CN103337037A - Mining area ecology monitoring method - Google Patents

Abstract

The invention discloses a kind of ecology of mining areas monitoring methods, lack the problems such as assessment of eco-environmental quality caused by considering underlying surface heterogencity, systematicness and accuracy etc. is uncertain for existing ecology of mining areas system monitoring and design. The method that remote-sensing inversion is applied in the present invention, and geology is combined to establish ecology of mining areas monitoring index model method with the means that the means of production and field investigation combine. The method seeks comprehensive monitoring result F (Ri) by following formula;

Or 3; Wherein, R1 is risk source risk, and R2 is ecosystem fragile degree, and R3 is ecological system loss degree. Using a kind of ecology of mining areas monitoring method of the present invention, have many advantages, such as that monitoring objective is clear, index system is complete, model is simple and practical, has dynamic and precision higher.

Description

The ecology of mining areas monitoring method

Technical field

Ecosphere of the present invention relates in particular to a kind of ecology of mining areas monitoring method.

Background technology

Underlying surface refers to earth surface, comprises plateau, mountain region, Plain, forest, grassland and the city etc. of ocean, land, land.Parameters such as underlying surface each several part temperature, moisture and surface configuration all have larger difference, thereby underlying surface has heterogencity.

Existing regional ecological monitoring method be primarily aimed at city, basin, farming region etc. and the design, the shortage system towards the index system of ecology of mining areas monitoring and model method, in addition owing to lack the quantitative spatial data support of multidate, be difficult to verify the mining industry exploitation down, the complicacy of complicated underlying surface monitoring index change procedure, so that the ecology of mining areas monitoring lacks reliability because shortage process-Analysis on Mechanism rests in the qualitative analysis mostly.

So exist, lack at the ecology of mining areas monitoring model and lack the heterogencity of considering the face of land and dynamic and cause the behavioral characteristics that is difficult to objective reaction ecology of mining areas, have bigger limitation.

Summary of the invention

(1) goal of the invention

Ecology of mining areas monitoring method of the present invention lacks systematicness, dynamic and spatiality at ecology of mining areas monitoring and proposes, and from minute having considered the heterogencity of mining area underlying surface, has solved the not strong problem of existing monitoring method process mechanism.

(2) technical scheme

For reaching above-mentioned purpose, ecology of mining areas monitoring method of the present invention is asked for monitoring result F (R by following formula _i);

F(R _i)=w ₁R ₁×w ₂R ₂×w ₃R ₃

$R_i=\underset{j=1}{\overset{\mathrm{ni}}{\mathrm{\Σ}}}{w}_{\mathrm{ij}}.R_{\mathrm{ij}}$

$R_{\mathrm{ij}}=\underset{k=1}{\overset{\mathrm{mij}}{\mathrm{\Σ}}}{w}_{\mathrm{ijk}}{.R}_{\mathrm{ijk}}$

I=1,2 or 3

Wherein, R ₁Be risk source risk, R ₂Be ecosystem fragility degree, R ₃Be ecological system loss degree;

w ₁Be the weight coefficient of risk source risk, w ₂Be the weight coefficient of ecosystem fragility degree, w ₃Weight coefficient for ecological system loss degree;

R _1jBe risk source j key element risk, R _2jBe ecosystem j key element fragility degree, R _2jBe ecosystem j key element loss degree;

w _1jBe the weight coefficient of risk source j key element risk, w _2jBe the weight coefficient of ecosystem j key element fragility degree, w _3jWeight coefficient for ecosystem j key element loss degree;

N1 is risk source key element sum, and n2 is ecosystem fragility degree key element sum, and n3 is ecological system loss degree key element sum;

R _1jkBe risk source k index risk, R _2jkBe ecosystem fragility degree k index risk, R _3jkBe the weak degree of ecosystem loss k index loss degree;

w _1jkBe the weight coefficient of k index risk under the j key element of risk source, w _2jkBe the weight coefficient of k index fragility degree under the ecosystem j key element, w _3jkWeight coefficient for k index loss degree under the ecosystem j key element;

M1j is index sum under the j key element of risk source, and m2j is index sum under the ecosystem fragility degree j key element, and m3j is index sum under the ecological system loss degree j key element.

Preferably,

Described risk source monitoring method comprises goaf top plate intensity key element, pollution intensity key element and soil erosion intensity key element;

Described ecosystem fragility degree monitoring comprises meteorological hydrographic features, geology and geomorphology key element, vegetation key element, ecosystem vigor key element, ecosystem institutional framework key element, recovery capability key element, interference strength key element and safeguard measure key element;

Described ecosystem loss degree monitoring comprises that ecosystem in adjusting functional imperative, ecosystem supply factors, social economic system development degree key element, measure perfect degree key element, mineral resources supply factors, water resource supply factors.

Preferably,

The described sky strength of roof key element of adopting comprises goaf superincumbent stratum degree of stability index and goaf filling extent index;

Described pollution intensity key element monitoring comprises soil pollution intensity index, air pollution intensity index and water pollution intensity index;

Described soil erosion intensity key element comprises the monitoring of soil erosion modulus index;

Described meteorological hydrographic features comprise the average precipitation index;

Described geology and geomorphology key element comprises gradient index and soil texture index;

Described vegetation key element comprises the vegetation coverage index;

Described ecosystem vigor key element comprises the clean primary productivity NPP of vegetation index;

Described ecosystem institutional framework key element comprises diversity indices index and mean patch area index;

Described recovery capability key element comprises comprehensive elastic index;

Described interference strength key element comprises that the soil utilizes intensity index and underground mineral recovery percent index;

Described safeguard measure key element comprises engineering protection measure index and land reclamation and ecological reconstruction index index;

Described ecosystem in adjusting functional imperative comprises that water and soil conservation index, water source conserve index, air purification index and nutriment and keep index;

Described ecosystem supply factors comprises that material provides index;

Described social economic system development degree key element comprises density of population index, building assets index;

Described measure perfects the degree key element and comprises that environment keeps the measure index;

Described mineral resources supply factors comprises the ore reserve index;

Described water resource supply factors comprises water resource reserves index.

Preferably,

Described goaf superincumbent stratum degree of stability index risk factor MRS passes through formula $\mathrm{MRS}=\underset{b=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{ab}}\×S_b/A_a$ Calculate;

A _AbArea for goaf b in the monitoring means; A _aArea for monitoring means; S _bStability coefficient for goaf b in the monitoring means;

Described goaf filling extent index MAF passes through formula

Calculate;

Be divided into according to the goaf filling extent that 0-20% fills, 20-40% fills, 40-60% fills, 60-80% fills, 80-100% fills 5 grades fully and represented by d successively; A _AdArea for goaf in the monitoring means; A _aArea for monitoring means; F _dBe goaf activity coefficient in the monitoring means.

Preferably,

Described soil pollution index risk SPI adopts following formula to ask for;

$\mathrm{SPI}=\underset{f=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{af}}\×K_f\×w_f/A_a$

K _f=S _f/SS _f

Be divided into farmland, orchard, residential area and public facilities, land use for greening and do not utilize the soil to be divided into 5 classes and represented by f according to the land used type; A _AfIt is f kind land used type area; K _fBe heavy metal in soil mean ratio content; S _fBe the heavy metal in soil average content; SS _fBe the unpolluted soil average content in this area; w _fWeights for f land used type;

Wherein, described land used type is obtained from the inverting of sensor information;

The risk API of described air pollution index adopts following formula to ask for:

$\mathrm{API}=L_a\×F_a\×A_{\mathrm{ae}}\×(w_1\×P_d+w_2\×{P_{\mathrm{NO}}}_x+w_3\×{P_{\mathrm{SO}}}_2)/A_a$

L _aFor monitoring means a from pollution source distance weighting function; F _aBe the average wind-force of monitoring means a; P _dBe pollution source mesexine dust content; Be NO in the pollution source _XContent;

Be SO in the pollution source ₂Content; w ₁Be dust pollution weight, w ₂Be NO _XPollute weight, w ₃Be grey SO ₂Pollute weight, A _AeFor pollution source in the monitoring means are exposed to airborne area, A _aArea for monitoring means;

Wherein, pollution source A _AeObtain as inverting by remote sensing information;

The risk WPI of described water pollution index adopts following formula to ask for:

WPI _g=A _ah/A _a，WPI _s=A _ak/A _a

WPI=w ₁₁×WPI _g+w ₁₂WPI _s

WPI _gFor the mining industry exploitation destroys the groundwater contamination degree; A _AhBe the underground water area that directly exposes in the mining in the monitoring means; Surface water pollution WPI _s, A _AkThe surface water area that destroys; Be w ₁₁Be the weight of expression groundwater contamination, w ₁₂Be the surface water pollution weight.

Preferably,

Described soil utilizes intensity index fragility degree LUI to calculate by following formula:

$\mathrm{LUI}=\underset{o=1}{\overset{p}{\mathrm{\Σ}}}{w}_o{S}_o/S$

S _oRefer to o class land use pattern, w _oBe weight, S is each cellar area of statistics, and p is the sum of land use pattern;

Described land reclamation index fragility degree LRC calculates by following formula:

$\mathrm{LRC}=\underset{x=1}{\overset{n}{\mathrm{\Σ}}}(A_{\mathrm{ax}}\×w_x\×V_c)/A_a$

A _AxBe the area of land reclamation in the monitoring means, x is the type of land reclamation; w _xWeight for the land reclamation type; V _cBe the quality of reclaiming;

Wherein, the area of the type of land reclamation, land reclamation and the quality information of reclaiming are by the sensor information inverting.

Preferably,

The loss degree V of described air purification monitoring index passes through following formula:

$V=\underset{j1=1}{\overset{n2}{\mathrm{\Σ}}}{A}_{\mathrm{aj}1}\×d_{j1}\×(X_{j1}\×C_d+X_N\×C_N+X_S\×C_s)/A_a$

A _Aj1Leaf area index for j1 kind vegetation in the monitoring means; X _J1Be the j1 class plant leaf blade unit area amount of laying the dust; d _J1Be the j1 class vegetation growth phase; C _dFor substitution expenditure method is subdued the dust cost; X _NBe j1 class vegetation blade unit area absorption of N O _XAmount; X _SFor j1 class vegetation blade unit area absorbs SO ₂Amount; C _NFor determining about NO according to Chinese atmosphere pollution exhaust criteria _XWeight, C _SFor determining about SO according to Chinese atmosphere pollution exhaust criteria ₂Weight; A _aArea for monitoring means;

Wherein, leaf area index and vegetation pattern are obtained by the sensor information inverting.

Preferably,

Described material provides the loss degree ESI of index to calculate by following formula:

$\mathrm{ESI}=\underset{i1=1}{\overset{n3}{\mathrm{\Σ}}}{W}_{i1}\×A_{i1}\×w_{i1}/A_a$

W _I1Be the amount that i1 class atural object unit area in the monitoring means provides, A _I1For i1 class material area, w are provided _I1Be the weight of i1 class material, n3 is for providing the ground class number of material, A in the monitoring means _aBe unit area;

Wherein, A _I1Obtain by the sensor information inverting.

Preferably,

The loss degree FA of described building assets index adopts following formula to calculate:

$\mathrm{FA}=(\underset{j2=1}{\overset{n4}{\mathrm{\Σ}}}{A}_{\mathrm{aj}2}\×P_{j2})/A_a$

A _Aj2Be the Architectural Equipment area; P _J2Weight for j2 class underlying surface; A _aBe the area of monitoring means, n4 is Architectural Equipment type sum.

Wherein, the Architectural Equipment type is by Remote Sensing Information Extraction.

Preferably,

Described environment keeps measure index loss degree ASWI to calculate by following formula:

$\mathrm{ASWI}=\underset{j3=1}{\overset{5}{\mathrm{\Σ}}}{F}_{\mathrm{vj}3}\×w_{j3}$

With environment keep engineering be divided into one-level, secondary, three grades, level Four and Pyatyi totally 5 grades represented F by j3 _Vj3Be the measure grade of j3 class environment maintenance engineering, w _J3Be the engineering measure weight;

Described mineral resources are supplied with index MS and are calculated by following formula:

$\mathrm{MS}={\stackrel{\‾}{h}}_1\×{\stackrel{\‾}{\mathrm{\ρ}}}_1\×\left(\underset{x1}{\overset{x2}{\mathrm{\Σ}}}{P}_{x1}\right)\×A_{\mathrm{ak}}/A_a$

Be the average thickness of rock stratum, Proportion for the rock stratum; P _X1Be the proportion of mineral x1, x2 is the mineral species number; A _AkFor containing the rock stratum area of mineral; A _aArea for monitoring means.

Described groundwater resource are supplied with index GMS and are calculated by following formula:

$\mathrm{GMS}={\stackrel{\‾}{h}}_2\×A_{\mathrm{al}}/A_a$

Be underground reservoir average thickness, A _AlBe underground reservoir area, A _aArea for monitoring means.

Partial parameters or index in this invention model: complicated meticulous information and consequent landscape indexes such as spoil (slag) mountain, heap mining area, surface subsidence district, residential area, farmland, forest land, meadow, water body, and parameter such as leaf area index (LAI), soil erosion modulus, net primary productivity (NPP), vegetation cover degree mainly obtained by the sensor information inverting, and other data are obtained by ore deposit figure, geologic map etc.

(3) beneficial effect of the present invention

Monitoring method of the present invention is to set up ecological monitoring index system and the correlation model method towards the mining area.On the basis that takes into full account face of land heterogencity and dynamic, use spatial information methods such as sensor information inverting, spatial information and model coupling with multidate expand to the graticule mesh level with the monitoring index space scale from pixel, by static state to dynamic.Thus, this monitoring method process mechanism is clear and definite, and has systematicness, and the monitoring result that obtains also has the advantage of spatiality and dynamic.

Description of drawings

Fig. 1 is the process flow diagram of ecology of mining areas monitoring method of the present invention.

Embodiment

The present invention is described further below in conjunction with Figure of description and embodiment.

As shown in Figure 1, present embodiment ecology of mining areas monitoring method is asked for ecological monitoring F (R as a result by following formula _i);

F(R _i)=w ₁R ₁×w ₂R ₂×w ₃R ₃

$R_i=\underset{j=1}{\overset{\mathrm{ni}}{\mathrm{\Σ}}}{w}_{\mathrm{ij}}.R_{\mathrm{ij}}$

$R_{\mathrm{ij}}=\underset{k=1}{\overset{\mathrm{mij}}{\mathrm{\Σ}}}{w}_{\mathrm{ijk}}.R_{\mathrm{ijk}}$

I=1,2 or 3

Wherein, R ₁Be risk source risk, R ₂Be ecosystem fragility degree, R ₃Be ecological system loss degree;

w ₁Be the weight coefficient of risk source risk, w ₂Be the weight coefficient of ecosystem fragility degree, w ₃Weight coefficient for ecological system loss degree;

R _1jBe risk source j key element risk, R _2jBe ecosystem j key element fragility degree, R _2jBe ecosystem j key element loss degree;

w _1jBe the weight coefficient of risk source j key element risk, w _2jBe the weight coefficient of ecosystem j key element fragility degree, w _3jWeight coefficient for ecosystem j key element loss degree;

N1 is risk source key element sum, and n2 is ecosystem fragility degree key element sum, and n3 is ecological system loss degree key element sum;

R _1jkBe risk source k index risk, R _2jkBe ecosystem fragility degree k index risk, R _3jkBe the weak degree of ecosystem loss k index loss degree;

w _1jkBe the weight coefficient of k mark risk under the j key element of risk source, w _2jkBe the weight coefficient of k index fragility degree under the ecosystem j key element, w _3jkWeight coefficient for k index loss degree under the ecosystem j key element;

M1j is index sum under the j key element of risk source, and m2j is index sum under the ecosystem fragility degree j key element, and m3j is index sum under the ecological system loss degree j key element.

Table 1 is asked for monitoring key element and index related in the process for the risk source described in the present embodiment in risk.

Table 1

Table 2 is asked for monitoring key element and index related in the process for the ecosystem fragility degree described in the present embodiment.

Table 3 is asked for key element related in the process and index for the ecosystem loss degree described in the present embodiment.

Further, described goaf superincumbent stratum degree of stability index risk factor MRS passes through formula $\mathrm{MRS}=\underset{b=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{ab}}\×S_b/A_a$ Calculate;

A _AbArea for goaf b in the monitoring means; A _aArea for monitoring means; S _bStability coefficient for goaf b in the monitoring means;

Described goaf filling extent index MAF passes through formula Calculate;

Be divided into according to the goaf filling extent that 0-20% fills, 20-40% fills, 40-60% fills, 60-80% fills, 80-100% fills 5 grades fully and represented by d; A _AdArea for goaf in the monitoring means; A _aArea for monitoring means; F _dBe goaf activity coefficient in the monitoring means;

Further,

Described soil pollution monitoring index risk SPI adopts following formula to ask for;

$\mathrm{SPI}=\underset{f=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{af}}\×K_f\×w_f/A_a$

K _f=S _f/SS _f

Be divided into farmland, orchard, residential area and public facilities, land use for greening and do not utilize the soil to be divided into 5 classes and represented by f according to the land used type; A _AfIt is f kind land used type area; K _fBe heavy metal in soil mean ratio content; S _fBe the heavy metal in soil average content; SS _fBe the unpolluted soil average content in this area; w _fWeights for f land used type;

The risk API of described air pollution index adopts following formula to ask for:

$\mathrm{API}=L_a\×F_a\×A_{\mathrm{ae}}\×(w_1\×P_d+w_2\×{P_{\mathrm{NO}}}_x+w_3\×{P_{\mathrm{SO}}}_2)/A_a$

L _aFor monitoring means a from pollution source distance weighting function; F _aBe the average wind-force of monitoring means a; P _dBe pollution source mesexine dust content; Be NO in the pollution source _XContent;

Be SO in the pollution source ₂Content; w ₁Be dust pollution weight, w ₂Be NO _XPollute weight, w ₃Be grey SO ₂Pollute weight, A _AeFor pollution source in the monitoring means are exposed to airborne area, A _aArea for monitoring means.

The risk WPI of described water pollution index adopts following formula to ask for:

WPI _g=A _ah/A _a，WPI _s=A _ak/A _a

WPI=w ₁₁×WPI _g+w ₁₂WPI _s

WPI _gFor the mining industry exploitation destroys the groundwater contamination degree; A _AhBe the underground water area that directly exposes in the mining in the monitoring means; Surface water pollution WPI _s, A _AkThe surface water area that destroys; Be w ₁₁Be the weight of expression groundwater contamination, w ₁₂Be the surface water pollution weight.

In concrete implementation process, described soil erosion intensity index risk, concrete acquiring method adopts soil loss equation USLE(Universal Soil Loss Equation):

A=R.K.LS.C.P

A is time and space average soil loss amount on the unit area; R is rainfall-runoff erosivity factor; K is soil erodibility factor; LS is terrain factor; C is for covering-the management factor; P is the water-and-soil conservation measures factor.The acquiring method of above-mentioned each factor has multiple acquiring method in the prior art, does not repeat them here.

The risk of described meteorological hydrology index is asked for and can be adopted following formula to ask for:

Obtain precipitation data for many years by weather station or hydrologic observation point, and obtain the average annual quantity of precipitation of space distribution by space interpolation:

$\stackrel{\‾}{P}=\mathrm{\Σ}{P}_{\mathrm{ii}}/n$

Be n mean annual precipitation, P _IiBe P _IiAnnual precipitation, n is total year number of statistics.

The employing ANUDEM algorithm of the fragile degree of described gradient index extracts the slope map in the digital elevation model (DEM).

The described soil texture can obtain by existing the whole bag of tricks, adopts the soil types storehouse to obtain in the present embodiment.

Described vegetation coverage index can adopt following formula to calculate:

f=（NDVI-NDVI _s）/（NDVI _v-NDVI _s）

NDVI _vBe pure vegetation normalization index NDVI value, NDVI _sNDVI value for pure exposed soil.

Described ecosystem vigor index fragility degree adopts NPP to characterize, and asks for by remotely-sensed data, and concrete acquiring method is as follows:

NPP=GPP-R _a

GPP=ε×APRA×f ₁(T)×f ₂(β)

$R_a=\frac{7.825+1.145T_a}{100}\×\mathrm{GPP}$

NPP is the clean primary productivity of expression, and GPP is total primary productivity, R _aEmpirical model by Goward is determined, is the function of GPP and temperature; GPP has considered the influence of illumination, temperature, moisture and nutrient, and wherein ε is that vegetation is converted into organic conversion ratio (being conversion of solar energy) with the photosynthetically active radiation that absorbs; APRA is the photosynthetically active radiation amount; f ₁(T) be temperature to photosynthetic influence function, be temperature T _aFunction; f ₂(β) be moisture to photosynthetic influence function, β is evaporite ratio.

The calculating of APRA

Consider the light of vegetation absorption and light and the effective radiation IPAR (PAR incident on the vegetation) that effective radiation APRA equals the leaf interception, according to beer law [i] (the be distributed as average radiation amount of light in colony successively decreased with the increase of leaf area index), then have:

APAR=IPAR=PAR(1-e ^-K×LAI)

In the formula: PAR is light and the effectively radiation (MJm-2month-1) of incident; LAI is leaf area index, is obtained by the direct inverting of remotely-sensed data; K is leaf layer extinction coefficient.

PAR=αQ

In the formula: Q is total solar radiation; α is the scale factor of photosynthetically active radiation and built-up radiation, can be calculated by test sample to obtain, and numerical value can be 0.49 in this research; Q can have radiation station Monitoring Data to obtain or be calculated by empirical model.

Leaf layer extinction coefficient distributes with the angle of planting the hat leaf and leaf is grown, and season is relevant, and Monsi thinks herbal K=0.3～0.5, and the K=1 of horizontal leaf.If planting the leaf of hat is spherical distribution, namely leaf inclination angle with respect to the horizontal plane is continuous distribution, and K is the function of solar zenith angle, and expression formula is as follows:

K=0.5cosθ _z

In the formula: θ _zBe solar zenith angle; Be geographic latitude; δ is solar declination; ω ₀Be the sunset hour angle.

Temperature is coerced coefficient f ₁(T)

f ₁(T) be the function of temperature T, expression formula is as follows:

$f_1\left(T\right)=\frac{1}{\[1+\exp (4.5-T_a)\]\·\[1+\exp (T_a-37.5)\]}$

In the formula: T _aBe atmosphere medial temperature (° C).

Water stress factor f ₂(β)

f ₂Be the function of evaporite ratio β (β), expression formula is as follows:

f ₂(β)=0.5+0.5β

$\mathrm{\β}=\frac{E{T}_a}{E{T}_P}$

In the formula: β is the climate-index that wet degree is done on reflection ground; ET _aIt is regional actual evapotranspiration; ET _PBe the potential evapotranspiration amount, ask for according to the complementary relationship that Boucher proposes.

Asking for of described diversity indices index fragility degree can adopt following formula to calculate:

H=-Σ（p _io）log2(p _io)

Wherein, p _IoIt is the ratio that io kind view accounts for the total area.

Described mean patch area

$\stackrel{\‾}{A}=\mathrm{\Σ}{A}_i/n$

A _iBe the area of i piece patch in the monitoring means, n is the monitoring means patch number.

Comprehensive elastic index fragility degree is used for the recovery capability of characterization system after being interfered, and its computing formula is: CEI=Si * Pi

Wherein Si is the area ratio of every kind of ground class; Pi is the numerical value after the elasticity score value normalized.

Further,

Described soil utilizes intensity index fragility degree LUI to calculate by following formula:

$\mathrm{LUI}=\underset{o=1}{\overset{p}{\mathrm{\Σ}}}{w}_o{S}_o/S$

S _oRefer to o class land use pattern, w _oBe weight, S is each cellar area of statistics, and p is the sum of land use pattern; Land use pattern comprises farmland, orchard, rural residential area, city dweller's point, traffic, mining industry development area, heap ore deposit or spoil laydown area etc.

The index fragility degree of described engineering protection measure refers to the engineering measure of all protection mining industry development area ecologies, discharges, exploits water conservation protection etc. as stone masonry wall supporting, goaf backfill, minimizing waste gas.Be made as the 1-5 level according to engineering protection measure degree of perfection.

EPMI=w ₁×S _i+w ₂×M _i+w ₃×P _i+w ₄×W _i

S _iBe water and soil conservation facility, w ₁Be weight; M _iFor reducing ore or slag measure, w ₂Be weight; P _iBe goaf backfill measure, w ₃Be weight; W _iBe purification of water quality measure, w ₄Be weight.

Further,

Described land reclamation index fragility degree LRC calculates by following formula:

$\mathrm{LRC}=\underset{x=1}{\overset{n}{\mathrm{\Σ}}}(A_{\mathrm{ax}}\×w_x\×V_c)/A_a$

A _AxBe the area of land reclamation in the monitoring means, x is the type of land reclamation, refers to be reclaimed by spoil (or slag) mountain, mining area, Subsidence Area etc. be forest zone, meadow, farmland, orchard, fish pond etc.; w _xWeight for the land reclamation type; V _cBe the quality of reclaiming, mainly by reflections such as vegetation coverage condition, Ecosystem Service.

The loss degree of described water and soil conservation index has several different methods in the prior art, and the water and soil conservation that preferred Ou Yangzhi cloud (2004) makes up in the present embodiment is worth the maintenance system and assesses.

Further,

Described air purification index loss degree V passes through following formula:

$V=\underset{j1=1}{\overset{n2}{\mathrm{\Σ}}}{A}_{\mathrm{aj}1}\×d_{j1}\×(X_{j1}\×C_d+X_N\×C_N+X_S\×C_s)$

A _Aj1Leaf area index for j1 kind vegetation in the monitoring means; X _J1Be j1 class plant (broad-leaved, needle etc.) the blade unit area amount of laying the dust; d _J1Be the j1 class vegetation growth phase; C _dFor substitution expenditure method is subdued the dust cost; X _NBe j1 class vegetation blade unit area absorption of N O _XAmount; X _SFor j1 class vegetation blade unit area absorbs SO ₂Amount; C _NFor determining about NO according to Chinese atmosphere pollution exhaust criteria _XWeight, C _SDetermine about SO for settling the standard according to Chinese atmosphere blowdown ₂Weight.

Further,

Described material provides index ESI to calculate by following formula:

$\mathrm{ESI}=\underset{i1=1}{\overset{n3}{\mathrm{\Σ}}}{W}_{i1}\×A_{i1}\×w_{i1}/A_a$

W _I1Be the amount that i1 class atural object unit area in the monitoring means provides, A _I1For i1 class material area, w are provided _I1Be the weight of i1 class material, n3 is for providing the ground class number of material, A in the monitoring means _aBe unit area.

Further,

Described building assets index loss degree FA adopts following formula to calculate:

$\mathrm{FA}=(\underset{j2=1}{\overset{n4}{\mathrm{\Σ}}}{A}_{\mathrm{aj}2}\×P_{j2})/A_a$

A _Aj2Be the area that comprises waterproof underlying surface, comprise communal facilitys such as hospital, school, infrastructure such as road, bridge, production facility homalographic such as residential district such as residential building and workshop, industrial premises; P _J2Weight for j2 class underlying surface; A _aBe the area of monitoring means, n4 is number of types.

Further,

Described environment keeps measure index ASWI to calculate by following formula:

$\mathrm{ASWI}=\underset{j3=1}{\overset{5}{\mathrm{\Σ}}}{F}_{\mathrm{vj}3}\×w_{j3}$

With environment keep engineering be divided into one-level, secondary, three grades, level Four and Pyatyi totally 5 grades represented F by j3 _Vj3Be the measure grade of j3 class maintenance engineering, w _J3Be the engineering measure weight;

Described mineral resources are supplied with index MS and are calculated by following formula:

$\mathrm{MS}={\stackrel{\‾}{h}}_1\×{\stackrel{\‾}{\mathrm{\ρ}}}_1\×\left(\underset{x1}{\overset{x2}{\mathrm{\Σ}}}{P}_{x1}\right)\×A_{\mathrm{ak}}/A_a$

Be the average thickness of rock stratum,

Proportion for the rock stratum; P _X1Be the proportion of mineral x1, x2 is the mineral species number; A _AkFor containing the rock stratum area of mineral; A _aArea for monitoring means.

Described groundwater resource are supplied with index GMS and are calculated by following formula:

$\mathrm{GMS}={\stackrel{\‾}{h}}_2\×A_{\mathrm{al}}/A_a$

Be underground reservoir average thickness, A _AlBe underground reservoir area, A _aArea for monitoring means.

Monitoring method of the present invention is to set up ecological monitoring index system and the correlation model method towards the mining area.On the basis that takes into full account face of land heterogencity and dynamic, use spatial information methods such as sensor information inverting, spatial information and model coupling with multidate expand to the graticule mesh level with the monitoring index space scale from pixel, by static state to dynamic.Thus, this monitoring method process mechanism is clear and definite, and has systematicness, and the monitoring result that obtains also has the advantage of spatiality and dynamic.

Above embodiment only is used for explanation the present invention; and be not limitation of the present invention; the those of ordinary skill in relevant technologies field; under the situation that does not break away from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all technical schemes that are equal to also belong to category of the present invention, and scope of patent protection of the present invention should be defined by the claims.

Claims (10)

1. an ecology of mining areas monitoring method is characterized in that, asks for monitoring result F (R by following formula _i);

F(R _i)=w ₁R ₁×w ₂R ₂×w ₃R ₃

$R_i=\underset{j=1}{\overset{\mathrm{ni}}{\mathrm{\Σ}}}{w}_{\mathrm{ij}}.R_{\mathrm{ij}}$

$R_{\mathrm{ij}}=\underset{k=1}{\overset{\mathrm{mij}}{\mathrm{\Σ}}}{w}_{\mathrm{ijk}}{.R}_{\mathrm{ijk}}$

I=1,2 or 3

Wherein, R ₁Be risk source risk, R ₂Be ecosystem fragility degree, R ₃Be ecological system loss degree;

w ₁Be the weight coefficient of risk source risk, w ₂Be the weight coefficient of ecosystem fragility degree, w ₃Weight coefficient for ecological system loss degree;

R _1jBe risk source j key element risk, R _2jBe ecosystem j key element fragility degree, R _2jBe ecosystem j key element loss degree;

w _1jBe the weight coefficient of risk source j key element risk, w _2jBe the weight coefficient of ecosystem j key element fragility degree, w _3jWeight coefficient for ecosystem j key element loss degree;

N1 is risk source key element sum, and n2 is ecosystem fragility degree key element sum, and n3 is ecological system loss degree key element sum;

R _1jkBe risk source k index risk, R _2jkBe ecosystem fragility degree k index risk, R _3jkBe the weak degree of ecosystem loss k index loss degree;

w _1jkBe the weight coefficient of k index risk under the j key element of risk source, w _2jkBe the weight coefficient of k index fragility degree under the ecosystem j key element, w _3jkWeight coefficient for k index loss degree under the ecosystem j key element;

M1j is index sum under the j key element of risk source, and m2j is index sum under the ecosystem fragility degree j key element, and m3j is index sum under the ecological system loss degree j key element.

2. want 1 described ecology of mining areas monitoring method according to right, it is characterized in that,

Described risk source monitoring method comprises goaf top plate intensity key element, pollution intensity key element and soil erosion intensity key element;

Described ecosystem fragility degree monitoring comprises meteorological hydrographic features, geology and geomorphology key element, vegetation key element, ecosystem vigor key element, ecosystem institutional framework key element, recovery capability key element, interference strength key element and safeguard measure key element;

Described ecosystem loss degree monitoring comprises that ecosystem in adjusting functional imperative, ecosystem supply factors, social economic system development degree key element, measure perfect degree key element, mineral resources supply factors, water resource supply factors.

3. ecology of mining areas monitoring method according to claim 2 is characterized in that,

The described sky strength of roof key element of adopting comprises goaf superincumbent stratum degree of stability index and goaf filling extent index;

Described pollution intensity key element monitoring comprises soil pollution intensity index, air pollution intensity index and water pollution intensity index;

Described soil erosion intensity key element comprises the monitoring of soil erosion modulus index;

Described meteorological hydrographic features comprise the average precipitation index;

Described geology and geomorphology key element comprises gradient index and soil texture index;

Described vegetation key element comprises the vegetation coverage index;

Described ecosystem vigor key element comprises the clean primary productivity NPP of vegetation index;

Described ecosystem institutional framework key element comprises diversity indices index and mean patch area index;

Described recovery capability key element comprises comprehensive elastic index;

Described interference strength key element comprises that the soil utilizes intensity index and underground mineral recovery percent index;

Described safeguard measure key element comprises engineering protection measure index and land reclamation and ecological reconstruction index index;

Described ecosystem in adjusting functional imperative comprises that water and soil conservation index, water source conserve index, air purification index and nutriment and keep index;

Described ecosystem supply factors comprises that material provides index;

Described social economic system development degree key element comprises density of population index, building assets index;

Described measure perfects the degree key element and comprises that environment keeps the measure index;

Described mineral resources supply factors comprises the ore reserve index;

Described water resource supply factors comprises water resource reserves index.

4. ecology of mining areas monitoring method according to claim 3 is characterized in that,

Described goaf superincumbent stratum degree of stability index risk factor MRS passes through formula $\mathrm{MRS}=\underset{b=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{ab}}\×S_b/A_a$ Calculate;

A _AbArea for goaf b in the monitoring means; A _aArea for monitoring means; S _bStability coefficient for goaf b in the monitoring means;

Described goaf filling extent index MAF passes through formula

Calculate;

Be divided into according to the goaf filling extent that 0-20% fills, 20-40% fills, 40-60% fills, 60-80% fills, 80-100% fills 5 grades fully and represented by d successively; A _AdArea for goaf in the monitoring means; A _aArea for monitoring means; F _dBe goaf activity coefficient in the monitoring means.

5. ecology of mining areas monitoring method according to claim 4 is characterized in that,

Described soil pollution index risk SPI adopts following formula to ask for;

$\mathrm{SPI}=\underset{f=1}{\overset{5}{\mathrm{\Σ}}}{A}_{\mathrm{af}}\×K_f\×w_f/A_a$

K _f=S _f/SS _f

Be divided into farmland, orchard, residential area and public facilities, land use for greening and do not utilize the soil to be divided into 5 classes and represented by f according to the land used type; A _AfIt is f kind land used type area; K _fBe heavy metal in soil mean ratio content; S _fBe the heavy metal in soil average content; SS _fBe the unpolluted soil average content in this area; w _fWeights for f land used type;

Wherein, described land used type is obtained from the inverting of sensor information;

The risk API of described air pollution index adopts following formula to ask for:

$\mathrm{API}=L_a\×F_a\×A_{\mathrm{ae}}\×(w_1\×P_d+w_2\×{P_{\mathrm{NO}}}_x+w_3\×{P_{\mathrm{SO}}}_2)/A_a$

L _aFor monitoring means a from pollution source distance weighting function; F _aBe the average wind-force of monitoring means a; P _dBe pollution source mesexine dust content;

Be NO in the pollution source _XContent;

Be SO in the pollution source ₂Content; w ₁Be dust pollution weight, w ₂Be NO _XPollute weight, w ₃Be grey SO ₂Pollute weight, A _AeFor pollution source in the monitoring means are exposed to airborne area, A _aArea for monitoring means;

Wherein, pollution source A _AeObtain as inverting by remote sensing information;

The risk WPI of described water pollution index adopts following formula to ask for:

WPI _g=A _ah/A _a，WPI _s=A _ak/A _a

WPI=w ₁₁×WPI _g+w ₁₂WPI _s

WPI _gFor the mining industry exploitation destroys the groundwater contamination degree; A _AhBe the underground water area that directly exposes in the mining in the monitoring means; Surface water pollution WPI _s, A _AkThe surface water area that destroys; Be w ₁₁Be the weight of expression groundwater contamination, w ₁₂Be the surface water pollution weight.

6. according to claim 4 or 5 described ecology of mining areas monitoring methods, it is characterized in that,

Described soil utilizes intensity index fragility degree LUI to calculate by following formula:

$\mathrm{LUI}=\underset{o=1}{\overset{p}{\mathrm{\Σ}}}{w}_o{S}_o/S$

S _oRefer to o class land use pattern, w _oBe weight, S is each cellar area of statistics, and p is the sum of land use pattern;

Described land reclamation index fragility degree LRC calculates by following formula:

$\mathrm{LRC}=\underset{x=1}{\overset{n}{\mathrm{\Σ}}}(A_{\mathrm{ax}}\×w_x\×V_c)/A_a$

A _AxBe the area of land reclamation in the monitoring means, x is the type of land reclamation; w _xWeight for the land reclamation type; V _cBe the quality of reclaiming;

Wherein, the area of the type of land reclamation, land reclamation and the quality information of reclaiming are by the sensor information inverting.

7. ecology of mining areas monitoring method according to claim 6 is characterized in that,

The loss degree V of described air purification monitoring index passes through following formula:

$V=\underset{j1=1}{\overset{n2}{\mathrm{\Σ}}}{A}_{\mathrm{aj}1}\×d_{j1}\×(X_{j1}\×C_d+X_N\×C_N+X_S\×C_s)/A_a$

A _Aj1Leaf area index for j1 kind vegetation in the monitoring means; X _J1Be the j1 class plant leaf blade unit area amount of laying the dust; d _J1Be the j1 class vegetation growth phase; C _dFor substitution expenditure method is subdued the dust cost; X _NBe j1 class vegetation blade unit area absorption of N O _XAmount; X _SFor j1 class vegetation blade unit area absorbs SO ₂Amount; C _NFor determining about NO according to Chinese atmosphere pollution exhaust criteria _XWeight, C _SFor determining about SO according to Chinese atmosphere pollution exhaust criteria ₂Weight; A _aArea for monitoring means;

Wherein, leaf area index and vegetation pattern are obtained by the sensor information inverting.

8. ecology of mining areas monitoring method according to claim 7 is characterized in that,

Described material provides the loss degree ESI of index to calculate by following formula:

$\mathrm{ESI}=\underset{i1=1}{\overset{n3}{\mathrm{\Σ}}}{W}_{i1}\×A_{i1}\×w_{i1}/A_a$

W _I1Be the amount that i1 class atural object unit area in the monitoring means provides, A _I1For i1 class material area, w are provided _I1Be the weight of i1 class material, n3 is for providing the ground class number of material, A in the monitoring means _aBe unit area;

Wherein, A _I1Obtain by the sensor information inverting.

9. ecology of mining areas monitoring method according to claim 8 is characterized in that,

The loss degree FA of described building assets index adopts following formula to calculate:

$\mathrm{FA}=(\underset{j2=1}{\overset{n4}{\mathrm{\Σ}}}{A}_{\mathrm{aj}2}\×P_{j2})/A_a$

A _Aj2Be the Architectural Equipment area; P _J2Weight for j2 class underlying surface; A _aBe the area of monitoring means, n4 is Architectural Equipment type sum.

Wherein, the Architectural Equipment type is by Remote Sensing Information Extraction.

10. ecology of mining areas monitoring method according to claim 9 is characterized in that,

Described environment keeps measure index loss degree ASWI to calculate by following formula:

$\mathrm{ASWI}=\underset{j3=1}{\overset{5}{\mathrm{\Σ}}}{F}_{\mathrm{vj}3}\×w_{j3}$

With environment keep engineering be divided into one-level, secondary, three grades, level Four and Pyatyi totally 5 grades represented F by j3 _Vj3Be the measure grade of j3 class environment maintenance engineering, w _J3Be the engineering measure weight;

Described mineral resources are supplied with index MS and are calculated by following formula:

$\mathrm{MS}={\stackrel{\‾}{h}}_1\×{\stackrel{\‾}{\mathrm{\ρ}}}_1\×\left(\underset{x1}{\overset{x2}{\mathrm{\Σ}}}{P}_{x1}\right)\×A_{\mathrm{ak}}/A_a$

Be the average thickness of rock stratum,

Proportion for the rock stratum; P _X1Be the proportion of mineral x1, x2 is the mineral species number; A _AkFor containing the rock stratum area of mineral; A _aArea for monitoring means.

Described groundwater resource are supplied with index GMS and are calculated by following formula:

$\mathrm{GMS}={\stackrel{\‾}{h}}_2\×A_{\mathrm{al}}/A_a$

Be underground reservoir average thickness, A _AlBe underground reservoir area, A _aArea for monitoring means.

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