CN110276797A - A kind of area of lake extracting method - Google Patents
A kind of area of lake extracting method Download PDFInfo
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- CN110276797A CN110276797A CN201910584480.3A CN201910584480A CN110276797A CN 110276797 A CN110276797 A CN 110276797A CN 201910584480 A CN201910584480 A CN 201910584480A CN 110276797 A CN110276797 A CN 110276797A
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- G06T7/62—Analysis of geometric attributes of area, perimeter, diameter or volume
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Abstract
The invention discloses a kind of area of lake extracting methods, and described method includes following steps: obtaining lake country TIFF remote sensing image using FROM-GLC data set, convert to lake country TIFF remote sensing image, obtain lake face salt file;Lake country raster file is obtained using lake face salt file;Lake country mask file is exported according to lake country raster file;According to lake country mask file, the lake country TIFF remote sensing image of the long timing of batch processing, batch extracting calculates area of lake.Area of lake extracting method provided by the invention, extraction accuracy are high, can batch extracting calculate area of lake, work efficiency is high, has practicability and universality.
Description
Technical field
The invention belongs to research of lakes technical fields, and in particular to a kind of area of lake extracting method.
Background technique
Lake is the key component of weather, water and biogeochemical cycle, variation of the change of Lake area to environment
There is great influence with human production activity.Area of lake reduces, and water-holding capacity can be deteriorated, and flood season can break out flood often,
Dry season is anhydrous available, can cause undesirable influence to the ecological balance around, influence diversity of organism, some species can disappear therewith
It loses, and will affect local weather and be unfavorable for the survival and development of the mankind so that ecological environment is more dull.Currently, probing into
The Annual variations trend and driving force of area of lake are the hot spots studied both at home and abroad.The accuracy of area of lake mutation analysis is taken
The precision certainly extracted in area of lake depends on the batch of area of lake to the high efficiency of area of lake age analysis of trend
It extracts.But the extraction accuracy of existing area of lake extracting method is low, low efficiency and the practicability is poor.
Summary of the invention
It is an object of the invention to overcome deficiency in the prior art, a kind of area of lake extracting method is provided, extracts essence
Degree is high, can batch extracting calculate area of lake, work efficiency is high, has practicability and universality.
The present invention provides the following technical solutions:
A kind of area of lake extracting method, described method includes following steps:
TIFF remote sensing image in lake country is obtained using FROM-GLC data set, lake country TIFF remote sensing image is turned
It changes, obtains lake face salt file;
Lake country raster file is obtained using lake face salt file;
Lake country mask file is exported according to lake country raster file;
According to lake country mask file, the lake country TIFF remote sensing image of the long timing of batch processing, batch extracting calculates lake
Moor area.
Preferably, the acquisition methods of lake face salt file include:
Under ARCGIS10.2 software platform, line feature shape in lake is made according to the lake country TIFF remote sensing image
File is selected under features then using the data management tools in the tool box ArcToolbox
The lake line feature shape file is converted lake face element shape file by feature to polygon.
Preferably, the acquisition methods of the lake country raster file include:
The former lake country TIFF remote sensing image is tentatively cut with lake face salt file, what acquisition was tentatively cut
Lake country raster file;
According to lake country TIFF remote sensing image and corresponding lake region feature on water, amendment mask text is set by threshold value
Part, make the lake country raster file tentatively cut gradually adjust to lake country TIFF remote sensing image it is a wide range of within, obtain
The lake country raster file finally cut.
Preferably, the acquisition methods of the lake country raster file tentatively cut include:
Utilize the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, selection
Then extraction selects extract by mask to generate the lake raster file tentatively cut.
Preferably, the method for correcting mask file includes:
Using the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, map is selected
Then algebra selects raster calculator, all 0 regions of being more than or equal to are set as 300, more than or equal to 0
Region is set as lake country, exports the lake country raster file of processing again, by merging raster file several times, obtains in lake
Moor area TIFF remote sensing image influence it is a wide range of within lake country raster file.
Preferably, the acquisition methods of the lake country raster file finally cut include:
For be located at lake country TIFF remote sensing image influence it is a wide range of within lake country raster file, utilize
The data management in the tool box ARCGIS10.2 software ArcToolBox selects raster, then selects raster
Area assignment within the scope of lake is 1 by the mosaic under dataset, and other area assignments are -9999, exports lake country
Raster file, the lake raster file as finally cut out.
Preferably, the revisiting period of the FROM-GLC data set is one day.
Preferably, the deriving method of the lake country mask file includes:
The lake country raster file finally cut is exported as into txt file;
The txt file is imported into MATLAB software, saves output lake country mask file.
Preferably, the deriving method of the txt file includes:
Using the conversion tool in the tool box ARCGIS10.2 software ArcToolBox, select under from raster
Raster to ascii generate the txt file.
Preferably, the calculation method of the area of lake includes:
With MATLAB software editing tiffread program, the lake of long timing is cut according to the lake country mask files in batch
Area TIFF remote sensing image is moored, the water pixel number of daily lake range is obtained, it is daily then to calculate long timing by formula (1)
Area of lake:
S=watercount × 463 × 463 (1)
S is daily Lake area in formula (1), and watercount is water pixel number.
Compared with prior art, the beneficial effects of the present invention are:
(1) present invention obtains lake country TIFF remote sensing image using FROM-GLC data set, solves massif, cloud and pool
The problem of mistake in domain point and spectrum land and water Mixed Zone, improve the extraction accuracy of area of lake.
(2) area of lake extracting method provided by the invention, it is easy to operate, original TIFF remote sensing shadow can be cut out in batches
Picture, batch extracting calculate area of lake, improve the efficiency of work, can be used for extracting the area in each department lake, have very strong
Practicability and universality.
Detailed description of the invention
Fig. 1 is Poyang Lake line feature administrative division map in embodiment;
Fig. 2 is lake surface element administrative division map in Poyang in embodiment;
Fig. 3 is the lake country TIFF remote sensing image that Poyang Lake is original in embodiment;
Fig. 4 is the Poyang Lake raster figure tentatively cut in embodiment;
Fig. 5 is the Poyang Lake raster figure of secondary cutting in embodiment;
Fig. 6 is the Poyang Lake raster figure finally cut out in embodiment;
Fig. 7 is the area change tendency chart of Poyang Lake 2001-2015 in embodiment;
Fig. 8 is Poyang Lake area Annual variations comparison diagram in embodiment and document 1;
Fig. 9 is Poyang Lake area change comparison diagram in embodiment and document 2, wherein (a) is the change of embodiment Poyang Lake area
Change figure, (b) is 2 Poyang Lake area change figure of document.
Specific embodiment
The invention will be further described below in conjunction with the accompanying drawings.Following embodiment is only used for clearly illustrating the present invention
Technical solution, and not intended to limit the protection scope of the present invention.
Embodiment
A kind of area of lake extracting method, by taking Poyang Lake as an example, described method includes following steps:
Step 1: lake face salt file makes
The 2nd day 2001 h28v06 image of Poyang Lake (lake country TIFF remote sensing shadow is obtained using FROM-GLC data set
Picture), under ARCGIS10.2 software platform, Poyang Lake line feature shape text is made according to the lake country TIFF remote sensing image
Part selects the feature under features then using the data management tools in the tool box ArcToolbox
The Poyang Lake line feature shape file is converted Poyang lake surface element shape file by polygon, if Fig. 1 is Poyang
Lake line feature region, if Fig. 2 is Poyang lake surface element region.
Step 2: lake country raster documenting
The lake country TIFF remote sensing image is tentatively cut with Poyang lake surface element shape file, it is specially sharp
With the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, extraction is selected, then
Selection extract by mask generates the Poyang Lake raster file tentatively cut, if Fig. 3 is that original lake country TIFF is distant
Image is felt, if Fig. 4 is the Poyang Lake raster file tentatively cut.
As can be seen from Figure 4, it is distant that the range of the Poyang Lake raster file tentatively cut is less than original lake country TIFF
Feel image capturing range, so carrying out the setting of next step threshold value, i.e., the Poyang Lake raster file tentatively cut is counted again
It calculates, specially using the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, selects map
Then algebra selects raster calculator, all 0 regions of being more than or equal to are set as 300, more than or equal to 0
Region is the range of Poyang Lake, exports the raster file of the Poyang Lake of processing again, as shown in Figure 5.
As can be seen from Figure 5, the raster file extent of the Poyang Lake of processing is still less than original lake country TIFF remote sensing shadow
As it is distant to be adjusted to original lake country TIFF again by raster file is merged by range for the raster file of the Poyang Lake of processing
Feel image it is a wide range of within, then utilize the tool box ARCGIS10.2 software ArcToolBox data management, choosing
Raster is selected, the mosaic under raster dataset is then selected, the raster file of the Poyang Lake after completing will be merged
Numerical value be adjusted, by the area assignment within the scope of lake be 1, other area assignments be -9999, export lake country raster
File, the Poyang Lake raster file as finally cut out, as shown in Figure 6.
Step 3: lake country mask documenting
The Poyang Lake raster file finally cut is exported as into txt file, specially utilizes ARCGIS10.2 software
The conversion tool in the tool box ArcToolBox is selected described in the raster to ascii generation under from raster
Txt file;Then the txt file is imported into MATLAB software, saves output Poyang Lake mask file.
Step 4: the long timing areal calculation in lake
With MATLAB software editing tiffread program, 2001-2015 is cut according to the Poyang Lake mask files in batch
The Poyang Lake range TIFF remote sensing image in year, obtains the water pixel number of the daily Poyang Lake range of 2001-2015, then passes through
Formula (1) calculates the daily Lake area of 2001-2015 Poyang Lake:
S=watercount × 463 × 463 (1)
S is daily Lake area in formula (1), and watercount is daily water pixel number.
Poyang Lake Lake area statistics
The long timing Poyang Lake Lake area that above-described embodiment obtains is handled with Excel software, calculates Poyang Lake
Then the average area of 2001-2015 month by month further calculates out the average area of Poyang Lake 2001-2015 year by year, make
The area data result of the area change tendency chart of Poyang Lake 2001-2015 out, such as Fig. 7, Poyang Lake 2001-2015 is as follows
Table 1:
1 2001-2015 Poyang Lake area sequence of table
The verifying of Poyang Lake Lake area
The present embodiment selects document 1, and (Zhang Kexiang .MODIS monitors middle and lower reach of Yangtze River typical case area of lake Changeement [D]
East China Institute of Technology, 2015) and (Poyang Lake Lake area remote sensing prison of Xu little Hua, Zhang Weiqi, the Hu Qiang based on MODIS of document 2
Survey the research Jiangxi [J] water economic system, 2008,34 (4): 256-258) carry out Lake area verifying.
Number based on the 250m vegetation index product MOD13Q1 of synthesis in Terra/MODIS data 16 days is used in document 1
According to overall classification accuracy 89.59%, the annual area change mean value of Poyang Lake 2001-2013 is shown in Table 2;Select phase the same year
The MOD13Q1/FROM-GLC data of part are compared, and are calculated by formula (2) and are deviateed percentage:
R=(AreaMOD13Q1-AreaFROM-GLC)/AreaFROM-GLC× 100% (2)
In formula (2): r is to deviate percentage, AreaMOD13Q1For the Poyang Lake area obtained based on MOD13Q1,
AreaFROM-GLCFor the Poyang Lake area obtained based on FROM-GLC, calculated result is shown in Table 3.
The average annual Lake area of 2001-2013 Poyang Lake in 2 document 1 of table
The deviation percentage for the Poyang Lake area that 3 document 1 of table is extracted with the present embodiment
Fig. 8 is shown in the comparison of Poyang Lake area Annual variations rule in document 1 and the present embodiment.
Document 2 extracts the Lake area of Poyang Lake the first half in 2007 and later six months in 2008 using MODIS data, now selects
The MODIS/FROM-GLC data for selecting phase same date are compared with Poyang Lake area in the present embodiment, such as Fig. 9 (a) and (b).
From in Fig. 8, Fig. 9 it is found that Poyang Lake Lake area and document 1 that the present embodiment extracts, the Lake area in document 2
Variation overall trend be consistent, thus verifying the obtained Poyang Lake Lake area time series of the present embodiment is to hold water
's.As shown in Table 3, the difference of the present embodiment obtains Poyang Lake Lake area and document 1 generates these differences in 6%-27%
The reason of be MOD13Q1 data and FROM-GLC data temporal resolution and spatial resolution and spectral resolution it is different
Sample.
The area of lake extracting method provided in the present embodiment is distant based on FROM-GLC data set acquisition lake country TIFF
Feel image, revisiting period is one day, and atural object resolution ratio is 463m.
FROM-GLC data set is the global multiclass land use data product based on landsat8TM/OLI satellite, is complete
First spectral resolution of ball be 30 meters, the product with fine resolution ratio observer and monitoring Global land cover pattern object, and
And a global moisture film can be extracted.The data product and other products comparison discovery producer's precision (PA) and user person's essence
4.62% and 0.51% has been respectively increased in degree (UA), and the global Inland Water gross area has dropped 15.83%.
FROM-GLC data set is to from FROM-GLC data product moisture film using object method, method is based on
Each of water calculation and object cloud features of terrain, spectral signature and geometrical relationship, and set specific rule and determine water
Whether object is mistakenly classified, with spectral information and terrain data come automatic identification massif shade, with the sun-sensor-cloud
The geometrical relationship of this three carrys out automatic identification cloud shade, to reject the water body accidentally divided.The data product solves image water
Two common problems of classification results, i.e. shade (including massif and cloud shade accidentally divide) and water-land spectral mixing region are accidentally divided, because
The extraction accuracy of area of lake can be improved in this.
In addition, by the way that original TIFF remote sensing image can be cut out in batches with MATLAB software editing tiffread program,
Batch extracting calculates area of lake, improves the efficiency of work, can be used for extracting the area in each department lake, has very strong reality
With property and universality.
The above is only a preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, several improvement and deformations can also be made, these improvement and deformations
Also it should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of area of lake extracting method, which is characterized in that described method includes following steps:
TIFF remote sensing image in lake country is obtained using FROM-GLC data set, lake country TIFF remote sensing image is converted, is obtained
Take lake face salt file;
Lake country raster file is obtained using lake face salt file;
Lake country mask file is exported according to lake country raster file;
According to lake country mask file, the lake country TIFF remote sensing image of the long timing of batch processing, batch extracting calculates lake face
Product.
2. area of lake extracting method according to claim 1, which is characterized in that the acquisition of lake face salt file
Method includes:
Under ARCGIS10.2 software platform, line feature shape file in lake is made according to the lake country TIFF remote sensing image,
Then using the data management tools in the tool box ArcToolbox, the feature under features is selected
The lake line feature shape file is converted lake face element shape file by polygon.
3. area of lake extracting method according to claim 1, which is characterized in that the lake country raster file obtains
The method is taken to include:
The former lake country TIFF remote sensing image is tentatively cut with lake face salt file, obtains the lake tentatively cut
Area's raster file;
According to lake country TIFF remote sensing image and corresponding lake region feature on water, amendment mask file is set by threshold value, is made
The lake country raster file tentatively cut gradually adjust to lake country TIFF remote sensing image it is a wide range of within, obtain final cut out
The lake country raster file sheared.
4. area of lake extracting method according to claim 3, which is characterized in that the lake country raster text tentatively cut
The acquisition methods of part include:
Utilize the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, selection
Then extraction selects extract by mask to generate the lake raster file tentatively cut.
5. area of lake extracting method according to claim 3, which is characterized in that the method for correcting mask file includes:
Using the spatial analyst tools in the tool box ARCGIS10.2 software ArcToolbox, map is selected
Then algebra selects raster calculator, all 0 regions of being more than or equal to are set as 300, more than or equal to 0
Region is set as lake country, exports the lake country raster file of processing again, by merging raster file several times, obtains in lake
Moor area TIFF remote sensing image it is a wide range of within lake country raster file.
6. area of lake extracting method according to claim 5, which is characterized in that the lake country raster finally cut
The acquisition methods of file include:
For be located at lake country TIFF remote sensing image influence it is a wide range of within lake country raster file, utilize
The data management in the tool box ARCGIS10.2 software ArcToolBox selects raster, then selects raster
Area assignment within the scope of lake is 1 by the mosaic under dataset, and other area assignments are -9999, exports lake country
Raster file, the lake raster file as finally cut out.
7. area of lake extracting method according to claim 1, which is characterized in that the FROM-GLC data set revisits
Period is one day.
8. area of lake extracting method according to claim 1, which is characterized in that the export of the lake country mask file
Method includes:
The lake country raster file finally cut is exported as into txt file;
The txt file is imported into MATLAB software, saves output lake country mask file.
9. area of lake extracting method according to claim 8, which is characterized in that the deriving method packet of the txt file
It includes:
Using the conversion tool in the tool box ARCGIS10.2 software ArcToolBox, select under from raster
Raster to ascii generates the txt file.
10. area of lake extracting method according to claim 1, which is characterized in that the calculation method of the area of lake
Include:
With MATLAB software editing tiffread program, the lake country of long timing is cut according to the lake country mask files in batch
TIFF remote sensing image obtains the water pixel number of daily lake range, then calculates the daily lake of long timing by formula (1)
Area:
S=watercount × 463 × 463 (1)
S is daily Lake area in formula (1), and watercount is water pixel number.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111738144A (en) * | 2020-06-19 | 2020-10-02 | 中国水利水电科学研究院 | Surface water product generation method and system based on Google Earth Engine cloud platform |
CN113011740A (en) * | 2021-03-18 | 2021-06-22 | 长江水资源保护科学研究所 | Method for constructing lake wetland ecology-water level gradient response relation |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2003094109A2 (en) * | 2002-05-03 | 2003-11-13 | International Hardwood Resources, Inc. | Method od feature identification and analysis |
WO2006105465A2 (en) * | 2005-03-30 | 2006-10-05 | Battelle Memorial Institute | Automated alignment of spatial data sets using geometric invariant information and parameter space clustering |
CN102033898A (en) * | 2010-09-27 | 2011-04-27 | 华东师范大学 | Extraction method for local cloud cover information metadata of moderate resolution imaging spectral image |
CN103955565A (en) * | 2014-04-08 | 2014-07-30 | 天津大学城市规划设计研究院 | GIS (Geographic Information System) platform-based urban water system construction planning method |
CN107330422A (en) * | 2017-07-28 | 2017-11-07 | 首都师范大学 | A kind of method for carrying out mima type microrelief classification to semiarid zone based on high accuracy number elevation model |
CN108256015A (en) * | 2018-01-08 | 2018-07-06 | 中国科学院遥感与数字地球研究所 | A kind of Chinese population spatial grid method based on nighttime light data |
CN108804805A (en) * | 2018-06-05 | 2018-11-13 | 中国水利水电科学研究院 | A method of automatically extracting a plurality of river basins exit point |
CN108830844A (en) * | 2018-06-11 | 2018-11-16 | 北华航天工业学院 | A kind of facilities vegetable extracting method based on multidate high-resolution remote sensing image |
-
2019
- 2019-07-01 CN CN201910584480.3A patent/CN110276797B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2003094109A2 (en) * | 2002-05-03 | 2003-11-13 | International Hardwood Resources, Inc. | Method od feature identification and analysis |
WO2006105465A2 (en) * | 2005-03-30 | 2006-10-05 | Battelle Memorial Institute | Automated alignment of spatial data sets using geometric invariant information and parameter space clustering |
CN102033898A (en) * | 2010-09-27 | 2011-04-27 | 华东师范大学 | Extraction method for local cloud cover information metadata of moderate resolution imaging spectral image |
CN103955565A (en) * | 2014-04-08 | 2014-07-30 | 天津大学城市规划设计研究院 | GIS (Geographic Information System) platform-based urban water system construction planning method |
CN107330422A (en) * | 2017-07-28 | 2017-11-07 | 首都师范大学 | A kind of method for carrying out mima type microrelief classification to semiarid zone based on high accuracy number elevation model |
CN108256015A (en) * | 2018-01-08 | 2018-07-06 | 中国科学院遥感与数字地球研究所 | A kind of Chinese population spatial grid method based on nighttime light data |
CN108804805A (en) * | 2018-06-05 | 2018-11-13 | 中国水利水电科学研究院 | A method of automatically extracting a plurality of river basins exit point |
CN108830844A (en) * | 2018-06-11 | 2018-11-16 | 北华航天工业学院 | A kind of facilities vegetable extracting method based on multidate high-resolution remote sensing image |
Non-Patent Citations (6)
Title |
---|
FENGHUAYOUSHI: "《ArcGIS下栅格裁剪的几种方法和批量处理方法》", 《HTTPS://BLOG.CSDN.NET/FENGHUAYOUSHI/ARTICLE/DETAILS/6072786》 * |
JOE WHEATON: "《Using ArcGIS’s Raster Calculator (Spatial Analyst) to Calculate DoD》", 《ECOGEOMORPHOLOGY & TOPOGRAPHIC ANALYSIS LABORATRY》 * |
朱志龙 等;: "《湖泊水面面积》", 《湖北省湖泊资源环境调查与保护利用研究》 * |
杨利: "《三峡工程对洞庭湖区湿地景观格局及生态健康的影响研究》", 《博士学位论文库》 * |
王宏伟: "《流域蒸散发量遥感估算及灵敏度分析》", 《中国优秀硕士学位论文全文数据库信息科技辑》 * |
金耀 等;: "《基于ArcGIS、MATLAB 及Surfer 的DGPS 冰碛垄测量模拟对比》", 《测绘科学》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111738144A (en) * | 2020-06-19 | 2020-10-02 | 中国水利水电科学研究院 | Surface water product generation method and system based on Google Earth Engine cloud platform |
CN113011740A (en) * | 2021-03-18 | 2021-06-22 | 长江水资源保护科学研究所 | Method for constructing lake wetland ecology-water level gradient response relation |
CN113011740B (en) * | 2021-03-18 | 2021-09-14 | 长江水资源保护科学研究所 | Method for constructing lake wetland ecology-water level gradient response relation |
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