CN105678225A - Urban heat island effect space variation detection method and system - Google Patents
Urban heat island effect space variation detection method and system Download PDFInfo
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Abstract
The invention provides an urban heat island effect space variation detection method and system. The urban heat island effect space variation detection method comprises the steps: constructing an urban remote sensing data image database for the processed urban remote sensing images; according to the image database, acquiring a plurality of thematic images of a target city; and according to the thematic images, detecting the space-time distribution information of urban heat islands, and analyzing the urban heat islands; according to the urban heat islands, offering a proposal for urban landscape. Therefore, the urban heat island effect space variation detection method and system can overcome the spatial overlay algorithm problem between the heat island effect spatial distribution and other feature layers of the city, and can improve the accuracy for urban heat island effect space variation detection.
Description
Technical field
The present invention relates to city management technical field, it is specifically related to a kind of urban heat land effect spatial variations detection method and system.
Background technology
Along with the quick propelling of Urbanization in China, the contradiction that simultaneously result also between the urban population increased without limitation and limited environment, resource capacity that urban population and land scale constantly expand, city can't bear the heavy load, and urban disease also produces thereupon. Urbanization (Land_use change (build building, repair the roads) and anthropogenic heat discharge etc.) impact often is strengthened realizing mainly through urban heat land effect. Conventional urban heat island research is main to be adopted and represents route observation and the method combined is observed in reconnaissance, the thermal radiation situation on the reflection ground that this kind of method can not be comprehensively synchronous. Therefore, along with the development of remote sensing technology, more and more scholars starts to apply the Thermal infrared bands of remote sensing image to study ground level heat situation. Early stage research general weather satellite, the density of observation is an observed value only, but advances the research of heat island greatly.
Remote Sensing Study for tropical island effect has had many researchists to do corresponding trial, prior art utilize the main thought of remote sensing image simulation city temperature as: first, set up bright temperature computation schema, the gray-scale value of thermal infrared images is changed into bright temperature (radiation temperature) data; Again by certain regression analysis pattern; Bright temperature is converted into the temperature on ground; Finally apply the method for image procossing, the thermal infrared information expressed by image is expressed with the colour sequential meeting visual experience. In conventional research, mostly only focus on having arrived one of them or two aspects, do not form a complete research system.
Summary of the invention
Have in view of that, it is necessary to the urban heat land effect spatial variations detection method providing a kind of accuracy high.
For achieving the above object, the present invention adopts following technical proposals:
A kind of urban heat land effect spatial variations detection method, comprises the steps:
Step S110: remote sensing image in city is carried out pre-treatment;
Step S120: build remotely-sensed data view data storehouse, city;
Step S130: according to the multiple special topic figure obtaining target cities in described view data storehouse;
Step S140: according to the spatial and temporal distributions information of described special topic figure detection urban heat island;
Step S150: according to described spatial and temporal distributions information analysis urban heat island;
Step S160: propose urban look suggestion according to described urban heat island.
In certain embodiments, in step S110, described remote sensing image comprises ETM, NOAA, MODIS image.
In certain embodiments, in step S110, described pre-treatment comprises remote sensing geometry correction and image radiation correction, described remote sensing geometry correction corrects the geometry distortion of original image in reference mark by utilizing, described radiative correction, by eliminating the impact of atural object radiation difference in multidate remote sensing, makes same atural object type between image have identical radiation quantity.
In certain embodiments, in step S130, according to the multiple special topic figure obtaining target cities in described view data storehouse, it is specially:
Adopt the direct relative method of spectrum and classification relative method, from described view data storehouse, extract change area, then variation zone is extracted varied number and type information, finally obtain the multiple special topic figure of urban surface view accurately.
In certain embodiments, in step S130, described special topic figure comprises topography and geomorphology figure, climograph, amusement lottery industry place distribution plan, bus route map, bus stop distribution plan, church and temple distribution plan, park distribution plan, primary attraction and hotel's distribution plan.
In certain embodiments, in step S140, according to the spatial and temporal distributions letter of described special topic figure detection urban heat island, specifically comprise the steps:
Mono window algorithm is adopted to carry out detecting the spatial and temporal distributions information obtaining urban heat island to the multiple special topic figure of target cities.
In certain embodiments, in step S150, according to described spatial and temporal distributions information analysis urban heat island, it is specially: adopt software FRAGSTATS, describes urban look change according to spatial and temporal distributions information calculating patch average area, boundary density, shape index, girth area ratio, average nearest-neighbor method distance, concentration class index.
In certain embodiments, in step S160, propose urban look suggestion according to described urban heat island, it be specially:
Utilize the space-time interaction relationship of geographical information system(GIS) spatial statistics analysis means selective analysis urban heat island and vegetation ratio, water body ratio, vegetation index, building load intensity, hardening earth's surface ratio, the density of population, road direction density, it is proposed to urban look is advised.
In addition, present invention also offers a kind of urban heat land effect spatial variations detection system, comprising:
Remote sensing image processing module, for carrying out pre-treatment to city remote sensing image;
Database sharing module, for building remotely-sensed data view data storehouse, city;
City special topic figure builds module, for according to the multiple special topic figure obtaining target cities in described view data storehouse;
Spatial and temporal distributions information module, for the spatial and temporal distributions information according to described special topic figure detection urban heat island;
Urban heat island analyzes module, for according to described spatial and temporal distributions information analysis urban heat island;
Urban look suggestion module, for proposing urban look suggestion according to described urban heat island.
The technique effect that the present invention adopts technique scheme to bring is:
Urban heat land effect spatial variations detection method provided by the invention and system, by the city remote sensing image after process is built remotely-sensed data view data storehouse, city, according to the multiple special topic figure obtaining target cities in described view data storehouse, spatial and temporal distributions information according to described special topic figure detection urban heat island, according to described spatial and temporal distributions information analysis urban heat island, according to described urban heat island, urban look suggestion is proposed again, thus overcome the space overlapping algorithm difficult problem between tropical island effect spatial distribution and other key element layer of city, improve the accuracy of urban heat land effect spatial variations detection.
Accompanying drawing explanation
Fig. 1 is the flow chart of steps of urban heat land effect spatial variations detection method provided by the invention.
Fig. 2 is that urban heat island is changed the algorithm principle figure studied by employing mono window algorithm provided by the invention.
Fig. 3 is the structural framing figure of urban heat land effect spatial variations detection system provided by the invention.
Embodiment
For the ease of understanding the present invention, below with reference to relevant drawings, the present invention is described more fully. Accompanying drawing gives the better embodiment of the present invention. But, the present invention can realize in many different forms, is not limited to enforcement mode described herein. On the contrary, it is provided that these implement the object of modes is make that the disclosure to the present invention understands more thorough comprehensive.
Unless otherwise defined, all technology used herein are identical with the implication that the those skilled in the art belonging to the present invention understand usually with scientific terminology. The term used in the description of the invention herein is the object in order to describe concrete enforcement mode, is not intended to be restriction the present invention. Term as used herein " and/or " comprise arbitrary and all combinations of one or more relevant Listed Items.
As shown in Figure 1, it is the urban heat land effect spatial variations detection method that the embodiment of the present invention one provides, comprises the steps:
Step S110: remote sensing image in city is carried out pre-treatment;
Preferably, in step S110, described remote sensing image comprises ETM, NOAA, MODIS image.
Preferably, in step S110, described pre-treatment comprises remote sensing geometry correction and image radiation correction.
Wherein, remote sensing geometry correction is exactly the geometry distortion utilizing reference mark to correct original image, produces a width and meets map projection or map and express the new images required, mainly comprise choose reference mark, set up geometric correction model, figure heavily samples three steps. The error of images match should be less than 0.5 picture unit.
Radiative correction is exactly the impact eliminating atural object radiation difference in multidate remote sensing, makes same atural object type between image have identical radiation quantity, is conducive to choosing and the raising of precision of classifying of sample point. In actual, radiative correction can be divided into: definitely air correction and relative atmospheric correct two classes. Common method comprises statistics adjusting method, histogram matching, linear regression method and air impedance vegetation index.
Step S120: build remotely-sensed data view data storehouse, city;
It can be appreciated that by the city remote sensing image after process is arranged, it is possible to obtain remotely-sensed data view data storehouse, city.
Step S130: according to the multiple special topic figure obtaining target cities in described view data storehouse;
Wherein, described special topic figure comprises topography and geomorphology figure, climograph, amusement lottery industry place distribution plan, bus route map, bus stop distribution plan, church and temple distribution plan, park distribution plan, primary attraction and hotel's distribution plan.
Preferably, according to the multiple special topic figure obtaining target cities in described view data storehouse, it is specially:
Adopt the direct relative method of spectrum and classification relative method, from described view data storehouse, extract change area, then variation zone is extracted varied number and type information, finally obtain the multiple special topic figure of urban surface view accurately.
For city, Shenzhen, collect the multiple special topic figure such as Shenzhen physical environment, city present situation, tourist resources, comprise topography and geomorphology figure, climograph, amusement lottery industry place distribution plan, bus route, bus stop distribution plan, church and temple distribution plan, park distribution plan, primary attraction and hotel's distribution plan etc.Adopt the first direct relative method of spectrum and classification relative method, extract change area, then variation zone is extracted varied number and type information, finally obtain urban surface view quantitative information accurately.
Step S140: according to the spatial and temporal distributions information of described special topic figure detection urban heat island;
Preferably, according to the spatial and temporal distributions letter of described special topic figure detection urban heat island, specifically comprise the steps:
Mono window algorithm is adopted to carry out detecting the spatial and temporal distributions information obtaining urban heat island to the multiple special topic figure of target cities.
It can be appreciated that the algorithm of surface temperature inverting can be divided into Split-window algorithm, NOAA-AVHRR data and temperature, emissivity separation algorithm. The application preferably adopts mono window algorithm urban heat island change to be studied. Specific algorithm is such as Fig. 2.
Wherein, the following algorithm of bright temperature: T6=0.12378+0.0054923DN, wherein: T6 is absolute bright temperature (K), and DN is TM6 image intensity value.
Ts=[a6 (1-C6-D6)+[b6 (1-C6-D6)+C6+D6] T6-D6Ta]/C6, in formula, Ts, Ta unit is K, Ta is average atmospheric temperature; A6 and b6 is constant.
Step S150: according to described spatial and temporal distributions information analysis urban heat island;
It is appreciated that, urban landscape pattern develops and reflects urban land use type and change thereof, and the change of urban land use/covering is closely bound up with the formation of urban heat island, in addition, description Process of Urbanization and city extended dynamic are had important references value by urban landscape pattern.
For Shenzhen, this research and utilization view index method combines with holistic approach, partition analysis method, research Shenzhen view general layout. Adopt software FRAGSTATS, calculate patch average area (MPS), boundary density (edgedensity) (ED), shape index (shapeindex, Shape), girth area ratio (perimeter-arearatio, PARA), average nearest-neighbor method distance (ENN), concentration class index (AggregationIndex, AI) etc. describe urban look change.
Step S160: propose urban look suggestion according to described urban heat island.
Preferably, utilize the space-time interaction relationship of geographical information system(GIS) spatial statistics analysis means selective analysis urban heat island and vegetation ratio, water body ratio, vegetation index, building load intensity, hardening earth's surface ratio, the density of population, road direction density, it is proposed to urban look is advised.
Wherein, impervious surface index (Impervioussurfaceindex, referred to as ISI) refers to the area ratio on unit surface hardening earth's surface. Can estimating impervious surface index from Land_use change/coverage diagram, water body, vegetation, bare area be merged, represent non-hardening earth's surface, other buildings (construction land), road and bridge etc. represent hardening earth's surface, generate hardening earth's surface binary map. According to impervious surface index, atural object is divided into high density settling pond land used HB (ISI>60%), medium construction density land used MB (40%<ISI<60%), low density urban land LB (10%<ISI<40%) and lower than 10% natural terrain NS. This kind of mode classification can embody the difference of urban land natural character, emphasizes hydrothermal condition difference and the natural, ecological process of urban land.
Building load intensity (BuiltPressure) is the product of building floor space and building floor area ratio. Site coverage can pass through the direct interpretation of image, and the determination of building floor area ratio needs the floor space of the first measuring and calculating building total area and this buildings. For overwhelming majority single building, owing to every floor area of plane is identical, namely floor number is the plot ratio of this buildings.The calculating of floor height is the key of estimation building floor area ratio, can extract from three-dimensional image. The calculation formula of building load intensity is as follows:
BP=BD × h, wherein BP is building load intensity index, and BD is site coverage, and h is building height.
Density of population spatial distribution utilizes CLARK model to calculate:
Wherein p (r) is the density of population, and p0 is the density of population in city characteristic radius, and r is the distance apart from urban characteristic center, and r0 is city characteristic radius.
It can be appreciated that principle component regression utilizes GIS space autoregressive model to carry out, higher-dimension variable system is carried out comprehensive best and simplify, set up regression equation, it is possible to determine the flexible strategy of each index objectively, avoid subjective random.
Refer to Fig. 3, a kind of urban heat land effect spatial variations detection system that the application provides, comprising: remote sensing image processing module 210, database sharing module 220, city special topic figure build module 230, spatial and temporal distributions information module 240, urban heat island analysis module 250 and urban look suggestion module 260.
Wherein, remote sensing image processing module 210 is for carrying out pre-treatment to city remote sensing image; Database sharing module 220 is for building remotely-sensed data view data storehouse, city; City special topic figure builds module 230 for according to the multiple special topic figure obtaining target cities in described view data storehouse; Spatial and temporal distributions information module 240 is for the spatial and temporal distributions information according to described special topic figure detection urban heat island; Urban heat island analyzes module 250 for according to described spatial and temporal distributions information analysis urban heat island; Urban look suggestion module 260 is for proposing urban look suggestion according to described urban heat island. The above-mentioned existing description of its detailed principle of work, repeats no more here.
Urban heat land effect spatial variations detection method provided by the invention and system, by the city remote sensing image after process is built remotely-sensed data view data storehouse, city, according to the multiple special topic figure obtaining target cities in described view data storehouse, spatial and temporal distributions information according to described special topic figure detection urban heat island, according to described spatial and temporal distributions information analysis urban heat island, according to described urban heat island, urban look suggestion is proposed again, thus overcome the space overlapping algorithm difficult problem between tropical island effect spatial distribution and other key element layer of city, improve the accuracy of urban heat land effect spatial variations detection.
Above-described embodiment of the present invention, does not form limiting the scope of the present invention. Any amendment, equivalent replacement and improvement etc. done within the spirit and principles in the present invention, all should be included within the claims of the present invention.
Claims (9)
1. a urban heat land effect spatial variations detection method, it is characterised in that, comprise the steps:
Step S110: remote sensing image in city is carried out pre-treatment;
Step S120: build remotely-sensed data view data storehouse, city;
Step S130: according to the multiple special topic figure obtaining target cities in described view data storehouse;
Step S140: according to the spatial and temporal distributions information of described special topic figure detection urban heat island;
Step S150: according to described spatial and temporal distributions information analysis urban heat island;
Step S160: propose urban look suggestion according to described urban heat island.
2. urban heat land effect spatial variations detection method according to claim 1, it is characterised in that, in step S110, described remote sensing image comprises ETM, NOAA, MODIS image.
3. urban heat land effect spatial variations detection method according to claim 1, it is characterized in that, in step S110, described pre-treatment comprises remote sensing geometry correction and image radiation correction, described remote sensing geometry correction corrects the geometry distortion of original image in reference mark by utilizing, described radiative correction, by eliminating the impact of atural object radiation difference in multidate remote sensing, makes same atural object type between image have identical radiation quantity.
4. urban heat land effect spatial variations detection method according to claim 1, it is characterised in that, in step S130, according to the multiple special topic figure obtaining target cities in described view data storehouse, it is specially:
Adopt the direct relative method of spectrum and classification relative method, from described view data storehouse, extract change area, then variation zone is extracted varied number and type information, finally obtain the multiple special topic figure of urban surface view accurately.
5. urban heat land effect spatial variations detection method according to claim 4, it is characterized in that, in step S130, described special topic figure comprises topography and geomorphology figure, climograph, amusement lottery industry place distribution plan, bus route map, bus stop distribution plan, church and temple distribution plan, park distribution plan, primary attraction and hotel's distribution plan.
6. urban heat land effect spatial variations detection method according to claim 1, it is characterised in that, in step S140, according to the spatial and temporal distributions letter of described special topic figure detection urban heat island, specifically comprise the steps:
Mono window algorithm is adopted to carry out detecting the spatial and temporal distributions information obtaining urban heat island to the multiple special topic figure of target cities.
7. urban heat land effect spatial variations detection method according to claim 1, it is characterized in that, in step S150, according to described spatial and temporal distributions information analysis urban heat island, it is specially: adopt software FRAGSTATS, describes urban look change according to spatial and temporal distributions information calculating patch average area, boundary density, shape index, girth area ratio, average nearest-neighbor method distance, concentration class index.
8. urban heat land effect spatial variations detection method according to claim 1, it is characterised in that, in step S160, propose urban look suggestion according to described urban heat island, it is specially:
Utilize the space-time interaction relationship of geographical information system(GIS) spatial statistics analysis means selective analysis urban heat island and vegetation ratio, water body ratio, vegetation index, building load intensity, hardening earth's surface ratio, the density of population, road direction density, it is proposed to urban look is advised.
9. a urban heat land effect spatial variations detection system, it is characterised in that, comprising:
Remote sensing image processing module, for carrying out pre-treatment to city remote sensing image;
Database sharing module, for building remotely-sensed data view data storehouse, city;
City special topic figure builds module, for according to the multiple special topic figure obtaining target cities in described view data storehouse;
Spatial and temporal distributions information module, for the spatial and temporal distributions information according to described special topic figure detection urban heat island;
Urban heat island analyzes module, for according to described spatial and temporal distributions information analysis urban heat island;
Urban look suggestion module, for proposing urban look suggestion according to described urban heat island.
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| CN107423858A (en) * | 2017-07-31 | 2017-12-01 | 深圳市盛路物联通讯技术有限公司 | A kind of urban planning method and system |
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| CN116561845A (en) * | 2023-04-04 | 2023-08-08 | 天津大学 | Digital technology energized urban roof greening multi-scenario simulation method and system |
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