全 文 :!23" !5#
Vol.23 No.5
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ACTA AGRESTIA SINICA
2015$ 9%
Sep. 2015
犱狅犻:10.11733/j.issn.10070435.2015.05.029
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犆犺犪狉犪犮狋犲狉犻狊狋犻犮狊犪狀犱犃狆狆犾犻犮犪狋犻狅狀狅犳犌犉1犐犿犪犵犲犻狀犌狉犪狊狊犾犪狀犱犕狅狀犻狋狅狉犻狀犵
WANGLei1,2,GENGJun1,YANGRanran1,TIANQingjiu1,YANGYanjun1,ZHOUYang1
(1.InternationalInstituteforEarthSystemScience,NanjingUniversity,Nanjing,JiangsuProvince210093,China;
2.KeyLaboratoryforRestorationandReconstructionofDegradedEcosysteminNorthwesternChinaofMinistryofEducation,
NingxiaUniversity,Yinchuan,Ningxia750021,China)
犃犫狊狋狉犪犮狋:InordertoevaluatethemonitoringabilityofGF1imageingrassland,onthebasisofanalysisof
thecharacteristicsofthebandsetting,radiometricandspectralresponsecoefficientofsensor,thedistribu
tedinformationwasextracted,andthevegetationindexofgrasslandwascalculated.Withthecombination
offieldmeasuredspectrum,vegetationcoverage,leafareaindexandabovegroundbiomassdata,thebest
vegetationindexforgrasslandparameterswasestimated.Theoptimalmodelwasdeterminedaccordingto
犚2and犚犕犛犈 (rootmeansquareerror).TheresultsshowedthatGF1sensorskeptconsistencyinband
setcomparingwithothersensors.Theimprovementofspatialresolutionenhancedtheidentificationability
ofobjecttypes,andtheimprovementofradiationresolutionenhancedthelevelsofdata.Thespectralre
sponsecoefficientscoveredbetterthespectralcurvesofdifferenttypesofgrassland.Thecorrelationofdif
ferentgrasslandvegetationparametersandGF1vegetationindexreachedahighlevel,andmettheneeds
ofremotesensingestimationorinversion.Theregressionanalysesshowedthatthebestestimationmodel
for犔犃犐andthebiomassofthegrasslandwerecubicpolynomialregressionmodelbasedon犚犞犐(ratioveg
etationindex),andthebestestimationmodelforthevegetationcoverageofthegrasslandwerepower
functionmodelbasedon犖犇犞犐(normalizeddifferencevegetationindex),andthegoodmappingeffectof
theresearchregionwasobtained.
犓犲狔狑狅狉犱狊:GF1sensor;Vegetationindex;Grasslandmonitoring;Remotesensingestimation;Image
characteristics
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Table1 Theimageacquisitioninformation
¢
Sensor
+#
Data
Time/UTC
(àctã
Solarzenithangle/°
(àNYã
Solarazimuthangle/°
°jctã
Sensorzenithangle/°
°jNYã
Sensorazimuthangle/°
GF1WFV4 2013730 03h42m 26.1747 158.4 54.0402 286.6640
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Table2 Vegetationindexformula
«]
Name
Á.ªÂ
Formula
Origin
犇犞犐 犖犐犚-犚犈犇 [19]
犚犞犐 犖犐犚/犚犈犇 [20]
犚犇犞犐 (犖犐犚-犚犈犇)/ (犖犐犚+犚犈犇槡 ) [21]
犖犇犞犐 (犖犐犚-犚犈犇)/(犖犐犚+犚犈犇) [22]
犛犃犞犐 (1+犔)(犖犐犚-犚犈犇)/(犖犐犚+犚犈犇+犔)犔=0.5 [23]
犕犛犃犞犐 (2犖犐犚+1- (2犖犐犚+1)2-8(犖犐犚-犚犈犇槡 ))/2 [24]
ò:犇犞犐Dõ8 «p;犚犞犐Èõ8 «p;犚犇犞犐C8<8 «p;犖犇犞犐8<8 «p;犛犃犞犐ËÌRà8 «p;犕犛犃犞犐~¿
QËÌR(8 «p
;犖犐犚#as~à;犚犈犇a±~à
Note:犇犞犐differencevegetationindex,犚犞犐ratiovegetationindex,犚犇犞犐renormalizeddifferencevegetationindex,犖犇犞犐normalized
differencevegetationindex,犛犃犞犐soiladjustedvegetationindex,犕犛犃犞犐modifiedsoiladjustedvegetationindex,犖犐犚nearinfraredband,
犚犈犇redband
2 lmY;n
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。
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Table3 ThekeypropertyofGF1WFV4,HJ1BCCD1,Landsat8OLIandLandsat7ETM+
¢
Sensor
Cøu#
Return
period/d
6z5
Spatial
resolution/m
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Numberof
bands
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Radiometric
resolution/bit
3
Blue
´
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a
Red
#as
NIR
GF1WFV4 4 16 4 10 0.45~0.52 0.52~0.59 0.63~0.69 0.77~0.89
HJ1BCCD1 4 30 4 8 0.41~0.52 0.52~0.60 0.63~0.69 0.76~0.90
Landsat8OLI 16 30 9 12 0.45~0.51 0.53~0.59 0.64~0.67 0.85~0.88
Landsat7ETM+ 16 30 8 8 0.45~0.52 0.52~0.60 0.63~0.69 0.77~0.90
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Fig.2 Spectralresponsesfunctionofdifferentsensorsandthemeasuredcurveofspectrumofmajorgrasslandcommunity
2.2 #;0=pq rhi0(¬sf*tþÿ
2.2.1 «¾ú¶·¿À»¼ G
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@gv*G0.66,犔犃犐818 «pB@A
p¦0.43~0.80,v*õG8 犚犞犐B
0.80。
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Table4 ThecorrelationcoefficientofGF1WFV4vegetationindexandgrassland犔犃犐,coverageorbiomass
犖犇犞犐 犇犞犐 犚犞犐 犚犇犞犐 犛犃犞犐 犕犛犃犞犐
©/«p
犔犃犐
0.71 0.50 0.80 0.62 0.43 0.57
æç¨
Coverage
0.83 0.61 0.82 0.74 0.53 0.67
:9ë
Biomass
0.55 0.40 0.66 0.49 0.35 0.46
2.2.2 «¾úqÁ1 ¼½@z{lm,
x81Nñ«¬@gv*B8 «p;i78
z{
,
zÆð8 «p8犔犃犐、æç¨、:9ë
B78éQ
(
P5),Ô½M@ApBLN犚2 =
犚犕犛犈µkvzÞ.éQ。Nñ犔犃犐BvzÞ.
éQG¦ GF1WFV4RVIBÙü²ÂéQ,
Ò犚2 G0.708,犚犕犛犈 G0.369;Nñæç¨B1
éQ犚2 õmnA#,v*õG¦ GF1 WFV4
NDVIB«©péQ,Ò 犚2 G0.699,犚犕犛犈 G
8.877;Nñ:9ëB1éQ犚2 õKÚ,w
¦GF1WFV4RVI:@BÙüN/´¨vì,犚2
G0.689,犚犕犛犈G948.46kg·ha-1。
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Table5 TheregressionmodelofGF1WFV4vegetationindextograssland犔犃犐,coverageorbiomass
Þ.«¬
Estimate
index
8 «p
Vegetation
index
éQ
Model
ÈkAp
犚2
N¼0D
犚犕犛犈
©/«p
犔犃犐
犚犞犐
狔=0.3908狓-0.9109 0.636 0.412
狔=0.0662狓2-0.341x+0.9843 0.703 0.372
狔=0.0108狓3-0.1258x2+0.7258x-0.8594 0.708 0.369
狔=0.1658e0.3357狓 0.595 0.376
狔=0.0603狓1.7113 0.588 0.403
狔=1.8788ln(狓)-1.9003 0.559 0.453
æç¨
Coverage
犖犇犞犐
狔=172.63狓-47.837 0.690 8.912
狔=178.65狓2-56.52狓+24.388 0.695 8.844
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