CN108109127A - A kind of city nighttime light data desaturation method based on NDBI - Google Patents
A kind of city nighttime light data desaturation method based on NDBI Download PDFInfo
- Publication number
- CN108109127A CN108109127A CN201810037550.9A CN201810037550A CN108109127A CN 108109127 A CN108109127 A CN 108109127A CN 201810037550 A CN201810037550 A CN 201810037550A CN 108109127 A CN108109127 A CN 108109127A
- Authority
- CN
- China
- Prior art keywords
- ndbi
- ntl
- norm
- light
- normalized
- 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 21
- 238000012952 Resampling Methods 0.000 claims abstract description 4
- 238000004364 calculation method Methods 0.000 claims description 9
- DFPOZTRSOAQFIK-UHFFFAOYSA-N S,S-dimethyl-beta-propiothetin Chemical compound C[S+](C)CCC([O-])=O DFPOZTRSOAQFIK-UHFFFAOYSA-N 0.000 description 5
- 230000000694 effects Effects 0.000 description 5
- 238000011161 development Methods 0.000 description 4
- 229920006395 saturated elastomer Polymers 0.000 description 4
- 241001269238 Data Species 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 238000012360 testing method Methods 0.000 description 3
- 230000015572 biosynthetic process Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000003205 fragrance Substances 0.000 description 2
- 238000002310 reflectometry Methods 0.000 description 2
- 238000003786 synthesis reaction Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000013210 evaluation model Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000004927 fusion Effects 0.000 description 1
- 238000010606 normalization Methods 0.000 description 1
- 230000005622 photoelectricity Effects 0.000 description 1
- 230000005855 radiation Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000001932 seasonal effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T5/00—Image enhancement or restoration
- G06T5/73—Deblurring; Sharpening
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30181—Earth observation
- G06T2207/30184—Infrastructure
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Investigating Or Analysing Materials By Optical Means (AREA)
Abstract
The invention discloses a kind of city nighttime light data desaturation method based on NDBI, step is as follows：Step 1）Obtain steady light data productNTL, the spatial resolution of the product is resampled to 500m, and the data after resampling are normalized, it obtainsNTL norm ；Step 2）It obtainsNTLThe identical time（During April September）MODIS MCD43A4 products, and be calculatedNDBITime series；Step 3）It is based onNDBITime series calculates the average of each pixel, obtainsNDBI mean , and it is rightNDBI mean It is normalized, obtainsNDBI norm ；Step 4）By normalized light dataNTL norm WithNDBI norm Multiplication is obtained based on the modified light index BANTLI of NDBI (NDBI Adjusted Night Time Light).
Description
Technical field
The present invention is the technology in an earth observation field, for the saturated phenomenon of DMSP/OLS nighttime light datas, is carried
A kind of city nighttime light data desaturation method based on NDBI is gone out, by structure based on the modified light indexes of NDBI
BANTLI can realize effective alleviation of nighttime light data saturation effect.
Background technology
Urbanization become the world today development general trend, the increase for being mainly shown as urban population of urbanization,
The expansion of cities and towns area, the fast development in cities and towns have direct shadow to the sustainable development of region social economy and ecological environment
It rings.Remote sensing has become the weight of city space information extraction, city development level evaluation as a big region fast monitoring technique
Want means.With nighttime light data（Nighttime light, NTL）Extensive use, DMSP/OLS have proved to be into
The valid data source of row cities and towns monitoring and evaluation research.
DMSP/OLS data are by U.S.A. military affairs meteorological satellite (Defense Meteorological Satellite
Program, DMSP) carry sensor (Operational Linescan System, OLS) obtain global night lamp
Light data.General sensor is different from, OLS sensors have higher photoelectricity amplifying power, can detect cities and towns light, fire
The information closely related with mankind's activity such as light, wagon flow, fishing boat light are suitble to dynamic monitoring large scale City expending.
Since the radiation detection scope of DMSP/OLS nighttime light datas is relatively narrow, in the higher down town meeting of intensity of light
There is light saturated phenomenon, it is often smaller than reality to detect night lamp light value.Light saturated phenomenon reduces NTL in city
The light value at center masks the intensity of light difference of downtown area, so as to influence the related prison based on light intensity data
Survey the precision of evaluation model.
Letu et al. (2010) corrects the intensity of light based on administration cell scale using Cubic regression model and satisfies
And problem, but this method cannot embody the intensity of light difference inside each administration cell, that is, may not apply to grid cell size.
Then, Letu et al. (2012) has also been proposed the NTL corrections based on grid cell size based on the unsaturation light data of 1999
Method, this method assume that the intensity of lights such as light zone of saturation do not change during 1996-1999, however this hypothesis is in city
The region that city makes fast progress is invalid.Ziskin et al. (2010) uses low gain NTL data and high-gain NTL data phases
The method of fusion corrects the global NTL data of 2006, alleviates saturation problem and effect is highly desirable, but this method takes
Effort and of high cost.
Except alleviating saturation problem using the NTL data characteristic of itself, some scholars are using other satellite datas come school
Positive NTL data.Zhang et al. (2008) proposes VANUI（Vegetation Adjusted NTL Urban Index）
Index alleviates NTL saturation effects, and this method is that apparent negatively correlated close is presented based on Vegetation abundance and city impervious surface
It is this feature, NTL is normalized using MODIS NDVI data, can preferably highlights downtown area intensity of light
Spatial diversity, but since NDVI itself is there are saturation problem, so as to influence the school of vegetative coverage difference not marking area NTL
Just.
Due to normalization building index NDBI（Normalized Difference Built-up Index）It can reflect
The dense degree of City Building, closely related with built-up areas, the present invention attempts to establish a kind of city night lamp based on NDBI
Light data desaturation method.
The content of the invention
The present invention proposes a kind of city nighttime light data desaturation method based on NDBI, and this method makes full use of NDBI
The closely related feature with completed region of the city, effectively alleviates nighttime light data saturation problem, and flow is simple, and operating process is complete
Automation, is beneficial to promote.This method comprises the following steps：
Step 1：Steady light data product to be corrected is obtained from American National geodata center website, by the product
Spatial resolution be resampled to 500m ensure its withNDBIResolution ratio be consistent, and to after resampling data carry out normalizing
Change is handled, and is obtainedNTL norm ；Step 2：The steady light number with step 1 is obtained from U.S. NASA Ge Dade space centers website
According to the product identical time（During April-September）MODIS MCD43A4 products（16 days synthesis Reflectivity for Growing Season products）, and calculate
It obtainsNDBITime series；Step 3：It is based onNDBITime series calculates the average of each pixel, obtains, and
It is rightIt is normalized, obtainsNDBI norm ；Step 4：By normalized light dataNTL norm WithNDBI norm Phase
It is multiplied to arrive based on the modified light index BANTLI of NDBI (NDBI Adjusted Night Time Light).
Further, in the step 1 normalized be by the DN values divided by 63 of steady light data NTL, this be by
In NTL minimum value for 0, and maximum is 63.
Further, MODIS MCD43A4 products are through the BRDF corrections, reflection synthesized in 16 days in the step 2
Rate, resolution ratio 500m；The calculation formula of NDBI is in the step 2,
In formulaRespectively the 2nd and the 7th wave band of MCD43A4 products；Using during April-September in the step 2
MCD43A4 products obtain NDBI be in order to eliminate the influence of urban ground accumulated snow, this is because the NDBI values of completed region of the city compared with
Greatly, and accumulated snow can substantially reduce NDBI values.
Further, the calculation formula of NDBI Time Series Means is in the step 3,
A total of 22 phase during April-September,iForNDBISequence number；In the step 3Normalized calculation formula is, in formulaForIn any picture
MemberValue,WithIts maximum and minimum value are represented respectively.
Description of the drawings
Fig. 1 is the city nighttime light data desaturation method flow diagram based on NDBI.
Fig. 2 is Beijing-tianjin-hebei Region nighttime light data figure in 2010.
Fig. 3 is schemed for 2010 for Beijing-tianjin-hebei Region based on the modified light index BANTLI of NDBI.
Comparative analysis figure before and after Fig. 4 corrects for nighttime light data（By taking Beijing as an example）.
Specific embodiment
" a kind of city nighttime light data desaturation method based on NDBI " of the invention is made into one with reference to example
Step explanation, according to implementing procedure（As shown in Figure 1）, detailed implementation detail is as follows.
Step 1：The present invention is using Beijing-tianjin-hebei Region as test block, from American National geodata center（http://
ngdc.noaa.gov/eog/download.html）Obtain the test block steady light data NTL of 2010（Such as Fig. 2 institutes
Show）, for the ease of computing and comparison, resolution ratio resampling and DN value normalizeds have been carried out to NTL.Due to the resolution of NDBI
Rate is 500m, and the resolution ratio of NTL is 1Km, and in order to ensure the uniformity of spatial resolution, the spatial resolution of NTL is adopted again
Sample is to 500m；Since the minimum DN values of NTL are 0, and maximum DN is 63, and normalized formula isNTL norm 。
Step 2：From U.S. NASA Ge Dade space centers website（http://modis.gsfc.nasa.gov/）
The MODIS MCD43A4 products during in April, the 2010-September of test block are obtained, MODIS MCD43A4 are to be corrected through BRDF
, 16 days synthesis reflectivity product, resolution ratio 500m.During in April, 2010-September, MCD43A4 products share
For each phase product, NDBI was calculated using its the 2nd and the 7th wave band, the calculation formula of NDBI is in 22 phases, eventually form 22 phase NDBI time serieses.The NDBI values of completed region of the city compared with
Greatly, but if subjected to the influence of deposite snow, NDBI values can substantially reduce, therefore, in order to avoid the influence of heavy snow weather, spy
The MCD43A4 products during April-September is selected to obtain NDBI.
Step 3：Due to being influenced be subject to seasonal variations and weather condition, same position different time NDBI exists different
The difference of degree, in order to ensure the stability of data, the present invention is using NDBI averages, calculation formula, a total of 22 phase during April-September,iForNDBISequence number；Due toData area for [- 1,1], in order to efficiently useNTL data are adjusted for weight,
It needs pairIt is normalized, it is ensured that its data area is [0,1], and normalized calculation formula is, in formulaForIn any picture
MemberValue,WithIts maximum and minimum value are represented respectively.
Step 4：By normalized light dataNTL norm With building indexNDBI norm Multiplication obtains modified based on NDBI
Light index BANTLI, as shown in Figure 3.
In order to analyze the effect of BANTLI indexes, analyzed by taking Beijing as an example（As shown in Figure 4）.It can from figure
The difference of downtown area intensity of light can be reflected compared with steady light data NTL very well by going out BANTLI indexes, such as A in figure
Region is Fragrance Hill, since light saturated phenomenon causes NTL that cannot clearly portray compared with BANTLI indexes the profile in Fragrance Hill；
In addition, BANTLI indexes can also clearly distinguish Capital Airport position（B regions）.
Claims (1)
1. a kind of city nighttime light data desaturation method based on NDBI, this method comprises the following steps：
Step 1）Obtain steady light data productNTL, the spatial resolution of the product is resampled to 500m, and to resampling
Data afterwards are normalized, and obtainNTL norm ；Normalized be by the DN values divided by 63 of steady light data NTL,
Formula isNTL norm =DN/63；
Step 2）It obtainsNTLThe identical time（During April-September）MODIS MCD43A4 products, and be calculatedNDBITime
Sequence；The calculation formula of NDBI isNDBI=(B7-B2)/(B7+B2), in formulaB2WithB7Respectively the 2nd He of MCD43A4 products
7th wave band；It is to eliminate the influence of urban ground accumulated snow using the MCD43A4 products acquisition NDBI during April-September；
Step 3）It is based onNDBITime series calculates the average of each pixel, obtainsNDBI mean , and it is rightNDBI mean Carry out normalizing
Change, obtainNDBI norm ；The calculation formula of NDBI Time Series Means is；NDBI mean Normalized calculation formula isNDBI norm =(DN i - DN min )/( DN max - DN min ), in formulaDN i ForNDBI mean In appoint
One pixelDNValue,DN max WithDN min Its maximum and minimum value are represented respectively;
Step 4）By normalized light dataNTL norm WithNDBI norm Multiplication is obtained based on the modified light indexes of NDBI
BANTLI (NDBI Adjusted Night Time Light)。
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810037550.9A CN108109127A (en) | 2018-01-16 | 2018-01-16 | A kind of city nighttime light data desaturation method based on NDBI |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810037550.9A CN108109127A (en) | 2018-01-16 | 2018-01-16 | A kind of city nighttime light data desaturation method based on NDBI |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN108109127A true CN108109127A (en) | 2018-06-01 |
Family
ID=62219354
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810037550.9A Pending CN108109127A (en) | 2018-01-16 | 2018-01-16 | A kind of city nighttime light data desaturation method based on NDBI |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108109127A (en) |
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109460445A (en) * | 2018-11-14 | 2019-03-12 | 许昌学院 | The building of Urban Space characteristic index and urban system evaluation method based on noctilucence remotely-sensed data |
| CN109522849A (en) * | 2018-11-22 | 2019-03-26 | 中国科学院遥感与数字地球研究所 | A kind of city impervious surface extracting method based on MNDII time series |
| CN110852159A (en) * | 2019-09-30 | 2020-02-28 | 广州地理研究所 | Remote sensing night light data desaturation method |
| CN112465710A (en) * | 2020-10-29 | 2021-03-09 | 江苏集萃未来城市应用技术研究所有限公司 | Night light data correction method based on EVI data |
| CN112785584A (en) * | 2021-02-01 | 2021-05-11 | 东南大学 | Night light data correction method based on EVI and GHS-POP data |
| CN113065481A (en) * | 2021-04-09 | 2021-07-02 | 中国测绘科学研究院 | Urban built-up area extraction method fusing multi-source data in transportation and delivery environment |
| CN115438295A (en) * | 2022-11-07 | 2022-12-06 | 北京英视睿达科技股份有限公司 | Night light correction method and CO estimation 2 Method of discharging amount |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440414A (en) * | 2013-08-22 | 2013-12-11 | 河南大学 | Night lamplight observation accuracy improving method based on geographic auxiliary data |
| CN106682830A (en) * | 2016-12-26 | 2017-05-17 | 中国科学院深圳先进技术研究院 | Urbanization ghost town index evaluating method and device |
| CN107368922A (en) * | 2017-07-20 | 2017-11-21 | 华中师范大学 | Average Price of City Residence predictor method based on nighttime light intensity |
-
2018
- 2018-01-16 CN CN201810037550.9A patent/CN108109127A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103440414A (en) * | 2013-08-22 | 2013-12-11 | 河南大学 | Night lamplight observation accuracy improving method based on geographic auxiliary data |
| CN106682830A (en) * | 2016-12-26 | 2017-05-17 | 中国科学院深圳先进技术研究院 | Urbanization ghost town index evaluating method and device |
| CN107368922A (en) * | 2017-07-20 | 2017-11-21 | 华中师范大学 | Average Price of City Residence predictor method based on nighttime light intensity |
Non-Patent Citations (2)
| Title |
|---|
| 卓莉等: "基于EVI指数的DMSP/OLS夜间灯光数据去饱和方法", 《地理学报》 * |
| 屈益挺等: "北京市城市扩张及其对城市增温效应的影响", 《首都师范大学学报》 * |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109460445A (en) * | 2018-11-14 | 2019-03-12 | 许昌学院 | The building of Urban Space characteristic index and urban system evaluation method based on noctilucence remotely-sensed data |
| CN109522849A (en) * | 2018-11-22 | 2019-03-26 | 中国科学院遥感与数字地球研究所 | A kind of city impervious surface extracting method based on MNDII time series |
| CN110852159A (en) * | 2019-09-30 | 2020-02-28 | 广州地理研究所 | Remote sensing night light data desaturation method |
| CN112465710A (en) * | 2020-10-29 | 2021-03-09 | 江苏集萃未来城市应用技术研究所有限公司 | Night light data correction method based on EVI data |
| CN112465710B (en) * | 2020-10-29 | 2022-08-19 | 江苏集萃未来城市应用技术研究所有限公司 | Night light data correction method based on EVI data |
| CN112785584A (en) * | 2021-02-01 | 2021-05-11 | 东南大学 | Night light data correction method based on EVI and GHS-POP data |
| CN112785584B (en) * | 2021-02-01 | 2022-05-27 | 东南大学 | Night light data correction method based on EVI and GHS-POP data |
| CN113065481A (en) * | 2021-04-09 | 2021-07-02 | 中国测绘科学研究院 | Urban built-up area extraction method fusing multi-source data in transportation and delivery environment |
| CN115438295A (en) * | 2022-11-07 | 2022-12-06 | 北京英视睿达科技股份有限公司 | Night light correction method and CO estimation 2 Method of discharging amount |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108109127A (en) | A kind of city nighttime light data desaturation method based on NDBI | |
| Frantz et al. | An operational radiometric landsat preprocessing framework for large-area time series applications | |
| Ma et al. | Quantifying spatiotemporal patterns of urban impervious surfaces in China: An improved assessment using nighttime light data | |
| Li et al. | An “exclusion-inclusion” framework for extracting human settlements in rapidly developing regions of China from Landsat images | |
| CN109919875B (en) | High-time-frequency remote sensing image feature-assisted residential area extraction and classification method | |
| CN108961199A (en) | Multi- source Remote Sensing Data data space-time fusion method and device | |
| Ye et al. | Standing water effect on soil moisture retrieval from L-band passive microwave observations | |
| CN102629378A (en) | Remote sensing image change detection method based on multi-feature fusion | |
| Guo et al. | Estimating socio-economic parameters via machine learning methods using Luojia1-01 Nighttime Light remotely sensed images at multiple scales of China in 2018 | |
| Jia et al. | Study of SAR image texture feature extraction based on GLCM in Guizhou Karst mountainous region | |
| CN106485718A (en) | One kind overdoes slash recognition methodss and device | |
| Sun et al. | Land use/cover change and the urbanization process in the Wuhan area from 1991 to 2013 based on MESMA | |
| Zhang et al. | Development of the direct-estimation albedo algorithm for snow-free Landsat TM albedo retrievals using field flux measurements | |
| Gao et al. | An improved topographic correction model based on Minnaert | |
| Tew et al. | Urban expansion analysis using Landsat images in Penang, Malaysia | |
| Wu et al. | Evaluation of winter wheat yield simulation based on assimilating LAI retrieved from networked optical and SAR remotely sensed images into the WOFOST model | |
| Hu et al. | Correcting the saturation effect in dmsp/ols stable nighttime light products based on radiance-calibrated data | |
| Zhang et al. | A 250 m annual alpine grassland AGB dataset over the Qinghai–Tibet Plateau (2000–2019) in China based on in situ measurements, UAV photos, and MODIS data | |
| Zhao et al. | Fusion and assessment of high-resolution WorldView-3 satellite imagery using NNDiffuse and Brovey algotirhms | |
| Shrestha et al. | Delineating an exurban development footprint using SPOT imagery and ancillary data | |
| Zhao et al. | Mapping global flying aircraft activities using Landsat 8 and cloud computing | |
| Jiang et al. | The Hi-GLASS all-wave daily net radiation product: Algorithm and product validation | |
| Jianjun et al. | Land cover changes in the rural-urban interaction of Xi’an region using Landsat TM/ETM data | |
| Dai et al. | Urbanization-induced land use and cover changes in Xuzhou, Jiangsu Province since the Mid-1990s | |
| Zhang et al. | A 250m annual alpine grassland AGB dataset over the Qinghai-Tibetan Plateau (2000–2019) based on in-situ measurements, UAV images, and MODIS Data |
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: 20180601 |
|
| RJ01 | Rejection of invention patent application after publication |