CN110189617A - A kind of the space mapping method, apparatus and medium of urban Heat Environment Dominated Factors - Google Patents
A kind of the space mapping method, apparatus and medium of urban Heat Environment Dominated Factors Download PDFInfo
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- CN110189617A CN110189617A CN201910391857.3A CN201910391857A CN110189617A CN 110189617 A CN110189617 A CN 110189617A CN 201910391857 A CN201910391857 A CN 201910391857A CN 110189617 A CN110189617 A CN 110189617A
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
- G09B29/003—Maps
- G09B29/005—Map projections or methods associated specifically therewith
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- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B29/00—Maps; Plans; Charts; Diagrams, e.g. route diagram
- G09B29/003—Maps
- G09B29/006—Representation of non-cartographic information on maps, e.g. population distribution, wind direction, radiation levels, air and sea routes
- G09B29/007—Representation of non-cartographic information on maps, e.g. population distribution, wind direction, radiation levels, air and sea routes using computer methods
Abstract
The invention discloses a kind of space mapping method, apparatus of urban Heat Environment Dominated Factors and media, which comprises obtains urban Heat Environment situation and urban green space information using remote sensing image data；Grid cell is set, chooses the pattern index for having close association with urban Heat Environment, calculates mean temperature information and green-space pattern index in each unit；The relative coefficient for calculating surface temperature and each pattern index filters out the highest typical pattern index of preceding 4 correlations；All combinations for considering this 4 pattern indexes construct 2 using Geographical Weighted Regression algorithm respectively4The model of a surface temperature and pattern index obtains all model part coefficient of determination Local R2Spatial distribution characteristic；Using hierachical decomposition algorithm to the Local R of all models2It is decomposed, identifies that the maximum pattern index of percentage contribution in each grid cell completes urban Heat Environment Dominated Factors space mapping.The present invention can accurately construct urban Heat Environment Dominated Factors space diagram.
Description
Technical field
The present invention relates to environmental monitoring technology fields, and in particular to a kind of space mapping side of urban Heat Environment Dominated Factors
Method, device and medium.
Background technique
Urbanization propulsion causes town site to be expanded, and profoundly changes surface heat flux budget, so that Urban Thermal
Environment constantly deteriorates.The extensive use of remote sensing image data on different spaces scale so that carry out urban Heat Environment drive mechanism
Research is possibly realized.But passing research is usually regarded as city the region of homogeneous, it is analyzing the result is that single one
A Dominated Factors have ignored the height heterogeneity feature of urban landscape pattern significantly.Therefore, seek the Urban Thermal ring being simple and efficient
Border Dominated Factors space mapping method, the crucial landscape feature of quick positioning effects urban Heat Environment, to improvement urban Heat Environment
There is important practice significance with building city good for habitation.
But in the research and practice process to the prior art, it was found by the inventors of the present invention that the prior art is generally adopted
Take single Geographically weighted regression procedure (geographic weighted regression) or hierachical decomposition algorithm
(Hierarchical partitioning), analysis result is more unilateral, causes the modeling accuracy based on geographical image lower,
Lack one kind and rationally and accurately constructs urban Heat Environment Dominated Factors space mapping method.
Summary of the invention
The technical problem to be solved by the embodiment of the invention is that providing a kind of space system of urban Heat Environment Dominated Factors
Drawing method, device and medium accurately construct urban Heat Environment Dominated Factors space diagram.
To solve the above problems, one embodiment of the present of invention provides a kind of space mapping of urban Heat Environment Dominated Factors
Method includes the following steps: suitable for executing computer equipment
Landsat TM image data based on remote sensing image equipment acquisition survey region is pre-processed, city is obtained
Surface temperature data and urban green space Patches information；
The grid cell of several same sizes is set in the survey region, each institute is calculated using range statistics method
The average surface temperature of grid cell is stated, and chooses the landscape indices for having substantial connection with urban Heat Environment, described in calculating
Pattern of Urban Green Land Features's index information in each grid cell；
Using each grid cell as sample, calculates separately the average surface temperature and refer to selected landscape pattern
Relative coefficient between number successively sorts according to its absolute value, chooses absolute value highest first 4 as typical green-space pattern
Index；
According to the average surface temperature and 4 typical green-space pattern indexes, using Geographical Weighted Regression algorithm point
It Gou Jian 24The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24A model part coefficient of determination Local
R2Spatial distribution characteristic；
Using hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2It is decomposed, is obtained every
The joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in one grid cell complete urban Heat Environment master
The space mapping of control factor.
Further, the pretreatment specifically:
The Landsat TM image data based on remote sensing image equipment acquisition survey region is converted into using the first formula
Urban surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains city
Greenery patches Patches information.
Further, first formula specifically:
Wherein, TsFor real surface temperature, unit K, a and b are constant, respectively 67.35 and 0.46, TaIt is flat for atmosphere
Equal operative temperature, C=ε τ and D=(1- ε) [1+ (1- ε) τ] are intermediate variable, and τ is atmospheric transmittance, and ε is emissivity.
Further, the space mapping for completing urban Heat Environment Dominated Factors, specifically:
The individual contributions for marking each grid cell in the survey region in different colors refer to than highest green-space pattern
Number；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and raw
At report.
Further, the landscape indices for having substantial connection with urban Heat Environment include area percentage (PER),
Average plaque size (MPS), boundary density (ED), total edge length (TE), mean patch fractal dimension number (MPFD), landscape shape refer to
Mark (LSI) and maximum plaque index (LPI).
Further, the urban Heat Environment prediction model, specifically:
Wherein, LSTiFor the surface temperature value of position i, β0(ui,vi) be position i regression coefficient, xizFor z-th of pattern
Index, (ui,vi) it is spatial position coordinate, ε is the error of specific position i.
One embodiment of the present of invention additionally provides a kind of space mapping device of urban Heat Environment Dominated Factors, comprising:
Preprocessing module, for being carried out to the Landsat TM image data based on remote sensing image equipment acquisition survey region
Pretreatment, obtains urban surface temperature data and urban green space Patches information；
Computing module is united for the grid cell of several same sizes to be arranged in the survey region using region
Meter method calculates the average surface temperature of each grid cell, and chooses the landscape pattern for having substantial connection with urban Heat Environment
Index calculates Pattern of Urban Green Land Features's index information in each grid cell；
Index screening module, for using each grid cell as sample, calculate separately the average surface temperature with
Relative coefficient between selected landscape indices successively sorts according to its absolute value, chooses absolute value highest preceding 4
It is a to be used as typical green-space pattern index；
Prediction model module is constructed, for adopting according to the average surface temperature and 4 typical green-space pattern indexes
2 are constructed respectively with Geographical Weighted Regression algorithm4The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24It is a
Model part coefficient of determination Local R2Spatial distribution characteristic；
Drawing module, for utilizing hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2Into
Row decomposes, and obtains the joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in each grid cell, complete
At the space mapping of urban Heat Environment Dominated Factors.
Further, the pretreatment specifically:
The Landsat TM image data based on remote sensing image equipment acquisition survey region is converted into using the first formula
Urban surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains city
Greenery patches Patches information.
Further, the space mapping for completing urban Heat Environment Dominated Factors, specifically:
The individual contributions for marking each grid cell in the survey region in different colors refer to than highest green-space pattern
Number；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and raw
At report.
One embodiment of the present of invention additionally provides a kind of computer readable storage medium, the computer-readable storage medium
Matter includes the computer program of storage, wherein controls the computer readable storage medium in computer program operation
Place equipment executes the space mapping method such as above-mentioned urban Heat Environment Dominated Factors.
The implementation of the embodiments of the present invention has the following beneficial effects:
The space mapping method, apparatus and medium of a kind of urban Heat Environment Dominated Factors provided in an embodiment of the present invention, institute
The method of stating includes: to pre-process to the Landsat TM image data based on remote sensing image equipment acquisition survey region, is obtained
Urban surface temperature data and urban green space Patches information；The grid list of several same sizes is set in the survey region
Member calculates the average surface temperature of each grid cell using range statistics method, and selection has closely with urban Heat Environment
The landscape indices of relationship calculate Pattern of Urban Green Land Features's index information in each grid cell；With described every
A grid cell is sample, calculates separately the correlation system between the average surface temperature and selected landscape indices
Number, successively sorts according to its absolute value, chooses absolute value highest first 4 as typical green-space pattern index；According to described flat
Equal surface temperature and 4 typical green-space pattern indexes, construct 2 using Geographical Weighted Regression algorithm respectively4A green-space pattern
The urban Heat Environment prediction model of index, obtains corresponding 24A model part coefficient of determination Local R2Spatial distribution characteristic；
Using hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2It is decomposed, obtains each grid list
The joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in member complete urban Heat Environment Dominated Factors
Space mapping.The present invention can give full play to Geographical Weighted Regression space expression advantage and hierachical decomposition in percentage contribution
The advantage of excavation, it is contemplated that the special heterogeneity of urban Heat Environment influence factor accurately constructs urban Heat Environment Dominated Factors
Space diagram realizes the fast accurate positioning of urban Heat Environment Dominated Factors.
Detailed description of the invention
Fig. 1 is a kind of process of the space mapping method for urban Heat Environment Dominated Factors that first embodiment of the invention provides
Schematic diagram；
Fig. 2 is the thermal environment Dominated Factors spatial distribution and a Dominated Factors accounting situation that first embodiment of the invention provides
Figure；
Fig. 3 is the stream of the space mapping method for another urban Heat Environment Dominated Factors that first embodiment of the invention provides
Journey schematic diagram；
Fig. 4 is a kind of structure of the space mapping device for urban Heat Environment Dominated Factors that second embodiment of the invention provides
Schematic diagram.
Specific embodiment
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
The application scenarios that the present invention can provide are introduced first, such as construct the space diagram of urban heat island Dominated Factors.
It should be noted that in the specific embodiment of the invention, it is distant using Guangzhou core space 20km × 20km as case region
Feel the Landsat TM image and city aerial images in 2010 that image data source is on June 1st, 2011.The present invention can be at it
It is used on its remote sensing image data, as MODIS image data provides for the surface temperature data of 1km spatial resolution, the number
According to the urban Heat Environment drive mechanism research that can be used on group of cities scale.Except, can by method provided by the invention also with
It is generalized to other subject, is used for Dominated Factors space mapping.
First embodiment of the invention:
Please refer to Fig. 1-3.
As shown in Figure 1, a kind of space mapping method of urban Heat Environment Dominated Factors provided in this embodiment, suitable for counting
It calculates and is executed in machine equipment, included the following steps:
S101, the Landsat TM image data based on remote sensing image equipment acquisition survey region is pre-processed, is obtained
To urban surface temperature data and urban green space Patches information；
Specifically, calculating urban surface temperature regime T based on Landsat TM image data for step S101s, it is based on
The research area aerial images data in 2010 carry out landscape types classification to image data using object-oriented method, extract city
City greenery patches Patches information.
In a preferred embodiment, the pretreatment specifically:
The Landsat TM image data based on remote sensing image equipment acquisition survey region is converted into using the first formula
Urban surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains city
Greenery patches Patches information.
In a preferred embodiment, first formula specifically:
Wherein, TsFor real surface temperature, unit K, a and b are constant, respectively 67.35 and 0.46, TaIt is flat for atmosphere
Equal operative temperature, the data see research on June 1st, 2011 area atmospheric condition and obtain, C=ε τ and D=(1- ε) [1+ (1- ε)
τ] it is intermediate variable, τ is atmospheric transmittance, and ε is emissivity.
S102, the grid cell that several same sizes are arranged in the survey region are calculated using range statistics method
The average surface temperature of each grid cell, and the landscape indices for having substantial connection with urban Heat Environment are chosen, meter
Calculate Pattern of Urban Green Land Features's index information in each grid cell；
Specifically, according to the range in selected research area, the grid list of certain 500m × 500m is arranged for step S102
Member calculates average surface temperature in each grid cell.According to existing research achievement, the present embodiment has chosen to be had with urban environment
The pattern index of close association, selected landscape indices include area percentage (percent cover, PER), are averaged
Patch size (mean patch size, MPS), boundary density (edge density, ED), total edge length (total
Edge, TE), mean patch fractal dimension number (Mean patch fractal dimension, MPFD), landscape shape index
(Landscape shape index, LSI) and maximum plaque index (Largest patch index, LPI) totally 7, asks calculation
Pattern of Urban Green Land Features's index information inside each grid cell.
In a preferred embodiment, the landscape indices for having substantial connection with urban Heat Environment include area percentage
Than (PER), average plaque size (MPS), boundary density (ED), total edge length (TE), mean patch fractal dimension number (MPFD), scape
See Shape Indexes (LSI) and maximum plaque index (LPI).
S103, using each grid cell as sample, calculate separately the average surface temperature and selected landscape
Relative coefficient between pattern index successively sorts according to its absolute value, chooses absolute value highest first 4 as typical green
Ground pattern index；
Specifically, for step S103, using all grid cells as sample, the average surface temperature of calculation and selected is sought
It is green to obtain the preceding highest typical case of 4 correlations by sequence after absolute value for relative coefficient between the pattern index of urban green space
Ground pattern index, in the present embodiment, by area percentage (PER), average plaque size (MPS), boundary density (ED) and most
The independent variable that big plaque index (LPI) is modeled as next step urban Heat Environment.
S104, according to the average surface temperature and 4 typical green-space pattern indexes, calculated using Geographical Weighted Regression
Method constructs 2 respectively4The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24A model part coefficient of determination
Local R2Spatial distribution characteristic；
Specifically, for step S104, all possible groups of the highest 4 green-space pattern indexes of the correlation considered
It closes, the present embodiment totally 4 pattern indexes, therefore all model groups have amounted to 24It is a.Utilize Geographical Weighted Regression algorithm building 24
The surface temperature prediction model of a green-space pattern index, obtains 24A model part coefficient of determination Local R2Spatial distribution it is special
Sign.
In a preferred embodiment, the landscape indices for having substantial connection with urban Heat Environment include area percentage
Than (PER), average plaque size (MPS), boundary density (ED), total edge length (TE), mean patch fractal dimension number (MPFD), scape
See Shape Indexes (LSI) and maximum plaque index (LPI).
In a preferred embodiment, the urban Heat Environment prediction model, specifically:
Wherein, LSTiFor the surface temperature value of position i, β0(ui,vi) be position i regression coefficient, xizFor z-th of pattern
Index, (ui,vi) it is spatial position coordinate, ε is the error of specific position i.
S105, using hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2It is decomposed, is obtained
The joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in each grid cell complete Urban Thermal ring
The space mapping of border Dominated Factors.
Specifically, for step S105, as shown in Fig. 2, there is sky to what all models obtained using hierachical decomposition algorithm
Between distribution characteristics Local R2It is decomposed, obtains the joint contribution percentage of every kind of green-space pattern index in each grid cell
Than with individual contributions percentage, as shown in Fig. 2 (a), most eventually by the individual contributions percentage identified in each grid cell
Big pattern index completes urban Heat Environment Dominated Factors space mapping, and the present embodiment result please refers to Fig. 2 (b), as the result is shown
The Dominated Factors spatial distribution of urban Heat Environment has notable difference, and the area percentage (PER) of urban green space spatially divides
Cloth is widest in area, accounts for the 69.29% of case regional scope, followed by boundary density (ED), accounting 26.48%, maximum spot
Block index (LPI) accounting is 3.88%, and the range of average plaque size (MPS) is minimum, only 0.36%.
In a preferred embodiment, the space mapping for completing urban Heat Environment Dominated Factors, specifically:
The individual contributions for marking each grid cell in the survey region in different colors refer to than highest green-space pattern
Number；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and raw
At report.
As shown in figure 3, in the particular embodiment, additionally providing the space mapping of another urban Heat Environment Dominated Factors
Method includes the following steps: to obtain urban Heat Environment situation and urban green space information using remote sensing image data；Setting is certain big
Small grid cell chooses the pattern index for having close association with urban Heat Environment, mean temperature in each unit is calculated
Information and green-space pattern index；The relative coefficient for calculating surface temperature and each pattern index, thus filters out preceding 4 correlations
Property highest typical pattern index；All combinations for considering this 4 pattern indexes, are constructed respectively using Geographical Weighted Regression algorithm
The model of surface temperature and pattern index obtains all model part coefficient of determination Local R2Spatial distribution characteristic；It utilizes
Local R of the hierachical decomposition algorithm to all models2It is decomposed, by identifying the percentage contribution in each grid cell most
Big pattern index completes urban Heat Environment Dominated Factors space mapping.
The space mapping method of a kind of urban Heat Environment Dominated Factors provided in this embodiment, which comprises to base
It is pre-processed in the Landsat TM image data of remote sensing image equipment acquisition survey region, obtains urban surface temperature data
With urban green space Patches information；The grid cell of several same sizes is set in the survey region, using range statistics
Method calculates the average surface temperature of each grid cell, and choose has the landscape pattern of substantial connection to refer to urban Heat Environment
Number calculates Pattern of Urban Green Land Features's index information in each grid cell；Using each grid cell as sample,
Calculate separately the relative coefficient between the average surface temperature and selected landscape indices, according to its absolute value according to
Minor sort chooses absolute value highest first 4 as typical green-space pattern index；According to the average surface temperature and described 4
A typical case's green-space pattern index, constructs 2 using Geographical Weighted Regression algorithm respectively4The urban Heat Environment of a green-space pattern index is pre-
Model is surveyed, obtains corresponding 24A model part coefficient of determination Local R2Spatial distribution characteristic；Utilize hierachical decomposition algorithm point
It is other to described 24A model part coefficient of determination Local R2It is decomposed, obtains every kind of green-space pattern in each grid cell and refer to
Several joint percentage contributions and individual contributions percentage completes the space mapping of urban Heat Environment Dominated Factors.Energy of the present invention
Enough give full play to the advantage that Geographical Weighted Regression is excavated in the advantage and hierachical decomposition of space expression in percentage contribution, it is contemplated that
The special heterogeneity of urban Heat Environment influence factor accurately constructs urban Heat Environment Dominated Factors space diagram, realizes Urban Thermal
The fast accurate of environment Dominated Factors positions.
Second embodiment of the invention:
Please refer to Fig. 2 and Fig. 4.
As shown in figure 4, the present embodiment additionally provides a kind of space mapping device of urban Heat Environment Dominated Factors, comprising:
Preprocessing module 100, for the Landsat TM image data based on remote sensing image equipment acquisition survey region
It is pre-processed, obtains urban surface temperature data and urban green space Patches information；
Specifically, calculating urban surface temperature regime based on Landsat TM image data for preprocessing module 100
Ts, the research area aerial images data in 2010 are based on, landscape types classification is carried out to image data using object-oriented method,
Extract urban green space Patches information.
In a preferred embodiment, the pretreatment specifically:
The Landsat TM image data based on remote sensing image equipment acquisition survey region is converted into using the first formula
Urban surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains city
Greenery patches Patches information.
In a preferred embodiment, first formula specifically:
Wherein, TsFor real surface temperature, unit K, a and b are constant, respectively 67.35 and 0.46, TaIt is flat for atmosphere
Equal operative temperature, the data see research on June 1st, 2011 area atmospheric condition and obtain, C=ε τ and D=(1- ε) [1+ (1- ε)
τ] it is intermediate variable, τ is atmospheric transmittance, and ε is emissivity.
Computing module 200, for the grid cell of several same sizes to be arranged in the survey region, using region
Statistic law calculates the average surface temperature of each grid cell, and chooses the landscape lattice for having substantial connection with urban Heat Environment
Office's index, calculates Pattern of Urban Green Land Features's index information in each grid cell；
Specifically, according to the range in selected research area, the net of certain 500m × 500m is arranged for computing module 200
Lattice unit calculates average surface temperature in each grid cell.According to existing research achievement, the present embodiment is had chosen and city ring
There is a pattern index of close association in border, selected landscape indices include area percentage (percent cover, PER),
Average plaque size (mean patch size, MPS), boundary density (edge density, ED), total edge length (total
Edge, TE), mean patch fractal dimension number (Mean patch fractal dimension, MPFD), landscape shape index
(Landscape shape index, LSI) and maximum plaque index (Largest patch index, LPI) totally 7, asks calculation
Pattern of Urban Green Land Features's index information inside each grid cell.
In a preferred embodiment, the landscape indices for having substantial connection with urban Heat Environment include area percentage
Than (PER), average plaque size (MPS), boundary density (ED), total edge length (TE), mean patch fractal dimension number (MPFD), scape
See Shape Indexes (LSI) and maximum plaque index (LPI).
Index screening module 300, for using each grid cell as sample, calculating separately the average surface temperature
It with the relative coefficient between selected landscape indices, is successively sorted according to its absolute value, it is highest to choose absolute value
First 4 as typical green-space pattern index；
Specifically, for index screening module 300, using all grid cells as sample, ask the average surface temperature of calculation with
Relative coefficient between selected urban green space pattern index obtains preceding 4 correlation highests by sorting after absolute value
Typical green-space pattern index, in the present embodiment, by area percentage (PER), average plaque size (MPS), boundary density
(ED) and the independent variable that is modeled as next step urban Heat Environment of maximum plaque index (LPI).
Prediction model module 400 is constructed, for referring to according to the average surface temperature and 4 typical green-space patterns
Number, constructs 2 using Geographical Weighted Regression algorithm respectively4The urban Heat Environment prediction model of a green-space pattern index, is corresponded to
24A model part coefficient of determination Local R2Spatial distribution characteristic；
Specifically, for constructing prediction model module 400, the highest 4 green-space pattern indexes of the correlation considered
All possible combinations, the present embodiment totally 4 pattern indexes, therefore all model groups have amounted to 24It is a.It is weighted using geography
Regression algorithm building 24The surface temperature prediction model of a green-space pattern index, obtains 24A model part coefficient of determination Local
R2Spatial distribution characteristic.
In a preferred embodiment, the landscape indices for having substantial connection with urban Heat Environment include area percentage
Than (PER), average plaque size (MPS), boundary density (ED), total edge length (TE), mean patch fractal dimension number (MPFD), scape
See Shape Indexes (LSI) and maximum plaque index (LPI).
In a preferred embodiment, the urban Heat Environment prediction model, specifically:
Wherein, LSTiFor the surface temperature value of position i, β0(ui,vi) be position i regression coefficient, xizFor z-th of pattern
Index, (ui,vi) it is spatial position coordinate, ε is the error of specific position i.
Drawing module 500, for utilizing hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2
It is decomposed, obtains the joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in each grid cell,
Complete the space mapping of urban Heat Environment Dominated Factors.
Specifically, for module 500 of charting, as shown in Fig. 2, having using hierachical decomposition algorithm to what all models obtained
The Local R of spatial distribution characteristic2It is decomposed, obtains the joint contribution hundred of every kind of green-space pattern index in each grid cell
Divide ratio and individual contributions percentage, as shown in Fig. 2 (a), eventually by the individual contributions percentage identified in each grid cell
Maximum pattern index completes urban Heat Environment Dominated Factors space mapping, and the present embodiment result please refers to Fig. 2 (b), as a result shows
Show that the Dominated Factors spatial distribution of urban Heat Environment has notable difference, the area percentage (PER) of urban green space is spatially
Distribution is most wide, accounts for the 69.29% of case regional scope, followed by boundary density (ED), and accounting 26.48% is maximum
Plaque index (LPI) accounting is 3.88%, and the range of average plaque size (MPS) is minimum, only 0.36%.
In a preferred embodiment, the space mapping for completing urban Heat Environment Dominated Factors, specifically:
The individual contributions for marking each grid cell in the survey region in different colors refer to than highest green-space pattern
Number；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and raw
At report.
The space mapping device of urban Heat Environment Dominated Factors provided in this embodiment, comprising: preprocessing module, for pair
Landsat TM image data based on remote sensing image equipment acquisition survey region is pre-processed, and urban surface temperature number is obtained
According to urban green space Patches information；Computing module, for the grid list of several same sizes to be arranged in the survey region
Member calculates the average surface temperature of each grid cell using range statistics method, and selection has closely with urban Heat Environment
The landscape indices of relationship calculate Pattern of Urban Green Land Features's index information in each grid cell；Index screening
Module, for using each grid cell as sample, calculating separately the average surface temperature and selected landscape pattern
Relative coefficient between index successively sorts according to its absolute value, chooses absolute value highest first 4 as typical greenery patches lattice
Office's index；Prediction model module is constructed, for adopting according to the average surface temperature and 4 typical green-space pattern indexes
2 are constructed respectively with Geographical Weighted Regression algorithm4The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24It is a
Model part coefficient of determination Local R2Spatial distribution characteristic；Drawing module, for utilizing hierachical decomposition algorithm respectively to institute
It states 24 model part coefficient of determination Local R2 to be decomposed, obtains the connection of every kind of green-space pattern index in each grid cell
Percentage contribution and individual contributions percentage are closed, the space mapping of urban Heat Environment Dominated Factors is completed.The present invention can be abundant
Play the advantage that Geographical Weighted Regression is excavated in the advantage and hierachical decomposition of space expression in percentage contribution, it is contemplated that Urban Thermal
The special heterogeneity of environmental impact factor accurately constructs urban Heat Environment Dominated Factors space diagram, realizes urban Heat Environment master
The fast accurate of control factor positions.
One embodiment of the present of invention additionally provides a kind of computer readable storage medium, the computer-readable storage medium
Matter includes the computer program of storage, wherein controls the computer readable storage medium in computer program operation
Place equipment executes the space mapping method such as above-mentioned urban Heat Environment Dominated Factors.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principle of the present invention, several improvement and deformations can also be made, these improvement and deformations are also considered as
Protection scope of the present invention.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can be magnetic
Dish, CD, read-only memory (Read-Only Memory, ROM) or random access memory (Random Access
Memory, RAM) etc..
Claims (10)
1. a kind of space mapping method of urban Heat Environment Dominated Factors, suitable for executing computer equipment, feature exists
In including the following steps:
Landsat TM image data based on remote sensing image equipment acquisition survey region is pre-processed, urban surface is obtained
Temperature data and urban green space Patches information；
The grid cell of several same sizes is set in the survey region, each net is calculated using range statistics method
The average surface temperature of lattice unit, and the landscape indices for having substantial connection with urban Heat Environment are chosen, it calculates described each
Pattern of Urban Green Land Features's index information in grid cell；
Using each grid cell as sample, calculate separately the average surface temperature and selected landscape indices it
Between relative coefficient, successively sorted according to its absolute value, choose absolute value highest first 4 and refer to as typical green-space pattern
Number；
According to the average surface temperature and 4 typical green-space pattern indexes, structure is distinguished using Geographical Weighted Regression algorithm
Build 24The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24A model part coefficient of determination Local R2
Spatial distribution characteristic；
Using hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2It is decomposed, obtains each net
The joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in lattice unit, complete urban Heat Environment master control because
The space mapping of element.
2. the space mapping method of urban Heat Environment Dominated Factors according to claim 1, which is characterized in that the pre- place
Reason specifically:
City is converted into the Landsat TM image data based on remote sensing image equipment acquisition survey region using the first formula
Surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains urban green space
Patches information.
3. the space mapping method of urban Heat Environment Dominated Factors according to claim 2, which is characterized in that described first
Formula specifically:
Wherein, TsFor real surface temperature, unit K, a and b are constant, respectively 67.35 and 0.46, TaAveragely make for atmosphere
With temperature, C=ε τ and D=(1- ε) [1+ (1- ε) τ] are intermediate variable, and τ is atmospheric transmittance, and ε is emissivity.
4. the space mapping method of urban Heat Environment Dominated Factors according to claim 1, which is characterized in that the completion
The space mapping of urban Heat Environment Dominated Factors, specifically:
The individual contributions of each grid cell in the survey region are marked in different colors than highest green-space pattern index；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and generates report
Table.
5. the space mapping method of urban Heat Environment Dominated Factors according to claim 1, which is characterized in that described and city
The landscape indices that city's thermal environment has substantial connection include that area percentage (PER), average plaque size (MPS), boundary are close
Spend (ED), total edge length (TE), mean patch fractal dimension number (MPFD), landscape shape index (LSI) and maximum plaque index
(LPI)。
6. the space mapping method of urban Heat Environment Dominated Factors according to claim 1, which is characterized in that the city
Thermal environment prediction model, specifically:
Wherein, LSTiFor the surface temperature value of position i, β0(ui,vi) be position i regression coefficient, xizFor z-th of pattern index,
(ui,vi) it is spatial position coordinate, ε is the error of specific position i.
7. a kind of space mapping device of urban Heat Environment Dominated Factors characterized by comprising
Preprocessing module, for being located in advance to the Landsat TM image data based on remote sensing image equipment acquisition survey region
Reason, obtains urban surface temperature data and urban green space Patches information；
Computing module, for the grid cell of several same sizes to be arranged in the survey region, using range statistics method
The average surface temperature of each grid cell is calculated, and choose has the landscape pattern of substantial connection to refer to urban Heat Environment
Number calculates Pattern of Urban Green Land Features's index information in each grid cell；
Index screening module, for using each grid cell as sample, calculate separately the average surface temperature with it is selected
The relative coefficient between landscape indices taken, successively sorts according to its absolute value, chooses highest preceding 4 works of absolute value
For typical green-space pattern index；
Prediction model module is constructed, is used for according to the average surface temperature and 4 typical green-space pattern indexes, using ground
Reason weighted regression algorithm constructs 2 respectively4The urban Heat Environment prediction model of a green-space pattern index, obtains corresponding 24A model
Local coefficient of determination Local R2Spatial distribution characteristic；
Drawing module, for utilizing hierachical decomposition algorithm respectively to described 24A model part coefficient of determination Local R2Divided
Solution obtains the joint percentage contribution and individual contributions percentage of every kind of green-space pattern index in each grid cell, completes city
The space mapping of city's thermal environment Dominated Factors.
8. the space mapping device of urban Heat Environment Dominated Factors according to claim 7, which is characterized in that the pre- place
Reason specifically:
City is converted into the Landsat TM image data based on remote sensing image equipment acquisition survey region using the first formula
Surface temperature data；
Landscape types classification is carried out to the Landsat TM imaged image using object-oriented method, extraction obtains urban green space
Patches information.
9. the space mapping device of urban Heat Environment Dominated Factors according to claim 7, which is characterized in that the completion
The space mapping of urban Heat Environment Dominated Factors, specifically:
The individual contributions of each grid cell in the survey region are marked in different colors than highest green-space pattern index；
The joint percentage contribution of the various green-space pattern indexes of all grid cells in the survey region is counted, and generates report
Table.
10. a kind of computer readable storage medium, which is characterized in that the computer readable storage medium includes the calculating of storage
Machine program, wherein equipment where controlling the computer readable storage medium in computer program operation is executed as weighed
Benefit requires the space mapping method of 1 to 6 described in any item urban Heat Environment Dominated Factors.
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