GEEgee遥感第一章节googleearthengine遥感云平台java数据处理遥感大数据处理

Modell

01.HelloWorld

print('HelloWorld');

//Variables

varcity='Bengaluru";

varcountry='India';

print(city,country);

varpopulation=8400000;

print(population);

//List

varmajorCities=['Mumbai','Delhi','Chennai','Kolkata'];

print(majorCities);

//Dictionary

varcityData={

'city':city,

,population':8400000,

,elevation':930

)：

print(cityData);

//Function

vargreet=function(name){

return'Hello'+name;

｝；

print(greet('World'));

//Thisisacomment

Inspector1*一1•Tasks

Usetowritetothisconsole.print(...)

HelloWorld

Bengaluru

India

8400000

►[*Mumbai*.*Delhi*.*Chennai*t*Kolkata*]

►Object(3properties)

HelloWorld

//excise1

//Thesearethe5largestcitiesintheworld:

//Tokyo,Delhi,Shanghai,MexicoCity,SaoPaulo

//Createalistnamed'largeCities'

//Thelistshouldhavenamesofalltheabovecities

//Printthelist

varlargeCities=['Tokyo','Delhi','Shanghai','MexicoCity'.'SaoPaulo'];

print(largeCities);

InspectorConsole

Usetowritetothisconsole,print(...)

▼List(5alomants)

0:Tokyo

1:Delhi

2:Shanghai

3:MexicoCity

4:SaoPaulo

02.图像集合WorkingwithImageCollections

从Sentinel-2,1C级页面中复制而来：

/**

*FunctiontomaskcloudsusingtheSentinel-2QAband

*@param{ee.Image}imageSentinel-2image

*@return{ee.Image}cloudmaskedSentinel-2image

*/

functionmaskS2clouds(image){

varqa=image.select('QA60')：

//Bits10and11arecloudsandcirrus,respectively.

varcloudBitMask=1«10;

varcirrusBitMask=1«11;

//Bothflagsshouldbesettozero,indicatingclearconditions.

varmask=qa.bitwiseAnd(cloudBitMask).eq(0)

.and(qa.bitwiseAnd(cirrusBitMask).eq(O));

returnimage.updateMask(mask).divide(10000);

)

//Mapthefunctionoveronemonthofdataandtakethemedian.

//LoadSentinel-2TOAreflectancedata.

vardataset=ee.lmageCollection('COPERNICUS/S2,)

.filterDatef^OlS-Ol-Ol','2018-01-31,)

//Pre-filtertogetlesscloudygranules.

flter(ee.FilteMt('CLOUDY_PIXEL_PERCENTACE',20))

.map(ma$kS2clouds);

varrgbVis={

min:0.0,

max:0.3,

bands:['B4','B3','B2'],

)；

Map.setCenter(91695,38.6917,12);〃该函数采用X坐标(经度)、Y坐标(纬度)

和缩放级别参数。取代X和Y与您所在城市的坐标坐标，然后单击“运了以查

看您所在城市的图像Map.setCenter()

Map.addLayer(dataset.median(),rgbVis,'RGB');

可修改经纬度查看自身所在城市，图为广州

MHip.(114.22.544$741112)；

35~p.>ddl・y««*(d・t”，t・xdL8(),rfbVls,'**>；

03.过滤FilteringImageCollections

//excise3

varShenzhen=ee.Geometry.Point([114.0545429,22.5445/41]);

vars2=ee.lmageCollection('COPERNICUS/S2_HARMONIZED');

varfiltered=s2

.filtertee.Filter.ltCCLOUDY-PIXEL-PERCENTAGE',30))

.filter(ee.Filter.date('2023-01,))

.filter(ee.Filter.bounds(shenzhen));

print{filtered.size());

y"*MnXMn■««.Oewetry.Wolfit([：11Usetowritetothiscoasoe.piiat

vacs2•C”

v«rfilter^■12

•Jilt-“2W1)》

.fliter(*«.Filt«r.eowvlt(^Mnxh»n));

prlnt(fliters.

04.马赛克、合成图像CreatingMosaicsand

CompositesfromImageCollections

//excise4

varshenzhen=ee.Geometry.Point([114.0545429,22.5445741]);

vars2=ee.lmageCollectionCCOPERNICUS/SZ.HARMONIZED');

vara={

min:0.0,

max:3000,

bands:['B4','B3','B2'],

)；

varfiltered=s2.filter(ee.Filter.lt：'CL0UDY_PIXEL_PERCENTAGE',30))

.filterfee.Filter.dateCZOZl-Ol-Ol'^O?2^!^1'))

.filter(ee.Filter.bounds(shenzhen));〃过滤函数

varmosaic=filtered.mosaic。;//马赛克生成

varmedianComposite=filteredmedian。;//合/J戈

Map.center0bject(shenzhen,10);

Map.addLayer(filtered,a,'FilteredCollection')；

Map.addLayer(mosaic,a,'Mosaic')；

Map.addLayer(medianComposite,a,'MedianComposite');

04b.Mosaic8.and.Composhes.(comp4«te),G»1Unk▼■Run

1varshenxhetwM.Geometry.Point([114.•545429^22.5445741]);

2v«rs2=e«.Iii«cKollection(CCP[P<ICUS/S2.HARM0RIZE0);

4-vara■{

5ain:e.0«

IMX：wee,

bands:[W,B3,,82],

10v«rfiltered=52.filter(ee.Filter.lt(CLOUOV.PIxei.PERCEWTAOE',M))

11.fnxer(«<.Filter.dattC2021-eier,2e22-eier))

12.filter(ee.Filter.bound$(Shenzhen));//：146IV

13

14v«rmosaic»filtered.»»osalc();//

05.特征集合WorkingwithFeatureCollections

varadmin2=ee.FeatureCollection('FAO/GAUL_SIMPLIFIED_500m/2015/level2')；

varkarnataka=admin2.filter(ee.Filter.eq('ADM2_NAME','Shenzhen'))；

varvisParams={color:'red'};

Map.addLayer(karnataka,visParams,'ShenzhenDistric');

06.引入数据ImportingData

//Importthecollection

varurban=ee.FeatureCollection('users/ujavalgandhi/e2e/ghs_urban_centers');

//Visualizethecollection

Map.addLayer(urban,{color:'blue'},'UrbanAreas')；

varurban=ee.FeatureCollection('users/ujavalgandhi/e2e/ghs_urban_centers');

print(urban.first());

vara=urban.filter(ee.Filter.eq(,CTR_MN_NM','China,));

//Map.addLayerfaXcolori'blue'J/Urban');

varb-a.filterfee.Filter.metadataCPlS'/greate^than',1000000));

Map.addLayerfb^colorz'blue'J/rban');

//Exercise

//Applyafiltertoselectonlylargeurbancenters

//inyourcountryanddisplayitonthemap.

//Selectallurbancentersinyourcountrywith

//apopulationgreaterthan1000000

//Hintl:Usetheproperty'CTR_MN_NM'containingcountrynames

//Hint2:Usetheproperty'P15'containing2015Population

//Exercise

//Applyafiltertoselectonlylargeurbancenters

//inyourcountryanddisplayitonthemap.

//Selectallurbancentersinyourcountrywith

//apopulationgreaterthan1000000

//Hintl:Usetheproperty'CTR_MN_NM'containingcountrynames

//Hint2:Usetheproperty'P15'containing2015Population

07.剪裁图像ClippingImages

vars2=ee.lmageCollection('COPERNICUS/S2_HARMONIZED');

varurban=ee.FeatureCollection('users/ujavalgandhi/e2e/ghs_urban_centers')；

MapaddLayer(urbar),{colQired'},'lipped');

varfiltered=urban.filter(ee.Filter.eq('UC_NM_MN,,'Guangzhou'));

vargeometry=filtered.geometry();

varrgbVis={

min:0.0,

max:3000,

bands:('B4','B3','B2'],

)；

varfiltered=s2.filter(ee.Hlter.lt：'CLUUUY_PixtL_PtKCtNiAbt'z3U))

.filtertee.Filter.dateCZOig-Ol-Ol','2020-01-01,))

.filter(ee.Filter.bounds(geometry));

varimage=filtered.median();

varclipped=image.clip(geometry);

Map.addLayer(clipped,rgbVis,'Clipped')；

//Exercise

//Changethefiltertoyourhomecityoranyurbanareaofyourchoice

//Hint:Findthenameoftheurbancentrebyaddingthe

//'urban'layertothemapandusingInspector.

08.导出数据ExportingData

vars2=ee.lmageCollection('COPERNICUS/S2_HARMONIZED');

varurban=ee.FeatureCollection('users/ujavalgandhi/e2e/ghs_urban_centers')；

varfiltered=urban.filter(ee.Filter.eq('UC_NM_MN,,'Guangzhou'));

vargeometry=filtered.geometry();

varrgbVis={

min:0.0,

max:3000,

bands:['B4','B3','B2'],

)；

varfiltered=s2.filter(ee.Filter.lt：'CLOUDY_PIXEL_PERCENTAGE',30)1

.filterfee.nlter.datef7Oiy-Ul-ul','2020-01-01,))

.filter(ee.Filter.bounds(geometry));

varimage=filtered.median();

varclipped=image.clip(geometry);

Map.centerObject(geometry);

Map.addLayer(clipped,rgbVis,'Clipped')；

varexportimage=clipped.select('B.*');

//Exercise

//Changethefiltertoselectyourcity

//Writetheexportfunctiontoexporttheresults

Export.image.toDrive({

image：exportimage,

description:'Guangzhou_Composite_Raw',

folder:'earthengine',

fileNamePrefix:'guangzhou_composite_raw',

region:geometry,

scale:10,

maxPixels:le9

})；

作业1:

//Assignment

//ExporttheNightLightsimagesforMay,2015andMay,2020

//Workflow:

//LoadtheVIIRSNighttimeDay/NightBandCompositescollection

//Filterthecollectiontothedaterange

//Extractthe'avg_rad'bandwhichrepresentsthenighttimelights

//Cliptheimagetothegeometryofyourcity

//ExporttheresultingimageasaGeoTIFFfile.

//Hintl:

//Thereare2VIIRSNighttimeCay/Nightcollections

//Usetheonethatcorrectsforstraylight

vardataset=ee.lmageCollectionCNOAA/VIIRS/DNB/MONTHLY-Vl/VCMSLCFG')

.filter(ee.Filter.date('2015-05-01','2020-05-31,))；

//Extractthe'avg_rad'bandwhichrepresentsthenighttimelights

varnighttime=dataset.select('avg_rad');

varnighttimeVis={min:0.0,max:60.0};

Map.setCenter(-77.1056,38.8904,8);

Map.addLayer(nighttime,nighttimeVis,'Nighttime')；

//Thecollectioncontains1globalimagepermonth

//Afterfilteringforthemonth,therewillbeonly1imageinthecollection

//Youcanusethefollowingtechniquetoextractthatimage

//varimage=ee.lmage(filtered.first());

varurban=ee.FeatureCollection；'users/ujavalgandhi/e2e/ghs_urban_centers')

varguangzhou=urban.filter(ee.Filter.eq(,UC_NM_MN',,Guangzhou'))；

vargeometry=guangzhou.geometry();

varimage=nighttime;

varimage=image.median();

varclipp=image.clip(geometry);

vara={min:0.0,max:60};

Map.centerObject(geometry);

Map.addLayer(clipp,a,'CLIP')；

Export.image.toDrive({

image:clipp,

description:'Guangzhou_Composite_Raw',

folder:'earthengine,,

fileNamePrefix:'bangalore_composite_raw',

region;geometry,

scale：10,

maxPixels:le9

})；

InspectorConsoleTasksI

Searchorcancelmultipletasksin

theTaskManagerM

SUBMITTEDTASKS

BGuangzhou_Composite_RawK3m

BGuangzhou_Composite_Raw11m

BGuangzhou_Composite_Raw18m

BBangalore_Composite_Visualized8m

常用集合：

vars2=ee.lmageCollection「COPERNICUS/S2_HARMONIZED');〃图像集合

varadminl=ee.FeatureCollection('FAO/GAUL_SIMPLIFIED_500m/2015/levell');〃特

征集合

可获得某个城市的地理坐标

取地理坐标

vargeometry=ee.Geometr/.Point([114,22]);

取某个城市的坐标(数据集---Filter.eq------.geometry())

varadmin2=ee.FeatureCollection('FAO/GAUL_SIMPLIFIED_500m/2015/level2,)；

varfilteredAdmin2=admin2.filter(ee.Filter.eq('ADM2_NAME\'Guangzhou'));

vargeometry=filteredAdmin2.geometry();

作用：

筛选

varfilteredS2=s2

.filterfee.Filter.ltCCLOUDY.PIXEL.PERCENTAGE',35))

.filterlee.Filter.dateCZOig-Ol-Ol','2020-01-01,))

.filter(ee.Filter.bounds(geometry));

定位

Map.centerObject(geometry);

显示特定图像

Map.addLayerfndvi.clipIgeometry),ndviVis,'ndvi*);

first。函数:

在gee中，first。函数用于获取图像集合中的第一张图像。它可以用于检索图像

集合中的最早时间的图像，或者按照特定条件筛选出符合要求的第一张图像。

first。函数的使用方法如下：

image=ee.lmageCollection("XXX").first()

其中，上.||^8"。归(:甘。4)乂犬)表不一个图像集合对象，可以根据需要替换为具

体的图像集合。通过调用first。函数，可以获取该图像集合中的第一张图像。

sort()函数

在gee中，sort。函数用于对图像集合或特定维度的图像进行排序。它可以按照

指定的属性对图像进行升序或降序排序。sort。函数常用于时间序列分析、数据

可视化和特定屈性的筛选等场景。

语法如下：

、、、

sortfproperty,ascending)

、、、

其中，property表示要排序的属性，可以是图像集合中的任意属性，比如时间、

云量等；ascending表示排序方式，为布尔值，True表示升序排序，False表示降

序排序。

例如，如果要对一个图像集合按照时间进行升序排序，可以使用以下代码：

、、、

varsortedCollection=imageCollection.sortCsystemitime-Start',true);

、、、

云量：'CLOUDY_PIXEL_PERCENTAGE'

Module2:EarthEngineIntermediate

01.对象EarthEngineObjects

//Let'sseehowtotakealistofnumbersandadd1toeachelement歹ij表

varmyList=ee.List.sequence(l,10);

//Defineafunctionthattakesanumberandadds1toit

varmyFunction=function(number){

returnnumber+1;

)；

print(myFunction(l));

//Re-DefineafunctionusingEarthEngineAPI

varmyFunction=function(number){

returnee.Number(number).add(l);

}；

print(myFunction(l));

//Mapthefunctionofthelist

varnewList=myList.map(myFunction);

print(newList);

〃Extractingvaluefromalist

varvalue=newList.get⑷;〃选择第几个数字

print(345);

print(value);

//Casting

〃Let'strytodosomecomputationontheextractedvalue选出的数字

//varnewValue=value.addll)//Line30:value.addisnotafunction

//print(newValue)

//YougetanerrorbecauseEarthEnginedoesn'tknowwhatisthetypeof'value'

//Weneedtocastittoappropriatetypefirst

varvalue=ee.Number(value);

varnewValue=value.add(li;

print(newValue);

//Dictionary

//ConvertjavascriptobjectstoEEObjects!!!!!!

vardata={'city':'Bengaluru','population':8400000,'elevation':930};

vareeData=ee.Dictionary(data);

//Onceconverted,youcanusethemethodsfromthe

//ee.Dictionarymodule

print(eeData.get('city'));

//Dates

//Foranydatecomputation,youshoulduseee.Datemodule

vardate=ee.Date('2019-01-01')；

varfutureDate=date.advance。,'year');〃可换成daymonth

print(futureDate);

InspectorTasks

AUseprintC..)towntetothisconsole.

2

U2.3.4.5.6.0.11]jsos

345

6

I

Bengalurujsas

♦Date(202001-0100:00:00)JSOS

02.计算指数CalculatingIndices

vars2=ee.lmageCollectioni'COPERNICUS/S2_HARMONIZED');

varadmin2=ee.FeatureCollection('FAO/GAUL_SIMPUFIED_500m/2015/level2');

,,

Map.addLayer(admin2/{color:'grey}/'A);

varfilteredAdmin2=admin2.filter(ee.Filter.eq('ADM2_NAME'/'Guangzhou'));

vargeometry=filteredAdmin2.geometry();

Map.centerObject(geometry);

,

varfilteredS2=s2.filter(ee.Filter.lt('CL0UDY_PIXEL_PERCENTAGE,30))

.filterlee.Filter.datel7OlS-Ol-Ol；'2020-01-01,))

.filter(ee.Filter.bounds(geometry));

varimage=filteredS2.median();

Map.addLayer(image.clip(geometry)zrgbVis,'Image')；

//

varrgbVis={min:0.0,max:3000,bands:['B4'z'B3','B2']};

varndviVis={min:0,max:l,palette:['white','green']};

varndwiVis={min:0,max:0.5,palette:['white','blue']};

//normalizedDifference()expression()

//'NIR'(B8)and'RED'(B4)'GREEN'(B3)and'SWIR1'(Bll)

//CalculateNormalizedDffereneeVegetationIndex(NDVI)归一化差异植被指数

〃'NIR'(B8)and'RED'(B4)

//varndvi=image.normalizedDifference(['B8\'BA'D.renamed'ndvi']);

Map.addLayer(ndvi.clip(geometry),ndviVis,'ndvi')；

//CalculateModifiedNormalizedDifferenceWaterIndex(MNDWI)归♦化差异水指

数

//'GREEN'(B3)and'SWIR1'(Bll)

varmndwi=image.normalizedDifferenced'BS','Bll']).rencme(['mndwi']);

Map.addLayerfmndwi.clipfgeometry),ndwiVis,'mndwi');

//CalculateSoil-adjustedVegetationIndex(SAVI)土壤调整植被指数

//1.5*((NIR-RED)/(NIR+RED+0.5))

//FortheSAVIformula,thepixelvalues像素值needtoconverted转换成to

reflectances反射率,Multiplyng乘thepixelvaluesby'scale'刻度值givesusthe

reflectancevalue

//Thescalevalueis0.0001forSentinel-2dataset

varsavi=image.expression(

'1.5*((NIR-RED)/(NIR+RED+0.5)),,{

'NIR':image.select('B8').multiply(0.0001),

'RED':image.selectfBA'I.multiplylO.OOOl),

}).rename('savi');

Map.addLayerfsavi.clipfgeometry),ndviVis,'savi');

Exercise

vars2=ee.lmageCollection「COPERNICUS/S2_HARMONIZED')；

varadmin2=ee.FeatureCollection('FAO/GAUL_SIMPLIFIED_500m/2015/level2');

,

varfilteredAdmin2=admin2.filter(ee.Filter.eq('ADM2_NAME/'Guangzhou'));

vargeometry=filteredAdmin2.geometry();

Map.centerObject(geometr/);

varfilteredS2=s2.filter(ee.Filter.lt(,CLOUDY_PIXEL_PERCENTAGE,,30))

.filterlee.Filter.dateCZOig-Ol-Ol','2020-01-01,))

.filter(ee.Filter.bounds(geometry));

varimage=filteredS2.median();

varndviVis-{min:0zmax:l,palette:['white','red']};

varrgbVis={min:0.0,max:3000,bands:['B4'z'B3','B2']};

Map.addLayer(image.clip(geometry)zrgbVis,'Image')；

//CalculatetheNormalizedDifferenceBuilt-UpIndex(NDEI)fortheimage

//Hint:NDBI=(SWIR1-NIR)/(SWIR1+NIR)

varndbi=image.expressionf

,(SWIR1-NIR)/(SWIR1+NIR)',{

'NIR':image.selectfBS'),

'SWIR1':image.selectCBll'),

}).rename('ndbi');

Map.addLayer(ndbi.clip(geometry),ndviVis,'ndbi')；

清远市

小完市

界

,佛山O市1

江门市।土

o由山市

03.指数ComputationonImageCollections

vars2=ee.lmageCollectionrcOPERNICUS/SZ—HARMONIZED');〃图像集合

varadminl=ee.FeatureCollection('FAO/GAUL_SIMPLIFIED_500m/2015/levell');//^

征集合一一

//SelectanAdminlregion

varfilteredAdminl=adminl.filterfee.Filter.eqCADM^NAME','Guangdong

Sheng'));〃选择广州

vargeometry=filteredAdminl.geometry();〃获取地理位置信息

Map.centerObject(geometiv);〃确定主要地理位置

varrgbVis={min:0.0,max:3000,bands:['B4','B3','B2']};

varfilteredS2=s2.filter(ee.Filter.lt('CL0UDY_PIXEL_PERCENTAGE'/30))

.filter(ee.Filter.date('2019-01-01','2020-01-01,))

.filter(ee.Filter.bounds(geometry));〃三层筛选

varcomposite=filteredS2.median().clip(geometry);〃取中间值+剪裁---图像

c

Map.addLayerfcomposite,rgbVis,'AdminlComposite')；

//WriteafunctionthatcomputesNDVIforanimageandaddsitasaband

functionaddNDVI(image){

varndvi=image.normalizedDifferenceffBS','BA'JJ.renameCndvi');

returnimage.addBands(ndvi);

}

//Mapthefunctionoverthecollection

varwithNdvi=filteredS2.map(addNDVI);

varcomposite=withNdvi.medianf);

varndviComposite=composite.select('ndvi');

varpalette=[

,

'FFFFFF；'CE7E45',DF923D'/'F1B555；'FCD163','99B718',

'74A901；'66A000',,529400；'3E8601；'207401；'056201,,

'004C00','023B01；'012E01','011D01','011301'];

varndviVis={miniO,max:0.5,palette:palette};

Map.addLayer(ndviComposite.clip(geometry),ndviVis,'ndvi')；

vars2=ee.lmageCollectionl'COPERNICUS/S2_HARMONIZED,);

varadminl=ee.FeatureCollection('FAO/GAUL_SIMPUFIED_500m/2015/levell,);

//SelectanAdminlregion

varfilteredAdminl=adminl.filterlee.Filter.eqCADM^NAME','GuangdongSheng'));

vargeometry=filteredAdminl.geometry();

Map.centerObject(geometry);

varrgbVis={min:0.0,max:3000,bands:['B4'z"B3','B2']};

varfilteredS2=s2.filter(ee.Filter.lt('CL0UDY_PIXEL_PERCENTAGE'/30))

.filtertee.Filter.datet7Oig-Ol-Ol','2020-01-01,))

.filter(ee.Filter.bounds(geometry));

varcomposite=filteredS2.median().clip(geometry);

Map.addLayerfcomposite,rgbVis,'AdminlComposite');

varimage=filteredS2.median();

//CalculateNormalizedDfferenceVegetationIndex(NDVI)归•化差异植被指数

11'NIR'(B8)and'RED'(B4)normalizedDifference()expression()

varndvi=image.normalizecDifference(['B8','BA'JI.renameil'ndvi']);

varndviVis={min:O,max:l,palette:['white','green']};

Map.addLayerfndvi.clipIgeometry),ndviVis,'ndvi');

//ThisfunctioncalculatesbothNDVIandNDWIindices

//andreturnsanimagewith2newbandsaddedtotheoriginalimage,

functionaddlndices(image){

,

varndvi=image.normalizedDifference(['B8'zB4']).rename('ndvi')；

varndwi=image.normalizedDifference(['B3','BS'D.renameCndwi');

returnimage.addBands(ndvi).addBands(ndwi);

}

//Mapthefunctionoverthecollection

varwithindices=filteredS2.map(addlndices);

//Composite

varcomposite=withlndices.median();

print(composite);

//Hint:Use.selectf)functiontoselectaband

varndviComposite=composite.select('ndwi');

varpalette=[

,FFFFFF','CE7E45','DF923D','F1B555','FCD163\'99B718',

,74A901；'66A000','529400；'3E8601；'207401；'056201,,

'004C00','023B01','012E01','OllDOl；'011301'];

varndviVis={min。max:0.5,palette:palette};

Map.addLayer(ndviComposite.clip(geometry),ndviVis,'ndvi2');

//Exercise

//DisplayamapofNDWIfortheregion

//Selectthe'ndwi'bandandclipitbeforedisplaying

//Useacolorpalettefrom/

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04.云遮罩CloudMasking

完整版：

vars2=ee.lmageCollection('COPERNICUS/S2_HARMONIZED');

vargeometry=ee.Geometr/.PointdllA,22]);

varfilteredS2=s2

.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE',35))

.filter(ee.Filter.date('2019-01-01','2020-01-01,))

.filter(ee.Filter.bounds(geometrv));

//Sortthecollectionandpickthemostcloudyimage

vara=filteredS2.sort({

property:'CLOUDY_PIXEL_PERCENTAGE',

ascending:false

})；

varimage=a.firstf);

varb={

min:0.0,

max:3000,

bands:['B4'z'B3；'B2'],

}；

Map.centerObject(image);

Map.addLayer(image,b,'FullImage',false);

//WriteafunctionforCloudmasking

functionmaskclouds(image]{

varqa=image.select('QA60');

varcloudBitMask=1«10;

varcirrusBitMask=1«11;

varmask=qa.bitwiseAnd(cloudBitMask).eq(0).and(

qa.bitwiseAnd(cirrusBitMask).eq(O));

returnimage.updateMask(mask)

.selectfB.*')

.copyProperties(image,['system:time_start']);

}"

varimageMasked=ee.lmage(maskclouds(image));

Map.addLayerfimageMasked,b,'MaskedImage')；

荧光显示的等同于下面这一段：

varqa=image.select('QA60');

varcloudBitMask=1«10;

varcirrusBitMask=1«11;

varmask=qa.bitwiseAnd(cloudBitMask).eq(0).and(

qa.bitwiseAnd(cirrusBitMask).eq(O));

vara=image.updateMask(mask)

.selectCB.*')

.copyPropertiesfimage,['system:time_start']);

varimageMasked=ee.lmage(a);

解析版：

vars2=ee.lmageCollectioni,COPERNICUS/S2_HARMONIZED,);//WS/g|Sf®

vargeometry=ee.Geometr/.Point([114,22]);〃选取地理坐标

varfilteredS2=s2

.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE'/35))

.filtertee.Filter.datet7Oig-Ol-Ol','2020-01-01,))

.filter(ee.Filter.bounds(geometry));〃三层筛选

//Sortthecollectionandpickthemostcloudyimage

vara=filteredS2.sort({

property:'CLOUDY_PIXEL_PERCENTAGE',

ascending:false

});//sort函数对图像进行排序按照云量升降序

varimage=a.first();〃图像集的第一张

varb={这段代码定义了一个变量b,其中包含了一些参数设置:

min:0.0,・.in：e.e:表示数嘉的最小值为0.0.

・ax：:表示数据的最大值为3000.

max:3000,•bands:['W,-8J-,82)：表示选择了三个波段，分别是

bands:['B4；'B3\'B21伏;'B3'和82'.这五常用于指定由1感影像中显示的波段顺序，

这里选择了红、绿.匹个波段，通常用于自然彩色显示.

)；

这样的设置通常用于在可视化遥影像时指定显示的波段就DS1版序.

以满保合适的显示效果和色彩表现.在实际应用中，这些参数可以根据

Map.centerObject(image);具体需求进行,，例如丽最小值最大值或选择不同的波段姐合来

实现不同的显示效果.

Map.addLayer(image,b,'FullImage',false);

//WriteafunctionforCloudmasking

functionmaskclouds(image；{

varqa=image.selectCQA6(T);〃选择名为QA60'的波段

〃定义了用于提取云和卷云的位掩码(bitmask)

varcloudBitMask=1«10;//数字i左移io位,即在第io位上设评为3用J提取匚估日

varcirrusBitMask=1«11;〃同汨.j提取卷云伤息.

1.：这出水Mt»as«And()雷

BWtq-W这两个遥。像皿进行按位与j1作.

varmask=qa.bitwiseAnd(cloudBitMask).eq(0)这个i射向电为了m个!««■»«««*池与运现

2

qa.bitwiseAnd(cirrusBitMask).eq-*«,>:M•*»<,>防《«»1桁圻

厚的比1。发竹.炉司院屋有7M新祐代'曲心写手

//零・

returnimage.updateMask(mask)3g…":

再次送行按位与■作.这次黑格8Kcirn.Uitm.kifi行按位与

.selectCB.*')//拂作，并列《陶知8否等于零.

在Gee中，这棒的表达式通常用于选择以3开头的所有列或字段.这种语法类似于SQL

中的通配符选择.反中.•表示选择所有以特定字符或字符串开头的列或字段.

举个例子，假设有一个朗8集包含以下列：从10»/8<011丁B_col2丁C_co「.如果你使用

这样的表达式,它会选择所有以B.开头的列.即和0coi2、

在Gee中，这的语法可以用于快速选择符合特定馒式的列，而不需要逐一列出列名，特别是在有大■见需

//要处理时更为方便.

.copyPropertiesfimage,['systemitime-Start']);

)

4.return

image.updateMask(mask).select('B・♦').copyPropertie$(image,

['system:ti«e_starf])；：这段代码将生成的掩膜应用到输入影像

image上，并保留影像中所有波段(通过selectCB.-)),最后

豆制脂像的属性，包括'system:time_start'等.

//

varimageMasked=ee.lmage(maskclouds(image));

Map.addLayer(imageMasked,b,'MaskedImage');

Sentinel-2掩码功能，将其应用丁图像

ImagebeforeImageafter

cloudmaskcloudmask

应用像素级QA位掩码

在Google的Gee库中，bitwiseAnd。是一个位运算函数，用于执行按位与操作。

按位与操作是指将两个数的二进制表示中相应的位进行逻辑与运算，只有当两个

对应位都为1时，结果位才为1,否则为0。在Gee库中，bitwiseAnd。函数可以

用来对整数进行按位与操作，返回两个整数按位与的结果。

intnuml-5;//

intnum2=3;//

intresult=bitwiseAnd(numl>nuii2);

print("按位与的结果为："+result);/.

Exercise

vars2=ee.lmageCollectionl'COPERNICUS/S2_HARMONIZED,)；

vargeometry=ee.Geometr/.Point([114,22]);

〃常规选取一张特定时间特定位置的图片

varfilteredS2=s2

〃云量低于的影像

.filter(ee.Filter.lt('CLOUDY_PIXEL_PERCENTAGE'/35))35%

.filter(ee.Filter.date('2019-01-01'z'2020-01-01,))

.filter(ee.Filter.bounds(geometry));

〃选取最多云量的一张图

〃做法：先对图片根据云量从多到少排序再挑选第一张

vara=filteredS2.sort({

property:'CLOUDY_PIXEL_PERCENTAGE',

ascending:false

})；

varimage=a.first();

〃定义一个可视化参数，包含图像选定的波段，控制显示的亮度范围

〃有助于直观理解影像

varrgbVis={

min:0.0,

max:3000,

bands:['B4；'B3','B2'],

)；

〃将地图挪到选定照片的中间

Map.centerObject(image);

〃显示的图像是哪一张、如何显示、图层命名

//false：不立即显示图像，需要手动选择该图层

Map.addLayerfimage,rgbVis,'FullImage',false);

//不变的这个函数

functionmaskS2clouds(image){

〃选取特定波段的图像，与云的信息有关

varqa=image.select('QA60')；

〃定义两个位掩码

〃云卷云

varcloudBitMask=1«10;〃在第十位上写1

varcirrusBitMask=1«11;〃在第H—位上写1

〃特定波段的图像跟云、卷云两个变量进行位运算，与。比较

varmask=qa.bitwiseAnd(cloudBitMask).eq(0).and(

qa.bitwiseAnd(cirrusBitMask).eq(O));

〃返回

returnimage.updateMask(mask)

.selectfB.*')

.copyPropertiesfimage,[,system:time_start,]);

)

〃经过处理的新图像

varimageMasked=ee.lmage(maskS2clouds(image));

〃显示出来

Map.addLayerfimageMasked,rgbVis,'MaskedImage(QA60Band),,false);

//UseGoogle'sCloudScore+Mask

//CloudScorePlus数据集中获取的Sentinel-2影像数据集。这里使用的数据集是

版本VI中的Sentinel-2Harmonized数据。

varcsPlus=

ee.lmageCollection('GOOGLE/CLOUD_SCORE_PLUS/Vl/S2_HARMONIZED')；

〃获取第一幅影像的波段名称列表

varcsPlusBands=csPlus.first().bandNames();

〃LinkS2andCS+results.将Sentinel-2影像数据image与CloudScorePlus数据

集csPlus的结果进行关联

〃关联数据集+关联波段

varimageWithCs=image.linkCollection(csPlus,csPlusBands);

//FunctiontomaskpixelswithlowCS+QAscores.

〃cs+QA分数代表像素的质量或可信度评估，可在影像处理时排除质量差的像素

〃将CS+QA分数低于某个阈值的像素视为低质量数据，并将这些像素标记为无

效或屏蔽掉

functionmaskLowQA(image){

〃阈值，当质量评分大于阈值的时候认为是高质量的像素

varclearThreshold=0.65;

〃从image图像中选择cs波段来进行评分

〃mask:布尔类型的蒙版照片，标记了CS+QA分数大于等于阈值的像素为true,

低于阈值的像素为false

varmask=image.selsct('cs').