken with distance, establishes polycyclic buffer zone analysis.Concrete operation step is such as
Under: multi-buffer area is established to fracture using the polycyclic buffer area function of analysis tool in tool box first, buffer distance is set respectively
For 500/1000/2000/4000/9000 (unit is rice), buffer area polar plot is generated；Then buffer area polar plot utilizes conversion
Tool switchs to grid；Then the extraction of the progress area Duo Longkuangji exposure mask, which is laid equal stress on, is sampled as 100m × 100m；Last counterweight sampling grids
Reclassification is carried out using grid reclassification tool and assignment realizes the quantification of breaking factor, and concrete outcome is as shown in figure 12.
(2) mining area location factor quantification
Quantitative allocation processing in mining area mainly establishes polycyclic buffer zone analysis, specific implementation flow to away from mining area distance
Are as follows: first to mineral deposit point using 800/1500/2500/4000/9000 (unit is rice) for buffer distance, establish polycyclic buffer area
Polar plot；Secondly to polycyclic buffer area polar plot be converted to grid, exposure mask cutting lay equal stress on be sampled as it is consistent with breaking factor；Finally
It carries out reclassification and realizes quantification processing, concrete outcome is as shown in figure 13.
(3) vegetation coverage factor quantification
The area Duo Longkuangji as shown in FIG. 6 vegetation coverage classification factor of diagram information is obtained, and it is carried out at quantification
Reason.Since vegetation coverage classification figure has been grating image, only need to carry out reclassification and assignment after its resampling can be complete
It is handled at quantification, concrete outcome is as shown in figure 14.
(4) drilling, exploratory trench factor quantification
Drilling, exploratory trench factor quantification process flow are as follows: the drilling of the selection area Duo Longkuangji Remotely sensed acquisition, exploratory trench first
Information is translated into unified vector point；Secondly, completing the dot density minute of vector point using ArcGis spatial analysis tool
Analysis generates dot density estimation figure；Reclassification assignment is carried out after finally estimating figure resampling to dot density degree, is realized at quantification
Reason, final result are as shown in figure 15.
(5) village factor quantification
Village, the respectively village Sa Malong, the village Zha Duonalaocun and Ben Song there are three being mainly distributed in the area Duo Longkuangji, three
Person is distributed in each mineral deposit periphery in triangular shape.The processing of its quantification mainly establishes the village information of Remotely sensed acquisition in Fig. 7
Polycyclic buffer zone analysis, buffer area distance is respectively as follows: 1000/2000/3000/5000/9000m, more close apart from village, gives a mark
Lower, on the contrary then higher, final result figure is as shown in figure 16.
(6) river factor quantification
River is developed in the area Duo Longkuangji, and local resident selects water mostly and dwells and River is local resident, domestic animal
The main drinking water source of poultry and wild animal.By establishing the polycyclic buffer zone analysis in river, buffer area distance is 500/1000/
2000/4000/9000m, and assign to divide from the near to the remote and be sequentially increased, complete the quantification processing of the water system river factor, concrete outcome
As shown in figure 17.
(7) road path divisor quantification
Quantification processing is carried out to road information, wherein it is higher apart from the more close then assignment of road, it is on the contrary then lower.It is quantitative
Change process flow is similar to fracture, and last quantification result is as shown in figure 18.
(8) gradient and height difference factor quantification
The gradient is similar with height difference treatment process, and detailed process is as follows: the Gradient progress resampling to extraction is and breaks
It is consistent to split the factor；Reclassification is carried out to different gradient range and assignment completes quantification processing.Final roll attitude, height difference assigned result
Figure is as illustrated in figures 19 and 20.
4, the weight coefficient for calculating the factor information after quantification, constructs mine addressing linear model.
The weight coefficient of factor information can pass through Logistic Regression model, evidence-right-weight " method, step analysis
Method (Analytic Hierarchy Process, AHP), artificial nerve network model, Newmark model calculate.The present embodiment
Selection analytic hierarchy process (AHP) calculates the weight coefficient of each factor information, for constructing mine addressing linear model.
In the present embodiment, because of 9 factors of sublayer, bored with fracture distance C1 with mining area distance C2, vegetation coverage C3
Hole exploratory trench density C4, and village distance C5, and river distance C6, with road distance C7, gradient C8, height difference C9.
It carries out important ratio two-by-two for the area Duo Longkuangji addressing region relatively to give a mark, the results are shown in Table 3.
Each Importance of Factors matrix of table 3
Each factor (C) is calculated to the weight coefficient of destination layer, by linear combination relationship it is found that matrix using judgment matrix
The weight coefficient corresponding to each factor: a is normalized in feature vector corresponding to the maximum eigenvalue of A1=0.1887,
a2=0.0659, a3=0.0941, a4=0.1236, a5=0.1018, a6=0.0711, a7=0.044, a8=0.1554, a9=
0.1554。
Finally, the area Duo Longkuangji mine Site Selection linear model is obtained are as follows:
Y=0.1887 × with fracture apart from quantification value+0.0659 × and mining area apart from quantification+0.0941 × vegetation of value
Coverage quantification value+0.1236 × drilling exploratory trench density quantification value+0.1018 × and village are apart from quantification value+0.0711
× and river apart from quantification value+0.044 × with road distance quantification value+0.1554 × gradient quantification value+0.1554 ×
Height difference quantification value.
(2) site selection model result figure in mine is constructed according to mine addressing linear model, the mine choosing in the area Duo Longkuangji is provided
Location scheme.
To obtain the area Duo Longkuangji mine Site Selection result figure, it is necessary first to according to the criteria for classifying of the factor each in table 4,
Reclassification and unified imparting score value are carried out to each factor, when the division of the grid factor is evaluated as fabulous being assignment to mine Site Selection
Be 10 points, evaluation be preferably to be assigned a value of 7 points, be evaluated as in be to be assigned a value of 4 points, be evaluated as being assigned a value of 2 points when difference, be evaluated as very poor
When be assigned a value of 1 point, it is final to realize that grid quantitatively normalizes；Secondly, seeking the weight system of each modeling factors using analytic hierarchy process (AHP)
Numerical value；Finally, each modeling factors are calculated according to mine Site Selection linear model using ArcGis raster symbol-base device,
Carrying out reclassification to calculated result can be obtained the area Duo Longkuangji mine Site Selection result figure, specific as shown in figure 21.
4 mine addressing modeling factors of table evaluate assignment table
Grade classification is carried out by final score to mine Site Selection model result figure (Figure 21), when score value is greater than 5.07 etc.
Grade be it is fabulous, score value between 4.41 to 5.07 grades preferably, during score value between 3.72-4.41 grade is, score value 2.95-3.72 etc.
Grade be it is poor, score value sets grade less than 2.95 to be very poor.The higher region of score value be suitable as mine place layout areas, and
The lower region of score value is not suitable for carrying out mine place layout.
Planning and displaying accurately are laid out to all kinds of places in mine in order to more intuitive, needed to Tibet Duo Longkuang Ji Qu
Remote sensing image and mine site selection model result figure carry out three-dimensional visualization processing.Present invention is primarily based on ArcGis ArcScene
Platform carries out the three-dimensional rendering processing of Various types of data, is carrying out three-dimensional rendering mistake to remote sensing image or mine model addressing result figure
Needing to use altitude data in journey, DEM (digital elevation model) data provide elevation information for Various types of data three-dimensional rendering, point
Resolution is about 10m.Specific process flow is as follows: being first turned on ArcScene software and loads dem data, remote sensing image number
According to, mine site selection model result figure, the base altitude in remote sensing image data (or site selection model result figure) attribute is then selected,
Then it selects to obtain elevation from the surface DEN, the elevation that finally will acquire is shown with 3 times of height, and three-dimensional rendering can be obtained
Figure, it is specific as shown in Figure 22 and Figure 23.
Obviously, the above embodiment of the present invention be only to clearly illustrate example of the present invention, and not be pair
The restriction of embodiments of the present invention may be used also on the basis of the above description for those of ordinary skill in the art
To make other variations or changes in different ways, all embodiments can not be exhaustive here, it is all to belong to this hair
The obvious changes or variations that bright technical solution is extended out are still in the scope of protection of the present invention.
The invention patent is by Geological Survey in China project " the Tibet mineral deposit Duo Long Technological Economy and Comprehensive appraisal of environment " (project
Number: DD20160330) and " the more metal resource base comprehensive survey evaluations of hiding northwest copper " joint funding.
Claims (6)
1. a kind of Green Mine site selecting method based on remotely-sensed data and GIS-Geographic Information System, which is characterized in that including following step
It is rapid:
It obtains the remote sensing image data in area to be studied and is pre-processed；
Extract the factor information of pretreated remote sensing image data；
The factor information that quantification processing is extracted；
The weight coefficient of factor information after calculating quantification constructs mine addressing linear model；
The factor information is selected from rift structure, mining area position, vegetation coverage, drilling and exploratory trench, village, river, road, slope
Degree, height difference,
The mine addressing linear model is y=a1×C1+a2×C2+...+a9× C9,
Wherein, y is grade score value, and C1 is with fracture apart from quantification value, and C2 is with mining area apart from quantification value, and C3 covers for vegetation
Cover degree quantification value, C4 are drilling exploratory trench density quantification value, and C5 is with village apart from quantification value, and C6 is fixed with river distance
Quantized value, C7 be with road distance quantification value, C8 be gradient quantification value, C9 be height difference quantification value；a1、a2…a9It is right
The weight coefficient for the C9 that answers C1, C2 ...,
Wherein, the mine addressing linear model are as follows:
Y=(0.1017~0.1350) × C1+ (0.1980~0.2863) × C2+ (0.1980~0.2863) × C3+ (0.1017
~0.1241) × C4+ (0.0282~0.0355) × C5+ (0.1017~0.1241) × C6+ (0.1017~0.1241) × C7+
(0.0550~0.0639) × C8+ (0.0550~0.0639) × C9.
2. Green Mine site selecting method according to claim 1, which is characterized in that constructed according to mine addressing linear model
Mine site selection model result figure provides the Green Mine addressing position in area to be studied.
3. Green Mine site selecting method according to claim 1, which is characterized in that it is described pretreatment selected from radiation calibration,
Atmospheric correction, visual fusion, image mosaic, image cut, one or more processing in Imaging enhanced.
4. Green Mine site selecting method according to claim 1, which is characterized in that the mathematical modulo for calculating weight coefficient
Type is analytic hierarchy process (AHP), Logistic Regression model, evidence-right-weight " method, artificial nerve network model or Newmark mould
Type.
5. a kind of more imperial mining area Green Mine site selecting methods based on remotely-sensed data and GIS-Geographic Information System, which is characterized in that packet
Include following steps:
It obtains the remote sensing image data in area to be studied and is pre-processed；
Extract the factor information of pretreated remote sensing image data；
The factor information that quantification processing is extracted；
The weight coefficient of factor information after calculating quantification；And
Mine addressing is carried out using following mine addressing linear model:
Y=0.1887 × with fracture apart from quantification value+0.0659 × and mining area apart from quantification+0.0941 × vegetative coverage of value
Spend quantification value+0.1236 × drilling exploratory trench density quantification value+0.1018 × and village apart from quantification value+0.0711 × and
River is apart from quantification value+0.044 × and+0.1554 × gradient of road distance quantification value quantification+0.1554 × height difference of value
Quantification value,
Wherein y is grade score value.
6. more imperial mining area Green Mine site selecting methods according to claim 5, which is characterized in that linear according to mine addressing
Model construction mine site selection model result figure provides the Green Mine addressing scheme in area to be studied.
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