CN110276797B - A kind of lake area extraction method - Google Patents

A kind of lake area extraction method Download PDF

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CN110276797B
CN110276797B CN201910584480.3A CN201910584480A CN110276797B CN 110276797 B CN110276797 B CN 110276797B CN 201910584480 A CN201910584480 A CN 201910584480A CN 110276797 B CN110276797 B CN 110276797B
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area
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lake area
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CN110276797A (en
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任黎
周悦
阴帅妮
徐伟
徐健
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Hohai University HHU
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Abstract

本发明公开了一种湖泊面积提取方法,所述方法包括如下步骤:采用FROM‑GLC数据集获取湖泊区TIFF遥感影像,对湖泊区TIFF遥感影像进行转换,获取湖泊面要素文件;利用湖泊面要素文件获取湖泊区raster文件;根据湖泊区raster文件导出湖泊区mask文件;根据湖泊区mask文件,批量处理长时序的湖泊区TIFF遥感影像,批量提取计算湖泊面积。本发明提供的湖泊面积提取方法,提取精度高,可批量提取计算湖泊面积,工作效率高,具有实用性和普适性。

Figure 201910584480

The invention discloses a lake area extraction method. The method includes the following steps: using a FROM-GLC data set to obtain a TIFF remote sensing image of a lake area, converting the TIFF remote sensing image of the lake area, and obtaining a lake area element file; using the lake area element Obtain the lake area raster file from the file; export the lake area mask file according to the lake area raster file; batch process long-sequence lake area TIFF remote sensing images according to the lake area mask file, and extract and calculate the lake area in batches. The lake area extraction method provided by the invention has high extraction accuracy, can extract and calculate the lake area in batches, has high work efficiency, and has practicability and universality.

Figure 201910584480

Description

Lake area extraction method
Technical Field
The invention belongs to the technical field of lake research, and particularly relates to a lake area extraction method.
Background
Lakes are a key component of the climate, water and biogeochemical cycles, and changes in lake surface area have a significant impact on environmental changes and human production activities. The lake area is reduced, the water storage capacity can be worsened, flood can often explode in the flood season, no water is available in dry seasons, adverse effects can be caused to the surrounding ecological balance, the diversity of organisms is influenced, some species can disappear along with the flood, and the local climate can be influenced, so that the ecological environment is monotonous, and the existence and development of human beings are not facilitated. At present, the research on the annual change trend and the driving force of the lake area is a hot point of domestic and foreign research. The accuracy of analysis of the lake area change depends on the accuracy of extraction of the lake area, and the high efficiency of analysis of the lake area age change trend depends on batch extraction of the lake area. However, the existing lake area extraction method has low extraction precision, low efficiency and poor practicability.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides the lake area extraction method which is high in extraction precision, high in working efficiency, practical and universal, and can be used for extracting and calculating the lake area in batches.
The invention provides the following technical scheme:
a lake area extraction method comprises the following steps:
acquiring a TIFF remote sensing image of a lake area by using a FROM-GLC data set, converting the TIFF remote sensing image of the lake area, and acquiring a lake surface element file;
acquiring a lake area raster file by using the lake surface element file;
exporting a lake area mask file according to the lake area raster file;
and processing TIFF remote sensing images of the lake regions with long time sequence in batches according to the mask file of the lake regions, and extracting and calculating the area of the lake in batches.
Preferably, the method for acquiring the lake surface element file comprises the following steps:
under an ARCGIS10.2 software platform, making a lake line element shape file according to the TIFF remote sensing image of the lake area, then selecting feature to polygon under features by using data management tools in an ArcToolbox tool box, and converting the lake line element shape file into a lake surface element shape file.
Preferably, the method for acquiring the lake area raster file comprises the following steps:
primarily cutting the original TIFF remote sensing image of the lake area by using a lake surface element file to obtain a primarily cut lake area raster file;
according to the TIFF remote sensing image of the lake area and the characteristics of the water area of the corresponding lake area, setting a correction mask file through a threshold value, gradually adjusting the preliminarily cut lake area raster file to be within a large range of the TIFF remote sensing image of the lake area, and obtaining the finally cut lake area raster file.
Preferably, the method for acquiring the primarily cut lake area raster file comprises the following steps:
and selecting an extraction by using specific analysis tools in an ARCGIS10.2 software ArcToolbox, and then selecting an extraction by mask to generate a primarily cut lake raster file.
Preferably, the method of correcting the mask file includes:
selecting map algabra by using specific analysis tools in an ARCGIS10.2 software ArcToolbox, then selecting a raster computer, setting all areas larger than or equal to 0 as 300, setting the areas larger than or equal to 0 as lake areas, outputting the processed lake area raser file again, and obtaining the lake area raser file within a large range influenced by TIFF remote sensing images in the lake areas by combining the raster files for a plurality of times.
Preferably, the method for acquiring the finally cut lake area raster file comprises the following steps:
aiming at lake area raster files in a large range influenced by TIFF remote sensing images in a lake area, raster is selected by using data management of an ARCGIS10.2 software ArcToolBox tool box, then mosaic under raster data set is selected, the area in the lake area is assigned as 1, other areas are assigned as-9999, and the lake area raster files are output, namely the finally cut lake raster files.
Preferably, the revisit cycle of the FROM-GLC dataset is one day.
Preferably, the method for exporting the lake area mask file comprises the following steps:
exporting the finally cut lake area raster file into a txt file;
and importing the txt file into MATLAB software, and storing and outputting a mask file of the lake area.
Preferably, the method for exporting the txt file comprises the following steps:
and selecting the raster to ascii under from raster to generate the txt file by using a conversion tool of an ARCGIS10.2 software ArcToolBox tool box.
Preferably, the method for calculating the lake area comprises the following steps:
editing tiffread program by MATLAB software, cutting TIFF remote sensing images of the long time sequence lake area in batches according to the lake area mask file to obtain the number of water pixels in the daily lake range, and then calculating the daily lake area of the long time sequence through a formula (1):
s=watercount×463×463 (1)
in the formula (1), s is the area of the lake surface every day, and the waterfount is the number of pixels of water.
Compared with the prior art, the invention has the beneficial effects that:
(1) according to the invention, the FROM-GLC data set is adopted to obtain the TIFF remote sensing image of the lake area, so that the problems of mistaken division of mountain, cloud and water areas and spectral land and water mixed areas are solved, and the extraction precision of the lake area is improved.
(2) The lake area extraction method provided by the invention is simple to operate, can cut original TIFF remote sensing images in batches, extracts and calculates the lake area in batches, improves the working efficiency, can be used for extracting the lake area of each region, and has strong practicability and universality.
Drawings
FIG. 1 is a block diagram of the yang lake line elements of in example;
FIG. 2 is a Poyang lake surface element area diagram in an embodiment;
FIG. 3 is an original TIFF remote sensing image of the lake region of the Yanghu of the example;
FIG. 4 is a view of the preliminarily cut Yanghu raster in the example;
FIG. 5 is a diagram of the Poyang lake raster in the second clipping of the example;
FIG. 6 is a diagram of the Poyang lake raster with the best clipping effect in the example;
FIG. 7 is a graph showing the trend of the area change in the year Yanghu 2001-2015 in the example;
FIG. 8 is a graph comparing the example with the annual variation of Poyang lake area in document 1;
FIG. 9 is a comparison graph of the example and the document 2 Poyang lake area change, in which (a) is the example Poyang lake area change graph, and (b) is the document 2 Poyang lake area change graph.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
Examples
A lake area extraction method takes Yanghu as an example, and comprises the following steps:
step one, manufacturing a lake surface element file
An h28v06 image (a lake region TIFF remote sensing image) of Yanghu 2001 day 2 is obtained by adopting a FROM-GLC data set, a Yanghu line element shape file is made according to the lake region TIFF remote sensing image under an ARCGIS10.2 software platform, and then a feature to polygon under featurs is selected by using data management tools in an ArcToolbox, so that the Yanghu line element shape file is converted into a Poyang lake surface element shape file, wherein the Poyang lake line element area is shown in figure 1, and the Poyang lake surface element area is shown in figure 2.
Step two, manufacturing a lake area raster file
The Poyang lake surface element shape file is used for primarily cutting the TIFF remote sensing image of the lake area, specifically, spatial analysis tools in an ARCGIS10.2 software ArcToolbox are used for selecting an extraction, and then an extraction by mask is selected to generate a primarily cut Yanghu raster file, for example, the original TIFF remote sensing image of the lake area is shown in FIG. 3, and for example, the primarily cut Yanghu raster file is shown in FIG. 4.
As can be seen from fig. 4, the range of the preliminarily cropped Yanghu raster file is smaller than the range of the TIFF remote sensing image of the original lake region, so that the next threshold setting is performed, that is, the preliminarily cropped Yanghu raster file is recalculated, specifically, map algabra is selected by using spatial analysis tools in the ArcToolbox of the arcsis 10.2 software, then raster computer is selected, all the regions greater than or equal to 0 are set to 300, the regions greater than or equal to 0 are the range of Yanghu, and the processed raster file of Yanghu is output again, as shown in fig. 5.
As can be seen from fig. 5, the raster file range of the processed yang lake is still smaller than the TIFF remote sensing image range of the original lake area, the raster file of the processed yang lake is adjusted to be within the large range of the TIFF remote sensing image range of the original lake area again by merging the raster files, then the raster is selected by using the data management of the arctools box of arccis 10.2 software, then the mosaic under raster dataset is selected, the numerical value of the raster file of the yang lake after completion of merging is adjusted, the area in the lake range is assigned as 1, the other areas are assigned as-9999, and the lake area raster file is output, i.e., the finally clipped yang lake raster file, as shown in fig. 6.
Step three, making a mask file of the lake area
Exporting the finally cut Yanghu raster file into a txt file, specifically, selecting raster to ascii under from raster to generate the txt file by using conversion tool of an ARCGIS10.2 software ArcToolBox toolbox; and then importing the txt file into MATLAB software, and storing an output Poyang lake mask file.
Step four, calculating the long time sequence area of the lake
Editing a tiffread program by MATLAB software, cutting the Poyang lake range TIFF remote sensing image in 2001-2015 in batches according to the Poyang lake mask file to obtain the number of water pixels in the Poyang lake range in 2001-2015 every day, and then calculating the area of the Poyang lake every day in 2001-2015 by using a formula (1):
s=watercount×463×463 (1)
in the formula (1), s is the area of the lake surface per day, and the watercount is the number of water pixels per day.
Poyang lake surface area statistics
Processing the long-time Yanghu lake surface area obtained in the above embodiment by Excel software, calculating the average area of Yanghu 2001-2015 year by month, further calculating the average area of Yanghu 2001-2015 year by year, making an area change trend graph of PoYang lake 2001-2015 year, as shown in FIG. 7, and the area data result of PoYang lake 2001-2015 year is as shown in the following table 1:
TABLE 12001-2015-year Poyang lake area sequence
Figure BDA0002114053950000071
Poyang lake surface area verification
In the embodiment, the lake surface area verification is performed by selecting document 1 (Zhang Xiang. MODIS monitoring typical lake area change research [ D ]. Donghua university of science and technology, 2015) and document 2 (Chi Hua, Zhang Weiqi, Huqiang, Poyang lake surface area remote sensing monitoring research based on MODIS [ J ]. Jiangxi water conservancy technology, 2008, 34 (4): 256-one 258).
The 250m vegetation index product MOD13Q1 synthesized by Terra/MODIS data for 16 days in the document 1 is basic data, the overall classification precision is 89.59%, and the average value of the annual area change in Poyang lake 2001-2013 is shown in Table 2; MOD13Q1/FROM-GLC data FROM the same year were selected for comparison and the percent deviation was calculated according to equation (2):
r=(AreaMOD13Q1-AreaFROM-GLC)/AreaFROM-GLC×100% (2)
in formula (2): r is the percent deviation, AreaMOD13Q1To obtain Poyang lake Area based on MOD13Q1, AreaFROM-GLCThe results of the calculations are shown in Table 3 for the Poyang lake area obtained based on FROM-GLC.
Table 2, document 1, 2001-2013, Poyang lake annual average lake surface area
Figure BDA0002114053950000081
TABLE 3 percent deviation of Poyang lake area extracted from article 1 and this example
Figure BDA0002114053950000082
Figure BDA0002114053950000091
The reference 1 is shown in FIG. 8 in comparison with the annual variation rule of Poyang lake area in this embodiment.
Document 2 uses MODIS data to extract the lake surface area of yang lake in the first half year of 2007 and the second half year of 2008, and MODIS/FROM-GLC data on the same date are selected to be compared with the Poyang lake area in the present embodiment, as shown in fig. 9(a) and (b).
It can be seen from fig. 8 and 9 that the Poyang lake surface area extracted in the present embodiment is consistent with the overall trend of the change of the lake surface area in documents 1 and 2, and thus it is verified that the Poyang lake surface area time series obtained in the present embodiment is correct and reasonable. As can be seen FROM Table 3, the Poyang lake surface area obtained in this example differs FROM that of reference 1 by 6% to 27%, and these differences are caused by the difference in the temporal resolution and the spatial resolution and the spectral resolution between the MOD13Q1 data and the FROM-GLC data.
The lake area extraction method provided in the embodiment obtains the TIFF remote sensing image of the lake area based on the FROM-GLC dataset, and the revisit cycle is one day and the ground feature resolution is 463 m.
The FROM-GLC dataset is a global multi-class land use data product based on the landsat8TM/OLI satellite, a global first spectral resolution of 30 meters, with fine resolution observers and monitoring of global land cover, and can extract a global water film. Compared with other products, the data product shows that the producer Precision (PA) and the user precision (UA) are respectively improved by 4.62 percent and 0.51 percent, and the total area of the global inland water body is reduced by 15.83 percent.
The FROM-GLC data set adopts an object-based method, which is characterized in that the topographic characteristics, the spectral characteristics and the geometric relations of clouds are calculated for each water object in a water film FROM the FROM-GLC data product, a specific rule is set to judge whether the water objects are wrongly classified or not, the mountain shadow is automatically identified by using the spectral information and the topographic data, and the cloud shadow is automatically identified by using the geometric relations of the sun, the sensor and the clouds, so that the water body which is wrongly classified is removed. The data product solves two common problems of image water classification results, namely shadow (including mountain shadow and cloud shadow misclassification) and water-land spectrum mixed region misclassification, so that the extraction precision of the lake area can be improved.
In addition, by editing the tiffread program by MATLAB software, the original TIFF remote sensing images can be cut in batches, the lake area can be extracted and calculated in batches, the working efficiency is improved, the method can be used for extracting the area of lakes in various regions, and the method has strong practicability and universality.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (6)

1.一种湖泊面积提取方法,其特征在于,所述方法包括如下步骤:1. a lake area extraction method, is characterized in that, described method comprises the steps: 采用FROM-GLC数据集获取湖泊区TIFF遥感影像,对湖泊区TIFF遥感影像进行转换,获取湖泊面要素文件;The FROM-GLC dataset was used to obtain the TIFF remote sensing image of the lake area, and the TIFF remote sensing image of the lake area was converted to obtain the lake surface element file; 利用湖泊面要素文件获取湖泊区raster文件;Use the lake surface element file to obtain the lake area raster file; 根据湖泊区raster文件导出湖泊区mask文件;Export the lake area mask file according to the lake area raster file; 根据湖泊区mask文件,批量处理长时序的湖泊区TIFF遥感影像,批量提取计算湖泊面积;According to the lake area mask file, batch process long-term lake area TIFF remote sensing images, and batch extract and calculate the lake area; 所述湖泊面要素文件的获取方法包括:The acquisition method of the lake surface element file includes: 在ARCGIS10.2软件平台下,根据所述湖泊区TIFF遥感影像制作湖泊线要素shape文件,然后利用ArcToolbox工具箱中的data management tools,选择features下的feature topolygon,将所述湖泊线要素shape文件转化为湖泊面要素shape文件;Under the ArcGIS 10.2 software platform, create a shapefile of lake line features based on the TIFF remote sensing image of the lake area, and then use the data management tools in the ArcToolbox toolbox to select feature topolygon under features to convert the shapefile of the lake line features shapefile for lake polygon features; 所述湖泊区raster文件的获取方法包括:The acquisition method of the lake area raster file includes: 用湖泊面要素文件对原所述湖泊区TIFF遥感影像进行初步裁剪,获取初步裁剪的湖泊区raster文件;Preliminarily trim the TIFF remote sensing image of the lake area with the lake surface element file, and obtain the preliminary trimmed lake area raster file; 根据湖泊区TIFF遥感影像及对应湖泊区域水域特点,通过阈值设定修正掩模文件,使初步裁剪的湖泊区raster文件逐步调整至湖泊区TIFF遥感影像的大范围之内,获取最终裁剪好的湖泊区raster文件;According to the TIFF remote sensing image of the lake area and the water characteristics of the corresponding lake area, the mask file is modified by threshold setting, so that the preliminary cropped raster file of the lake area is gradually adjusted to the large range of the TIFF remote sensing image of the lake area, and the final cropped lake is obtained. District raster file; 修正掩模文件的方法包括:Methods for correcting mask files include: 利用ARCGIS10.2软件ArcToolbox工具箱中的spatial analyst tools,选择mapalgebra,然后选择raster calculator,把所有大于等于0的区域设置为300,大于等于0的区域设为湖泊区,再次输出处理的湖泊区raster文件,通过若干次合并栅格文件,获得在湖泊区TIFF遥感影像的大范围之内的湖泊区raster文件;Use the spatial analyst tools in the ArcGIS 10.2 software ArcToolbox toolbox, select mapalgebra, then select raster calculator, set all areas greater than or equal to 0 to 300, and areas greater than or equal to 0 as lake areas, and output the processed lake area raster again file, by merging raster files several times, the raster file of the lake area within a large range of the TIFF remote sensing image of the lake area is obtained; 最终裁剪好的湖泊区raster文件的获取方法包括:The method of obtaining the final cropped lake area raster file includes: 针对位于湖泊区TIFF遥感影像影响的大范围之内的湖泊区raster文件,利用ARCGIS10.2软件ArcToolBox工具箱的data management,选择raster,然后选择rasterdataset下的mosaic,将湖泊范围内的区域赋值为1,其它区域赋值为-9999,输出湖泊区raster文件,即为最终剪裁好的湖泊raster文件。For the raster file in the lake area that is within the large area affected by the TIFF remote sensing image of the lake area, use the data management of the ArcGIS 10.2 software ArcToolBox toolbox, select raster, and then select mosaic under the rasterdataset, and assign the area within the lake area to 1 , other areas are assigned -9999, and the output lake area raster file is the final tailored lake raster file. 2.根据权利要求1所述的湖泊面积提取方法,其特征在于,初步裁剪的湖泊区raster文件的获取方法包括:2. lake area extraction method according to claim 1, is characterized in that, the acquisition method of the lake area raster file of preliminary trimming comprises: 利用ARCGIS10.2软件ArcToolbox工具箱中的spatial analyst tools,选择extraction,然后选择extract by mask生成初步裁剪好的湖泊raster文件。Use the spatial analyst tools in the ArcGIS 10.2 software ArcToolbox toolbox, select extraction, and then select extract by mask to generate a preliminary cropped lake raster file. 3.根据权利要求1所述的湖泊面积提取方法,其特征在于,所述FROM-GLC数据集的重访周期为一天。3. The lake area extraction method according to claim 1, wherein the revisit period of the FROM-GLC data set is one day. 4.根据权利要求1所述的湖泊面积提取方法,其特征在于,所述湖泊区mask文件的导出方法包括:4. lake area extraction method according to claim 1, is characterized in that, the deriving method of described lake area mask file comprises: 将最终裁剪好的湖泊区raster文件导出为txt文件;Export the final cropped lake area raster file as a txt file; 将所述txt文件导入MATLAB软件,保存输出湖泊区mask文件。Import the txt file into MATLAB software and save the output lake area mask file. 5.根据权利要求4所述的湖泊面积提取方法,其特征在于,所述txt文件的导出方法包括:5. lake area extraction method according to claim 4, is characterized in that, the deriving method of described txt file comprises: 利用ARCGIS10.2软件ArcToolBox工具箱的conversion tool,选择from raster下的raster to ascii生成所述txt文件。Using the conversion tool of the ArcGIS 10.2 software ArcToolBox toolbox, select raster to ascii under from raster to generate the txt file. 6.根据权利要求1所述的湖泊面积提取方法,其特征在于,所述湖泊面积的计算方法包括:6. The lake area extraction method according to claim 1, wherein the calculation method of the lake area comprises: 用MATLAB软件编辑tiffread程序,根据所述湖泊区mask文件批量裁剪长时序的湖泊区TIFF遥感影像,得到每日湖泊范围的水像元数,然后通过公式(1)计算出长时序每日的湖泊面积:Edit the tiffread program with MATLAB software, and batch crop long-series lake area TIFF remote sensing images according to the lake area mask file to obtain the number of water pixels in the lake area per day, and then calculate the long-series daily lake area by formula (1). area:
Figure DEST_PATH_IMAGE002
(1)
Figure DEST_PATH_IMAGE002
(1)
式(1)中S为每日的湖面面积,
Figure DEST_PATH_IMAGE004
为水像元数。
In formula (1), S is the daily lake surface area,
Figure DEST_PATH_IMAGE004
is the number of water pixels.
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Citations (8)

* Cited by examiner, † Cited by third party
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

Patent Citations (8)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
Title
《ArcGIS下栅格裁剪的几种方法和批量处理方法》;fenghuayoushi;《https://blog.csdn.net/fenghuayoushi/article/details/6072786》;20180628;第1页; *
《Using ArcGIS’s Raster Calculator (Spatial Analyst) to Calculate DoD》;Joe Wheaton;《ecogeomorphology & topographic analysis laboratry》;20100520;第1-3页; *
《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》;杨利;《博士学位论文库》;20141231;第1-147页; *
《基于ArcGIS、MATLAB 及Surfer 的DGPS 冰碛垄测量模拟对比》;金耀 等;;《测绘科学》;20130331;第38卷(第2期);第53-55页; *
《流域蒸散发量遥感估算及灵敏度分析》;王宏伟;《中国优秀硕士学位论文全文数据库信息科技辑》;20121215;第I140-201页 *
《湖泊水面面积》;朱志龙 等;;《湖北省湖泊资源环境调查与保护利用研究》;20140331;第37-42页; *

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