CN106682830A - Urbanization ghost town index evaluating method and device - Google Patents
Urbanization ghost town index evaluating method and device Download PDFInfo
- Publication number
- CN106682830A CN106682830A CN201611218887.7A CN201611218887A CN106682830A CN 106682830 A CN106682830 A CN 106682830A CN 201611218887 A CN201611218887 A CN 201611218887A CN 106682830 A CN106682830 A CN 106682830A
- Authority
- CN
- China
- Prior art keywords
- index
- target area
- built
- areas
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000010276 construction Methods 0.000 claims abstract description 58
- 238000004364 calculation method Methods 0.000 claims abstract description 6
- 230000003287 optical effect Effects 0.000 claims description 40
- 238000002310 reflectometry Methods 0.000 claims description 26
- 238000012937 correction Methods 0.000 claims description 22
- 238000000605 extraction Methods 0.000 claims description 17
- 230000002708 enhancing effect Effects 0.000 claims description 13
- 239000000284 extract Substances 0.000 claims description 7
- 238000011161 development Methods 0.000 abstract description 17
- 238000011156 evaluation Methods 0.000 description 8
- 238000012360 testing method Methods 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 238000012544 monitoring process Methods 0.000 description 5
- 238000010606 normalization Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000011835 investigation Methods 0.000 description 3
- 241001269238 Data Species 0.000 description 2
- 230000009471 action Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000008878 coupling Effects 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 238000004458 analytical method Methods 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 239000012141 concentrate Substances 0.000 description 1
- 230000006378 damage Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000004141 dimensional analysis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000000796 flavoring agent Substances 0.000 description 1
- 235000019634 flavors Nutrition 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 238000005286 illumination Methods 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000013508 migration Methods 0.000 description 1
- 230000005012 migration Effects 0.000 description 1
- 208000035824 paresthesia Diseases 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 210000003296 saliva Anatomy 0.000 description 1
- 239000002689 soil Substances 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Educational Administration (AREA)
- Physics & Mathematics (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Geophysics And Detection Of Objects (AREA)
Abstract
The invention discloses an urbanization ghost town index evaluating method and device. The urbanization ghost town index evaluating method comprises the steps that a construction index of a target area is obtained; a light index in a preset period of the target area is obtained; the light index of the target area is divided by the construction index of the target area to obtain a ghost town index of the target area. The urbanization ghost town index evaluating device comprises a construction index acquisition unit, a light index acquisition unit and a ghost town index calculation unit. By the scheme of the invention, the quantitative ghost town index is used for recognizing urbanization region ghost town space conditions to have an objective and comprehensive judgment for the urbanization development coordination degree and to provide sustainable development of the city with technical support and scientific basis.
Description
Technical field
The present invention relates to urban planning technical field, and in particular to a kind of urbanization ghost town index evaluating method and device.
Background technology
" ghost town " is former to refer to the city protruded with mythological flavor or clever paresthesia, but language is there occurs in urbanization process
Justice migration, the housing vacancy rate now refering in particular to occur in urbanization process is too high, the urban area that even goes out of use.According to ghost town shape
Into the reason for, catastrophic type ghost town, decline type ghost town and planning type ghost town can be divided into.Catastrophic type ghost town refers to because nature or people
To build the high city of vacancy rate, such as the northeastern Japan portion Fukushima for being influenceed by Fukushima nuclear accident caused by the destruction of factor
County etc.;Decline type ghost town refers to be formed because resource exhaustion, upgrading of industries or industry transfer cause population to be lost in
The high city of building vacancy rate, for example, move Gansu Province's Yumen City in city etc. because of reasons such as oil amount of storage reductions;Planning type
Ghost town refers to build the high city of vacancy rate, the big Asia of such as Guangdong Huizhou caused by failure due to early stage urban planning
Gulf new city etc..
Existing urbanization monitoring relate generally to city space distribution, urban population, urban heat island, urban energy utilization,
Ghost town during urban green space, urban sprawl, city luminous environment, city noise etc., but the fresh Development of Urbanization of concern less shows
As.Only correlative study is also generally to visit and investigate or subjective news report, lacks the objective quantitative to urbanization ghost town
Test and appraisal.
The content of the invention
The invention provides a kind of urbanization ghost town index evaluating method and device, it is intended to quantify the space of Development of Urbanization
General layout difference and development degree, for the sustainable development in city provides technical support and scientific basis.
First aspect present invention provides a kind of urbanization ghost town index evaluating method, the urbanization ghost town index evaluation and test side
Method includes:
Obtain the construction index of target area;
Obtain light index of the target area in preset time period;
By the light index of the target area divided by the construction index of the target area, the target area is obtained
Ghost town index.
Second aspect present invention provides a kind of urbanization ghost town index evaluating apparatus, urbanization ghost town index evaluation and test dress
Put including:
Build index acquiring unit, the construction index for obtaining target area;
Light index acquiring unit, for obtaining light index of the target area in preset time period;
Ghost town exponent calculation unit, the light index of the target area for the light index acquiring unit to be got
The construction index of the target area got divided by the construction index acquiring unit, the ghost town for obtaining the target area refers to
Number.
Therefore, in embodiments of the present invention, the construction index of target area is obtained first, then obtain when default
Between section region of interest within light index, the finally construction by the light index of the target area divided by the target area refers to
Number, obtains the ghost town index of the target area.By the present invention program, with the ghost town index identification UrbaniZed Area ghost for quantifying
City special case, objective comprehensive evaluation is carried out to Development of Urbanization coordination degree.
Brief description of the drawings
Technical scheme in order to illustrate more clearly the embodiments of the present invention, below by to be used needed for embodiment
Accompanying drawing is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the present invention, for ability
For the those of ordinary skill of domain, without having to pay creative labor, can also obtain other according to these accompanying drawings
Accompanying drawing.
Fig. 1 is that urbanization ghost town index evaluating method provided in an embodiment of the present invention realizes flow chart;
Fig. 2 is that urbanization ghost town index evaluating method step S101 provided in an embodiment of the present invention implements flow
Figure;
Fig. 3 is that urbanization ghost town index evaluating method step S102 provided in an embodiment of the present invention implements flow
Figure;
Fig. 4 is the structured flowchart of urbanization ghost town index evaluating apparatus provided in an embodiment of the present invention.
Specific embodiment
To enable that goal of the invention of the invention, feature, advantage are more obvious and understandable, below in conjunction with the present invention
Accompanying drawing in embodiment, is clearly and completely described to the technical scheme in the embodiment of the present invention, it is clear that described reality
It is only a part of embodiment of the invention to apply example, and not all embodiments.Based on the embodiment in the present invention, the common skill in this area
The every other embodiment that art personnel are obtained under the premise of creative work is not made, belongs to the model of present invention protection
Enclose.
Realization of the invention is described in detail below in conjunction with specific embodiment:
Embodiment one
Fig. 1 shows the flow of realizing of the urbanization ghost town index evaluating method that the embodiment of the present invention one is provided, and detailed description is such as
Under:
In step S101, the construction index of target area is obtained.
In embodiments of the present invention, need to specify target area to be evaluated first, then obtain above-mentioned target to be evaluated
The construction index in region.Under normal circumstances, above-mentioned target area to be evaluated is a city, but it is also possible to according to user
Demand, the region of arbitrary size is appointed as target area, i.e., being specified for above-mentioned target area be not limited with dividing.
The construction index of above-mentioned target area can embody the target area building quantity.It is swollen in the domestic a large amount of real estates of appearance at present
Under swollen regional situation, most of ghost town is all not good due to planning, capital is excessively dropped on Real estate industry, is taken big
Amount urban land is with building, but rarely people moves in.Thus, use the building for building index to weigh the target area
The number of quantity.
In step s 102, light index of the above-mentioned target area in preset time period is obtained.
In embodiments of the present invention, in addition it is also necessary to obtain light index of the above-mentioned target area within the default time period.It is aobvious
And easy insight, under the background of modern society, the night lights in area become measurement this area to a certain extent is
No bustling flourishing standard.Due to there is the mankind to hang up one's hat the area of activity, the time-division at night generally can be using carrying out to light
Illumination, thus night light can reflect this area's size of population number.Herein, we are represented using light index
Population of the real-life in above-mentioned target area.And just because of under normal circumstances only night just can utilize lighting, and
And people can close light under sleeping at night state, so in step s 102, above-mentioned target area is only obtained when default
Between light index in section, for example only obtain above-mentioned target area light in late 8 points to ten one points of this period of times of evening and refer to
Number, enables that this index truly reflects the population situation of the target area with this.
In step s 103, the light index of above-mentioned target area is obtained divided by the construction index of above-mentioned target area
The ghost town index of above-mentioned target area.
In embodiments of the present invention, to obtain target area construction index and light index first do normalized,
The two normative reference is set to be consistent, and by the two Numerical Control in the range of identical.Then division arithmetic is remake, will
The light index of target area finally gives the ghost town index of above-mentioned target area divided by the construction index of above-mentioned target area
Value.Due to ghost town index molecule for target area light index, i.e., molecules present be target area true people's saliva
It is flat;And denominator is the construction index of target area, i.e. denominator represents the building site level of target area, thus, when above-mentioned meter
When the ghost town index for obtaining is relatively low, it is meant that some region of true underpopulation and real estate quantity are excessive, i.e. the region
It is more serious in ghost town, ghost town phenomenon.
From the foregoing, it will be observed that in embodiments of the present invention, application and construction index and light index are calculated target to be evaluated
The ghost town index in region, the data for obtaining in the process are all objective data, it is thus possible to more objective quantitative to urbanization
Ghost town degree is evaluated and tested, and realizes the objective evaluation to target area urban development.
Fig. 2 shows that urbanization ghost town index evaluating method step S101's provided in an embodiment of the present invention implements stream
Cheng Tu:
In step s 201, the built-up areas of above-mentioned target area delimited.
In embodiments of the present invention, the built-up areas of above-mentioned target area first delimited.Due to the city not geography of China
On urbanized area, a but administrative unit division, administration concentrated in flakes or several scattered urbanization with one
Regional center, a large amount of non-urbanized area around big region, thus the area in city can not truly reflect the area of urbanization
Domain, i.e., the area in usually said city urban size not in geography meaning.In order to by urbanized area and generally meaning
The urban area of justice is mutually made a distinction, and generates " built-up areas " this noun, and it is referred in the range of administrative area by requisition
Soil and the non-agricultural construction location got up of actual development, include urban district and concentrate part in flakes and be dispersed in closely
There are close ties in suburb with city, the town site with substantially perfect public utility, i.e. this city reality
The boundary scope that border construction land is reached.The evaluation and test of urbanization ghost town index is directed to due to the embodiment of the present invention, thus
Be limited in the built-up areas that Development of Urbanization gets up in the region of evaluation and test by needs.
Specifically, above-mentioned steps S201 includes:
Obtain the microwave remote sensing data and optical remote sensing data of above-mentioned target area;
Based on Object-oriented Technique, microwave remote sensing data and optical remote sensing data according to above-mentioned target area build above-mentioned
The built-up areas information extraction model of target area;
The built-up areas border of above-mentioned target area is extracted from above-mentioned built-up areas information extraction model, is built up according to above-mentioned
The built-up areas of target area delimited on area border.
Wherein, after getting the microwave remote sensing data and optical remote sensing data of target area, object-oriented skill can be based on
Art, is that above-mentioned target area builds built-up areas information extraction model, then built-up areas border is extracted from above-mentioned model, according to upper
State the built-up areas that target area delimited on built-up areas border.Above-mentioned microwave remote sensing data can be obtained from microwave remote sensing satellite series satellite
, for example the U.S.'s seasat series, Japanese marine satellite, ERS, Canadian radar satellite or other
The satellite of microwave remote sensing data can be obtained, is not construed as limiting herein.Above-mentioned optical remote sensing data are with Landsat
(Landsat satellites) is main data source, while using the data of Earth Observing System Satellite (SPOT satellites) as right
The supplement of Landsat satellite datas, it is of course also possible to distant as optics from the satellite that other can obtain optical remote sensing data
Feel the source of data, be not construed as limiting herein.Using the microwave remote sensing data and optical remote sensing data of above-mentioned target area, can be with structure
Build out target area built-up areas information extraction model.In order to ensure the accuracy of above-mentioned built-up areas information extraction model, can be with
Add the artificial data for carrying out and being obtained after ground investigation, using the data of artificial ground investigation as modeling sample, improve built-up areas
The accuracy of information extraction model.And after the final urbanization ghost town index for obtaining target area, can also be according to artificially
The data of face investigation are verified again, it is ensured that the reliability of evaluation and test.
In step S202, the optical remote sensing data of above-mentioned built-up areas, the optical remote sensing number according to above-mentioned built-up areas are obtained
According to the construction land index for being calculated above-mentioned built-up areas.
In embodiments of the present invention, the optical remote sensing data for obtaining built-up areas are calculated the construction land of built-up areas and refer to
Number.Town site information extraction is the important content of urbanization remote sensing monitoring, thus is necessary to realize using urban construction
The accurate and effective extraction of ground information.Specifically, it is possible to use normalization building index (NDBI, Normalized
Difference Build-up Index) the construction land information of completed region of the city is extracted, computing formula is as follows:
NDBI=(B5-B4)/(B5+B4)
In above formula, B5 is middle-infrared band reflectivity, and B4 is near infrared band reflectivity.It should be noted that target area
Any point has the middle-infrared band reflectivity and near infrared band reflectivity of oneself in domain, i.e. for any of target area
Point, the normalization building index for having its own.Therefore, it is possible to the change for obtaining normalization building index in the target area becomes
The variation tendency of the building dense degree of gesture, the i.e. region.
In step S203, using the construction land index of above-mentioned built-up areas as above-mentioned target area construction index.
In embodiments of the present invention, what is obtained in above-mentioned steps S202 is the construction land index of target area built-up areas,
And as being had been described above in step S201, ghost town phenomenon of concern is existed only in urbanized area, therefore, it is possible to will
The construction land index of the built-up areas obtained in above-mentioned steps S202 as above-mentioned target area construction index.
From the foregoing, it will be observed that in the embodiment of the present invention, being built using the microwave remote sensing data and optical remote sensing data that get
Into area's information extraction model, and index as the construction index of target area is built into the normalization of built-up areas, can be trueer
The building quantity levels of real reflection target area;And when structure builds up section model, artificial ground survey data is added,
Further improve the accuracy and reliability of built-up areas information extraction model.
Fig. 3 shows that urbanization ghost town index evaluating method step S102's provided in an embodiment of the present invention implements stream
Cheng Tu:
In step S301, night lights remotely-sensed data of the above-mentioned target area in preset time period is obtained.
In embodiments of the present invention, can be by DMSP (DMSP, Defense Meteorological
Satellite Program) or U.S.A. military affairs meteorological satellite (OLS, Operational Linescan System) or other
Satellite obtains night lights remotely-sensed data of the target area in preset time period.Because generally, the non-of city builds up
Area's population is less, and the night lights remotely-sensed data of substantially non-built-up areas need not be carved just close to nothing in step S301
Meaning obtains night lights remotely-sensed data just for built-up areas, and the nighttime light data of the target area being directly obtained can just be made
It is the nighttime light data of the target area built-up areas.
In step s 302, the night lights remotely-sensed data to above-mentioned target area is corrected, and obtains above-mentioned target area
The correction light data in domain.
In embodiments of the present invention, because the night lights remotely-sensed data got in step S301 does not make onboard process,
Cause the long-term sequence data deficiency comparativity obtained by multiple satellites.In order to improve between above-mentioned night lights remotely-sensed data
Comparativity, it is necessary to mutually being corrected between above-mentioned night lights remotely-sensed data.In step s 302, can be based on default
One- place 2-th Order regression model night lights remotely-sensed data is corrected, its computing formula is as follows:
DNcorrect=a*DN2+b*DN+c
Wherein, the DN in above formula is the night lights remotely-sensed data before got in step S301, correction, DNcorrect
It is the correction light data of the night lights remotely-sensed data after correction, i.e. target area, a, b, c are default parameter.Need
It is noted that above-mentioned default parameter is not fixed, for different target areas, above-mentioned default parameter value can also be made
Corresponding change, is not construed as limiting to it herein.
In step S303, the correction light data to above-mentioned target area carries out spatial information enhancing treatment, obtains
State the light index of target area.
In embodiments of the present invention, although step S302 night lights remotely-sensed datas to being got in step S301
Corrected, but because the night lights remotely-sensed data resolution ratio got in step S301 is thicker, thus in urban area
Carrying out Remote sensing monitoring has limitation.Accordingly, it would be desirable to the correction light data to being obtained in step S302 carries out space letter
Breath enhancing treatment, can meet urban remote sensing and research and analyse.
Specifically, above-mentioned steps S303 includes:
Obtain the optical remote sensing data of above-mentioned target area, go out from the optical remote sensing extracting data of above-mentioned target area on
State the near infrared band reflectivity and red wave band reflectivity of target area;
Based on default normalized differential vegetation index computing formula, near infrared band reflectivity according to above-mentioned target area and
Red wave band reflectivity is calculated the vegetation index of above-mentioned target area;
According to above-mentioned vegetation index and above-mentioned light correction data, the light index for obtaining above-mentioned target area is calculated.
Wherein, step S303 can be based on the relation between the normalized differential vegetation index of target area and correction light data
Carry out spatial information enhancing treatment, above-mentioned normalized differential vegetation index (NDVI, Normalized Difference Vegetation
Index computing formula) is as follows:
NDVI=(B4-B3)/(B4+B3)
In above-mentioned computing formula, B4 be near infrared band reflectivity, B3 be red wave band reflectivity, above-mentioned data both from
In the optical remote sensing data of target area.After normalized differential vegetation index has been got, believed according to default light data cavity
Breath enhancing computing formula, obtains the final light index in target area.Above-mentioned default light data spatial information enhancing is calculated
Formula is as follows:
NI=DNcorrect*(1-NDVI)
Wherein, NI is the light index of target area finally given in step S303.It should be noted that with above-mentioned step
The normalization building index obtained in rapid S202 is similar, and what is finally given in step S303 is any for target area
The light index of point.
Alternatively, the specific formula for calculation of ghost town index is as follows in above-mentioned steps S103:
GI=NInor/NDBInor
As being illustrated in step S103, it is necessary to the target area to obtaining is built before ghost town index is calculated
If index and light index first do normalized, the two normative reference is consistent, and the two Numerical Control is existed
In the range of identical.Thus, in the computing formula of above-mentioned ghost town index, NInorFinally given in normalized step S303
The light index of target area, NDBInorIt is the construction index of target area finally given in normalized step S203, GI
It is the ghost town index of target area.Lead to above-mentioned ghost town formula of index, the ghost town of target area any point can be calculated
Index, i.e., can carry out three-dimensional analysis to target area.
From the foregoing, it will be observed that in the embodiment of the present invention, the ghost town index of target area is not a unique numerical value, in fact,
In any point of target area built-up areas, the ghost town index of the point can be obtained by the method for the embodiment of the present invention, finally
Whole target area ghost town index big data is obtained in that, the ghost town phenomenon situation of change solid of target area is presented to use
Family, more intuitively.The present invention program is with strong points to the UrbaniZed Area that excessive real estate expands, being capable of efficient measure urbanization
Ghost town spatial distribution, quantify Development of Urbanization coordination degree, be urbanization remote sensing monitoring, Land Development and environmental protection,
Ecological city good for habitation's construction and urban sustainable development provide technical support and scientific basis.
One of ordinary skill in the art will appreciate that all or part of step in realizing above-described embodiment method can be
The hardware of correlation is instructed to complete by program, corresponding program can be stored in a computer read/write memory medium,
Above-mentioned storage medium, such as ROM/RAM, disk or CD.
Embodiment two
Fig. 4 shows the concrete structure block diagram of the urbanization ghost town index evaluating apparatus that the embodiment of the present invention two is provided, and is
It is easy to explanation, illustrate only the related part of the embodiment of the present invention.Urbanization ghost town index evaluating apparatus 4 include:It is yet to be built
If index acquiring unit 41, light index acquiring unit 42, ghost town exponent calculation unit 43.
Wherein, building index acquiring unit 41 is used to obtain the construction index of target area;
Light index acquiring unit 42 is used to obtain light index of the above-mentioned target area in preset time period;
Ghost town exponent calculation unit 43 is used for the light of the target area for getting above-mentioned light index acquiring unit 42
The construction index of the target area that index gets divided by above-mentioned construction index acquiring unit 41, obtains the ghost of above-mentioned target area
City index.
Alternatively, above-mentioned construction index acquiring unit 41, including:
Subelement, the built-up areas for delimiting above-mentioned target area delimited in built-up areas;
Construction land index computation subunit, the optics of the built-up areas that subelement delimited delimited for obtaining above-mentioned built-up areas
Remotely-sensed data, the optical remote sensing data according to above-mentioned built-up areas are calculated the construction land index of above-mentioned built-up areas;
Index determination subelement is built, for the built-up areas that are calculated above-mentioned construction land index computation subunit
Construction land index as above-mentioned target area construction index.
Alternatively, subelement delimited in above-mentioned built-up areas, including:
Microwave remote sensing data acquisition subelement, the microwave remote sensing data for obtaining above-mentioned target area;
Optical remote sensing data acquisition subelement, the optical remote sensing data for obtaining above-mentioned target area;
Modeling subelement, for based on Object-oriented Technique, being got according to above-mentioned microwave remote sensing data acquisition subelement
Target area microwave remote sensing data and the optics of target area that gets of above-mentioned optical remote sensing data acquisition subelement it is distant
Sense data build the built-up areas information extraction model of above-mentioned target area;
Boundary information extract subelement, for being extracted in the built-up areas information extraction model that is built from above-mentioned modeling subelement
Go out the built-up areas border of above-mentioned target area, the built-up areas of target area delimited according to above-mentioned built-up areas border.
Alternatively, above-mentioned light index acquiring unit 42, including:
Night lights remotely-sensed data obtains subelement, for obtaining night lamp of the above-mentioned target area in preset time period
Light remotely-sensed data;
Night lights remotely-sensed data corrects subelement, is got for obtaining subelement to above-mentioned night lights remotely-sensed data
The night lights remotely-sensed data of target area be corrected, obtain the correction light data of above-mentioned target area;
Spatial information enhancing treatment subelement, for the target obtained to above-mentioned night lights remotely-sensed data correction subelement
The correction light data in region carries out spatial information enhancing treatment, obtains the light index of above-mentioned target area.
Alternatively, above-mentioned spatial information enhancing treatment subelement, including:
First optical data extracts subelement, the optical remote sensing data for obtaining above-mentioned target area, from above-mentioned target
The optical remote sensing extracting data in region goes out the near infrared band reflectivity and red wave band reflectivity of above-mentioned target area;
Vegetation index computation subunit, for based on default normalized differential vegetation index computing formula, according to above-mentioned first
The near infrared band reflectivity and red wave band reflectivity that optical data extracts the target area that subelement is extracted are calculated
State the vegetation index of target area;
Light index computation subunit, for the vegetation index that is calculated according to above-mentioned vegetation index computation subunit and
The light correction data that above-mentioned night lights remotely-sensed data correction subelement is obtained, the light for calculating the above-mentioned target area of acquisition refers to
Number.
Alternatively, above-mentioned construction land index computation subunit, including:
Second optical data extracts subelement, the optical remote sensing data for obtaining above-mentioned built-up areas, from above-mentioned built-up areas
Optical remote sensing extracting data go out the near infrared band reflectivity and red wave band reflectivity of above-mentioned built-up areas;
Construction land information extraction subelement, for extracting the built-up areas that subelement is obtained according to above-mentioned second optical data
Near infrared band reflectivity and red wave band reflectivity, calculate the construction land index for obtaining above-mentioned built-up areas.
From the foregoing, it will be observed that in the embodiment of the present invention, urbanization ghost town index evaluating apparatus application and construction index and light index
The ghost town index of target area to be evaluated is calculated, the data for obtaining in the process are all objective data, it is thus possible to
Being evaluated and tested to urbanization ghost town degree for more objective quantitative, realizes the objective evaluation to target area urban development.Also, most
The ghost town index of the target area for obtaining eventually is not a unique numerical value, in fact, in any point of target area built-up areas,
The ghost town index of the point can be obtained by urbanization ghost town index evaluating apparatus provided in an embodiment of the present invention, finally can
Whole target area ghost town index big data is obtained, the ghost town phenomenon situation of change solid of target area user is presented to, more
For directly perceived.The present invention program is with strong points to the UrbaniZed Area that excessive real estate expands, being capable of efficient measure urbanization ghost town
Spatial distribution, quantifies Development of Urbanization coordination degree, is urbanization remote sensing monitoring, Land Development and environmental protection, ecology
City good for habitation builds and urban sustainable development provides technical support and scientific basis.
It should be noted that in several embodiments provided herein, it should be understood that disclosed device and side
Method, can realize by another way.For example, device embodiment described above is only schematical, for example, above-mentioned
The division of unit, only a kind of division of logic function, can there is other dividing mode when actually realizing, such as multiple units
Or component can be combined or be desirably integrated into another system, or some features can be ignored, or not perform.It is another, institute
Display or the coupling each other for discussing or direct-coupling or communication connection can be by some interfaces, device or unit
INDIRECT COUPLING or communication connection, can be electrical, mechanical or other forms.
For foregoing each method embodiment, in order to simplicity is described, therefore it is all expressed as a series of combination of actions, but
It is that those skilled in the art should know, the present invention is not limited by described sequence of movement, because according to the present invention, certain
A little steps can sequentially or simultaneously be carried out using other.Secondly, those skilled in the art should also know, be retouched in specification
The embodiment stated belongs to preferred embodiment, necessary to involved action and module might not all be the present invention.
In the above-described embodiments, the description to each embodiment all emphasizes particularly on different fields, and does not have the portion described in detail in certain embodiment
Point, may refer to the associated description of other embodiments.
It is more than the preferred embodiment to a kind of urbanization ghost town index evaluating method provided by the present invention and device, it is right
In those of ordinary skill in the art, according to the thought of the embodiment of the present invention, can in specific embodiments and applications
There is change part, to sum up, this specification content should not be construed as limiting the invention.
Claims (10)
1. a kind of urbanization ghost town index evaluating method, it is characterised in that the urbanization ghost town index evaluating method includes:
Obtain the construction index of target area;
Obtain light index of the target area in preset time period;
By the light index of the target area divided by the construction index of the target area, the ghost town of the target area is obtained
Index.
2. urbanization ghost town index evaluating method as claimed in claim 1, it is characterised in that the acquisition target area is built
If index, including:
Delimit the built-up areas of the target area;
Obtain the optical remote sensing data of the built-up areas, the optical remote sensing data according to the built-up areas be calculated described in build up
The construction land index in area;
Using the construction land index of the built-up areas as the target area construction index.
3. urbanization ghost town index evaluating method as claimed in claim 2, it is characterised in that the delimitation target area
Built-up areas, including:
Obtain the microwave remote sensing data and optical remote sensing data of the target area;
Based on Object-oriented Technique, microwave remote sensing data and optical remote sensing data according to the target area build the target
The built-up areas information extraction model in region;
The built-up areas border of the target area is extracted from the built-up areas information extraction model, according to the built-up areas side
Boundary delimit the built-up areas of target area.
4. the urbanization ghost town index evaluating method as described in any one of claims 1 to 3, it is characterised in that the acquisition institute
Light index of the target area in preset time period is stated, including:
Obtain night lights remotely-sensed data of the target area in preset time period;
Night lights remotely-sensed data to the target area is corrected, and obtains the correction light data of the target area;
Correction light data to the target area carries out spatial information enhancing treatment, and the light for obtaining the target area refers to
Number.
5. urbanization ghost town index evaluating method as claimed in claim 4, it is characterised in that described to the correction light number
According to spatial information enhancing treatment is carried out, the light index of the target area is obtained, including:
The optical remote sensing data of the target area are obtained, the mesh is gone out from the optical remote sensing extracting data of the target area
Mark the near infrared band reflectivity and red wave band reflectivity in region;
Based on default normalized differential vegetation index computing formula, near infrared band reflectivity and red ripple according to the target area
Section reflectivity is calculated the vegetation index of the target area;
According to the vegetation index and the light correction data, the light index for obtaining the target area is calculated.
6. a kind of urbanization ghost town index evaluating apparatus, it is characterised in that the urbanization ghost town index evaluating apparatus include:
Build index acquiring unit, the construction index for obtaining target area;
Light index acquiring unit, for obtaining light index of the target area in preset time period;
Ghost town exponent calculation unit, for the light index of target area that gets the light index acquiring unit divided by
The construction index for building the target area that index acquiring unit gets, obtains the ghost town index of the target area.
7. urbanization ghost town index evaluating apparatus as claimed in claim 6, it is characterised in that the construction index obtains single
Unit, including:
Subelement, the built-up areas for delimiting the target area delimited in built-up areas;
Construction land index computation subunit, the optical remote sensing of the built-up areas that subelement delimited delimited for obtaining the built-up areas
Data, the optical remote sensing data according to the built-up areas are calculated the construction land index of the built-up areas;
Build index determination subelement, the construction of the built-up areas for the construction land index computation subunit to be calculated
Land used index as the target area construction index.
8. urbanization ghost town index evaluating apparatus as claimed in claim 7, it is characterised in that it is single that son delimited in the built-up areas
Unit, including:
Microwave remote sensing data acquisition subelement, the microwave remote sensing data for obtaining the target area;
Optical remote sensing data acquisition subelement, the optical remote sensing data for obtaining the target area;
Modeling subelement, for based on Object-oriented Technique, according to the mesh that the microwave remote sensing data acquisition subelement gets
The optical remote sensing number of the target area that the microwave remote sensing data and the optical remote sensing data acquisition subelement in mark region get
According to the built-up areas information extraction model for building the target area;
Boundary information extract subelement, for extracting institute from the built-up areas information extraction model of the modeling subelement structure
The built-up areas border of target area is stated, the built-up areas of target area delimited according to the built-up areas border.
9. urbanization ghost town index evaluating apparatus as described in any one of claim 6 to 8, it is characterised in that the light refers to
Number acquiring unit, including:
Night lights remotely-sensed data obtains subelement, distant for obtaining night lights of the target area in preset time period
Sense data;
Night lights remotely-sensed data corrects subelement, for obtaining the mesh that subelement gets to the night lights remotely-sensed data
The night lights remotely-sensed data for marking region is corrected, and obtains the correction light data of the target area;
Spatial information enhancing treatment subelement, for the target area obtained to night lights remotely-sensed data correction subelement
Correction light data carry out spatial information enhancing treatment, obtain the light index of the target area.
10. urbanization ghost town index evaluating apparatus as claimed in claim 9, it is characterised in that at the spatial information enhancing
Reason subelement, including:
First optical data extracts subelement, the optical remote sensing data for obtaining the target area, from the target area
Optical remote sensing extracting data go out the near infrared band reflectivity and red wave band reflectivity of the target area;
Vegetation index computation subunit, for based on default normalized differential vegetation index computing formula, according to first optics
The near infrared band reflectivity and red wave band reflectivity that data extract the target area that subelement is extracted are calculated the mesh
Mark the vegetation index in region;
Light index computation subunit, for the vegetation index that is calculated according to the vegetation index computation subunit and described
The light correction data that night lights remotely-sensed data correction subelement is obtained, calculates the light index for obtaining the target area.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201611218887.7A CN106682830A (en) | 2016-12-26 | 2016-12-26 | Urbanization ghost town index evaluating method and device |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201611218887.7A CN106682830A (en) | 2016-12-26 | 2016-12-26 | Urbanization ghost town index evaluating method and device |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106682830A true CN106682830A (en) | 2017-05-17 |
Family
ID=58870697
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201611218887.7A Pending CN106682830A (en) | 2016-12-26 | 2016-12-26 | Urbanization ghost town index evaluating method and device |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106682830A (en) |
Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108109127A (en) * | 2018-01-16 | 2018-06-01 | 中国科学院遥感与数字地球研究所 | A kind of city nighttime light data desaturation method based on NDBI |
CN109522788A (en) * | 2018-09-30 | 2019-03-26 | 广州地理研究所 | City scope extracting method, device and electronic equipment based on random forest sorting algorithm |
CN109784667A (en) * | 2018-12-21 | 2019-05-21 | 中国科学院遥感与数字地球研究所 | A kind of vacant monitoring method in house based on noctilucence remotely-sensed data |
CN110570470A (en) * | 2019-09-06 | 2019-12-13 | 南京大学 | ghost community identification and housing vacancy rate estimation method based on multi-source remote sensing data |
CN111506677B (en) * | 2019-01-31 | 2024-03-22 | 阿里巴巴集团控股有限公司 | Method and device for generating urban built-up area range |
-
2016
- 2016-12-26 CN CN201611218887.7A patent/CN106682830A/en active Pending
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108109127A (en) * | 2018-01-16 | 2018-06-01 | 中国科学院遥感与数字地球研究所 | A kind of city nighttime light data desaturation method based on NDBI |
CN109522788A (en) * | 2018-09-30 | 2019-03-26 | 广州地理研究所 | City scope extracting method, device and electronic equipment based on random forest sorting algorithm |
CN109522788B (en) * | 2018-09-30 | 2020-11-06 | 广州地理研究所 | City range extraction method and device based on random forest classification algorithm and electronic equipment |
CN109784667A (en) * | 2018-12-21 | 2019-05-21 | 中国科学院遥感与数字地球研究所 | A kind of vacant monitoring method in house based on noctilucence remotely-sensed data |
CN109784667B (en) * | 2018-12-21 | 2023-09-19 | 中国科学院遥感与数字地球研究所 | House space monitoring method based on noctilucent remote sensing data |
CN111506677B (en) * | 2019-01-31 | 2024-03-22 | 阿里巴巴集团控股有限公司 | Method and device for generating urban built-up area range |
CN110570470A (en) * | 2019-09-06 | 2019-12-13 | 南京大学 | ghost community identification and housing vacancy rate estimation method based on multi-source remote sensing data |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Gerten et al. | The sprawling planet: Simplifying the measurement of global urbanization trends | |
CN106682830A (en) | Urbanization ghost town index evaluating method and device | |
Wong et al. | Modelling building energy use at urban scale: A review on their account for the urban environment | |
Long et al. | Mapping block-level urban areas for all Chinese cities | |
Han et al. | How do 2D/3D urban landscapes impact diurnal land surface temperature: Insights from block scale and machine learning algorithms | |
Xu et al. | Combining night time lights in prediction of poverty incidence at the county level | |
Kotharkar et al. | Approach to local climate zone based energy consumption assessment in an Indian city | |
Li et al. | Analysis of the relationship between urban landscape patterns and thermal environment: A case study of Zhengzhou City, China | |
Wang et al. | A patch‐based cellular automaton for simulating land‐use changes at fine spatial resolution | |
Fisher-Gewirtzman et al. | View-oriented three-dimensional visual analysis models for the urban environment | |
Zambon et al. | Emerging urban centrality: An entropy-based indicator of polycentric development and economic growth | |
Yang et al. | Evaluation of a diagnostic equation for the daily maximum urban heat island intensity and its application to building energy simulations | |
Sezer et al. | Urban microclimate and building energy models: A review of the latest progress in coupling strategies | |
CN110991874A (en) | Building group microenvironment evaluation method, platform and system | |
Zhou et al. | Development and implementation of a spatial unit non-overlapping water stress index for water scarcity evaluation with a moderate spatial resolution | |
CN105354781A (en) | Rural hollowing degree early warning system | |
Hughes | Three decades of hydrological modelling research in South Africa | |
Li et al. | Evaluating rural sustainable land use from a system perspective based on the ecosystem service value | |
Hu et al. | Green-gray imbalance: Rapid urbanization reduces the probability of green space exposure in early 21st century China | |
Zhang et al. | Impact of spatial structure on the functional connectivity of urban ecological corridors based on quantitative analysis | |
Zhang et al. | Towards a Fairer Green city: Measuring unfairness in daily accessible greenery in Chengdu’s central city | |
Li et al. | Assessing urban micro-climates with vertical and horizontal building morphological cutting deep transfer learning neural networks | |
Yang et al. | Improved landscape sampling method for landscape character assessment | |
Kotharkar et al. | Investigating outdoor thermal comfort variations across Local Climate Zones in Nagpur, India, using ENVI-met | |
CN102880753B (en) | Based on the land utilization space characteristic dimension conversion method of fractal dimension |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20170517 |
|
RJ01 | Rejection of invention patent application after publication |